Management Approach Research Articles

Endoscopic management of colonic perforations.

We will review the current management of colonic perforations, with particular emphasis on iatrogenic perforations caused by colonoscopy, the leading etiology. We will focus on recently developed endoscopic techniques and technologies that obviate morbid emergency surgery (the standard management approach in years past). Colonic perforations are rare but potentially fatal complications of both diagnostic and therapeutic colonoscopy resulting in death in approximately 5% of cases with the mortality increasing with delay in diagnosis and treatment. As novel endoscopic techniques and tools have flourished in recent years, our approach to management of these perforations has evolved. With the availability of newer tools such as over the scope clips, enhanced through the scope clips and novel endoscopic suturing devices, colonic perforations can be managed effectively in many or most patients without the morbidity of surgical interventions. With expanding use of colonoscopy, inadvertent outcomes such as perforations are bound to increase as well. Early diagnosis permits minimally invasive, nonsurgical, endoscopic management in most cases if the expertise and tools are available. Centers with high colonoscopy volumes including therapeutic procedures would be well served to invest in the requisite technologies and expertise.

Results From a Randomized Trial of Intensive Glucose Management Using CGM Versus Usual Care in Hospitalized Adults With Type 2 Diabetes: The TIGHT Study.

To evaluate whether continuous glucose monitoring (CGM) could assist providers in intensifying glycemic management in hospitalized patients with type 2 diabetes. At six academic hospitals, adults with type 2 diabetes hospitalized in a non-intensive care setting were randomly assigned to either standard therapy with glucose target 140-180 mg/dL (standard group) or intensive therapy with glucose target 90-130 mg/dL guided by CGM (intensive group). The primary outcome was mean glucose measured with CGM (blinded in standard group), and the key secondary outcome was CGM glucose <54 mg/dL. For the 110 participants included in the primary analysis, mean ± SD age was 61 ± 12 years and mean HbA1c was 8.9 ± 2.3% (73.8 ± 1.6 mmol/mol). During the study, CGM-measured mean glucose was 170 mg/dL for the intensive group (n = 60) vs. 175 mg/dL for the standard group (n = 50; risk-adjusted difference -7 mg/dL, 95% CI -19 to 5; P = 0.25). Only 7% of the intensive group achieved the mean glucose target range of 90-130 mg/dL. CGM readings <54 mg/dL were infrequent (0.2% for intensive and 0.4% for standard; adjusted treatment group difference -0.1%, 95% CI -0.6 to 0.3). One severe hypoglycemia event occurred in the standard group. The study's glucose management approach using CGM did not improve glucose levels compared with standard glucose management in the non-intensive care unit hospital setting. A glucose target of 90-130 mg/dL may not be realistic in the current environment of insulin management in the hospital.

Factors affecting collective action in low-cost housing, Malaysia: commoning the governance

PurposeThis paper aims to explain the factors shaping collective action within low-cost housing communities, focusing on parcel holders, through the utilisation of an expanded institutional analysis development (IAD) framework, which extends upon Ostrom’s foundational framework. Additionally, the paper explores four different property management approaches accessible to these communities.Design/methodology/approachThe research employed a mixed-method approach comprising four sequential steps. Firstly, a quantitative inquiry entailed a questionnaire survey administered to 633 parcel holders across four low-cost housing schemes, aimed at discerning factors influencing collective action. Subsequently, a qualitative investigation involved face-to-face interviews with key stakeholders to elucidate the contributing factors of collective action, with a specific focus on Nursa Kurnia (a successful low-cost housing scheme comprising 200 units), accessible via Kuala Lumpur Middle Ring Road II. Thirdly, the study explored the social practice of “commoning the governance”. Lastly, the paper advocated for housing policy interventions, specifically proposing government subsidies for lower-income parcel holders.FindingsExemplified by the success of Nursa Kurnia, the research findings emphasised the importance of shifting local management’s mindset from a zero-sum approach to a win-win perspective. It highlighted the pivotal role of four factors (resource system, governance system, context and historical development) in shaping collective action and fostering improved property management practices. Moreover, the study highlighted the potential of “commoning the governance” as a new approach capable of addressing collective action challenges in low-cost housing management, presenting a promising avenue for future endeavours.Research limitations/implicationsAs more studies utilising the expanded IAD framework become available in the future, there is potential for further refinement and enhancement of the framework.Practical implicationsThis study offers valuable insights for policymakers, property developers, local management and local communities, shedding light on challenges associated with the self-organisation of shared resources. Moreover, it highlights the potential of “commoning the governance” as a new property management approach to mitigate the impact of collective action problems.Social implicationsThe well-being of society’s most vulnerable segment is indicative of the overall societal health. This underscores the significance of addressing the interests and needs of these lower-income groups within the broader social context.Originality/valueExploring collective action within the context of self-organising low-cost housing, the study delves into an area marked by persistent challenges like free-riding tendencies and vandalism. Despite significant attention given to collective action issues in the past, the novel approach of “commoning the governance” remains unexamined in the realm of low-cost housing maintenance and management.

Lean Green Tendency

Lean philosophy and Green practices have been identified as management approaches that allow organizations to reach better economic and environmental results. Nevertheless, some authors argue that results can be enhanced with the integration of the Lean and Green practices. This synchronous effort has led to the developing a new Lean philosophy branch, the Lean Green. Goal: This work aims to deepen the Lean Green state of the art, as well as to understand how companies have adopted it. Design / Methodology / Approach: The methodology was supported by a systematic literature review following three steps: Planning, data collection, data analysis throughout content analysis. Results: The results showed that Lean Green is still an emerging theme in scientific research, with an increasing trend of publications worldwide in the last six years, adopting distinctive research strategies. Companies' main motivations and barriers to adopting Lean Green were also identified. Finally, were identified the key factors that could help organizations to adopt Lean Green, namely critical implementation factors, facilitator models and tools, and the main results and advantages obtained. Limitations of the investigation: The main work´s limitation is that it was considered only the Scopus database. Practical implications: Help companies find solutions that enhance their performance and competitiveness, reduce their environmental impact, and improve their social responsibility. Originality/Value: The originality of this work is defended by crossing the results at the academic and practical levels. This allows the usefulness of academic research results by bringing them into a practical organizational context.

AI-Driven Prediction of Symptom Trajectories in Cancer Care: A Deep Learning Approach for Chemotherapy Management.

This study presents an advanced method for predicting symptom escalation in chemotherapy patients using Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs). The accurate prediction of symptom escalation is critical in cancer care to enable timely interventions and improve symptom management to enhance patients' quality of life during treatment. The analytical dataset consists of daily self-reported symptom logs from chemotherapy patients, including a wide range of symptoms, such as nausea, fatigue, and pain. The original dataset was highly imbalanced, with approximately 84% of the data containing no symptom escalation. The data were resampled into varying interval lengths to address this imbalance and improve the model's ability to detect symptom escalation (n = 3 to n = 7 days). This allowed the model to predict significant changes in symptom severity across these intervals. The results indicate that shorter intervals (n = 3 days) yielded the highest overall performance, with the CNN model achieving an accuracy of 81%, precision of 87%, recall of 80%, and an F1 score of 83%. This was an improvement over the LSTM model, which had an accuracy of 79%, precision of 85%, recall of 79%, and an F1 score of 82%. The model's accuracy and recall declined as the interval length increased, though precision remained relatively stable. The findings demonstrate that both CNN's temporospatial feature extraction and LSTM's temporal modeling effectively capture escalation patterns in symptom progression. By integrating these predictive models into digital health systems, healthcare providers can offer more personalized and proactive care, enabling earlier interventions that may reduce symptom burden and improve treatment adherence. Ultimately, this approach has the potential to significantly enhance the overall quality of life for chemotherapy patients by providing real-time insights into symptom trajectories and guiding clinical decision making.

Dermal Filler-Induced Alopecia: A Case Report and Literature Review.

Dermal filler-induced alopecia is a rare yet significant complication of aesthetic procedures primarily associated with vascular occlusion and subsequent tissue ischemia. Hyaluronic acid (HA) fillers, though widely used for facial rejuvenation, can lead to adverse outcomes such as skin necrosis and hair loss, particularly in high-risk areas like the temples and glabella. This case report aims to highlight the clinical presentation, diagnostic approach, and multidisciplinary management of filler-induced alopecia, contributing to the existing literature with a comprehensive review of previously reported cases. A 21-year-old female presented with localized skin necrosis and alopecia four days after receiving 7 mL of HA filler injections in the temples, tear trough, and eyebrow glabella regions. Trichoscopy revealed follicular dropout and white dots, consistent with ischemic hair loss. Treatment included hyaluronidase injections (1500 units), intralesional corticosteroids, topical minoxidil, and CO2 laser therapy. Over 1 year of follow-up, the patient achieved complete hair regrowth and resolution of facial scarring. Only 16 cases of filler-induced alopecia have been documented, predominantly involving HA fillers. This case underscores the importance of early recognition and intervention with hyaluronidase to mitigate ischemic damage. The multidisciplinary management approach employed here demonstrates the potential for full cosmetic recovery. Filler-induced alopecia, though rare, necessitates heightened awareness among dermatologists and aesthetic practitioners. Adhering to recommended injection techniques and dosages, alongside the judicious use of ultrasound guidance, can minimize risks and improve patient safety.

AI Based Resource Management for 5G Network Slicing: History, Use Cases, and Research Directions

ABSTRACT5G, 6G, and beyond networks promise to support vertical industrial services with strict QoS parameters, but the hardware‐based "one‐size‐fits‐all" model of legacy networks lacks the flexibility needed for diverse services. The foundation of 5G networks lies in softwarization, with network slicing, Software Defined Networking (SDN), and Network Function Virtualisation (NFV) serving as its core components. The network‐slicing‐based shared network environment necessitates an intelligent and flexible resource management approach. In this case, traditional approaches are no longer suitable for dealing with a dynamic network environment. With recent advancements, AI‐based approaches have the potential to manage resources autonomously. This paradigm shift underscores the need for deep and extensive investigation. However, existing literature on this subject is fragmented and lacks a cohesive overview of network slicing. To address these gaps, our review paper aims to provide a comprehensive scope of network slicing in a unified manner. In this sequence at first, this paper presented a conceptual overview of network slicing and enabling technologies, including SDN, NFV, and edge computing. Secondly, this paper identifies the relevant phases of resource management and presents AI‐based resource management for network traffic classification, admission, allocation, and scheduling. Finally, it also discusses the deployment of network slicing‐enabled key use cases and their practical deployment, the research gap, and open research challenges. To the best of our knowledge, this is the first attempt to critically analyze and present a consolidated review of the state of the art in network slicing resource management modules and network slicing‐enabled key industrial use cases. This paper aims to guide researchers in developing innovative solutions and assist network players in the practical deployment of network slices for industrial applications.

Can We Offset Local Recurrence in Locally Advanced Non-Small Cell Lung Cancer? The Merry-Go-Round of Radiation Dose Escalation and Stubborn Outcomes.

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice.

Diversity of Honeybee Behavior Is a Potential Inbuilt Trait for Varroa Tolerance: A Basic Tool for Breeding Varroa-Resistant Strains

The ectoparasitic mite Varroa destructor is well known for transmitting a number of viruses that can contribute to the collapse of honeybee colonies. To date, the many control measures put in place to limit the spread of V. destructor have yielded no satisfactory results. This is challenging because the effect of the parasite on honeybee colonies is becoming notorious. This has weakened the beekeeping industry and reduced pollination services, which may contribute to global food insecurity in the future. Therefore, it is necessary to put in place possible control measures and outline sustainable approaches to mitigate research efforts against the Varroa destructor. Extensive research to elaborate on the best possible solution has revealed that the selective breeding of naturally occurring V. destructor immune-related traits of honeybee strains is sustainable. Since the Integrated Pest Management approach was introduced, while still being very unreliable, there are open questions as to what control strategy could be considered effective. After cross-examination of existing strategies, a more practical way could be the adoption of an integrated approach. This approach should involve the association of selective breeding of honeybee colonies with V. destructor immune-related traits and the application of soft chemical treatment.

CD2 expressing innate lymphoid and T cells are critical effectors of immunopathogenesis in hidradenitis suppurativa

Hidradenitis suppurativa (HS) is a chronic, debilitating inflammatory skin disease with a poorly understood immunopathogenesis. Here, we report that HS lesional skin is characterized by the expansion of innate lymphocytes and T cells expressing CD2, an essential activation receptor and adhesion molecule. Lymphocytes expressing elevated CD2 predominated with unique spatial distribution throughout the epidermis and hypodermis in the HS lesion. CD2+ cells were mainly innate lymphocytes expressing the NK cell marker, CD56, and CD4+ T cells. Importantly, these CD2+ cells interacted with CD58 (LFA3) expressing epidermal keratinocytes and fibroblasts in the hypodermis. Granzyme Abright NKT cells (CD2+CD3+CD56bright) clustered with α-SMA expressing fibroblasts juxtaposed to epithelialized tunnels and fibrotic regions of the hypodermis. Whereas NK cells (CD2+CD56dim) were perforin+, granzymes A+ and B+, and enriched adjacent to hyperplastic follicular epidermis and tunnels of HS showing presence of apoptotic cells. The cytokines IL-12, IL-15, and IL-18, which enhance NK cell maturation and function were significantly elevated in HS. Ex vivo HS skin explant cultures treated with CD2:CD58 interaction-blocking anti-CD2 monoclonal antibody attenuated secretion of inflammatory cytokines/chemokines and suppressed inflammatory gene signature. Additionally, CD2:CD58 blockade altered miRNAs involved in NK/NKT differentiation and/or function. In summary, we show that a cellular network of heterogenous NKT and NK cell populations drives inflammation and is critical in the pathobiology of HS, including tunnel formation and fibrosis. Finally, CD2 blockade is a viable immunotherapeutic approach for the effective management of HS.

Towards a microRNA-based Johne's disease diagnostic predictive system: Preliminary results.

Johne's disease, caused by Mycobacterium avium subspecies paratuberculosis (MAP), is a chronic enteritis that adversely affects welfare and productivity in cattle. Screening and subsequent removal of affected animals is a common approach for disease management, but efforts are hindered by low diagnostic sensitivity. Expression levels of small non-coding RNA molecules involved in gene regulation (microRNAs), which may be altered during mycobacterial infection, may present an alternative diagnostic method. The expression levels of 24 microRNAs affected by mycobacterial infection were measured in sera from MAP-positive (n = 66) and MAP-negative cattle (n = 65). They were then used within a machine learning approach to build an optimal classifier for MAP diagnosis. The method provided 72% accuracy, 73% sensitivity and 71% specificity on average, with an area under the curve of 78%. Although control samples were collected from farms nominally MAP-free, the low sensitivity of current diagnostics means some animals may have been misclassified. MicroRNA profiling combined with advanced predictive modelling enables rapid and accurate diagnosis of Johne's disease in cattle.

A Centenary Review on Leaf Rot Disease of Coconut

Coconut leaf rot disease (LRD) has posed a significant threat to coconut palms for over a century, causing widespread foliar damage, stunted growth, and reduced yield. The disease, often associated with the complex interaction of Root (wilt) disease (RWD), has been a persistent challenge since its first reports in the early 1900s. Despite extensive research, understanding the etiological agents and developing effective management strategies remain difficult due to evolving pathogenic profiles and climate variability. This centenary review consolidates over 100 years of research on LRD, offering a comprehensive analysis of the disease’s progression, and environmental influences, in coconut cultivation. It contrasts traditional management methods, such as cultural and chemical controls, with modern integrated disease management (IDM) approaches, including biological control agents and host resistance breeding. The review also explores the role of plant-microbe interactions, emphasizing the potential of microbial antagonists as biocontrol agents. Given the economic significance of coconuts in tropical regions, this review highlights the urgent need for region-specific disease management strategies and the development of climate-resilient coconut varieties. Additionally, it identifies research gaps and future directions to advance sustainable solutions for mitigating the impact of LRD.

From prevention to management: exploring AI’s role in metabolic syndrome management: a comprehensive review

BackgroundThis review aims to comprehensively explore the integration of artificial intelligence (AI) in the prevention, diagnosis, and treatment of metabolic syndrome (MetS). MetS is characterized by a cluster of conditions, posing a growing public health threat globally. Recognizing the limitations of traditional management approaches, we emphasize the potential of AI in transforming the management of MetS, focusing on recent advancements and applications in risk prediction and diagnosis.Body and conclusion.The integration of artificial intelligence in medicine is expanding, particularly in managing MetS, involving conditions like hypertension and dyslipidemia. Diagnosis and treatment challenges stem from addressing multiple conditions simultaneously. AI tools prove essential in monitoring indices such as blood pressure and glucose, and identifying trends for treatment adjustments. Lifestyle modifications are crucial, and AI can facilitate these changes through user-friendly interfaces and positive reinforcement. Standardization and successful implementation of AI tools in medical practices are necessary for revolutionizing MetS management, requiring focused future research efforts.

Strip-Grazing Stockpiled Annual Forages: Impact on Carrying Capacity and Cattle Performance

Abstract Strip grazing can increase forage utilization, though it has been shown to decrease individual animal performance. The objective of this study was to evaluate forage utilization and cattle performance when strip grazing (STRIP) vs. continuously grazing (CONT) stockpiled annual forages. Exp. 1 consisted of a mix of Jerry oats (Avena sativa) and Trophy rapeseed (Brassica napus) while Exp. 2 was a 17-species mix in which the forage mass was predominantly pearl millet (Pennisetum glaucum), german millet (Setaria italica), and browntop millet (Urochloa ramosa). Fields were divided into six 6.3 ha (Exp. 1) or 4.1 ha (Exp. 2) paddocks which were blocked by location. Treatment was randomly assigned within block (n = 3 replicates per treatment per Exp.). Grazing was initiated in November and terminated in February. This resulted in a total of 83 and 54 grazing days for Exp. 1 and 2, respectively. Forage was allocated to STRIP twice a week. The STRIP steers gained 16% less (P = 0.01) per day in Exp. 1, but in Exp. 2, there was no difference (P = 0.56) between treatments. Compared to CONT, carrying capacity (AUM/ha) of STRIP was increased (P = 0.03) by 81% in Exp. 1 and tended to increase (P = 0.10) in Exp. 2. Gain per hectare increased (P = 0.02) for STRIP by 56% in Exp. 1 and by 31% in Exp. 2. Strip grazing stockpiled annual forages can be an effective way to increase carrying capacity and gain per hectare during the fall and winter months but effects on individual animal performance are inconsistent. Disparities in response to strip grazing could stem from differences in forage quality and allocation. Further research is needed to refine and optimize the utilization of this management approach.

Genitourethral foreign bodies: 20-year experience and outcomes from a single center.

The presentation of a foreign body in the lower urinary tract is a challenging urological emergency with highly variable management approaches. A retrospective cohort study was undertaken to identify the patients who presented with self-inserted genitourethral foreign body to adult tertiary centers within our local health network (Southern Adelaide Local Health Network, Adelaide, Australia) from October 2002 to October 2022. Patient demographics, type of foreign body, psychiatric comorbidities, retrieval techniques, complications, and readmission data were extracted. Twenty-seven cases were identified with a median age of 44 years. Twenty-three (85.2%) were male and 4 (14.8%) were female. Ten patients (37.0%) had a concurrent psychiatric illness. The most commonly inserted foreign bodies were plastic tubes/wires (29.6%). Twenty cases (74.1%) were retrieved endoscopically. Three patients (11.1%) required open cystotomy and one underwent a transperineal urethrotomy. Four patients (14.8%) represented after discharge. Two patients had repeat presentations for genitourinary foreign body insertion. A significant monotonic positive trend of foreign body presentations was identified (Mann-Kendall tau = 0.95, P = 0.043). Presentations of genitourethral foreign body insertions have trended upward over the past two decades. However, most cases were successfully managed endoscopically.

The Role of AI in Data Engineering and Integration in Cloud Computing

This article presents a comprehensive analysis of the transformative role of Artificial Intelligence (AI) in revolutionizing data engineering and integration processes within cloud computing environments. The article examines the implementation of AI-driven solutions across multiple dimensions, including automated pipeline generation, intelligent schema matching, anomaly detection, and real-time data integration. Through a mixed-methods approach incorporating both quantitative and qualitative analyses, the article demonstrates significant improvements in data processing efficiency, with organizations achieving up to 67% reduction in processing time and 89% enhancement in accuracy. The article encompasses case studies from financial services, healthcare, and e-commerce sectors, providing concrete evidence of practical applications and scalability. Key findings reveal that AI-powered systems substantially outperform traditional approaches in cost efficiency, scalability, and data quality management, while simultaneously reducing operational overhead. The article also addresses implementation challenges, including legacy system integration and initial deployment complexities, offering strategic insights for organizations pursuing AI integration in their data engineering workflows. These article contribute to the broader understanding of how AI technologies can be effectively leveraged to address the growing challenges of data management in cloud computing environments, while providing a framework for future developments in this rapidly evolving field.

Risk factors for deep vein thrombosis and pulmonary embolism: a comparative study between acute hospital care and mental health inpatient settings for older people

Purpose This study aims to establish if risk factors for venous thromboembolism (VTE) in older hospitalized psychiatric patients differ from geriatric inpatients and if the current risk assessment tools being used are suitable. Design/methodology/approach The authors undertook a single centre retrospective review of 75 records for presence of predetermined risk factors. In total, 55 discharged patients with thrombotic events within geriatric settings were compared with 20 from mental health settings. Differences in risk factors were determined using t-test and Fisher’s exact test. Findings VTE patients in geriatric units were older and had reduced mobility. Psychiatric patients were more likely to be dehydrated and treated with psychotropics. Whilst rates of VTE screening were comparable in both settings, geriatric inpatients were more frequently prescribed thromboprophylaxis. Research limitations/implications Older psychiatric inpatients differ from those in medical/surgical settings in their profiles and risk factors for VTE. Approaches for VTE risk management also differed. Practical implications The study suggests the need for VTE screening tools and treatment protocols specific to older psychiatric settings. Social implications Targeted approaches may improve outcomes specific to each group. Originality/value To the best of the authors’ knowledge, this is the first attempt in comparing VTE risk factors across acute physical health care and mental health settings.

Physiological and Molecular Mechanisms of Lepidopteran Insects: Genomic Insights and Applications of Genome Editing for Future Research.

Lepidopteran insects are a major threat to global agriculture, causing significant crop losses and economic damage. Traditional pest control methods are becoming less effective due to the rapid evolution of insecticide resistance. This study explores the current status and genomic characteristics of 1315 Lepidopteran records, alongside an overview of relevant research, utilizing advanced functional genomics techniques, including RNA-seq and CRISPR/Cas9 gene-editing technologies to uncover the molecular mechanisms underlying insecticide resistance. Our genomic analysis revealed significant variability in genome size, assembly quality, and chromosome number, which may influence species' biology and resistance mechanisms. We identified key resistance-associated genes and pathways, including detoxification and metabolic pathways, which help these insects evade chemical control. By employing CRISPR/Cas9 gene-editing techniques, we directly manipulated resistance-associated genes to confirm their roles in resistance, demonstrating their potential for targeted interventions in pest management. These findings emphasize the value of integrating genomic data into the development of effective and sustainable pest control strategies, reducing reliance on chemical insecticides and promoting environmentally friendly integrated pest management (IPM) approaches. Our study highlights the critical role of functional genomics in IPM and its potential to provide long-term solutions to the growing challenge of Lepidopteran resistance.

A Comprehensive Review and Update on Cannabis Hyperemesis Syndrome.

Cannabis, derived from Cannabis sativa plants, is a prevalent illicit substance in the United States, containing over 400 chemicals, including 100 cannabinoids, each affecting the body's organs differently upon ingestion. Cannabis hyperemesis syndrome (CHS) is a gut-brain axis disorder characterized by recurring nausea and vomiting intensified by excessive cannabis consumption. CHS often goes undiagnosed due to inconsistent criteria, subjective symptoms, and similarity to cyclical vomiting syndrome (CVS). Understanding the endocannabinoid system (ECS) and its dual response (pro-emetic at higher doses and anti-emetic at lower doses) is crucial in the pathophysiology of CHS. Recent research noted that type 1 cannabinoid receptors in the intestinal nerve plexus exhibit an inhibitory effect on gastrointestinal motility. At the same time, the thermoregulatory function of endocannabinoids might explain compulsive hot bathing in CHS patients. The prevalence of cannabis CHS is expected to rise as legal restrictions on its recreational use decrease in several states. Education and awareness are vital in diagnosing and treating CHS as its prevalence increases. This comprehensive review explores the ECS's involvement, CHS management approaches, and knowledge gaps to enhance understanding of this syndrome.

Advantages and disadvantages of a closed-loop economy: the path to environmentally friendly production

The relevance of the study is related to the development of the circular economy in the national economies of many countries of the world, where it is receiving increasing attention. Circular technological and economic models can be considered promising areas of strategic transformation for companies that contrast themselves with traditional business models of an open economic system based on extensive growth. The concept of a circular economy appeared in order to create closed-loop production and consumption models that aim to increase resource efficiency, use waste management approaches and achieve stable coexistence between the economy, the environment and the population. The purpose of the study is to analyze relevant scientific sources and statistical information to determine the advantages and disadvantages of closed-loop economic models at the current stage of scientific and technological progress. The research methodology is based on the use of general scientific research methods such as analysis, generalization, abstraction, synthesis. The results of the study. The article evaluates the current situation of the development of the circular economy in the world, identifies factors that emphasize the extensiveness of the current economy. The main advantages, disadvantages and barriers of the circular economy are presented, classified into four aspects: environmental, economic, technological and social. It is established that from the point of view of the economic development of the branches of the national economy, the circular economy will create new markets and business opportunities in the sectors of recycling and servicing of goods. It is also assumed that circular business models can increase the competitiveness of companies through innovation and optimization of production processes. In addition, circular economic systems will contribute to the development of innovative technologies and processing methods aimed at more efficient use of raw materials and materials.