Quality Control System Research Articles

Food-Induced Adverse Reactions: A Review of Physiological Food Quality Control, Mucosal Defense Mechanisms, and Gastrointestinal Physiology

Although food is essential for the survival of organisms, it can also trigger a variety of adverse reactions, ranging from nutrient intolerances to celiac disease and food allergies. Food not only contains essential nutrients but also includes numerous substances that may have positive or negative effects on the consuming organism. To protect against potentially harmful components, all animals have evolved defense mechanisms, which are similar to antimicrobial defenses but often come at the cost of the organism’s health. When these defensive responses are exaggerated or misdirected, they can lead to adverse food reactions, where the costs outweigh the benefits. Furthermore, due to the persistent toxicity of harmful food components, the failure of defense mechanisms can also result in pathological effects triggered by food. This article review presents a food quality control framework that aims to clarify how these reactions relate to normal physiological processes. Organisms utilize several systems to coexist with symbiotic microbes, regulate them, and concurrently avoid, expel, or neutralize harmful pathogens. Similarly, food quality control systems allow organisms to absorb necessary nutrients while defending against low-quality or harmful components in food. Although many microbes are lethal in the absence of antimicrobial defenses, diseases related to microbiome dysregulation, such as inflammatory bowel disease, have significantly increased. Antitoxin defenses also come with costs and may fail due to insufficiencies, exaggerations, or misdirected actions, ultimately leading to adverse food reactions. With the changes in human diet and lifestyle, the failure of defense mechanisms has contributed to the rising incidence of food intolerances. This review explores the mechanisms of antitoxin defenses and analyzes how their failure can lead to adverse food reactions, emphasizing the importance of a comprehensive understanding of food quality control mechanisms for developing more effective treatments for food-triggered diseases.

Novel approach for quality control testing of medical displays using deep learning technology

Objectives:In digital image diagnosis using medical displays, it is crucial to rigorously manage display devices to ensure appropriate image quality and diagnostic safety. The aim of this study was to develop a model for the efficient quality control (QC) of medical displays, specifically addressing the measurement items of contrast response and maximum luminance as part of constancy testing, and to evaluate its performance. In addition, the study focused on whether these tasks could be addressed using a multitasking strategy.Methods:The model used in this study was constructed by fine-tuning a pretrained model and expanding it to a multioutput configuration that could perform both contrast response classification and maximum luminance regression. QC images displayed on a medical display were captured using a smartphone, and these images served as the input for the model. The performance was evaluated using the area under the receiver operating characteristic curve (AUC) for the classification task. For the regression task, correlation coefficients and Bland-Altman analysis were applied. We investigated the impact of different architectures and verified the performance of multi-task models against single-task models as a baseline.Results:Overall, the classification task achieved a high AUC of approximately 0.9. The correlation coefficients for the regression tasks ranged between 0.6 and 0.7 on average. Although the model tended to underestimate the maximum luminance values, the error margin was consistently within 5% for all conditions.Conclusion:These results demonstrate the feasibility of implementing an efficient QC system for medical displays and the usefulness of a multitask-based method. Thus, this study provides valuable insights into the potential to reduce the workload associated with medical-device management the development of QC systems for medical devices, highlighting the importance of future efforts to improve their accuracy and applicability.

Towards Intelligent Universities Enhanced with Artificial Intelligence (AI)

This paper presents a comprehensive and integrated paradigm for intelligent universities using artificial intelligence (AI) to transform management systems and teaching, thus complementing sustainable development objectives. Through a systematic examination of top worldwide universities’ AI applications, this study reveals key achievements, obstacles, and strategies for successfully implementing AI-driven intelligent universities. Every case study focuses on a particular AI-driven project, including the adaptive learning systems at MIT, the AI teaching assistant Jill Watson at Georgia Tech, and the AI-enabled quality control system at Cambridge University. Combining systematic review, meta-analysis, and case studies under a mixed-methods approach, the study provides a practical guide for implementing artificial intelligence to improve administrative and academic roles. Results show how artificial intelligence can solve institutional issues, automate quality assurance, and personalize learning. Recommendations advocate for gradual adoption strategies, ethical AI deployment, and capacity-building measures to enable sustainable digital transformation.

An Assay System for Plate-based Detection of Endogenous Peptide:N-glycanase/NGLY1 Activity Using A Fluorescence-based Probe.

Cytosolic peptide:N-glycanase (PNGase/NGLY1 in mammals), an amidase classified under EC:3.5.1.52, is a highly conserved enzyme across eukaryotes that catalyzes the removal of N-glycans from glycoproteins, converting N-glycosylated asparagine residues into aspartic acid. This enzyme also plays a role in the quality control system for nascent glycoproteins. Despite the development of non-radioisotope-based assay systems such as those using S-alkylated RNase or fluorescent-labeled glycopeptides as substrates, these methods are incompatible with crude enzyme sources, primarily due to the degradation of reaction products by contaminating endogenous proteases. We previously developed an assay system using a 5-carboxyfluorescein-labeled glycosylated cyclo-heptapeptide (5FAM-GCP), a substrate remarkably resistant to endogenous peptidase activity. This system enables the accurate measurement of endogenous NGLY1 activity in various samples, including cell lines, tissues, peripheral blood mononuclear cells, and NGLY1-deficient patient-derived cells, without the interference of proteolytic degradation. We recently advanced this approach by producing a novel fluorescence resonance energy transfer (FRET)-based GCP probe (fGCP) and demonstrated its ability to detect endogenous NGLY1 activity across diverse enzyme sources via fluorescence on multiarray plates. This innovative and straightforward assay now offers reliable disease diagnostics and also allows the measurement of endogenous PNGase/NGLY1 activities across various organisms. Key features • fGCP assay enables measurement of endogenous PNGase/NGLY1 activity in cells and tissues. • An aliquot of 1-5 × 106 cells or 50-100 μg of protein extract from tissues is used for this assay. • This assay enables microplate-based real-time measurement of endogenous PNGase/NGLY1 activities. • This protocol requires a fluorescence plate reader equipped with an incubation function.

Solid State Wave Gyroscope Parameter Assessment at Various Production Stages

The paper considers a solid-state wave gyroscope and describes the principles of its operation. Key stages of production together with parameters of solid-state wave gyroscope, characterizing quality, are studied and analyzed. The problem of automated quality control system development is raised. The set of gyroscope parameters, physical parameters of resonator oscillation modes, is chosen. The proposed set of parameters gives full description of device quality and can be analyzed at any of key production stages. So as to develop the evaluation method for solid-state wave gyroscope parameters a solid-state wave gyroscope mathematical model, as a free oscillation partial oscillator, that relates the phase variable dynamics with physical parameters, is analyzed. The resonator intrinsic wave drift rate being the principal quality parameter of gyroscope is studied. The relation between the drift rate and solid-state wave gyroscope physical parameters is considered. The measuring diagram for the suggested parameter set is developed on the basis of considered mathematical models, the technique is proposed, and software solutions for suggested approach implementation is developed. Structure diagram and state chart for the proposed solid-state wave gyroscope measurement parameters are described. The proposed diagram consists of two components: measurement and computational ones. The performance features of each component are described. Various operation modes of solid-state wave gyroscope parameter evaluation system are considered: free oscillation mode, wave pattern rotation, operation mode, and transition processes. The problem of applicability and efficiency of the proposed solutions is studied. The example of the developed system application is given. The results of obtaining the operating mode drift rate direct evaluation and drift rate evaluation obtained according to mathematical model and evaluated solid-state wave gyroscope physical parameter are analyzed. Possible ways of solid-state wave gyroscope parameter evaluation method improvement are considered.

Introduction of methodology for assessing the quality of medical examination of adult population in system of internal control of quality and safety of medical activities

INTRODUCTION: It is reasonable that the realization of the state project of medical examination of adult population (MEAP) be assessed simultaneously with the assessment of the quality of medical care, and be integrated into the internal control of quality and safety of medical activities. The process approach is effective in realization of quality control of medical care provided as part of MEAP. AIM: To develop and introduce the methodology of assessing MEAP quality, to assess the results of expertise conducted at the initial stage of MEAP introduction, and on the basis of the results of introduction of measures that improved MEAP organization. MATERIALS AND METHODS: To assess the quality of MEAP, the ‘Expert Assessment Card for a Medical Examination Case’ was developed and introduced using the integrated quality assessment method. The assessment was carried out according to the blocks of the Card developed by I. V. Uspenskaya and O. N. Selyavina in accordance with the adopted assessment scale (0–0.5–1). The expertise of MEAP cases was carried out twice: in 2013 at the initial stage of realization of MEAP according to the new procedure, and in 2018 on the basis of the results of the realization of measures to improve the organization of MEAP. RESULTS: Comparative analysis of defects identified at the initial stage of the medical examination in 2013 and as a result of the work performed for the introduction of the quality control system of medical examination cases in 2018, revealed a marked decrease (by 27.0%) in the defects in determining risk factors for chronic non-communicable diseases and indications for prescribing II stage MEAP measures. For other defects, a marked decrease by 5.2%–17.3% was revealed. Nevertheless, the leading positions were retained by defects in prescribing stage II measures (34.5% of the analyzed expert cards) and in determining risk factors for chronic non-communicable diseases (26.5% of the analyzed expert cards), which requires continuation of the work on MEAP control quality as part of the internal control of quality and safety of the medical activities. CONCLUSION: Expert integration of the assessment of organization and introduction of MEAP and of the internal system of control of the quality and safety of medical activities led to a reliable reduction of the number of defects according to the results of expert assessment of medical examination cases.

Design and Development of a Precision Defect Detection System Based on a Line Scan Camera Using Deep Learning

The manufacturing industry environment is rapidly evolving into smart manufacturing. It prioritizes digital innovations such as AI and digital transformation (DX) to increase productivity and create value through automation and intelligence. Vision systems for defect detection and quality control are being implemented across industries, including electronics, semiconductors, printing, metal, food, and packaging. Small and medium-sized manufacturing companies are increasingly demanding smart factory solutions for quality control to create added value and enhance competitiveness. In this paper, we design and develop a high-speed defect detection system based on a line-scan camera using deep learning. The camera is positioned for side-view imaging, allowing for detailed inspection of the component mounting and soldering quality on PCBs. To detect defects on PCBs, the system gathers extensive images of both flawless and defective products to train a deep learning model. An AI engine generated through this deep learning process is then applied to conduct defect inspections. The developed high-speed defect detection system was evaluated to have an accuracy of 99.5% in the experiment. This will be highly beneficial for precision quality management in small- and medium-sized enterprises

How do proteins shape our lifespan? Exploring aging at the molecular level

Aging is a major risk factor for many diseases, including neurodegenerative, diabetes, cancer and cardiovascular diseases. Protein misfolding and consequent aggregation are key pathogenic features of number of age-related disorders. Therefore, correct protein folding and its maintenance are necessary for all cellular health. Proper functional balance of the cellular proteins referred as protein homeostasis (or proteostasis) is vital for all living cells. Thus, cells maintain protein quality control systems or proteostasis network (PN), which coordinates protein synthesis, folding, and degradation to protect the proteins. However, PN function declines with age, and loss of proteostasis is considered as one of the primary hallmarks of aging. It is not clear whether aging is a cause or consequence of proteostasis decline. Intriguingly, signaling pathways that regulate longevity are also found to modulate the PN. This raises a question whether aging pathways can be targeted to boost proteostasis and extend healthy lifespan. This essay explores the relationship between proteins, aging, and strategies to improve both lifespan and health span.

Autophagy and Protein Quality Control in Parkinson's Disease.

Autophagy is a vital cellular process responsible for the degradation of proteins, organelles, and other cellular components within lysosomes. In neurons, basal autophagy is indispensable for maintaining cellular homeostasis and protein quality control. Accordingly, lysosomal dysfunction has been proposed to be associated with neurodegeneration, and with Parkinson's disease (PD) in particular. Aging, dopamine metabolism, and PD-linked genetic mutations are thought to impair the autophagic-lysosomal pathway, disrupt cellular proteostasis, and contribute to PD pathogenesis. These alterations represent an opportunity to identify potential new therapeutic targets and disease biomarkers, thus laying the groundwork for the development of novel disease-modifying strategies for PD that are aimed at restoring cellular proteostasis and quality control systems.

Implementation Of Audit Quality Control System Policy on Intern Supervision of The Regional Inspectorate West Sumbawa District

This research discusses the implementation of the Audit Quality Control System Policy in the Internal Supervision of the Regional Inspectorate of West Sumbawa Regency. The aim of this research is to describe the obstacles and implementation of audit quality control system policies in the internal supervision of the Regional Inspectorate of West Sumbawa Regency. The type of research used in this research design uses a qualitative descriptive method with a comparative approach. The research results found that the Implementation of the Audit Quality Control System Policy in the Internal Supervision of the West Sumbawa Regency Regional Inspectorate was based on George C. Edward III's Theory, namely a). Communication: External communication has been carried out in accordance with Audit Standards. Meanwhile, internal communication is still not established intensively. The obstacles found were the lack of persuasive 2 (two) way communication; b). Resources: supporting resources include human resources, budget and facilities and infrastructure. The obstacles found were the lack of fulfillment of these resources in accordance with applicable needs and regulations; c). Disposition or attitude: The auditor is still negligent and not fully objective in carrying out his duties. The obstacles found were the lack of motivation and commitment of the Auditor and insufficient support from APIP Leadership; d). Bureaucratic structure: there is no SOP for implementing audit quality control. The obstacle found is that there has been no development of a quality assurance and improvement program within the scope of APIP. So, it is concluded that the implementation of the Audit Quality Control System Policy in the Internal Supervision of the Regional Inspectorate of West Sumbawa Regency has not been fully implemented properly in accordance with applicable regulations and standards and there are still obstacles found in communication factors, resources, disposition or attitude and organizational structure.

Classification of Plant-Based Drinks Based on Volatile Compounds.

The increasing popularity of plant-based drinks has led to an expanded consumer market. However, available quality control technologies for plant-based drinks are time-consuming and expensive. Two alternative quality control methods, gas chromatography with ion mobility spectrometry (GC-IMS) and an electronic nose, were used to assess 111 plant-based drink samples. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to compare 58 volatile organic compound areas of GC-IMS gallery plots and 63 peptide sensors of the electronic nose. PCA results showed that GC-IMS was only able to completely separate one sample, whereas the electronic nose was able to completely separate seven samples. LDA application to GC-IMS analyses resulted in classification accuracies ranging from 15.4% to 100%, whereas application to electronic nose analyses resulted in accuracies ranging from 96.2% to 100%. Both methods were useful for classification, but each had drawbacks, and the electronic nose performed slightly better than GC-IMS. This study represents one of the first studies comparing GC-IMS and an electronic nose for the analysis of plant-based drinks. Further research is necessary to improve these methods and establish a rapid, cost-effective food quality control system based on volatile organic compounds.

A nuclear protein quality control system for elimination of nucleolus-related inclusions.

The identification of pathways that control elimination of protein inclusions is essential to understand the cellular response to proteotoxicity, particularly in the nuclear compartment, for which our knowledge is limited. We report that stress-induced nuclear inclusions related to the nucleolus are eliminated upon stress alleviation during the recovery period. This process is independent of autophagy/lysosome and CRM1-mediated nuclear export pathways, but strictly depends on the ubiquitin-activating E1 enzyme, UBA1, and on nuclear proteasomes that are recruited into the formed inclusions. UBA1 activity is essential only for the recovery process but dispensable for nuclear inclusion formation. Furthermore, the E3 ligase HUWE1 and HSP70 are components of the ubiquitin/chaperone systems that promote inclusion elimination. The recovery process also requires RNA Pol I-dependent production of the lncRNA IGS42 during stress. IGS42 localises within the formed inclusions and promotes their elimination by preserving the mobility of resident proteins. These findings reveal a protein quality control system that operates within the nucleus for the elimination of stress-induced nucleolus-related inclusions.

Herbal Medicine in India Metanalysis and Clinical Approaches

Traditional herbal medicines include herbs, herbal materials, herbal preparations and finished herbal products that contains as active ingredients parts of plants, or other plant materials, or combinations. Clinical trials of traditional herbal medicines are carried out with herbal preparations only after standardization and identification of markers to ensure that the substances being evaluated are always the same. It is very important to assess the direct and indirect risks associated with traditional herbal medicines. This can only be established once safety and efficacy of herbal medicines are being proven during clinical trials. There are various concerns over the clinical trial designs in India. It has been observed that during clinical trials various problems are being observed such as Batch to batch variation, use of placebo instead of innovative product, in adequate quality control system, inadequate requirement for the assessment of safety and efficacy for different types of herbal medicines and difficulty in quantification due to complex nature of extract. This review focuses on the current status of clinical trials of traditional herbal medicines in India and an attempt has also been made to review the problems encountered during conduction of clinical trials and suggestions and recommendations are also provided to ensure that the clinical trials can be conducted with safety and efficacy.

Organellar quality control crosstalk in aging-related disease: Innovation to pave the way.

Organellar homeostasis and crosstalks within a cell have emerged as essential regulatory and determining factors for the survival and functions of cells. In response to various stimuli, cells can activate the organellar quality control systems (QCS) to maintain homeostasis. Numerous studies have demonstrated that dysfunction of QCS can lead to various aging-related diseases such as neurodegenerative, pulmonary, cardiometabolic diseases and cancers. However, the interplay between QCS and their potential role in these diseases are poorly understood. In this review, we present an overview of the current findings of QCS and their crosstalk, encompassing mitochondria, endoplasmic reticulum, Golgi apparatus, ribosomes, peroxisomes, lipid droplets, and lysosomes as well as the aberrant interplays among these organelles that contributes to the onset and progression of aging-related disorders. Furthermore, potential therapeutic approaches based on these quality control interactions are discussed. Our perspectives can enhance insights into the regulatory networks underlying QCS and the pathology of aging and aging-related diseases, which may pave the way for the development of novel therapeutic targets.

Methodology for selecting energy-efficient thermal insulation materials using the Dynamo visual programming environment

Purpose of research: development of a methodology for selecting energy-efficient thermal insulation materials using the Dynamo visual programming environment in order to increase the energy efficiency of building envelopes and structures.Methods. The study was carried out using theoretical and practical methods. The theoretical study was carried out based on an analysis of scientific publications, as well as regulatory requirements in the field of energy efficiency. The practical study was carried out using the implementation of the methodology for selecting thermal insulation materials in the Revit software package using the Dynamo visual programming environment.Results. The capabilities of the visual programming environment Dynamo have been studied, allowing to automate the modeling and development of design documentation in the Revit software package, automate the process of reinforcing structures, designing utility networks and systems, creating automated quality control systems for BIM models, etc. Particular attention in the work is paid to the capabilities of Dynamo for automation performing thermal engineering calculations and selecting energy-efficient thermal insulation materials. A library of thermal insulation materials has been created, which can be supplemented and copied from one project to another using standard Revit functionality. Two Dynamo scripts have been created. The result of the work of the first is the complete automation of thermal engineering calculations in Revit, the result of the work of the second is the selection of thermal insulation material taking into account the requirements for thermal protection of buildings. A methodology has been developed for selecting energy-efficient thermal insulation materials using the Dynamo visual programming environment. The reliability of calculations obtained on the basis of developed scripts is confirmed by the results of manual calculations.Conclusion. The use of modern BIM technologies when choosing energy-efficient thermal insulation materials allows you to optimize the calculation process, and also makes it possible to find the most cost-effective solutions to reduce costs and increases design speed.

Implementation of the Audit Quality Control System Policy in the Internal Supervision of the Regional Inspectorate of West Sumbawa Regency

This research discusses the implementation of the Audit Quality Control System Policy in the Internal Supervision of the Regional Inspectorate of West Sumbawa Regency. The aim of this research is to describe the obstacles and implementation of audit quality control system policies in the internal supervision of the Regional Inspectorate of West Sumbawa Regency. The type of research used in this research design uses a qualitative descriptive method with a comparative approach. The research results found that the Implementation of the Audit Quality Control System Policy in the Internal Supervision of the West Sumbawa Regency Regional Inspectorate was based on George C. Edward III's Theory, namely a). Communication: External communication has been carried out in accordance with Audit Standards. Meanwhile, internal communication is still not established intensively. The obstacles found were the lack of persuasive 2 (two) way communication; b). Resources: supporting resources include human resources, budget and facilities and infrastructure. The obstacles found were the lack of fulfillment of these resources in accordance with applicable needs and regulations; c). Disposition or attitude: The auditor is still negligent and not fully objective in carrying out his duties. The obstacles found were the lack of motivation and commitment of the Auditor and insufficient support from APIP Leadership; d). Bureaucratic structure: there is no SOP for implementing audit quality control. The obstacle found is that there has been no development of a quality assurance and improvement program within the scope of APIP. So it is concluded that the implementation of the Audit Quality Control System Policy in the Internal Supervision of the Regional Inspectorate of West Sumbawa Regency has not been fully implemented properly in accordance with applicable regulations and standards and there are still obstacles found in communication factors, resources, disposition or attitude and organizational structure.

Artificial Intelligence in Quality Control Systems: A Cross-Industry Analysis of Applications, Benefits, and Implementation Frameworks

This article presents a comprehensive analysis of artificial intelligence applications in quality control across manufacturing, service, and infrastructure maintenance sectors. The article examines how AI-driven systems are transforming traditional quality control processes through automated defect detection, real-time monitoring, and adaptive testing methodologies. Through systematic review of industry implementations and case studies, we investigate the impact of machine learning algorithms, computer vision systems, and deep learning applications on quality assurance processes. The findings demonstrate significant improvements in inspection accuracy, reduction in manual inspection requirements, and enhanced detection of subtle defects across various industrial applications. The article reveals that AI-driven quality control systems offer substantial benefits in terms of operational efficiency, cost reduction, and quality consistency, while also identifying key implementation challenges such as initial infrastructure requirements, data quality concerns, and workforce adaptation needs. Additionally, the article provides insights into emerging trends and future opportunities for AI integration in quality control systems, contributing to the broader understanding of Industry 4.0 implementation strategies. This work serves as a foundational reference for organizations considering AI implementation in their quality control processes and provides a framework for evaluating the potential benefits and challenges across different industrial contexts.

Effect of X-ray scan quality on the collective effective dose in patients in telemedicine

BACKGROUND: The key objective of a healthcare provider is to ensure the quality and increase the efficiency of X-ray diagnostics in both municipal and private medical facilities. A poor-quality radiologic image requires repeated procedures, which results in further reputation, time, and economic losses for the medical organization. Moreover, repeated examinations further contribute to the patient’s total radiation exposure. AIM: To assess the contribution of poor-quality X-ray examinations to patient exposure in outpatient medical organizations with telemedicine services. MATERIALS AND METHODS: This study aimed to evaluate poor-quality X-ray examinations recorded by radiologists at the Moscow Reference Center in 2022 by applying a specially developed quality control system for diagnostic examinations based on information technology. In addition, during X-ray examinations, the methods for finding effective doses received by patients were applied in compliance with current regulatory requirements. Statistical methods were also used. RESULTS: In this study, 2,059 poor-quality examinations were recorded, accounting for 0.084% of the total number of examinations interpreted with telemedicine. The collective effective dose from poor-quality examinations was 3.613 man-Sv, which was 0.11% of the total collective dose of patients in outpatient medical organizations. CONCLUSION: The implementation of a quality control system for diagnostic examinations based on information technology proved to be efficient for medical organizations rendering telemedicine services.

An advanced retrieval-augmented generation system for manufacturing quality control

The rise of Large Language Models (LLMs) with generative artificial intelligence has revolutionized the development of knowledge-based systems, enabling intuitive interactions through natural language. This paper explores the implementation of an advanced Retrieval-Augmented Generation (RAG) system, designed to improve manufacturing quality control by utilizing the capabilities of LLMs, particularly OpenAI’s GPT models. We focus on the ceramic tile manufacturing process, where the system retrieves and analyzes specialized bibliographic sources to diagnose defects and propose solutions. In addition to core RAG functionalities, the system incorporates tailored pre-processing and post-processing mechanisms to optimize document retrieval and response generation. The system’s effectiveness in solving quality issues is demonstrated through its application in identifying defect causes and generating actionable solutions, significantly improving non-conformities management. This approach not only streamlines troubleshooting but also enhances the quality control system, providing a comprehensive, scalable tool for manufacturers.

Dysregulation of protein degradation and alteration of secretome in α-synuclein-exposed astrocytes: implications for dopaminergic neuronal dysfunction

BackgroundA key factor in the propagation of α-synuclein pathology is the compromised protein quality control system. Variations in membrane association and astrocytic uptake between different α-synuclein forms suggest differences in exocytosis or membrane cleavage, potentially impacting the secretome's influence on dopaminergic neurons. We aimed to understand differences in protein degradation mechanisms of astrocytes for both wild-type (WT) and mutant forms of α-synuclein, specifically during periods of reduced degradation efficiency. We also investigated α-synuclein release into the secretome and its effects on healthy dopaminergic neurons.MethodsCellular models used were rat primary astrocytes alongside hiPSC-derived astrocytes, whose impact on rat primary dopaminergic neurons and the human SH-SY5Y cell line was investigated. We examined the release and accumulation of α-synuclein resulting from impaired degradatory pathways, including matrix metalloprotease-MMP9, the ubiquitin proteasomal pathway-UPS, and the autophagy-lysosomal pathway-ALP, using immunocytochemical analysis and flow cytometry. Additionally, we explored the effect of astrocytic secretome on dopaminergic-neuronal survival, neurite collapse and function.ResultsAt early stages, astrocytes were able to deal efficiently with monomeric α-synuclein (via UPS), and larger aggregates (through MMP9 and autophagy), clearing extracellular α-synuclein and maintaining neuronal health. However, extended exposure to extracellular monomeric and aggregated α-synuclein compromised their proteasomal activity, inhibiting MMP9 and destabilizing autophagy, transforming astrocytes from protectors to promoters of neurodegeneration. This study is the first to elucidate the astrocytes' preferred degradation pathways for both monomeric and aggregated forms of α-synuclein, along with the subsequent effects of these payloads on the cellular degradation machinery. The astrocytic transformation is characterized by α-synuclein expulsion, increased release of inflammatory cytokines, and diminished secretion of growth factors leading to dopaminergic neuronal apoptosis and dysfunction, particularly neurite collapse, intracellular Ca2+ response and vesicular dopamine release. The presence of phosphorylated and nitrated α-synuclein species in astrocytes also suggests their potential involvement in modifying both forms of the protein.ConclusionThe initial protective action of astrocytes in clearing and degrading extracellular α-synuclein is severely compromised at latter stages, leading to astrocytic dysfunction and impairing neuron-glia cross-talk. This study underscores the criticality of integrating astrocytes into treatment paradigms in synucleinopathies.