Monitoring Of Progression Research Articles

Interaction between α-Synuclein and Bioactive Lipids: Neurodegeneration, Disease Biomarkers and Emerging Therapies.

The present review provides a comprehensive examination of the intricate dynamics between α-synuclein, a protein crucially involved in the pathogenesis of several neurodegenerative diseases, including Parkinson's disease and multiple system atrophy, and endogenously-produced bioactive lipids, which play a pivotal role in neuroinflammation and neurodegeneration. The interaction of α-synuclein with bioactive lipids is emerging as a critical factor in the development and progression of neurodegenerative and neuroinflammatory diseases, offering new insights into disease mechanisms and novel perspectives in the identification of potential biomarkers and therapeutic targets. We delve into the molecular pathways through which α-synuclein interacts with biological membranes and bioactive lipids, influencing the aggregation of α-synuclein and triggering neuroinflammatory responses, highlighting the potential of bioactive lipids as biomarkers for early disease detection and progression monitoring. Moreover, we explore innovative therapeutic strategies aimed at modulating the interaction between α-synuclein and bioactive lipids, including the development of small molecules and nutritional interventions. Finally, the review addresses the significance of the gut-to-brain axis in mediating the effects of bioactive lipids on α-synuclein pathology and discusses the role of altered gut lipid metabolism and microbiota composition in neuroinflammation and neurodegeneration. The present review aims to underscore the potential of targeting α-synuclein-lipid interactions as a multifaceted approach for the detection and treatment of neurodegenerative and neuroinflammatory diseases.

Time-dependent relations between emotion regulation, frustration, and metacognitive strategy use in technology-mediated learning

ABSTRACT Understanding how learners regulate their emotions and engage in metacognitive strategies is crucial for fostering self-regulated learning, particularly in technology-mediated learning. This study examines the temporal relationships between two emotion regulation (ER) strategies, reappraisal and suppression, frustration, and use of progress monitoring as metacognitive strategy, within the context of an educational game on financial literacy. The study involved 82 undergraduate students whose levels of frustration, progress monitoring behaviour, ER strategies were assessed at various points during the learning task. Findings revealed that the use of both reappraisal and suppression decreased during the learning task. Additionally, both ER strategies were negatively associated with frustration, although the relationship between reappraisal and frustration diminished over time. Frustration was negatively related to progress monitoring, indicating that effective emotion regulation can help maintain engagement in metacognitive strategies by keeping cognitive resources available. Notably, suppression and progress monitoring showed a positive relation that increased over time, highlighting the potential usefulness of suppression in extended learning tasks, despite its generally lower effectiveness compared to reappraisal. The results highlight the importance of considering temporal dynamics in the application of ER strategies during extended learning. Practical implications for the design of technology-mediated learning environments and educational interventions are proposed.

Plasma-based proteomic profiling identifies the distinct regulation of proteins in hyperplasia and endometrial cancer

BackgroundAmong gynaecological malignancies, endometrial cancer (EC) is the most prevalent type of uterine cancer affecting women. This study explored the proteomic profiles of plasma samples obtained from EC patients, those with hyperplasia (Hy), and a control group (CO). A combination of techniques, such as 2D-DIGE, mass spectrometry, and bioinformatics, including pathway analysis, was used to identify proteins with modified expression levels, biomarkers and their associated metabolic pathways in these groups.MethodsThirty-four patients, categorized into three groups—10 with EC, 12 with Hy, and 12 CO—between the ages of 46 and 75 years old were included in the study. Untargeted proteomic analysis was carried out using two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS).ResultsIn all three groups, 114 proteins that were significantly (p ≤ 0.05 and fold change ≥ 1.5) altered were successfully identified using peptide mass fingerprints (PMFs). Compared with those in the control group (CO), the EC samples had 85 differentially expressed proteins (39 upregulated and 46 downregulated), and in the Hy group, 81 proteins were dysregulated (40 upregulated and 41 downregulated) compared to those in the CO group, while 33 proteins exhibited differential regulation (12 upregulated and 21 downregulated) in the EC plasma samples compared to those in the Hy group. Vitamin D binding protein and complement C3 distinguished Hy and EC from CO with the greatest changes in expression. Among the differentially expressed proteins identified, enzymes with catalytic activity represented the largest group (42.9%). In terms of biological processes, most of the proteins were involved in cellular processes (28.8%), followed by metabolic processes (16.7%). STRING analysis for protein interactions revealed that the significantly differentially abundant proteins in the three groups are involved in three main biological processes: signalling of complement and coagulation cascades, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), and plasma lipoprotein assembly, remodelling, and clearance.ConclusionThe identified plasma protein markers have the potential to serve as biomarkers for differentiating between EC and Hy, as well as for early diagnosis and monitoring of cancer progression.

Novel automated non-invasive detection of ocular surface squamous neoplasia using artificial intelligence.

Ocular surface squamous neoplasia (OSSN) is a common eye surface tumour, characterized by the growth of abnormal cells on the ocular surface. OSSN includes invasive squamous cell carcinoma (SCC), in which tumour cells penetrate the basement membrane and infiltrate the stroma, as well as non-invasive conjunctival intraepithelial neoplasia, dysplasia, and SCC in-situ thereby presenting a challenge in early detection and diagnosis. Early identification and precise demarcation of the OSSN border leads to straightforward and curative treatments, such as topical medicines, whereas advanced invasive lesions may need orbital exenteration, which carries a risk of death. Artificial intelligence (AI) has emerged as a promising tool in the field of eye care and holds potential for its application in OSSN management. AI algorithms trained on large datasets can analyze ocular surface images to identify suspicious lesions associated with OSSN, aiding ophthalmologists in early detection and diagnosis. AI can also track and monitor lesion progression over time, providing objective measurements to guide treatment decisions. Furthermore, AI can assist in treatment planning by offering personalized recommendations based on patient data and predicting the treatment response. This manuscript highlights the role of AI in OSSN, specifically focusing on its contributions in early detection and diagnosis, assessment of lesion progression, treatment planning, telemedicine and remote monitoring, and research and data analysis.

Single-Use, Metabolite Absorbing, Resonant Transducer (SMART) Culture Vessels for Label-Free, Continuous Cell Culture Progression Monitoring.

Secreted metabolites are an important class of bio-process analytical technology (PAT) targets that can correlate to cell conditions. However, current strategies for measuring metabolites are limited to discrete measurements, resulting in limited understanding and ability for feedback control strategies. Herein, a continuous metabolite monitoring strategy is demonstrated using a single-use metabolite absorbing resonant transducer (SMART) to correlate with cell growth. Polyacrylate is shown to absorb secreted metabolites from living cells containing hydroxyl and alkenyl groups such as terpenoids, that act as a plasticizer. Upon softening, the polyacrylate irreversibly conformed into engineered voids above a resonant sensor, changing the local permittivity which is interrogated, contact-free, with a vector network analyzer. Compared to sensing using the intrinsic permittivity of cells, the SMART approach yields a 20-fold improvement in sensitivity. Tracking growth of many cell types such as Chinese hamster ovary, HEK293, K562, HeLa, and E. coli cells as well as perturbations in cell proliferation during drug screening assays are demonstrated. The sensor is benchmarked to show continuous measurement over six days, ability to track different growth conditions, selectivity to transducing active cell growth metabolites against other components found in the media, and feasibility to scale out for high throughput campaigns.

Inattention negatively moderates the effectiveness of a mathematics intervention in low performing primary school students

Research suggest that attention skills play distinct roles in children's acquisition of mathematics. Despite a growing number of mathematics interventions in general, little research has been devoted to mathematics interventions for students with attention/hyperactivity problems (ADHD). Extant literature suggests lower benefits of mathematics interventions for students with ADHD symptoms. This study aimed at investigating the influence of ADHD on the effectiveness of a mathematics intervention. In a single-case research design, a total of N = 10 students in Grades 2 and 4 with varying ADHD profiles were observed and trained in an ABAB-design with a computer-cased mathematics intervention. Intervention and progress monitoring were administered twice a week. The intervention showed heterogenous effects ranging from no to substantial learning progress during the intervention phases. Hierarchical piecewise regression models revealed lower learning progress for students with all ADHD symptoms as well as isolated attention difficulties. However, students with isolated hyperactivity but no attention difficulties did not respond less to the intervention. As a conclusion, mathematics interventions are supposed to address students with attention deficits more explicitly.

Business Transformation Towards Sustainability: The Role of Green Accounting in Sustainability Management

Green accounting, as an accounting approach that integrates environmental and social factors into a company's financial reporting system, plays an important role in supporting business transformation towards sustainability. This article aims to explore the role of green accounting in sustainability management and how its application can assist companies in managing and reporting their sustainability performance effectively. Through a review of literature and previous research, it is found that green accounting enables companies to identify, measure and disclose the environmental impacts of their business activities more comprehensively. The integration of green accounting in sustainability management also allows companies to develop more comprehensive sustainability performance indicators, set targets, and monitor progress in achieving their sustainability goals. The implementation of green accounting can increase corporate transparency and accountability, build trust and a better reputation, and increase the competitiveness and value of the company in the long run. This article concludes that the role of green accounting is crucial in ensuring that companies consider environmental and social impacts in their business decisions, and create long-term value for stakeholders while minimizing negative impacts on the environment and society.

Shotgun Proteomics Links Proteoglycan-4+ Extracellular Vesicles to Cognitive Protection in Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder lacking reliable biomarkers for early diagnosis and disease progression monitoring. This study aimed to identify the novel biomarkers in plasmatic extracellular vesicles (EVs) isolated from ALS patients and healthy controls (HCs). A total of 61 ALS patients and 30 age-matched HCs were enrolled in the study and the protein content of circulating EVs was analyzed by shotgun proteomics. The study was divided into a discovery phase (involving 12 ALS and 12 HC patients) and a validation one (involving 49 ALS and 20 HC patients). In the discovery phase, more than 300 proteins were identified, with 32 proteins showing differential regulation in ALS patients compared to HCs. In the validation phase, over 400 proteins were identified, with 20 demonstrating differential regulation in ALS patients compared to HCs. Notably, seven proteins were found to be common to both phases, all of which were significantly upregulated in EVs from ALS patients. Most of them have previously been linked to ALS since they have been detected in the serum or cerebrospinal fluid of ALS patients. Among them, proteoglycan (PRG)-4, also known as lubricin, was of particular interest since it was significantly increased in ALS patients with normal cognitive and motor functions. This study highlights the significance of EVs as a promising avenue for biomarker discovery in ALS. Moreover, it sheds light on the unexpected role of PRG-4 in relation to cognitive status in ALS patients.

Advances in blood biomarkers for Alzheimer disease (AD): A review.

Alzheimer disease (AD) and Alzheimer Disease and Related Dementias (AD/ADRD) are growing public health challenges globally affecting millions of older adults, necessitating concerted efforts to advance our understanding and management of these conditions. AD is a progressive neurodegenerative disorder characterized pathologically by amyloid plaques and tau neurofibrillary tangles that are the primary cause of dementia in older individuals. Early and accurate diagnosis of AD dementia is crucial for effective intervention and treatment but has proven challenging to accomplish. Although testing for AD brain pathology with cerebrospinal fluid (CSF) or positron emission tomography (PET) has been available for over 2 decades, most patients never underwent this testing because of inaccessibility, high out-of-pocket costs, perceived risks, and the lack of AD-specific treatments. However, in recent years, rapid progress has been made in developing blood biomarkers for AD/ADRD. Consequently, blood biomarkers have emerged as promising tools for non-invasive and cost-effective diagnosis, prognosis, and monitoring of AD progression. This review presents the evolving landscape of blood biomarkers in AD/ADRD and explores their potential applications in clinical practice for early detection, prognosis, and therapeutic interventions. It covers recent advances in blood biomarkers, including amyloid beta (Aβ) peptides, tau protein, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP). It also discusses their diagnostic and prognostic utility while addressing associated challenges and limitations. Future research directions in this rapidly evolving field are also proposed.

Diagnostic value of galectin-3, fractalkine, IL-6, miR-21 and cardiac troponin I in human ischemic cardiomyopathy.

The primary objective of this study was to assess the diagnostic potential of galectin-3 (Gal-3), fractalkine (FKN), interleukin (IL)-6, microRNA(miR)-21, and cardiac troponin I (cTnI) in patients with ischemic cardiomyopathy (ICM). A total of 78 ICM patients (Case group) and 80 healthy volunteers (Control group) admitted to our hospital for treatment or physical examination from Aug. 2018 to Feb. 2020 were included in the current study. The serum concentration of Gal-3, FKN, IL-6, miR-21, and plasma expression of cTnI of both groups were determined. The severity of ICM was classified using New York Heart Association (NYHA) scale. When compared with the control group, the case group had a significantly high blood concentration of Gal-3, FKN, IL-6, miR-21, and cTnI (P < 0.001). NYHA class II patients had lower blood levels of Gal-3, FKN, IL-6, miR-21, and cTnI than that in patients of NYHA class III and IV without statistical significance (P > 0.05). However, statistical significance could be achieved when comparing the above-analyzed markers in patients classified between class III and IV. Correlation analysis also revealed that serum levels of Gal-3, FKN, IL-6, miR-21, and cTnI were positively correlated with NYHA classification (R = 0.564, 0.621, 0.792, 0.981, P < 0.05). Our study revealed that up-regulated serum Gal-3, FKN, IL-6, miR-21, and cTnI levels were closely related to the progression of ICM. This association implies that these biomarkers have diagnostic potential, offering a promising avenue for early detection and monitoring of ICM progression.

Evaluation of Urinary Free Light Chains as a Marker of Severity of HIV Disease and Its Correlation with CD4 Count: A Pilot Study.

Human immunodeficiency virus (HIV) infection weakens immunity. Monitoring the immune status of the patient has become an important aspect of evaluating the progression of the disease and informing follow-up after treatment. Estimation of CD4 counts is quite costly and requires expertise in flow cytometry. In certain pathologies, free light chains (FLCs) are secreted in serum and urine and the magnitude can be used to monitor the severity, progression, and therapeutic monitoring of the disease. Urine as a specimen proves cost-effective and presents reduced risks during sample collection. The stability of light chains in urine at room temperature over extended periods simplifies the management of sample transportation as well. Hence, a pilot cross-sectional study was planned to evaluate the levels of urinary immunoglobulins in patients with HIV. The study was conducted at PGIMER, Dr. Ram Manohar Lohia Hospital (presently ABVIMS), New Delhi. Sixty-nine consecutive ART-naive HIV patients aged between 18 and 40 years and 69 age- and sex-matched healthy controls were included in the study. Urinary FLC kappa (κ) and lambda (λ) were measured using an immunoglobulin ELISA kit. Baseline urinary κ light chain levels were significantly higher in cases when compared with controls (p < .001) and were found to be increased with increasing WHO immunological classes (p < .001) and inversely related to CD4 cell count. However, no significant difference in mean urinary λ immunoglobulin light chain between cases and controls was found and no correlation with CD4 cell count or with stages of WHO immunological classification of HIV disease was observed. It is suggested that urinary free κ chain measurements combined with serum light chain measurements may be a useful marker in the follow-up and monitoring of response to therapies in patients with HIV where testing by flow cytometry is not available.

Rapid identification of living cancer cells based on label-free surface-enhanced Raman spectroscopy

Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive vibration spectroscopy technique that can obtain fingerprint information of biomolecules in cells, and it has demonstrated significant potential in the early diagnosis of cancer. Here, we propose a rapid and efficient identification method of living cancer cells (within 10 min), which is based on the label-free SERS detection using iodide-modified Ag nanoparticles (Ag IMNPs) and the ultra-fast Raman mapping by line illumination. The Ag IMNPs achieve a better balance between sensitivity, reproducibility, and biocompatibility when compared to conventional Au or Ag nanoparticles. Statistical analysis of Raman peak frequency and intensity across substantial SERS spectra reveals a wealth of intracellular chemical information about the three cell lines 7701/7703/Caski. This method can not only accurately identify and classify normal cells, cancer cells, and various types of cancer cells, but it can also detect fingerprint changes in the distribution of intracellular chemicals. Furthermore, we discover that, among the three cell lines, liver cancer cells 7703 had the highest level of reactive oxygen species (ROS). This rapid SERS method can provide a new optical detection method for early screening, progression monitoring and prognosis assessment of tumors.

Circulating non-coding RNA biomarkers of endocrine tumours.

Circulating non-coding RNA (ncRNA) molecules are being investigated as biomarkers of malignancy, prognosis and follow-up in several neoplasms, including endocrine tumours of the pituitary, parathyroid, pancreas and adrenal glands. Most of these tumours are classified as neuroendocrine neoplasms (comprised of neuroendocrine tumours and neuroendocrine carcinomas) and include tumours of variable aggressivity. We consider them together here in this Review owing to similarities in their clinical presentation, pathomechanism and genetic background. No preoperative biomarkers of malignancy are available for several forms of these endocrine tumours. Moreover, biomarkers are also needed for the follow-up of tumour progression (especially in hormonally inactive tumours), prognosis and treatment efficacy monitoring. Circulating blood-borne ncRNAs show promising utility as biomarkers. ThesencRNAs, including microRNAs, long non-coding RNAs and circular RNAs, are involved in several aspects of gene expression regulation, and their stability and tissue-specific expression could make them ideal biomarkers. However, no circulating ncRNA biomarkers have yet been introduced into routine clinical practice, which is mostly owing to methodological and standardization problems. In this Review, following a brief synopsis of these endocrine tumours and the biology of ncRNAs, the major research findings, pathomechanisms and methodological questions are discussed along with an outlook for future studies.

Photoluminescent sensing of HepG2 cells with a metal-organic framework / molybdenum disulphide nanosheets composite probe

The photoluminescence-based detection of circulating tumor cells (CTCs) can offer the development of rapid, simple, and sensitive techniques for the screening of cancer at early stages as well the monitoring of therapy progression. The present work reports the application of a photoluminescent composite of Terbium based metal–organic framework (Tb-BTC MOF) with L-cysteine conjugated molybdenum disulphide (MoS2) nanosheets for the highly sensitive immunosensing of HepG2 cells. The formation of the above composite facilitates the achievement of a highly fluorescent, large surface area material with abundant carboxyl functionality. This novel composite has been immobilized with the anti-EpCAM antibodies to form the desired immunosensor for HepG2 cells. After spectroscopic and morphological characterizations, the antibody immobilized Tb-BTC/MoS2 bioprobe (Ab/Tb-BTC/MoS2) has been investigated for the sensing of HepG2 cells (10–1000 cells). Based on the PL quenching mechanism, the above bioprobe has delivered a broad range analysis with a low limit of detection (8 cells). The Ab/Tb-BTC/MoS2 bioprobe is also found selective toward other possible interferants, such as HEK cells, bovine serum albumin, immunoglobin G, and glucose.

Development of an LC-HRMS/MS Method for Quantifying Steroids and Thyroid Hormones in Capillary Blood: A Potential Tool for Assessing Relative Energy Deficiency in Sport (RED-S).

Relative energy deficiency in sport (RED-S) is a condition that arises from persistent low energy availability (LEA), which affects the hypothalamic-pituitary axis and results in alterations of several hormones in both male and female athletes. As frequent blood hormone status determinations using venipuncture are rare in sports practice, microsampling offers promising possibilities for preventing and assessing RED-S. Therefore, this study aimed at developing a liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS) method for quantifying relevant steroids and thyroid hormones in 30 μL of capillary blood obtained using Mitra® devices with volumetric absorptive microsampling technology (VAMS®). The results of the study showed that all validation criteria were met, including a storage stability of more than 28 days in a frozen state (-18 °C) and 14 days at room temperature (20 °C). The validated assay provided precise (<12%) and accurate (<13%) results for all the target analytes. Furthermore, as a proof of concept, autonomously collected VAMS® samples from 50 female and male, healthy, active adults were analyzed. The sensitivity of all analytes was adequate to quantify the decreased hormone concentrations in the RED-S state, as all authentic samples could be measured accordingly. These findings suggest that self-collected VAMS® samples offer a practical opportunity for regular hormone measurements in athletes and can be used for early RED-S assessment and progress monitoring during RED-S recovery.

Understanding ESL Postgraduate Students’ Dissertation Writing Challenges: The Interplay Between Second Language Writing Anxiety and Writer’s Block

No matter how hard they try, some ESL postgraduate students experience periods when they can produce, if any, little writing. When such periods last for a considerable amount of time, the student is said to have a writer’s block (WB). Given the reciprocal connection between WB and second language writing anxiety (SLWA), more evidence is needed to determine the connection between the two factors in dissertation writing. Hence, this study aimed to investigate how challenges in second language (L2) postgraduate dissertation writing may heighten SLWA and WB, while also examining their interplay. In this mixed-method study, a total of 43 postgraduate students participated by completing an online survey to assess their levels of SLWA, while a subset of nine participants underwent semi-structured interviews. The thematic analysis revealed that WB stems from: i) SLWA experience; and ii) challenges in the writing process, research conceptualization, academic writing conventions, and academic reading. To overcome SLWA and WB, it is recommended that supervisors and language teachers provide specific suggestions to resolve writing issues, refrain from using anxiety to provoke performance, help break down the ultimate goal of dissertation writing into several obtainable goals, and foster open discussions about strategies for motivation and progress monitoring.

Using machine learning algorithms to detect fear of falling in people with multiple sclerosis in standardized gait analysis

Introduction: Multiple sclerosis (MS) is the most common chronic inflammatory disease of the central nervous system. The progressive impairment of gait is one of the most important pathognomic symptoms which are associated with falls and fear of falling (FOF) in people with MS (pwMS). 60 % of pwMS show a FOF, which leads to restrictions in mobility as well as physical activity and reduces the quality of life in general. Therefore, early detection of FOF is crucial because it enables early implementation of rehabilitation strategies as well as clinical decision-making to reduce progression. Qualitative and quantitative evaluation of gait pattern is an essential aspect of disease assessment and can provide valuable insights for personalized treatment decisions in pwMS. Our objective was to identify the most appropriate clinical gait analysis methods to identify FOF in pwMS and to detect the optimal machine learning (ML) algorithms to predict FOF using the complex multidimensional data from gait analysis.Methods: Data of 1240 pwMS was recorded at the MS Centre of the University Hospital Dresden between November 2020 and September 2021. Patients performed a multidimensional gait analysis with pressure and motion sensors, as well as patient-reported outcomes (PROs), according to a standardized protocol. A feature selection ensemble (FS-Ensemble) was developed to improve the classification performance. The FS-Ensemble consisted of four filtering methods: Chi-square test, information gain, minimum redundancy maximum relevance and ReliefF. Gaussian Naive Bayes, Decision Tree, k-Nearest Neighbor, and Support Vector Machines (SVM) were used to identify FOF.Results: The descriptive analysis showed that 37 % of the 1240 pwMS had a FOF (n = 458; age: 51 ± 16 years, 76 % women, median EDSS: 4.0). The FS-Ensemble improved classification performance in most cases. The SVM showed the best performance of the four classification models in detecting FOF. The PROs showed the best F1 scores (Early Mobility Impairment Questionnaire F1 = 0.81 ± 0.00 and 12-item Multiple Sclerosis Scale F1 = 0.80 ± 0.00).Conclusion: FOF is an important psychological risk factor associated with an increased risk of falls. To integrate a functional early warning system for fall detection into MS management and progression monitoring, it is necessary to detect the relevant gait parameters as well as assessment methods. In this context, ML strategies allow the integration of gait parameters from clinical routine to support the initiation of early rehabilitation measures and adaptation of course-modifying therapeutics. The results of this study confirm that patients' self-assessments play an important role in disease management.

Rapid Development of a Registry to Accelerate COVID-19 Vaccine Clinical Trials.

The unprecedented scientific response to the SARS-Cov-2 pandemic in 2020 required the rapid development and activation of extensive clinical trial networks to study vaccines and therapeutics. The COVID-19 Prevention Network (CoVPN) coordinated hundreds of sites conducting phase 2 and 3 clinical trials of vaccines and antibody therapeutics. To facilitate these clinical trials, the CoVPN Volunteer Screening Registry (VSR) was created to collect volunteer information at scale, identify volunteers at risk of COVID-19 who met enrollment criteria, distribute candidates across clinical trial sites, and enable monitoring of volunteering and enrollment progress. We developed a secure database to support three primary web-based interfaces: a national volunteer questionnaire intake form, a clinical trial site portal, and an Administrative Portal. The Site Portal supported filters based on volunteer attributes, visual analytics, enrollment status tracking, geographic search, and clinical risk prediction. The Administrative Portal supported oversight and development with pre-specified reports aggregated by geography, trial, and trial site; charts of volunteer rates over time; volunteer risk score calculation; and dynamic, user-defined reports. Over 650,000 volunteers joined the VSR, and 1094 users were trained to utilize the system. The VSR played a key role in recruitment for the Moderna, Oxford-AstraZeneca, Janssen, and Novavax vaccine clinical trials, provided support to the Pfizer and Sanofi vaccine and prophylactic antibody clinical trials, and enhanced the diversity of trial participants. Clinical trial sites selected 166,729 volunteer records for follow-up screening, and of these 47·7% represented groups prioritized for increased enrollment. Despite the unprecedented urgency of its development, the system maintained 99·99% uptime. The success of the VSR demonstrates that information tools can be rapidly yet safely developed through a public-private partnership and integrated into a distributed and accelerated clinical trial setting. We further summarize the requirements, design, and development of the system, and discuss lessons learned for future pandemic preparedness.

EUROPEAN POLICY OF SUSTAINABLE DEVELOPMENT OF AGRICULTURE: CHALLENGES FOR UKRAINE

Ukraine, despite the damages and losses inflicted on agriculture by Russian large-scale aggression, actively participates in the implementation of the main tasks of the global goals defined by the European strategy for sustainable development. The purpose of the article is to analyze the relationship between the policy of sustainable rural development of the European Union and the possibilities of its implementation in various spheres of life, economic, social, ecological, and institutional to support sustainable rural development in Ukraine. Ukraine is an active participant in the implementation of the system of transfer of knowledge and innovations in the agricultural sector – Agricultural Knowledge and Innovation Systems at the regional level, since the rural population needs to increase its own level of awareness of opportunities and potential risks in conducting economic activities and understanding of rational use of resources. The methodology includes analysis of the report on monitoring progress in achieving the goals of sustainable development in the context of the EU, which are directly related to agriculture or the development of rural areas, directives of the Commission of the European Union, statistical data of the State Statistics Service of Ukraine, primary and secondary sources. The originality of the article lies in the fact that in the article for the first time covers a detailed analysis of the indicators of the goals of sustainable development of agriculture and rural areas and their correspondence to the tasks of the strategy of the common European agricultural policy. The results of the analysis can be used in planning future projects for rural communities or agricultural enterprises to improve their social and economic situation

Validating Curriculum-Based Measurement Oral Reading Fluency (CBM ORF) Applicability To Evaluate Arabic Readers’ Performance

While curriculum-based measurement (CBM) accurately indicates reading skills, such as progress monitoring and early detection of reading difficulty, it has yet to be developed for Arabic. This study aimed to develop and validate a curriculum-based measurement for oral reading fluency (CBM-ORF) tailored to assess Arabic language students' reading abilities and create preliminary norms for students from second to sixth grades. Methods and Procedures: Various forms of the CBM-ORF were developed and administered to a sample of 414 students. After data analysis, the students' readings were rated by teachers to compare the CBM-ORF with an independent measure. Outcomes and Results: The results indicate that the CBM-ORF exhibits strong reliability and validity, making it a valuable tool for monitoring progress and identifying reading difficulties in Arabic readers. Furthermore, ORF norms have been established and proposed. Conclusions and Implications: This study emphasizes the absence of a valid reading tool for Arabic language students. It offers resources for teachers to make data-driven decisions, especially for students with learning disabilities.