Area Of Interest Research Articles

Milestone review: GABA, from chemistry, conformations, ionotropic receptors, modulators, epilepsy, flavonoids, and stress to neuro-nutraceuticals.

Arising out of a PhD project more than 50 years ago to synthesise analogues of the neurotransmitter GABA, a series of new chemical entities were found to have selective actions on ionotropic GABA receptors. Several of these neurochemicals are now commercially available. A new subtype of these receptors was discovered that could be a target for the treatment of myopia, the facilitation of learning and memory, and the improvement of post-stroke motor recovery. The development of these new chemical entities over many years demonstrates the importance of neurochemicals with which to investigate selective aspects of GABA receptors and illustrates the significance of collaboration between chemists and biologists in neurochemistry. Vital were the improvements in synthetic organic chemistry and the use of functional human receptors expressed in oocytes. Current interest in ionotropic GABA receptors includes the clinical development of subtype-specific agents and the role of gain-of-function receptor variants in epilepsy. Dietary flavonoids were found to cross the blood-brain barrier to influence brain function. Natural and synthetic flavonoids had a range of effects on GABA receptors, ranging from positive, silent, and negative allosteric modulators, to even second-order modulation of first-order modulators. Flavonoids have been called "a new family of benzodiazepines." Like benzodiazepines, flavonoids reduce stress. Stress produces changes in GABA receptors in the brain that may be because of changes in endogenous modulators, such as neurosteroids and corticosteroids. GABA also occurs naturally in the diet leading to studies of the effects of oral GABA on brain function. This finding has resulted in studies of GABA and related neurochemicals as neuro-nutraceuticals. GABA systems in the gut microbiome are essential to such studies. The actions of oral GABA and of GABA-enriched beverages and foodstuffs are now an area of considerable scientific and commercial interest. GABA is a deceptively simple chemical that can take up many shapes, which may underlie its complex functions. The need for new chemical entities with selective actions for further studies highlights the need for continuing collaboration between chemists and biologists.

War drives forest fire risks and highlights the need for more ecologically-sound forest management in post-war Ukraine.

Since 24 February 2022, Ukraine has experienced full-scale military aggression initiated by the Russian Federation. The war has had a major negative impact on vegetation cover of war-affected regions. We explored interactions between pre-war forest management and the impacts of military activities in three of the most forested Ukrainian areas of interest (AOI), affected by the war. These were forests lying between Kharkiv and Luhansk cities (AOI 'East'), forests along the Dnipro River delta (AOI 'Kherson'), and those of the Chornobyl Exclusion Zone (AOI CEZ). We used Sentinel satellite imagery to create damaged forest cover masks for the year 2022. We mapped forests with elevated fire hazard, which was defined as a degree of exposure to the fire-supporting land use (mostly an agricultural land, a common source of ignitions in Ukraine). We evaluated the forest disturbance rate in 2022, as compared to pre-war rates. We documented significant increases in non-stand replacing disturbances (low severity fires and non-fire disturbances) for all three of the AOIs. Damaged forest cover varied among the AOIs (24,180 ± 4,715ha, or 9.3% ± 1.8% in the 'East' AOI; 7,293 ± 1,925ha, or 15.7% ± 4.1% in the 'Kherson' AOI; 7,116 ± 1,274ha, or 5.0% ± 0.9% in the CEZ AOI). Among the forests damaged in 2022, the 'Kherson' AOI will likely have the highest proportion of an area with elevated fire hazard in the coming decades, as compared to other regions (89% vs. 70% in the 'East' and CEZ AOIs respectively). Future fire risks and extensive war-related disturbance of forest cover call for forest management to develop strategies explicitly addressing these factors.

Triglyceridemic Waist Phenotypes as Risk Factors for Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis

Introduction: Triglyceride waist phenotypes, which combine high triglyceride levels and central obesity, have recently emerged as an area of interest in metabolic disease research.
 Objective: To conduct a systematic review (SR) with meta-analysis to determine if triglyceride waist phenotypes are a risk factor for T2DM.
 Materials: SR with meta-analysis of cohort studies. The search was conducted in four databases: PubMed/Medline, Scopus, Web of Science, and EMBASE. Participants were classified into four groups, based on triglyceride level and waist circumference (WC): 1) Normal WC and normalConduct triglyceride level (NWNT); 2) Normal WC and high triglyceride level (NWHT), 3) Altered WC and normal triglyceride level (EWNT) and 4) Altered WC and high triglyceride level (EWHT). For the meta-analysis, only studies whose measure of association were presented as Hazard ratio (HR) along with 95% confidence intervals (CI95%) were used.
 Results: Compared to people with NWHT, a statistically significant association was found for those with NWHT (HR: 2.65; CI95% 1.77–3.95), EWNT (HR: 2.54; CI95% 2.05–3.16) and EWHT (HR: 4.41; CI95% 2.82–6.89).
 Conclusions: There is a clear association between triglyceride waist phenotypes and diabetes, according to this SR and meta-analysis. Although central obesity and high triglyceride levels are associated with a higher risk of the aforementioned disease, their combination appears to pose an even greater risk. Therefore, in the clinical setting, it is important to consider this when assessing the risk of diabetes.

Ten Influential Point-of-Care Ultrasound Papers: 2023 in Review.

In an effort to help keep busy clinicians up to date with the latest ultrasound research, our group of experts has selected 10 influential papers from the past 12 months and provided a short summary of each. We hope to provide emergency physicians, intensivists, and other acute care providers with a succinct update concerning some key areas of ultrasound interest.

Decolonizing the Design Process: A Case Study in Authorship, Power, and Control

While the concept of decolonization has long been an area of academic interest, it has more recently spilled over into mainstream discussion among designers, clients, and other cultural mediators. In Canada, this conversation has been amplified, in part, by the Truth and Reconciliation Commission (TRC), which has shed light on the destructive legacy of Canada’s settler colonialism and its Residential School Program. What started as a curriculum development project in the Design Formation Program at Langara College, necessitated a case study in how to turn theory to practice, primarily by investigating the structural biases inherent in the Western traditions of design and exploring ways in which that design paradigm might be shifted.

Abortion as a sociological case

AbstractFor over a century, abortion has been politically and socially contested, affecting people's lives through personal experience and/or public discourse. In the United States (US), abortion is sometimes exceptional—treated differently from other procedures, professions, and political issues—and sometimes an exemplar—an accessible example of a commonly occurring social, political, or personal phenomenon. It is, in other words, an excellent sociological case study. Yet the sociological literature on abortion is relatively thin. In this essay, we review research on abortion and opportunities for future sociological work in eight areas: gender; race; the body and embodiment; political economy; organizations, occupations, and work; medical sociology; law and society; and social movements. Sociologists have much to contribute to characterizing and understanding abortion, particularly following the 2022 US Supreme Court decision overturning the constitutional right to abortion. The discipline also has much to learn from studying abortion as a case. With its multifaceted social and political status and intersections with key areas of sociological interest, abortion offers a generative case for advancing sociological concepts, subfields, and constructs. While not exhaustive, our review aims to spark interest and inquiry, showcasing how a topic that spurs strong opinions can also catalyze sociological insights.

What makes a multimodal construction? Evidence for a prosodic mode in spoken English

Traditionally, grammar deals with morphosyntax, and so does Construction Grammar. Prosody, in contrast, is deemed paralinguistic. Testifying to the “multimodal turn,” the past decade has witnessed a rise in interest in multimodal Construction Grammar, i.e., an interest in grammatic constructions other than exclusively morphosyntactic ones. Part of the debate in this recent area of interest is the question of what defines a multimodal construction and, more specifically, which role prosody plays. This paper will show that morphosyntax and prosody are two different semiotic modes and, therefore, can combine to form a multimodal construction. To this end, studies showing the independence of prosody for meaning-making will be reviewed and a small-scale experimental study on the ambiguous utterance Tell me about it will be reported on.

Nurses and Climate Change: A Narrative Review of Nursing Associations' Recommendations for Integrating Climate Change Mitigation Strategies.

According to the World Health Organization, climate change is the greatest challenge of the twenty-first century. It is already affecting the health of many Canadians through extreme heat, wildfires and the expansion of zoonotic diseases. As trusted professionals, nurses are in favourable position to take action on climate change. To document the recommendations issued by Quebec, Canadian, American and international nursing associations regarding nursing practices that address climate change or environmental issues. This narrative review was conducted by establishing a list of environmental and general nursing associations in the geographical areas of interest through Google searches as well as by retrieving documents about climate change or environmental issues published by these organizations on their websites. Data related to the documents' characteristics and recommended nursing roles were then extracted. The review identified 13 nurses' organizations and 20 documents describing 37 recommendations for nurses in seven socioecological areas: individual, patient-focused, workplace, nursing associations, public health organizations, political and education. There is a gap between the breadth of roles that nurses may be called upon to play in addressing climate change and the degree to which relevant organizations are prepared to create the required conditions for them to do so. Several lessons emerged, including that the urgency of the climate crisis requires clear guidelines on how nurses can integrate climate change and its resultant health concerns into practice through nurses' associations, education and bottom-up nursing innovations. Funding is required for such initiatives, which must also prioritize health inequalities.

Social media analysis of pain outcomes following targeted muscle reinnervation

AimTMR was developed to improve myoelectric prosthesis control for amputees; however, it has become an area of interest in pain modulation. Studies show evidence that this procedure alleviates chronic pain in amputees. The primary objective of this study is to utilize social media analysis to understand patients’ post-operative pain, satisfaction, and recovery time after TMR. MethodsData was collected from one Facebook group via posts and comments referencing TMR. Posts published between January 1st, 2020, and March 24th, 2023, were analyzed. Data collected included pain prior to surgery, pain in immediate post-op period, and how pain changed after surgery. Results43 individuals commented on their TMR experience. 31 had favorable surgical outcomes, 7 felt surgery worsened their pain or there was not significant change in their pain levels, and the remaining 5 commented during the initial post-operative period. 24 patients described their pain in the immediate post-operative period and 100% said that post-operative pain was worse than chronic pain. Of 28 authors who commented on overall reduction in chronic pain, 24 reported TMR reduced their pain, while 4 had no change or worsened pain. ConclusionsThe 24 patients who reported improvement in chronic pain aligns with current literature suggesting that TMR is a viable treatment option for pain. Current medical management of similar conditions leaves up to 80% of patients unsatisfied with pain control. This analysis supports the evidence that TMR is an effective treatment for patients who are experiencing post-amputation pain.

Teaching and learning spelling: an analysis of 6th grade students' writing

Understanding how students acquire orthographic knowledge has become an area of interest for many teachers, especially Portuguese language teachers. As different theorists have argued, a reflective teaching-learning process is important, enabling students to understand graphophonemic relationships and overcome the obstacles that can arise in appropriating knowledge of orthographic conventions. This paper presents the results of a study which aimed to: Identify the most productive spelling changes in the writing of 6th grade students. The investigative analysis, carried out by means of quantitative-descriptive and field research, was based on eight written productions by 6th grade students from a public and state school in Piauí. The theoretical framework was based on studies by authors such as Cagliari (1994), Zorzi (1998, 2009, 2018), Morais (1999, 2000, 2007), Simões (2006), among others. This research, like the studies by Zorzi (1998, 2009), Miranda, Medina and Silva (2005), Quadros (2015), concluded that multiple representations, resulting from the arbitrariness of the system, are the most recurrent types of errors in the written productions of elementary school students. In view of this, it is argued that these errors should be understood as hypotheses that students formulate in order to acquire knowledge of the written language.

Drug–target affinity prediction with extended graph learning-convolutional networks

BackgroundHigh-performance computing plays a pivotal role in computer-aided drug design, a field that holds significant promise in pharmaceutical research. The prediction of drug–target affinity (DTA) is a crucial stage in this process, potentially accelerating drug development through rapid and extensive preliminary compound screening, while also minimizing resource utilization and costs. Recently, the incorporation of deep learning into DTA prediction and the enhancement of its accuracy have emerged as key areas of interest in the research community. Drugs and targets can be characterized through various methods, including structure-based, sequence-based, and graph-based representations. Despite the progress in structure and sequence-based techniques, they tend to provide limited feature information. Conversely, graph-based approaches have risen to prominence, attracting considerable attention for their comprehensive data representation capabilities. Recent studies have focused on constructing protein and drug molecular graphs using sequences and SMILES, subsequently deriving representations through graph neural networks. However, these graph-based approaches are limited by the use of a fixed adjacent matrix of protein and drug molecular graphs for graph convolution. This limitation restricts the learning of comprehensive feature representations from intricate compound and protein structures, consequently impeding the full potential of graph-based feature representation in DTA prediction. This, in turn, significantly impacts the models’ generalization capabilities in the complex realm of drug discovery.ResultsTo tackle these challenges, we introduce GLCN-DTA, a model specifically designed for proficiency in DTA tasks. GLCN-DTA innovatively integrates a graph learning module into the existing graph architecture. This module is designed to learn a soft adjacent matrix, which effectively and efficiently refines the contextual structure of protein and drug molecular graphs. This advancement allows for learning richer structural information from protein and drug molecular graphs via graph convolution, specifically tailored for DTA tasks, compared to the conventional fixed adjacent matrix approach. A series of experiments have been conducted to validate the efficacy of the proposed GLCN-DTA method across diverse scenarios. The results demonstrate that GLCN-DTA possesses advantages in terms of robustness and high accuracy.ConclusionsThe proposed GLCN-DTA model enhances DTA prediction performance by introducing a novel framework that synergizes graph learning operations with graph convolution operations, thereby achieving richer representations. GLCN-DTA does not distinguish between different protein classifications, including structurally ordered and intrinsically disordered proteins, focusing instead on improving feature representation. Therefore, its applicability scope may be more effective in scenarios involving structurally ordered proteins, while potentially being limited in contexts with intrinsically disordered proteins.

Machine learning algorithms for identifying autism spectrum disorder through eye-tracking in different intention videos

To investigate the differences in visual perception between children with autism spectrum disorder (ASD) and typically developing (TD) children when watching different intention videos, and to explore the feasibility of machine learning algorithms in objectively distinguishing between ASD children and TD children. A total of 58 children with ASD and 50 TD children were enrolled and were asked to watch the videos containing joint intention and non-joint intention, and the gaze duration and frequency in different areas of interest were used as original indicators to construct classifier-based models. The models were evaluated in terms of the indicators such as accuracy, sensitivity, and specificity. When using eight common classifiers, including support vector machine, linear discriminant analysis, decision tree, random forest, and K-nearest neighbors (with K values of 1, 3, 5, and 7), based on the original feature indicators, the highest classification accuracy achieved was 81.90%. A feature reconstruction approach with a decision tree classifier was used to further improve the accuracy of classification, and then the model showed the accuracy of 91.43%, the specificity of 89.80%, and the sensitivity of 92.86%, with an area under the receiver operating characteristic curve of 0.909 (P<0.001). The machine learning model based on eye-tracking data can accurately distinguish ASD children from TD children, which provides a scientific basis for developing rapid and objective ASD screening tools.

Assessment of Student Satisfaction With the Quality of Education Using the Example of One of the Departments of the Kyrgyz-Russian Slavic University

To improve the quality of education at a university, analysis of the educational process and organization of effective interaction between teachers and students are crucial. The professional activity of a university teacher is multifaceted and covers many types of work, which are assessed during periodic certification. However, evaluation of a teacher’s performance is incomplete without taking into account the opinions of students, which can be identified using a survey. Therefore, the teacher should be an interesting person; hence, his subject will become an interesting science area. This article presents a comparative analysis of the students’ satisfaction at the Faculty of Medicine with the quality of taught disciplines, such as biology, physics, medical informatics and evidence-based medicine. These subjects are given in junior and senior courses at the Department of Physics, Medical Informatics and Biology at the Kyrgyz-Russian Slavic University. This analysis was carried out for the first time at the department in 2020 (297 students), again in 2023 (504 students), and showed that in general the average score of the department increased slightly, as well as the pedagogical qualities of the teacher in the rating of lecture courses. Nevertheless, the ratings for practical classes remained unchanged. An analysis of students’ feedback expressed in free form to the teacher showed the majority of students are grateful for the teachers’ work.

Geospatial Crisis Index

Security geography examines the military geography factors influencing the security system and environment of an area, and its investigation method is rooted in geography. The data set related to this, mainly open source databases, is a rapidly changing data set, so its analysis only shows the current state, but if the data set is large enough and considered mass data, it may be suitable for drawing new connections and conclusions for the future. A geospatial analysis system applicable to security geographic analysis is under development, which is continuously collecting data by taking predefined variables into account for a specific area of interest. The geospatial crisis index can be obtained from these local data following a professional analysis procedure based on predefined algorithms. This new index is a unitless numerical value issued by the geospatial evaluation and analysis system used to analyse crisis zones. It is a benchmark allowing areas to be compared in terms of a fixed risk factor or factors to be ranked in a hierarchy by fixing the area. This helps shape the order of the analysis, speeds up the actual text and map evaluation, reduces the need for human resources, and supports commanders in decision-making.

Enhanced vacuum pair production by combination of two spatially separated electric fields

The effective enhancement of the pair production rate using a subcritical electromagnetic field is an active area of interest in quantum electrodynamics. Enhanced pair production was investigated using the Dirac–Heisenberg–Wigner (DHW) formalism with spatially separated electric fields. Symmetric and asymmetric combinations of two separate electric fields with the same temporal shape were considered. The interplay and dynamical assistance between the fields were examined from a numerical perspective to elucidate the effects of the spatial distance and asymmetry of the field on the pair production efficiency. For the symmetric combination, the total particle number was reduced with an increase in the distance between the two fields up to one Compton length and then remained constant with distance. For the asymmetric combination, the total number of created pairs increased significantly up to a distance of one Compton length. It was also determined that not only was the separation distance crucial for enhancing pair production, but the spatial field asymmetries were also important, both of which had nontrivial effects on the particle momentum distribution. Finally, we have studied the validity of the DHW and analytical approximation in the spatially separated two electric fields. We found that the analytical approximation could almost estimate the DHW results.

A314 UNDIFFERENTIATED PANCREATIC CARCINOMA WITH OSTEOCLAST-LIKE GIANT CELLS: A CASE REPORT

Abstract Background Pancreatic undifferentiated carcinoma with osteoclast-like giant cells (UCOGC) is a rare form of pancreatic cancer representing under 1% of cases. UCOGC is hypothesized to be a variant of pancreatic adenocarcinoma and while the pathophysiology is incompletely defined, it is felt to be an undifferentiated sarcomatoid carcinoma variant with chemotaxis of osteoclastic giant cells. Clinical, radiographic, or biochemical features do not reliably differentiate this from other tumors. Definitive diagnosis is made by histologic examination demonstrating non-neoplastic multinucleated osteoclastic giant cells (CD68 positive), mononuclear histiocytes, and neoplastic mononuclear cells. Aims To describe the case of a patient with UCOGC, highlighting key clinicopathologic features and management. Methods Case report and literature review. Results A 79-year-old man with atrial fibrillation on Xarelto presented with 4 months of abdominal pain, nausea, vomiting, and weight loss (22 kg). An MRI revealed a dilated main pancreatic duct and side branches with abrupt cutoff in the neck due to an ill-defined lesion. Endoscopic ultrasound confirmed a 36 mm hypoechoic ill-defined mass in the pancreatic neck. Biopsy performed with a 22-gauge needle with dry suction showed tissue fragments consistent with UCOGC (Figure 1). Unfortunately, the patient presented to hospital with worsened abdominal pain and nausea and was found to have new portal, superior mesenteric, and splenic vein thrombosis. His anticoagulant was changed to Dalteparin. A multidisciplinary cancer conference was held including input from experts in Toronto, and due to surrounding inflammation and new thrombosis he was not considered a surgical candidate at the time and neoadjuvant treatment with standard adenocarcinoma chemotherapy was planned. Unfortunately, the patient continued to decline and he was treated with palliative intent FOLFIRINOX for 2 cycles before opting for a medical assistance in dying procedure. Conclusions Treatment for UCOGC has not been well studied due to its rarity. Surgery is first-line therapy if appropriate based on patient status and cancer stage. The efficacy of chemotherapy and radiation is unclear but as a suspected adenocarcinoma variant, standard chemotherapy regimens are often used. Research is ongoing with an area of interest being PD-L1 inhibition due to high tumor PD-L1 positivity rates. Recognition of this rare entity is crucial due to its distinct diagnostic and therapeutic characteristics with more research needed to establish optimal therapy. Figure 1: Pathologic examination with HPS and CD68 stains demonstrating UCOGC Funding Agencies None

AI Strategy in Healthcare CHRM: Analyzing the Influence Organization Effective Performance Evidence from the Private Hospitals of Lahore Pakistan

Background: The advent of Artificial Intelligence (AI) within organizational frameworks, particularly in the realm of Human Resource Management (HRM), has initiated a transformative shift in operational efficiencies and strategies across various sectors. This integration aims to leverage AI's capabilities to augment human decision-making, enhance operational efficiency, and foster a culture of innovation within organizations. Despite the potential benefits, the practical application and tangible impact of AI strategies on organizational effectiveness remain areas of significant academic and practical interest. Objective: This study aimed to investigate the influence of AI strategies and creativity oriented HRM practices on organizational effective performance. It sought to explore the synergistic relationship between AI implementation and innovative HR practices, and their collective impact on enhancing organizational efficiency and performance metrics. Methods: Employing a cross-sectional survey design, the study collected data from employees working in private hospitals in Lahore, Pakistan. A total of 144 valid responses were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the relationships between AI strategy implementation, creativity-oriented HRM practices, and organizational effective performance. Reliability and validity of the constructs were evaluated through Cronbach's alpha, composite reliability, and average variance extracted (AVE) measures. Results: The findings revealed that AI strategy implementation (Cronbach's alpha = 0.942, AVE = 0.611) and creativity oriented HRM practices (Cronbach's alpha = 0.932, AVE = 0.585) were both significantly associated with enhanced organizational effective performance (Cronbach's alpha = 0.932, AVE = 0.533). The path analysis indicated strong positive relationships between AI strategies and creativity-oriented HRM practices (β = 0.688, p &lt; 0.001), between AI strategies and organizational performance (β = 0.228, p = 0.004), and between creativity-oriented HRM practices and organizational performance (β = 0.597, p &lt; 0.001). The model explained 59% of the variance in organizational effective performance. Conclusion: The study concludes that the strategic integration of AI within HRM frameworks significantly contributes to organizational effectiveness. Emphasizing creativity-oriented HRM practices in conjunction with AI strategies can lead to substantial improvements in organizational performance. These findings underscore the importance of a strategic approach to AI integration in HRM, highlighting the need for organizations to foster environments that promote innovation and creativity.

Approach to febrile neutropenia in patients undergoing treatments for hematologic malignancies.

Febrile neutropenia (FN) is common among hematologic malignancy patients, including recipients of hematopoietic cell transplantation (HCT) and cellular therapies such as chimeric antigen receptor (CAR)-T-cell therapy. Prompt empiric antibiotic use has been the mainstay for decades but a "one-size-fits-all" approach is no longer broadly accepted, as treatment-related infectious risk are more understood. Growing antimicrobial resistance is an increasing clinical challenge. Evolving strategies on de-escalation of broad-spectrum antibiotics in FN without identified infection are areas of particular interest.

Ultrasound-guided botulinum toxin injections of salivary glands in cerebral palsy children with sialorrhea

Objective: Excessive salivation and drooling are distressing problems that affect both children and their families. Salivary gland botulinum toxin injection is a widely studied therapeutic method for treating sialorrhea. The proper protocol for such treatment modality is an area of interest for researchers. This study set out to assess the success of ultrasound-guided botulinum toxin injections in either the submandibular or combined with parotid salivary glands for children with cerebral palsy suffering from sialorrhea, while also identifying factors that predict a positive treatment outcome. Method: This cross-sectional study included 30 children with cerebral palsy who have Sialorrhea. Ultrasound-guided botulinum toxin injections of submandibular salivary glands alone or combined with parotid glands were done. Drooling was evaluated using Drooling Rating Scale, Drooling Impact Scale, and 5-minute Drooling Quotient. Children were followed up weekly for 12 weeks after botulinum toxin injections. Result: All children showed a significant decline in drooling and sufficient caregivers’ satisfaction for the first 8 weeks after botulinum toxin injections, with gradual worsening of drooling later in 60% of children. Assessment scores were significantly lower in those who received combined parotid and submandibular injections than those who received submandibular gland injections alone. Changes in drooling scores have a significant negative correlation with the severity of motor disabilities. Conclusion: Submandibular salivary gland injection alone has a satisfactory response in decreasing drooling in children with cerebral palsy. However, a combined injection of both parotid and submandibular salivary glands gives a better response for at least 8 weeks without complications. This study not only addresses the clinical effectiveness of botulinum toxin injections in managing sialorrhea in children with cerebral palsy but also opens avenues for improved dietary strategies. Keywords: botulinum toxin; salivary gland; sialorrhea; cerebral palsy

A retrospective study exploring parents' perceptions of their child's assessment.

The current study investigates parents' perceptions of their child's assessment, focusing on their responses to the Italian version of the Parents' Experience of Assessment Scale (QUEVA-G). Twenty parents, who voluntarily agreed to be contacted after completing the questionnaire, participated in qualitative interviews to gain deeper insights into their assessment experiences. A thematic analysis was conducted on the interview transcriptions, highlighting three primary domains of parental experience: (1) parental perceptions of the assessment process; (2) effects of the assessment; and (3) parental perceptions of their relationship with their children's teachers. The findings indicate that the QUEVA-G accurately captures most areas of interest as well as reveals unexplored aspects.