Plain Language Summary What is this summary about? The AboLiSh study looked at how well people with leg spasticity achieved their treatment goals after receiving botulinum toxin (abobotulinumtoxinA) treatment over 16 months. All participants received at least one injection. What are the key takeaways? Most patients benefited from the treatment. After the first injection cycle, 72% to 84% of patients reached their personal goals – such as walking better or having less pain. Results continued to improve with additional injection cycles. The study also found that using tools to guide the injections into the correct muscles (like ultrasound, electrical stimulation, or electromyography) increased the chances of success. The safety of abobotulinumtoxinA was also confirmed. What were the main conclusions reached by the researchers? The study supports using abobotulinumtoxinA to treat leg spasticity after a stroke, especially when treatment goals are clearly defined and guided injection techniques are used. These findings can help clinicians make informed decisions when treating their own patients with abobotulinumtoxinA. How to say (download PDF and double click sound icon to play sound)… abobotulinumtoxinA: AB-oh-BOH-chew-lih-num-tox-in-A Botulinum toxin: BOH-chew-lih-num tox-in Spasticity: spa-STISS-ih-tee AbobotulinumtoxinA: A type of botulinum toxin used to treat spasticity and other conditions. Botulinum toxin: A type of protein called a neurotoxin, which stops muscles from contracting. Botulinum toxins, often known for their use in cosmetic treatments, are also commonly used to treat medical conditions that involve unwanted muscle contraction – such as muscle stiffness from over contraction of muscles (spasticity) after a stroke. Spasticity: A common post-stroke condition that affects 30–40% of stroke survivors and causes stiff or rigid muscles due to prolonged muscle contraction. Treatment goals: Specific aims that a patient and their healthcare provider work towards during the treatment process. This is an abstract of the Plain Language Summary of Publication article. View the full Plain Language Summary PDF of this article to read the full-text Link to original article here Trial registration: ClinicalTrials.gov identifier: NCT04050527.

Endovascular therapy (EVT) has proven benefit for patients with anterior circulation large vessel occlusion (LVO) strokes with moderate-to-severe deficits, but its value in patients presenting 6-24 hours after onset with mild symptoms (NIH Stroke Scale score ≤5) remains unclear. This journal club article examines a retrospective analysis of CLEAR registry data comparing EVT with medical management in this patient subgroup. The authors used multivariable regression and sensitivity analyses to adjust for baseline differences but found no significant association between EVT and improved functional outcomes. Key takeaways for trainees include critical appraisal of nonrandomized data, interpretation of nonsignificant results, and understanding the role of adjusted models and sensitivity analyses in observational research. Limitations of this study include its retrospective, nonrandomized design and potential for selection bias. Until randomized trial data from ENDOLOW and MOSTE become available, treatment decisions should be individualized, incorporating imaging findings and clinical context.

Contemporary marketing thoughts seem too rigidly glued to the view that consumer purchase decision-making processes are primarily motivated by extrinsic variables and rational drivers more than anything else. However, neuroscientific evidence from archived and current sources shows that intrinsic brain processes activated by subtle sensory cues significantly influence consumer purchase decisions. Exploring that illuminating discourse, this study employs a meta-analytical approach, systematically searching databases such as Scopus and Web of Science to synthesize existing literature to bring out insights that enrich our understanding of consumer behaviour. The analysis culminates in the conceptualisation of a five-construct neurological model that embody the sequential consumer decision-making process as comprised of: the challenge, inquiry, experiment, experience, and content. Rigorous inclusion-exclusion criteria narrowed an initial pool of 457 articles to 98 relevant studies, assessing sample sizes, demographic characteristics, and effect sizes. The DerSimonian-Laird random-effects model evaluated between-study variance, supplemented by sensitivity and stratified analyses to refine insights. Key takeaways from the model highlight the importance of addressing intrinsic consumer needs during the neural challenge stage, delivering clear information during neural inquiry, and enhancing brand loyalty through experiential learning in neural experimentation. This theoretical framework enriches our understanding of the interplay between emotion and rationality, offering practical implications for marketing strategies and encouraging insights into evolving consumer psychology.

Streamlined and accelerated nonclinical development of COVID-19 vaccines and therapeutics - an IQ consortium DruSafe survey.

Among the fields where Artificial Intelligence (AI) tools are having an impact is the legal profession, and law librarians are among those positioned to help law students understand, assess, and make use of relevant AI tools during their time as law students and to develop skills in, and recognize the implications of, using AI options that will be part of their new work environments once they formally begin their legal careers. One way of capturing law student attention and emphasizing key features of generative AI tools while also highlighting some key implications of using such tools in the legal profession is through a case exhibit. Exhibits can provide a simple and effective way to engage audiences and convey information. This study describes the creation and implementation of an exhibit titled Lawyering and AI that was displayed in the entry area of the MacMillan Law Library at Emory University’s School of Law between fall 2023 and January 2024. This is a chronological account of the stages and steps involved in creating the exhibit. The exhibit benefitted the Law School community – and law students in particular – by conveying information about some of the ways in which AI is impacting and will continue to impact the practice of law. The author describes the process of creating a display case exhibit that combined images and text, including topical examples from legal news and law firm reports. Primary goals of the project, tools used to create the display, and key takeaways are presented.

Sustainable tourism education integrates tourism economic, environmental and socio-cultural impacts and learners’ understanding while fostering critical thinking, systems thinking, and responsible action toward sustainable development goals (SDG). While previous studies focused on collaborative teaching and sustainable tourism education separately, the integration of Spanish culture, computer-supported collaborative learning (CSCL) and sustainable education are notably scarce suggesting the current research as both timely and innovative. This study addresses the gap by assessing learners’ overall perceptions and understanding of Spanish culture in relation to sustainable tourism education. It exemplifies a collaborative pedagogical design that augments formal academic with authentic cultural insights from a native expert under the collaborative teaching module between HTT280 Geography and Culture in Tourism lecturers at UiTM Alor Gajah Campus and the Embassy of Spain in Malaysia. A post-webinar survey was administered to 98 participants following the session. Descriptive analysis summarized participants’ perceptions while thematic analysis was employed to identify key cultural takeaways and additional feedback. Findings indicated that the webinar significantly enhanced participants understanding of Spanish culture, demonstrating its effectiveness in fostering cultural awareness. The webinar’s content delivery and the value of the cultural experience was found to be effective. The native speaker’s deep-rooted knowledge and firsthand experience in Spanish culture and tourism and shared reflections acted as key drivers that shaped their learning experience. The webinar’s format, duration, and platform were perceived as effective in delivering ethical and cultural learning outcomes, suggesting that sustainable tourism education conducted virtually can be as impactful as conventional face-to-face methods. The study’s implications suggest that adopting collaborative teaching to create authentic learning experiences fosters intercultural understanding, vital for sustainable tourism education. Furthermore, investing in digital technology demonstrates a scalable and environmentally-friendly approach to align cross-cultural education with sustainability principles. Consequently, stakeholders and policymakers should design a comprehensive syllabus integrating collaborative pedagogies and digital learning to enhance cultural competence while minimizing the carbon footprint.

Abstract Non-thermal food processing has opened up new space and has emerged as a promising alternative to conventional thermal methods of food processing. These foods meet the growing consumer demands for high-quality, convenient, and minimally processed foods. The idea of proposing a machine learning (ML) strategy for finding the optimum process parameters and kinetics in food processing applications is new and challenging, but this new innovative approach requires considerable scientific effort. This review presents the applications of ML in the optimization of non-thermal food processing technologies such as high-pressure processing (HPP), pulsed light (PL), ultrasound (US), pulsed electric fields (PEF), cold plasma (CP), and irradiation (IR). These technologies have exhibited conspicuous advantages with respect to microbial inactivation, preservation of food quality, and environmental sustainability. Integration of ML with non-thermal technologies will enable better control and monitor in real time and optimize critical parameters such as pressure, frequency, and treatment duration. While numerical models have conventionally been used successfully for process optimization, ML provides better adaptability by identification of complex nonlinear relationships in food systems for more accurate prediction and adjustment. The key takeaways of this paper lie in the ML-driven monitoring system, integrated sensors, and real-time data accumulation in response to enhancing process efficiency with dependency natures inherently presented by food matrices. Further development of ML models, apparatus collection, and intelligent systems is expected to yield non-thermal food processing methods with enhanced sustainability, safety, and quality.

Key Takeaways Lowering per‐ and polyfluoroalkyl substances (PFAS) levels in the long term requires more than end‐of‐pipe treatment and expensive infrastructure upgrades. A continuous‐improvement framework can serve as a guide for active communication and engagement with upstream industrial dischargers. Measurement and monitoring, source reduction, management, and workforce development form essential pillars for effective PFAS management.

Key Takeaways Drinking water distribution systems may use chlorine or chloramines to maintain a secondary disinfectant residual all the way to customer taps. Improvements are needed to ensure accurate, reliable, user‐friendly field measurement methods for monitoring chloramine species. Establishing a robust baseline of system data on free chlorine and chloramine species is key to managing residual disinfectants.

Key Takeaways Smart water distribution systems are highly susceptible to false data injection attacks that can compromise reliability and safety. False data injections on pumping stations could cut off water supply and drive up operational costs. Leakages and disturbances can amplify the impact of cyberattacks, resulting in worst‐case operational losses. The vulnerability assessment model presented in this article can help utilities strengthen the security of their smart water distribution systems.

The advent of sixth-generation (6G) technology heralds a new era in telecommunications, promising to revolutionize connectivity by addressing the limitations of its predecessors and introducing groundbreaking advancements. This paper gives a comprehensive overview of 6G, highlighting its potential to deliver unprecedented data rates, ultra-low latency and enhanced reliability. Unlike 5G, which primarily focuses on improving mobile broadband and IoT, 6G aims to integrate a wider range of services, including holographic communication, pervasive Artificial Intelligence (AI), Internet-of-Everything (IoE) and advanced edge computing. Research indicates that 6G will leverage technologies such as terahertz (THz) communication, intelligent reflecting surfaces (IRSs), optical wireless communication (OWC), visible light communication (VLC) and quantum communication, thereby enabling applications that were previously deemed impossible. These advancements are expected to support industries ranging from healthcare and education to smart cities and autonomous systems. However, challenges such as spectrum management, security, resource optimization and the environmental impact of 6G infrastructure remain significant. This paper synthesizes key insights from recent studies, providing a comprehensive overview of the technological 6G landscape, its convergence, potential applications, design challenges and the sustainable future research directions necessary to realize the full potential of 6G. Finally, the key takeaways for the readers are provided.

Case Description: A 66-year-old male with a history of non-obstructive coronary artery disease [Image 1], unprovoked pulmonary embolism, hypertension, and diastolic heart failure presented with left-sided chest pressure three weeks post-NSTEMI. High-sensitivity troponin was elevated at 141 ng/L. He concurrently reported fingertip pain, intermittent confusion, and dizziness. On hospital day two, he developed acute delirium, digital ischemia [Image 2], and right upper extremity pain. Brain MRI revealed multiple acute infarcts in bilateral frontoparietal, thalamic, and parieto-occipital territories [Image 3]. Despite therapeutic anticoagulation, a right upper extremity venous duplex showed acute brachial vein thrombosis. Anticoagulation was temporarily held, and warfarin was initiated due to suspected apixaban failure. Laboratory workup revealed markedly elevated antiphospholipid antibodies (cardiolipin IgG >112 GPL, β2-glycoprotein I >112 SGU) and progressive thrombocytopenia (253K --> 91). Additional findings included retinal cotton wool spots and digital ischemia, confirming multi-organ involvement consistent with CAPS. The patient was treated with combination “triple therapy” (therapeutic anticoagulation, high-dose steroids, and plasmapheresis), alongside rituximab, achieving clinical stabilization. Notably, failure of direct oral anticoagulant therapy reinforces the importance of using vitamin K antagonists in high-risk APS, consistent with current EULAR recommendations. Discussion: This case illustrates CAPS masquerading as recurrent ACS, with diagnostic ambiguity compounded by prior cardiac history and elevated troponins in the absence of coronary obstruction. Key red flags—including multi-territory infarcts, peripheral thromboses, and systemic signs—should prompt early evaluation for APS/CAPS. DOAC failure in this context adds to the growing evidence base against their use in high-risk APS patients. Warfarin remains the first-line therapy, particularly in triple-positive cases or those with recurrent thrombosis. Key Takeaways: 1. Consider CAPS in patients with thrombotic events despite adequate anticoagulation. 2. Elevated troponins with non-obstructive coronary disease may reflect microvascular thrombosis. 3. Early recognition of multi-organ involvement is vital to prevent morbidity and mortality. 4. This case reinforces guideline-directed therapy with warfarin in high-risk APS/CAPS.

Summary Chronic inflammation has been recognized as a key contributor to cancer initiation, progression, and treatment response across various malignancies. In this short review we summarize the key takeaways from ASCO 2025 with regard to studies presented on chronic inflammation and cancer. Emerging evidence suggests that systemic inflammation can be modulated by lifestyle-based interventions such as diet or physical activity. Systemic inflammation may also contribute to complex symptoms such as cancer-related fatigue or depression, impairing quality of life. Markers of systemic inflammation such as the neutrophil-to-lymphocyte ratio can be used as prognostic markers and highlight the role of myeloid-driven inflammation in cancer. In line with this, clonal hematopoiesis—an aging-associated condition of clonal myeloid immune cell expansion—is commonly identified infiltrating solid cancers, shaping the immune landscape of the tumor microenvironment and thereby modulating cancer behavior and therapy effectivity.

Impacts of Nutrition Policy on Food Insecurity and Individual Health in the United States: A Narrative Review.

Nondegradable implants, such as titanium or steel screws, are commonly used in orthopedic surgery as they provide strength and stability. However, metallic implants have been associated with multiple issues, such as additional surgery to remove hardware, interference with imaging modalities, and stress shielding. Biodegradable magnesium-based implants are an innovative alternative due to good biocompatibility and osteoconductivity, similar to Young’s elastic modulus to bone, and they exhibit less metallic distortion in imaging modalities. The MAGNEZIX compression screw became the first magnesium implant to be approved for use in humans and has been widely used ever since, most commonly in foot and ankle conditions, with generally good outcomes. Despite its advantages, implant biodegradation introduces unique imaging challenges that can be misinterpreted as complications. This article aimed to familiarize radiologists and clinicians with the expected imaging findings of magnesium-based implants to reduce unnecessary advanced imaging and misdiagnosis. Pre-operative and post-operative radiological images of 75 patients with foot and ankle injuries who were treated with MAGNEZIX screws between 2020 and 2022 in Changi General Hospital were retrospectively evaluated. Selected cases are presented in detail to illustrate key principles in understanding radiological findings of MAGNEZIX screws.Seven cases are presented in detail with pre-operative and serial post-operative images, along with each case emphasizing a key learning point essential to understanding when interpreting radiological images of patients who receive MAGNEZIX screws as part of their treatment. Key takeaways include the following points: (1) recognizing the normal evolution and degradation pattern of magnesium implants and being aware of potential pitfalls, (2) the importance of correlating radiological findings with clinical assessment, (3) effective multidisciplinary communication, and (4) staying updated with ongoing literature on degradable magnesium-based implants. Biodegradable implants, such as MAGNEZIX screws, are an innovative and effective alternative to metallic implants in orthopedic surgery. However, knowledge of the expected imaging findings of magnesium-based implants after insertion is essential in reducing unnecessary advanced imaging and misdiagnosis.

ABSTRACT In VUCA-world conditions, collaborative approach in business processes is the prevailing understanding. Collaboration is supported by smart technologies and extended to cross-partner innovation creation. Simultaneous utilisation of various smart technologies reforms design and innovation processes. Via an integrative review, this article overviews the smart technologies in relation to collaborative innovation and develops a generic framework. Benefits and performance improvements obtained in the design and innovation lifecycle are discussed comprehensively. Findings reveal main contributions of these technologies as: seamless integration of design databases with ERP and manufacturing systems; accelerated dynamic innovation processes; designer collaboration via virtual platforms; rapid joint prototyping via simulation, virtual and augmented reality tools; and active customer involvement in design via 3D-printer technology. Hardships to obtain technology-based collaboration across partners are discussed under the dimensions of ‘technological’, ‘managerial and organisational’, and ‘behavioural and cultural’, key takeaways being offered under each dimension. Results indicate the vitality of handling the soft aspects along with technological components.

Cancer-related loneliness is a feeling of social disconnection caused by a diagnosis of cancer, and it is associated with individuals' cancer-related social expectations. It is conceptually distinct when compared with loneliness in a general population due to the unique challenges of cancer. Cancer-related loneliness also impacts close persons including caregivers and dependent youth, with both these populations reporting experiences of loneliness. Given that loneliness is related to a range of harmful psychological and physical outcomes, and there is a paucity of interventions to address cancer-related loneliness in patients and close persons, it is vital for healthcare professionals to be aware of loneliness in these populations. This review provides key takeaways for healthcare professionals to best support patients and close persons experiencing cancer-related loneliness and provides recommendations for future research directions.

Abstract - We present a comprehensive study exploring quantum machine learning (QML) approaches for plant disease detection from leaf images and compare them against well-established classical counterparts. Specifically, we implement and analyze Quantum Support Vector Machines (QSVMs) vs classical SVMs, and Quantum Convolutional Neural Networks (QCNNs) vs classical CNNs. Using the widely used PlantVillage and complementary field datasets, we describe image preprocessing, classical baseline architectures, quantum data-encoding strategies, circuit-level QSVM and QCNN designs for near-term quantum devices, and hybrid training procedures. Where possible, we review literature-reported performance and propose a reproducible experimental pipeline for empirical evaluation on simulated/noisy quantum backends. We discuss expected strengths and limitations of quantum approaches (expressivity, kernel advantages, resource constraints), provide detailed evaluation metrics and ablations, and propose directions for real-device experiments and field deployment. Key takeaways: QSVM/quantum-kernel methods can provide superior separability on certain feature maps and small-to-medium-sized datasets, while QCNNs show promise as compact feature extractors for hybrid pipelines — but both approaches currently require careful circuit design and error-mitigation to outperform well-tuned classical models in realistic field settings. Key Words: QCNN, Plant Disease, SVM, CNN, QSVM

Soil health is critical for healthy cities, yet little is known about how communities experience and address soil contamination. Contamination of soils can expose residents to heavy metals, which may have detrimental health effects. This study focuses on Buffalo, NY, using a mixed-methods approach to understand community experiences surrounding soil contaminants, planning, and policy. Findings reveal that spatial patterns of lead contaminants mirror segregation patterns, echoing environmental justice concerns. Residents engage in individual self-help actions, but some adopt risk-averse behaviors. Key takeaways include how policy tools are used to address issues of soil contamination and recommendations for addressing this issue.

Re-analysis results (Left) and takeaway messages (Right) are summarized above. RCOP, reverse crossover point. Figure created with Biorender.com.Reverse Crossover Point (RCOP) analysis showing a man on an exercise bike and running, indicating training intensity. A graph illustrates substrate oxidation levels over time, with fat oxidation surpassing carbohydrate oxidation. Key takeaways: Fat oxidation increased significantly despite carbohydrate intake, suggesting additional carbohydrate sources and reliance on lipids for energy.