Background: It is expected that blinatumomab will be increasingly incorporated into the care of children with B-lineage acute lymphoblastic leukemia (B-ALL) based on improved survival for subsets of patients, and a favorable safety profile. Most of the 28-day continuous infusion can be administered in outpatient or home settings. Limited studies have described low rates of complications at home when appropriate safety plans are in place. However, home administration shifts the burden of monitoring and care to caregivers. Procedure: Caregivers of children with B-ALL within one month of completing a first cycle of blinatumomab at home were recruited from three tertiary care centers and participated in virtual, audio-recorded, semi-structured interviews, with translation services available as required. Interviews were transcribed, coded independently in duplicate, and analyzed using thematic analysis. Identified caregiving context-specific barriers and facilitators were coded deductively. Results: Participating caregivers (n=21) described a timebound confidence response where initial infusion anxiety was gradually replaced with caregiving self-assurance. Growing confidence co-occurred with improved caregiver wellness and child quality of life characterized by resuming more usual family activities amid therapy. Barriers and facilitators to successful home-based blinatumomab included caregiver, access to hospital-based support, and particular aspects of a family’s social and material environment and these underpinned recommendations for future caregivers. CONCLUSIONS: Caregivers can confidently manage home-based continuous infusion blinatumomab with anticipatory guidance and support and with attention paid to context-related modifiers to care. Caregiver insights should be reflected in the principles that become the basis of future pediatric B-cell ALL clinical trials and care.

Retinoblastoma mortality remains high in many low- and middle-income countries (LMICs), primarily due to late diagnosis and delayed treatment. While efforts have been made to implement systematic screening at a population level, its feasibility remains challenging, except for subjects with germline Rb1 mutation and family history for retinoblastoma. Screening for retinoblastoma faces significant challenges, including the lack of a reliable, widely available test with high sensitivity and specificity. Smartphone applications or red-eye reflex have shown potential in detecting leukocoria, but their real-world utility is uncertain. Early diagnosis actions have been recommended to improve outcomes in LMICs. This requires not only timely detection but also ensuring that patients reach centers of excellence and they are referred and diagnosed expeditiously while minimizing treatment abandonment. Strengthening early diagnosis efforts through public awareness campaigns, primary care education, and streamlined referral pathways is essential. The impact of early diagnosis actions should improve the disease-free survival rate, reduce cases diagnosed at the extraocular stage which would lead to diagnosis at a younger age. Efforts should prioritize robust early diagnosis by strengthening the health system, universal access to specialized retinoblastoma centers and abandonment reduction programs over universal screening.

This paper introduces a comprehensive theoretical framework that integrates quantum mechanics and metaphysical philosophy to investigate the intricate relationship between cosmic order and governance. In an effort to transcend the traditional divide between science and philosophy, this study establishes its foundations in mathematical formalism and empirical analogies, thereby mitigating the risk of philosophical overreach often associated with theoretical physics. The proposed framework reimagines quarks as fundamental nodes within a cosmic information network, governed by the principles of quantum chromodynamics (QCD) and non-local coherence, offering a novel perspective on the interconnectedness of physical phenomena. Central to this exploration is the development of a Nash equilibrium model, which balances deterministic constants (α), probabilistic variables (β), and stochastic noise (γ), drawing inspiration from quantum indeterminacy and theological notions of free will. Furthermore, the study fosters interdisciplinary dialogue by bridging ancient and modern philosophical paradigms—such as Platonic Logos, Penrose’s twistor theory, and Quranic Qadar —through carefully constructed thought experiments and analogies, ensuring a clear distinction between empirical observations and metaphysical interpretations. The research concludes by proposing future experimental directions, including collider tests and quantum sensor arrays, aimed at grounding the Cosmic Control Panel model in empirically verifiable science. By challenging reductionist paradigms while upholding theoretical humility, this study lays the groundwork for a rigorous and testable interdisciplinary framework, paving the way for deeper insights into the harmonious interplay between cosmic determinism and human agency.

The increasing reliance on machine learning (ML) models in critical applications has heightened concerns about model poisoning attacks, where adversaries manipulate training data to compromise model integrity. To address this challenge, we propose a comprehensive framework for detecting ML model poisoning using a novel integration of forensic analysis techniques. Unlike traditional approaches that focus on input data anomalies, our framework analyzes the model itself to uncover signs of poisoning. We integrate reverse engineering (model inversion), topological data analysis, Shapley values, and Benford’s Law analysis to systematically identify subtle deviations indicative of adversarial manipulation. We evaluate our proposed framework on multiple deep learning architectures, including convolutional neural networks, ResNet-18 and YOLOv8, used to train models using the CIFAR-10 dataset. Further, we benchmark our framework against existing forensic analysis and ML model poisoning detection techniques, highlighting its improved detection capabilities. Our findings establish a robust and interpretable methodology for securing ML models against sophisticated model poisoning attacks, paving the way for enhanced resilience in real-world deployments.

An accurate understanding of river dynamics is critical to preserve ecological diversity, supporting economic activities, and addressing environmental challenges amidst climate change. To tackle these challenges, advanced modeling tools are essential to grasp historical river dynamics and thus project future scenarios effectively. This study introduces a hybrid approach that integrates physics-based models and deep learning to reconstruct long-term water level, applied for the Seine Estuary in Normandy, France. Deep learning models initially enhance the well-established physics-based model by refining its input data to provide more reliable hydrodynamic simulations as a baseline. The outcomes of this physics-based model, combined with diverse data sources, then feeds the relative neural network to enhance overall performance. This successive refinement optimizes the utilization of complex spatial and temporal variability observed across extensive modeling areas, leveraging Bidirectional Long Short-Term Memory neural networks to enhance the quality of both models. The study thus highlights the explainability and significance of datasets in driving the output accuracy across various hydrodynamic zones. The hybrid approach outperforms standalone physics-based and traditional deep learning models, achieving roughly 58% reduction in RMSE compared to the physics-based model. Insights reveal that reconstruction accuracy mainly relies on physics-based outcomes and observational data, with their relevance to the target station. During major storm events since 2017, this hybrid model has consistently enhanced accuracy by 50-65% in RMSE, highlighting its superior performance under challenging conditions. This approach holds promise for application to other rivers and broader hydrological challenges.

In vivo investigation of STN1 downregulation in melanoma formation in adult mice following UV irradiationSara Knowles1, Maarten C. Bosland2, Shobhan Gaddameedhi3, Weihang Chai1, *1 Center for Genetic Diseases, Rosalind Franklin University of Medicine and Science, North Chicago, Illinois2 Department of Pathology, University of Illinois Chicago, Chicago, Illinois3 Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina* Corresponding author:Weihang Chai, PhD.ProfessorCenter for Genetic DiseasesRosalind Franklin University of Medicine and ScienceNorth Chicago, IL 60064Email: weihang.chai@rosalindfranklin.eduPhone: 847-578-8517

The emergence of wireless technology brought about enhanced communication across various devices, resulting in the demand for efficient and reliable wireless networks, like wireless mesh networks (WMNs) and mobile Ad-hoc Networks (MANETs). MANETs are known for their decentralized nature, rapid deployment, infrastructure-less, adaptability, and ease of use in several applications and outdoor events. Despite its flexibility, it often faces challenges relating to security vulnerabilities, together with blackhole and grayhole attacks and trade-offs in terms of performances relating to reliability and integrity. This paper proposes an improved, innovative routing protocol for Ad-hoc On-Demand Distance Vector (AODV) by infusion of blockchain’s proof of stake (PoS) consensus mechanism named PoSAODV, whose objective is to enhance security, energy-efficiency, and adaptability while reducing packet loss rate, routing overheads and increase throughput. Smart contract-based validator selection was utilized to ensure fairness and reduce blackhole and grayhole attacks. The result obtained through simulation demonstrates that PoSAODV outperforms the original AODV by reduced latency of 0.79 milliseconds, average throughput of 45Mbps, and packet delivery ratio of 80% to 100% in both unsafe and safe environments. This makes PoSAODV suitable for resource-constrained ad-hoc networks with dynamic topologies.

Methane (CH4) ebullition is a major emission pathway in lakes. However, ebullition remains difficult to assess, and data from large lakes are scarce. This study investigates ebullition in the littoral zone of a large lake, demonstrating that ship waves, even after traveling long distances, regularly trigger gas bubble releases from the sediments in shallow waters. Although these ebullitions events occur only during the short time intervals of ship-wave passages, they lead to substantial CH4 emissions. Comparing several littoral sites, we assess the frequency and extent of ship-wave-induced ebullition events and contrast them with ebullition caused by a storm event. Our findings reveal a strong cross-correlation between pressure drops due to ship waves and ebullition fluxes, highlighting ship-wave-induced pressure changes as a significant yet understudied driver of CH4 emissions in lakes. With ship traffic on lakes steadily increasing, understanding ship-wave-induced ebullition is essential for improving estimates of lake-wide CH4 emissions.

Home and preschool are central contexts for children’s language development. However, the child’s language environment—adult speech around the child, the child’s own speech production, and conversational turns between the child and adults—is rarely compared between these contexts. Furthermore, we know little about potential differences between children with and without autism spectrum disorder (ASD) in the two contexts. We used objective measures of vocalizations to quantify children’s real-time dyadic vocal interactions. Participants included 11 preschoolers in an inclusive classroom, observed both at home and in preschool. Overall, there were no significant differences in child vocalizations, conversational turns, and adult word counts between preschool and home. However, children with ASD exhibited larger effects of context—having higher rates of conversational turns at home than in preschool—than other children. Findings highlight the interaction between children’s developmental characteristics and the external environment as drivers of language environment in early childhood.

Studying intergenerational transmission of parenting enriches our knowledge of similarities and differences in parenting across generations, but existing research is largely limited to quantitative studies. This qualitative study explored parent-child relationship quality and parenting behaviours across generations among Dutch women who have raised their children without the biological father present in the home ( n = 17, M age = 51.53 years, range = 37-65 years). Thematic analyses revealed that women 1) reported closer relationships with their children than with their parents, 2) often only partially continued how they were raised themselves, and 3) related continuities and discontinuities in parenting to the context of non-residential fatherhood – specifically to the support and stress they experienced raising their children without the biological father present in the home. This qualitative study provides a comprehensive understanding of potential explanations for intergenerational transmission of parenting, which may help to identify intervention targets to reduce the transmission of suboptimal parenting practices.

Einstein's Theories are considered as significant theories of the nowadays Science of Physics. However, the nowadays Science of Physics did not provide yet a verified theory for unifying the Gravitation and the Electromagnetism. Kaluza Klein Theory addresses that issue by predicting that there are five dimensions, with the fifth dimension being of the shape of a tiny circle, with a radius of 23 times the Planck length, which is of the order of 10 −33 cm. However, because there is no foreseeable technology for verifying that prediction, about that fifth dimension, the Kaluza Klein Theory is not yet accepted as a complete viable theory, which implies that the issues of presenting a theory which unifies the Gravitation and the Electromagnetism is still an open issue. This paper, and several other preprints, by the author of this paper, also tries to address that issue, by presenting an alternate theory, which is also accompanied by a proposal for an experiment, which might either disprove the proposed theory, if the proposed experiment implementation will turn out to be unsuccessful, or, alternatively, provide validity to the proposed theory, if the proposed experiment implementation will turn out to be successful.

Advances in methodologies and technologies over the previous decade has led to a depth of analysis of a cell’s biomolecules that is unprecedented, with entire genomes able to be sequenced in hours and up to 10,000 transcripts or ORF products (proteins) able to be quantifed from a single cell. Methods for analysing individual omes are now optimised, reliable and robust but are often performed in isolation with other biomolecules considered contaminants. However, there is a growing body of systems biology studies that aim to study multiple omes from the same sample. This review details the current state of the “multi-omics” field, trying to define what the field is, the methodologies employed and the challenges facing researchers in this field. It also critically evaluates whether these approaches are “fit-for-purpose” and how the field needs to evolve to enhance our understanding of how biomolecules from distinct omes interact with one another to alter cellular phenotype in response to change.

Seasonality in temperate ecosystems shapes species phenology, influencing interactions and food web structure. Variations in species richness and biomass affect trophic interaction strength, a crucial factor for community stability, which can be assessed through energy fluxes—an essential indicator of ecosystem function. Yet, we still have limited understanding on how energy fluxes and food web structure vary overtime and how the seasonal dynamics influence stability. We examined how the structure, energy fluxes and stability of a highly resolved multitrophic lake food web change across seasons over three successive years. Two estimates representing different facets of stability were considered: resilience and reactivity. We found a strong seasonal pattern in food web structure, with higher complexity observed in summer and autumn. In addition, we found that more complex food webs are more reactive to perturbations, and consequently, less stable than simpler ones over short time-scale. This was influenced by a lower proportion of strong energy fluxes. Resilience was unaffected by seasonality, food web structure and energy fluxes, highlighting the need to account for multifaceted nature of stability. The seasonal variability of stability suggests that food webs may vary temporally in their vulnerability to environmental perturbations, which has important implications for ecosystem management.

Predators are a leading cause of breeding failure as well as adult mortality in most bird species, prompting the evolution of various anti-predator behaviours. Among these, cryptic breeding birds often rely on strategies such as nest concealment and reduced activity to avoid detection. However, even some cryptic species have been observed to respond more actively to an approaching predator. One behaviour suggested to have an anti-predatory function is defecating over the nest and eggs when departing. In this study, we investigate this behaviour in incubating female Eurasian woodcocks (Scolopax rusticola) using a large dataset of 399 photographed nests sourced from various open-source internet platforms. Our analysis reveals that signs of defecation are obvious in 54% of nests photos. Moreover in 67% nests are visible freshly moulted feathers around the nest, indicating possible application of fright moulting — a behaviour not previously documented in the context of the antipredatory response during escape. We give both these behaviours into the common context and suggests that may help to aid the female’s escape rather than to protect the nest, although their anti-predatory nature, let alone their effectiveness, remains unclear. The presence of faeces and feathers may, in fact, increase the risk of nest predation by making the nest more conspicuous to predators. Our findings thus also emphasize the importance of minimising nest disturbance during research to preserve the integrity of nest environment. We show that open-source platforms can provide valuable data for studies of breeding behaviour in wild birds.

Animals that use crops as a food source must also sustain themselves when the crops are not available, and this period of their annual life cycle can make the use of crops a winning or losing strategy. We monitored two male Barbary macaques from two neighboring groups that had access to the same orchards that bordered Ifrane National Park, Morocco. Cherries were grown commercially in these orchards, with some interspersed walnut trees. Both study individuals (and expectedly their groups) remained in the vicinity of the orchards all winter long. They visited the orchards the most when walnuts were available at the beginning of the study, and the least when cherries were available at the end of the study. This result confirmed the key role of the hired wardens that protected the cherry crop, whereas walnuts were not guarded against macaque raids. Per capita home range sizes were smallest and inter-group overlap was largest when walnuts were available, highlighting the bottom-up control of this system. The movement parameters that underlaid the variation in home range size and composition over the winter (diffusion and home range crossing time) suggested a role for competition between the two groups and with livestock, and a key role for herbaceous forage inside the orchards.

Shah Htet Naing March 5, 2022

In today’s fast-evolving technological landscape, engineering leaders play a pivotal role in driving organizational transformation. However, resistance to change, misaligned vision, and ineffective communication often lead to failed initiatives. This study presents a structured leadership framework that integrates Kotter’s 8-Step Model and Lewin’s Change Theory to guide engineering teams through transitions. Through a mixed-method research approach—including 150+ engineering leadership surveys and case studies from three technology companies—this paper identifies key leadership traits and strategies that correlate with successful change implementation. Findings highlight the significance of vision clarity, psychological safety, participatory leadership, and reinforcement mechanisms in fostering change adoption. These insights provide actionable recommendations for engineering leaders, HR strategists, and organizational transformation specialists.

Multi-Ancestry Epigenome-Wide Association Study of Asthma ExacerbationsElena Martin-Gonzalez1,a, Javier Perez-Garcia1,2,a, Mario Martin-Almeida1, Jonathan Witonsky3, Celeste Eng3, Scott Huntsman3, Donglei Hu3, Fabian Lorenzo-Diaz1,4, Ruperto González-Pérez5,6, José M. Hernández-Pérez7,8, Paloma Poza-Guedes5,6, Olaia Sardón-Prado9,10, Inmaculada Sánchez-Machín5, Elena Mederos-Luis5, Paula Corcuera-Elosegui9, Jesús Villar11-14, Jose Rodriguez-Santana15, Elad Ziv3, Esteban G Burchard3, Maria Pino-Yanes1,11,16,*

Traditional research methods for addressing nonlinear problems in radio frequency (RF) amplifiers often suffer from complexity, high computational demands, and limited precision. To overcome these challenges, this paper proposes a nonlinear modeling approach using neural networks. The fundamental principles and mechanisms of neural networks are introduced, highlighting their advantages in nonlinear modeling and analysis. The nonlinear characteristics of RF power amplifiers in satellite communications, including nonlinear distortion and nonlinear gain, are thoroughly examined. By collecting extensive input and output data from RF power amplifiers, a neural network model is constructed, trained, and optimized. Experimental results demonstrate that applying neural networks to analyze the nonlinear characteristics of RF power amplifiers in satellite communications significantly improves analysis precision (maximum: 97.9%), reduces computational complexity (minimum: 0.209), and enables comprehensive nonlinear analysis. This approach is of great significance for optimizing the performance and reliability of satellite communication systems.

A key capability for future artificial intelligence (AI)-enabled cognitive radio systems is the ability to identify dynamic patterns of spectrum usage and pinpoint areas of under and oversupply of spectrum. For mobile broadband services, the dynamic usage patterns are largely governed by user demand in both time and location. The ability to accurately predict spectrum demand, particularly in dense urban areas, is an essential capability for future intelligent wireless systems. Data-driven methodologies, including the application of machine learning (ML) and advanced analytics, are seen as promising approaches to addressing the complex problem of spectrum demand prediction. However, conventional machine learning models struggle to provide robust and accurate predictions due to the spatially dependent nature of spectrum usage. This paper presents an AI-driven framework for spectrum demand estimation that addresses the spatial dependencies in demand data to improve the accuracy of the predictive models. The approach combines two-stage spatial and feature-based clustering to create representative datasets that capture both spatial and land-use variations. Additionally, a Spatial Error Model (SEM) is integrated to correct for spatial dependencies in the residuals, ensuring robust and unbiased spectrum demand predictions. Experimental results using data from five Canadian cities demonstrate how this framework can enhance spectrum demand predictions and provide insights into usage patterns that can be leveraged by future adaptive cognitive systems.

In this paper, we extend Darbo's fixed point theorem through the concept of Geraghty-L-contractions in Banach space. We will apply these contraction conditions to find the existence of solution of a fractional integral equation by using combinations of functions in a Banach space. In addition, an application is presented. We also provide an example to confirm the results.

IntroductionBreast cancer remains the most common cancer and one of the leading causes of death in women 1,2. Invasive lobular carcinoma represents approximately 5% to 15% of invasive breast carcinomas, with an incidence between 1% and 20% in the literature, increasing in the last 20 years, possibly related to hormone replacement therapy, compared to ductal carcinoma, which remains stable3. At diagnosis, from 3% to 12% of patients are metastatic, and 30% to 80% of patients experience distant metastatic progression after surgery, chemotherapy, hormone therapy, and radiotherapy 4,5. The preferred metastatic sites are the lymph nodes, skeleton, gynecological organs, and peritoneum. Extrahepatic digestive metastases remain rare, with incidences reported in the literature between 6% and 18%, sometimes synchronous with the diagnosis of the primary lesion 6, and sometimes appearing years after the diagnosis of the breast lesion7–9. The stomach is more frequently affected compared to the colon (6-18% versus 8-12%) 10. We present the case of a female patient with metastatic infiltrating lobular carcinoma, who developed unexpected secondary gastric metastases 20 years after the management of the primary tumor. To the best of our knowledge, this is the first report on the identification of such lesions by [18F]fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT). Other metastatic sites, particularly bone, were controlled under treatment. Notably, the patient had a history of gastroesophageal reflux and histologically confirmed Helicobacter pylori -negative gastritis, which might have misled the diagnosis toward a benign condition.

Title:Untying the next genetic thread in a family with MEN2A syndrome: A case report

Objective To investigate the approach of obstetricians and gynaecologists in Ireland to optimising the fertility of young women with moderate to severe endometriosis, who have not yet completed their family. Design Scoping questionnaire Setting The study survey was delivered via an anonymous online survey platform forum. Population Doctors working in Obstetrics and Gynaecology in Ireland Methods A scoping survey was delivered via an online forum. Obstetrics and gynaecology consultants and trainees were identified through the national professional and training body for Obstetrics and Gynaecology in Ireland. Results Almost 60% of respondents were consultants or senior registrars. Most (98%) take age and fertility desire into consideration when planning treatment, 71% always perform ultrasound prior to operating, with 36% usually performing an AMH test, and 37% discussing the risk of ovarian cystectomy to patient ovarian reserve. Although most (86%) reported counselling women with moderate to severe endometriosis to consider starting a family, only 25% routinely discuss fertility preservation before complex surgery. Conclusion This study demonstrates the significant heterogeneity in the management of women with severe endometriosis in Ireland. There is a low level of assessment of ovarian reserve and consideration of ART procedures such as IVF and egg freezing. This may have been related to the lack of public funding for these services in Ireland at the time of this survey. Further studies are needed to try define the characteristics of women with endometriosis who will benefit most from fertility preservation.