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Modern AI systems excel at pattern recognition and task execution, but they often fall short of replicating the layered, self-referential structure of human thought that unfolds over time. In this paper, we present a mathematically grounded and conceptually simple framework based on smoothed step functions-sigmoid approximations of Heaviside functions-to model the recursive development of mental activity. Each cognitive layer becomes active at a specific temporal threshold, with the abruptness or gradualness of activation governed by an impressiveness parameter [Formula: see text], which we interpret as a measure of emotional salience or situational impact. Small values of [Formula: see text] represent intense or traumatic experiences, producing sharp and impulsive responses, while large values correspond to persistent background stress, yielding slow but sustained cognitive activation. We formulate the recursive dynamics of these cognitive layers and demonstrate how they give rise to layered cognition, time-based attention, and adaptive memory reinforcement. Unlike conventional memory models, our approach captures thoughts and recall events through a recursive, impressiveness-sensitive pathway, leading to context-dependent memory traces. This recursive structure offers a new perspective on how awareness and memory evolve over time, and provides a promising foundation for designing artificial systems capable of simulating recursive, temporally grounded consciousness.

Messenger RNA (mRNA) has emerged as a powerful tool for protein expression in clinical settings, yet its potential as a platform for biologics manufacturing remains underexplored. Here, we evaluate transient mRNA transfection in Chinese hamster ovary (CHO) cells as a rapid and versatile system for protein production. Using reporter mRNAs, we optimize transfection efficiency and benchmark performance against industry-standard plasmid transfection and stable cell line methods. We demonstrate that co-transfection of heavy and light chain mRNAs enables the efficient synthesis, assembly and secretion of the monoclonal antibody bevacizumab with high fidelity. Compared to conventional approaches, mRNA transfection drives rapid and predictable protein expression, reducing cell incubation times and enabling sequential or conditional expression. These features highlight mRNA as a flexible and efficient platform for transient expression, providing a foundation for accelerating the development and manufacturing of biologics.

Rare monogenic diseases are increasingly identified in children with chronic kidney disease. We describe a consanguineous preterm male infant with a clinical picture of advanced kidney dysfunction and severe renal salt-wasting, highly suggestive of prenatal onset Bartter syndrome. Patient's follow-up was characterized by severe polyuria; episodes of hyponatremia, hypokalemia, and hypochloremia; and metabolic alkalosis and hyperuricemia. We found a homozygous pathogenic variant in the TFCP2L1 gene, a transcription factor required for normal kidney development, that regulates acid-base and salt-water homeostasis. To our knowledge, there is only one published case of a child with TFCP2L1 gene pathogenic variants with a similar phenotype. This report adds evidence to TFCP2L1 as a cause of monogenic kidney disorders. Rare kidney dysplasias may manifest as phenocopies of primary tubulopathies. Genetic diagnosis plays a major role and should be carefully considered in patients with refractory course to standard treatment to facilitate management and family counselling.

Background: Parental stress in pediatric chronic illness is well known; however, there is a dearth of literature describing parental stress in pediatric chronic kidney disease (CKD). This pilot study evaluated parenting stress in mild to moderate pediatric CKD relative to caregivers of healthy, typically developing children.

Methods: The study included 38 children, ages 6 to 12 years, and their parents (CKD Group = 10, Typical Group = 28). Pediatric CKD participants had mild to moderate kidney dysfunction for at least 3 months. Parents completed the Parenting Stress Index (PSI-3) as a measure of their current stress.

Results: Serial linear regressions revealed no significant group differences on the Child, Parent, Total Stress, or Life Stress domains; however, exploratory analyses revealed significant parental stress on the subscales of Mood and Acceptability, as well as concerns about their own Competence and Health. Compared to the control group, parents of patients with CKD also reported significantly high levels of stress on Adaptability (50% versus 21.4%), Mood (60% versus 25%), and Acceptability (50% versus 10.7%).

Conclusions: While overall levels of parenting stress were not unduly elevated in group comparisons, increased stress levels with respect to their child's mood, acceptability, and their own personal health were noted. The proportion of CKD parent ratings reaching significantly high stress levels also was uniformly high, particularly in Adaptability, Mood, Acceptability, (parental) Competence, and Total Stress. These pilot results should guide future studies exploring parent/family factors and potential interventions for reducing parenting stress and related burdens in the clinical care of children with CKD.

Background: Pediatric hypertension is a growing health concern, with prolonged exposure to high blood pressure potentially causing electrical instability and increasing arrhythmia risk. The index of cardiac electrophysiological balance (iCEB), calculated as QT interval divided by QRS duration, is a potential non-invasive marker for arrhythmogenesis. This study aimed to evaluate iCEB and corrected iCEB (iCEBc) in hypertensive children and investigate their relationship with arrhythmic risk.

Methods: This cross-sectional study included 81 children with primary hypertension and 36 age- and sex-matched healthy controls. Office blood pressure, 24-h ambulatory blood pressure monitoring (ABPM), standard echocardiography, and 12-lead electrocardiograms (ECGs) were obtained. QT, QTc, Tp-e, Tp-e/QT, Tp-e/QTc, iCEB, and iCEBc were calculated. Echocardiographic measurements and laboratory parameters were also evaluated.

Results: The mean age of the hypertensive group was 13.8 ± 3 years, with 60.5% males. Most (64.2%) demonstrated a non-dipping BP pattern. Echocardiography showed preserved ejection fraction (72.7 ± 5.4%) and shortening fraction (42 ± 5.1%), with left ventricular hypertrophy (LVH) observed in 8.6% of cases. ECG analysis revealed significantly prolonged QTc interval (416.8 ± 30.2 ms vs. 401.8 ± 23.4 ms; p = 0.008), iCEB (3.92 vs. 3.44; p = 0.02), and iCEBc (4.58 vs. 4.09; p = 0.001) values in hypertensive patients compared to controls. No significant differences were observed in Tp-e, Tp-e/QT, or Tp-e/QTc.

Conclusion: Children with hypertension exhibit subclinical alterations in cardiac electrophysiology, including significantly elevated iCEB and iCEBc values, which may indicate electrical instability and a higher arrhythmia risk. These indices may serve as practical, non-invasive tools for early detection of subclinical electrophysiological changes in pediatric hypertension.

Functional differentiation in the brain emerges as distinct regions specialize and is key to understanding brain function as a complex system. Previous research has modeled this process using artificial neural networks with specific constraints. Here, we propose a novel approach that induces functional differentiation in recurrent neural networks by minimizing mutual information between neural subgroups via mutual information neural estimation. We apply our method to a 2-bit working memory task and a chaotic signal separation task involving Lorenz and Rössler time series. Analysis of network performance, correlation patterns, and weight matrices reveals that mutual information minimization yields high task performance alongside clear functional modularity and moderate structural modularity. Importantly, our results show that functional differentiation, which is measured through correlation structures, emerges earlier than structural modularity defined by synaptic weights. This suggests that functional specialization precedes and probably drives structural reorganization within developing neural networks. Our findings provide new insights into how information-theoretic principles may govern the emergence of specialized functions and modular structures during artificial and biological brain development.

The processing of information within complex neural networks is a challenge topic that has intrigued researchers for many years. In this paper, we conducted an in-depth investigation into the learning mechanisms that are intrinsic to discrete memristor spiking neural networks. We also explored the effectiveness of information transmission and synchronization among various neurons and networks. Firstly, a memristor model with memory regulation function and tanh function's nonlinear characteristics was constructed. This model not only ensures that the internal state variables of the memristor do not exhibit divergence, but also demonstrates that this memristor is suitable for spiking signal processing and has the ability to transmit spiking signals. Secondly, our research delved into the intricate dynamics of these discrete spiking neural networks, including the ternary coupled spiking neural network and ring coupled spiking neural network, aiming to shed light on how they operate and interact. Thirdly, based on the designed pulse neurons, this study constructed a simple pulse neuron network. By reasonably setting the relevant parameters, the research found that this network possesses the ability for pattern recognition. The results of our investigation are crucial for understanding the mechanisms of information processing and synchronization phenomena within neural networks. It provides valuable insights into the potential of memristor networks in advancing artificial intelligence and computational neuroscience.