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Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique assumptions about the system’s temporal evolution. This disparity of approaches makes it challenging to systematically advance mean-field methods beyond previous contributions. Here, we propose a unifying framework for mean-field theories of asymmetric kinetic Ising systems from an information geometry perspective. The framework is built on Plefka expansions of a system around a simplified model obtained by an orthogonal projection to a sub-manifold of tractable probability distributions. This view not only unifies previous methods but also allows us to develop novel methods that, in contrast with traditional approaches, preserve the system’s correlations. We show that these new methods can outperform previous ones in predicting and assessing network properties near maximally fluctuating regimes. Many mean-field theories are proposed for studying the non-equilibrium dynamics of complex systems, each based on specific assumptions about the system’s temporal evolution. Here, Aguilera et al. propose a unified framework for mean-field theories of asymmetric kinetic Ising systems to study non-equilibrium dynamics.

The spread of seizures across brain networks is the main impairing factor, often leading to loss-of-consciousness, in people with epilepsy. Despite advances in recording and modeling brain activity, uncovering the nature of seizure spreading dynamics remains an important challenge to understanding and treating pharmacologically resistant epilepsy. To address this challenge, we introduce a new probabilistic model that captures the spreading dynamics in patient-specific complex networks. Network connectivity and interaction time delays between brain areas were estimated from white-matter tractography. The model’s computational tractability allows it to play an important complementary role to more detailed models of seizure dynamics. We illustrate model fitting and predictive performance in the context of patient-specific Epileptor networks. We derive the phase diagram of spread size (order parameter) as a function of brain excitability and global connectivity strength, for different patient-specific networks. Phase diagrams allow the prediction of whether a seizure will spread depending on excitability and connectivity strength. In addition, model simulations predict the temporal order of seizure spread across network nodes. Furthermore, we show that the order parameter can exhibit both discontinuous and continuous (critical) phase transitions as neural excitability and connectivity strength are varied. Existence of a critical point, where response functions and fluctuations in spread size show power-law divergence with respect to control parameters, is supported by mean-field approximations and finite-size scaling analyses. Notably, the critical point separates two distinct regimes of spreading dynamics characterized by unimodal and bimodal spread-size distributions. Our study sheds new light on the nature of phase transitions and fluctuations in seizure spreading dynamics. We expect it to play an important role in the development of closed-loop stimulation approaches for preventing seizure spread in pharmacologically resistant epilepsy. Our findings may also be of interest to related models of spreading dynamics in epidemiology, biology, finance, and statistical physics.

Focal epileptic seizures can remain localized or, alternatively, spread across brain areas, often resulting in impairment of cognitive function and loss of consciousness. Understanding the factors that promote spread is important for developing better therapeutic approaches. Here, we show that: (1) seizure spread undergoes “critical” phase transitions in models (epileptor-networks) that capture the neural dynamics of spontaneous seizures while incorporating patient-specific brain network connectivity, axonal delays and identified epileptogenic zones (EZs). We define a collective variable for the spreading dynamics as the spread size, i.e. the number of areas or nodes in the network to which a seizure has spread. Global connectivity strength and excitability in the surrounding non-epileptic areas work as phase-transition control parameters for this collective variable. (2) Phase diagrams are predicted by stability analysis of the network dynamics. (3) In addition, the components of the Jacobian’s leading eigenvector, which tend to reflect the connectivity strength and path lengths from the EZ to surrounding areas, predict the temporal order of network-node recruitment into seizure. (4) However, stochastic fluctuations in spread size in a near-criticality region make predictability more challenging. Overall, our findings support the view that within-patient seizure-spread variability can be characterized by phase-transition dynamics under transient variations in network connectivity strength and excitability across brain areas. Furthermore, they point to the potential use and limitations of model-based prediction of seizure spread in closed-loop interventions for seizure control.

Trientine tetrahydrochloride (TETA-4HCl, Cuvrior ) is a copper chelating agent with the active moiety triethylenetetramine (trientine), developed by Orphalan, Inc. to address the unmet needs in the treatment of Wilson disease. The journey from bench to bedside builds upon the documented safety profile of trientine hydrochloride capsules developed initially to meet the needs of individuals intolerant to D-penicillamine (DPA). Trientine hydrochloride capsules are inherently unstable requiring strict cold chain storage conditions from production, transportation, and use at home by the patient. Trientine tetrahydrochloride has a distinctive, patent-protected unique polymorphic form, which permits the production at scale of film-coated scored tablets deemed room temperature stable for 36 months. Trientine tetrahydrochloride is supported by a well-characterized pharmacodynamic, pharmacokinetic, and metabolic profile demonstrating reliable and predictable dose linearity and dose proportionality kinetics. Trientine tetrahydrochloride is the only trientine formulation that has been compared with DPA in a prospective randomized clinical trial, demonstrating non-inferiority to DPA in adults with stable Wilson disease. On 28 April, 2022, the US Food and Drug Administration approved TETA-4HCl for use in adult patients with Wilson disease who are de-coppered and tolerant to DPA. Health authorities in multiple countries worldwide have approved TETA-4HCl for the treatment of adults and children aged 5 years or more who are intolerant to DPA including the European Union, UK, Saudi Arabia, Switzerland, Colombia, Australia, New Zealand, and China. This article aims to provide a comprehensive narrative review of the key milestones in the development of TETA-4HCl.

Background & objectives The reproductive efficiency of buffalo bulls is crucial for genetic improvement, herd fertility, and overall productivity. Identifying genetic markers linked to semen traits can thus enhance breeding programs and optimize artificial insemination strategies. The objectives of this study were to estimate variance components and heritability. estimating the breeding values (EBVs), plotting the genetic and phenotypic trends and detection of the molecular genetic associations of FSHR and GH genes using PCR–RFLP with semen traits comprising ejaculate volume (EV), sperms motility (SM), live sperms (LS), abnormal sperms (AS) and sperms concentration (SC) in Egyptian buffalo. Methods Data of 5178 semen ejaculates were collected from 2013 to 2022 from 111 bulls, progeny of 34 sires and 92 dams in two experimental herds. For molecular genetic analysis, a total of 86 buffalo bulls were used to characterize FSHR and GH genes. Results The heritabilities estimates for semen traits were low and moderate, being 0.17, 0.28, 0.27, 0.27 and 0.23 for EV, SM, LS, AS and SC, respectively. Wide ranges of the EBVs were observed, being -0.69 to 1.27 ml for EV, -18.19 to 11.59% for SM, -19.31 to 9.15% for LS, -2.05 to 6.41% for AS and -0.39 to 0.54 × 10 9 sperms/ ml for SC. The averages of EBV throughout different years of semen collection were ranged from -0.26 to 0.43 ml for EV, -9.73 and 3.32% for SM, -9.99 and 3.45% for LS, -0.65 to 0.53% for AS and -0.19 to 0.13 × 10 9 sperms per ml for SC. The phenotypic trends plotted throughout the experimental period increased for all semen traits except for EV. The GLSM of the semen phenotypic values were ranged from 3.09 to 3.86 ml for EV, 61.55 and 66.53% for SM, 60.91 and 65.12% for LS, 4.34 to 9.28% for AS and 0.73 to 1.33 × 10 9 sperms per ml for SC.The differences in generalized least square means among GG, GC and CC genotypes of FSHR gene for semen traits were significantly in favor of GG genotype relative to GC and CC genotypes (P < 0.01). Two genotypes of TC and CC were detected for GH gene and the molecular genetic associations were significantly in favor of CC genotype relative to TC genotype (P < 0.01). Conclusion Enhancing management and feeding practices, the implementation and widespread use of artificial insemination as well as employing precise estimations of predicted breeding values in genetic improvement programs, should effectively enhance the semen traits of Egyptian buffalo bulls. FSHR and GH genes could be used as potential candidate genes for marker-assisted selection to improve semen traits in buffalo bulls.

Congenital long QT syndrome (LQTS) is characterised by heart rate corrected QT interval prolongation and life-threatening arrhythmias, leading to syncope and sudden death. Variations in genes encoding for cardiac ion channels, accessory ion channel subunits or proteins modulating the function of the ion channel have been identified as disease-causing mutations in up to 75% of all LQTS cases. Based on the underlying genetic defect, LQTS has been subdivided into different subtypes. Growing insights into the genetic background and pathophysiology of LQTS has led to the identification of genotype–phenotype relationships for the most common genetic subtypes, the recognition of genetic and non-genetic modifiers of phenotype, optimisation of risk stratification algorithms and the discovery of gene-specific therapies in LQTS. Nevertheless, despite these great advancements in the LQTS field, large gaps in knowledge still exist. For example, up to 25% of LQTS cases still remain genotype elusive, which hampers proper identification of family members at risk, and it is still largely unknown what determines the large variability in disease severity, where even within one family an identical mutation causes malignant arrhythmias in some carriers, while in other carriers, the disease is clinically silent. In this review, we summarise the current evidence available on the diagnosis, clinical management and therapeutic strategies in LQTS. We also discuss new scientific developments and areas of research, which are expected to increase our understanding of the complex genetic architecture in genotype-negative patients, lead to improved risk stratification in asymptomatic mutation carriers and more targeted (gene-specific and even mutation-specific) therapies.

Background & objectives Genetic polymorphisms in key candidate genes such as PRL , DGAT1 , FSHR , and GH play a pivotal role in regulating lactation and reproductive traits, making them critical markers for breeding programs in buffalo. Molecular characterization and associations of PRL , DGAT1 , FSHR and GH candidate genes with test day milk yield (TDMY), fat yield (TDFY), protein yield (TDPY), somatic cell score (TDSCS), age at first calving (AFC), days open (DO) and calving interval (CI) in Egyptian buffalo. Methods Lactation and reproduction records were obtained from Egyptian buffaloes reared in three experimental herds affiliated with the Animal Production Research Institute (APRI), Agricultural Research Center (ARC), Ministry of Agriculture, Egypt. For molecular characterization and association analysis of candidate genes with the studied traits, blood samples were collected from a total of 286 animals (both males and females). Specifically, 101 animals were successfully genotyped for PRL and DGAT1 genes, 98 females and 71 males for FSHR gene, and 103 females and 71 males for GH gene. PCR-RFLP technique using XbaI restriction enzyme for PRL gene and using AluI restriction enzyme for DGAT1 , FSHR and GH genes was used for animal’s genotyping. Results The generalised least square means (GLSMs) for AA genotype of PRL gene were superior relative to GG genotype, being 6.0 vs. 5.3 kg for TDMY, 390 vs. 340 g for TDFY, 290 vs. 220 g for TDPY and 2.47 vs. 2.50 for TDSCS, while the GLSM for GG genotype was favourable than AA genotype for all the studied reproductive traits. The CC genotype of FSHR gene was superior relative to GG and GC genotypes for all lactation traits, being 6.8 vs. 5.6 and 5.7 kg for TDMY, 380 vs. 360 and 350 g for TDFY, 290 vs. 220 and 230 g for TDPY and 2.41 vs. 2.48 and 2.45 for TDSCS, while the CC genotype was favourable than GG and GC genotypes for AFC, DO and CI. For GH gene, TC genotype was superior compared to CC genotype, being 6.1 vs. 5.6 kg for TDMY, 390 vs. 350 g for TDFY, 290 vs. 220 g for TDPY, 2.41 vs. 2.45 for TDSCS, 34.4 vs. 37.6 mo for AFC, 95 vs. 107 d for DO and 377 vs. 399 d for CI. Conclusion The significant molecular associations detected between AA genotype of PRL gene, CC genotype of FSHR gene and TC genotype of GH gene and lactation and reproduction traits may be helpful for marker-assisted selection programs aiming to improve lactation traits and reproduction performance in Egyptian buffalo.

Networks of excitable nodes have recently attracted much attention particularly in regards to neuronal dynamics, where criticality has been argued to be a fundamental property. Refractory behavior, which limits the excitability of neurons is thought to be an important dynamical property. We therefore consider a simple model of excitable nodes which is known to exhibit a transition to instability at a critical point ( λ  = 1), and introduce refractory period into its dynamics. We use mean-field analytical calculations as well as numerical simulations to calculate the activity dependent branching ratio that is useful to characterize the behavior of critical systems. We also define avalanches and calculate probability distribution of their size and duration. We find that in the presence of refractory period the dynamics stabilizes while various parameter regimes become accessible. A sub-critical regime with λ  < 1.0, a standard critical behavior with exponents close to critical branching process for λ  = 1, a regime with 1 <  λ  < 2 that exhibits an interesting scaling behavior, and an oscillating regime with λ  > 2.0. We have therefore shown that refractory behavior leads to a wide range of scaling as well as periodic behavior which are relevant to real neuronal dynamics.

This comprehensive review delves into the forefront of biosensor technologies and their critical roles in disease biomarker detection and therapeutic drug monitoring. It provides an in-depth analysis of various biosensor types and applications, including enzymatic sensors, immunosensors, and DNA sensors, elucidating their mechanisms and specific healthcare applications. The review highlights recent innovations such as integrating nanotechnology, developing wearable devices, and trends in miniaturisation, showcasing their transformative potential in healthcare. In addition, it addresses significant sensitivity, specificity, reproducibility, and data security challenges, proposing strategic solutions to overcome these obstacles. It is envisaged that it will inform strategic decision-making, drive technological innovation, and enhance global healthcare outcomes by synthesising multidisciplinary insights.

A heat source model is proposed to simulate the effect of periodic and recurrent arcing and metal deposition phenomena in the cold metal transfer type of welding. This model will facilitate studying of weld pool behavior and resultant mechanical properties in detail for this type of welding. The proposed model utilizes a double-ellipsoidal heat source model as the basis and makes the geometrical and heat input parameters dependent on time.