High-Throughput Microfluidic Electroporation (HTME): A Scalable, 384-Well Platform for Multiplexed Cell Engineering.

Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to integrate into highly multiplexed workflows, owing to limitations in their scalability and tunability. These challenges ultimately increase the time and cost per transformation.

Evaluating AUC estimators across complex sampling designs: insights from COVID-19 patient data.

Purpose: Many studies in medical research are currently based on large-scale health surveys. Data collected in these surveys are usually obtained by following complex sampling designs, which include techniques such as stratification and clustering. Thus, special care should be taken with this kind of data, given that traditional statistical techniques are usually not valid in this context.

Assessing the spatio-temporal risk of Aedes-borne arboviral diseases in non-endemic regions: The case of Northern Spain.

Arboviral diseases represent a growing global health challenge. While dengue cases surge in endemic regions, non-endemic areas in southern Europe are seeing a rise in imported cases of dengue, Zika, and chikungunya, along with the first autochthonous dengue transmissions. The expanding Aedes mosquito populations, influenced by climate change, and increased international travel introducing viremic cases further elevate the risk of outbreaks.

Explosive neural networks via higher-order interactions in curved statistical manifolds.

Higher-order interactions underlie complex phenomena in systems such as biological and artificial neural networks, but their study is challenging due to the scarcity of tractable models. By leveraging a generalisation of the maximum entropy principle, we introduce curved neural networks as a class of models with a limited number of parameters that are particularly well-suited for studying higher-order phenomena. Through exact mean-field descriptions, we show that these curved neural networks implement a self-regulating annealing process that can accelerate memory retrieval, leading to explosive order-disorder phase transitions with multi-stability and hysteresis effects.

Biphasic changes in hippocampal granule cells after traumatic brain injury.

Traumatic brain injury (TBI) leads to a wide range of long-lasting physical and cognitive impairments. Changes in neuronal excitability and synaptic functions in the hippocampus have been proposed to underlie cognitive alterations. The dentate gyrus (DG) acts as a "gatekeeper" of hippocampal information processing and as a filter of excessive or aberrant input activity.

The impact of non-pharmaceutical interventions on COVID-19 transmission and its effect on life expectancy in two European regions.

Background: In response to the rapid global transmission of COVID-19, governments worldwide enacted lockdowns and other non-pharmaceutical interventions (NPI) to control the disease. In this study, we aim to quantify the influence of NPIs on the transmission of COVID-19 within selected European regions, specifically Spain (including the Basque Country) and Italy (including Tuscany), during the period of February to December 2020, which predates the initiation of COVID-19 vaccinations. We investigate potential correlations and associations between the implementation of NPIs, changes in COVID-19 transmission rates, and alterations in life expectancy across different age and sex categories from the year 2019 to 2020.

Nonlocal models in biology and life sciences: Sources, developments, and applications.

Mathematical modeling is one of the fundamental techniques for understanding biophysical mechanisms in developmental biology. It helps researchers to analyze complex physiological processes and connect like a bridge between theoretical and experimental observations. Various groups of mathematical models have been studied to analyze these processes, and the nonlocal models are one of them.

AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation.

The primary practice of healthcare artificial intelligence (AI) starts with model development, often using state-of-the-art AI, retrospectively evaluated using metrics lifted from the AI literature like AUROC and DICE score. However, good performance on these metrics may not translate to improved clinical outcomes. Instead, we argue for a better development pipeline constructed by working backward from the end goal of positively impacting clinically relevant outcomes using AI, leading to considerations of causality in model development and validation, and subsequently a better development pipeline.

The role of soil surface in a sustainable semiarid ecosystem.

Patterns in a semiarid ecosystem are important because they directly and indirectly affect ecological processes, biodiversity, and ecosystem resilience. Understanding the causes and effects of these patterns is critical for long-term land surface management and conservation efforts in semiarid regions, which are especially sensitive to climate change and human-caused disturbances. In addition, developing mathematical models is challenging because of the involvement of several interacting components within an ecosystem.

Discontinuity-Induced Dynamics in the Conductance-Based Adaptive Exponential Integrate-and-Fire Model.

In this article, we present a computational study of the Conductance-Based Adaptive Exponential (CAdEx) integrate-and-fire neuronal model, focusing on its multiple timescale nature, and on how it shapes its main dynamical regimes. In particular, we show that the spiking and so-called delayed bursting regimes of the model are triggered by discontinuity-induced bifurcations that are directly related to the multiple-timescale aspect of the model, and are mediated by canard solutions. By means of a numerical bifurcation analysis of the model, using the software package COCO, we can precisely describe the mechanisms behind these dynamical scenarios.

Genuine Multipartite Entanglement Detection with Imperfect Measurements: Concept and Experiment.

Standard procedures for entanglement detection assume that experimenters can exactly implement specific quantum measurements. Here, we depart from such idealizations and investigate, in both theory and experiment, the detection of genuine multipartite entanglement when measurements are subject to small imperfections. For arbitrary qubits number n, we construct multipartite entanglement witnesses where the detrimental influence of the imperfection is independent of n.

Impact of High Covid-19 Vaccination Rate in an Aging Population: Estimating Averted Hospitalizations and Deaths in the Basque Country, Spain Using Counterfactual Modeling.

COVID-19 vaccines have demonstrated significant efficacy in reducing severe symptoms and fatalities, although their effectiveness in preventing transmission varies depending on the population's age profile and the dominant variant. This study evaluates the impact of the COVID-19 vaccination campaign in the Basque Country region of Spain, which has the fourth highest proportion of elderly individuals worldwide. Using epidemiological data on hospitalizations, ICU admissions, fatalities, and vaccination coverage, we calibrated four versions of an ordinary differential equations model with varying assumptions on the age structure and transmission function.

Pre-asymptotic analysis of Lévy flights.

We study the properties of Lévy flights with index 0<α<2 at elapsed times smaller than those required for reaching the diffusive limit, and we focus on the bulk of the walkers' distribution rather than on its tails. On the basis of the analogs of the Kramers-Moyal expansion and of the Pawula theorem, we show that, for any α≤2/3, the bulk of the walkers' distribution occurs at wave-numbers greater than (2/α)1/(2α)≥1, and it remains non-self-similar for a time-scale longer than the Markovian time-lag of at least one order of magnitude. This result highlights the fact that for Lévy flights, the Markovianity time-lag is not the only time-scale of the process and indeed another and longer time-scale controls the transition to the familiar power-law regime in the final diffusive limit.

A probabilistic generative model to discover the treatments of coexisting diseases with missing data.

Background And Objective: Comorbidities, defined as the presence of co-existing diseases, progress through complex temporal patterns among patients. Learning such dynamics from electronic health records is crucial for understanding the coevolution of diseases. In general, medical records are represented through temporal sequences of clinical variables together with their diagnosis.

Resource-Efficient High-Dimensional Entanglement Detection via Symmetric Projections.

We introduce two families of criteria for detecting and quantifying the entanglement of a bipartite quantum state of arbitrary local dimension. The first is based on measurements in mutually unbiased bases and the second is based on equiangular measurements. Both criteria give a qualitative result in terms of the state's entanglement dimension and a quantitative result in terms of its fidelity with the maximally entangled state.

Effects of optogenetic and visual stimulation on gamma activity in the visual cortex.

Studying brain functions and activity during gamma oscillations can be a challenge because it requires careful planning to create the necessary conditions for a controlled experiment. Such an experiment consists of placing the brain into a gamma state and investigating cognitive processing with a careful design. Cortical oscillations in the gamma frequency range (30-80 Hz) play an essential role in a variety of cognitive processes, including visual processing and cognition.

Role of immigration and emigration on the spread of COVID-19 in a multipatch environment: a case study of India.

Human mobility has played a critical role in the spread of COVID-19. The understanding of mobility helps in getting information on the acceleration or control of the spread of disease. The COVID-19 virus has been spreading among several locations despite all the best efforts related to its isolation.

Nonequilibrium thermodynamics of the asymmetric Sherrington-Kirkpatrick model.

Most natural systems operate far from equilibrium, displaying time-asymmetric, irreversible dynamics characterized by a positive entropy production while exchanging energy and matter with the environment. Although stochastic thermodynamics underpins the irreversible dynamics of small systems, the nonequilibrium thermodynamics of larger, more complex systems remains unexplored. Here, we investigate the asymmetric Sherrington-Kirkpatrick model with synchronous and asynchronous updates as a prototypical example of large-scale nonequilibrium processes.

Ensemble heterogeneity mimics ageing for endosomal dynamics within eukaryotic cells.

Transport processes of many structures inside living cells display anomalous diffusion, such as endosomes in eukaryotic cells. They are also heterogeneous in space and time. Large ensembles of single particle trajectories allow the heterogeneities to be quantified in detail and provide insights for mathematical modelling.

A High-Quality Genome-Scale Model for Metabolism.

is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE).

Morning naps architecture and mentation recall complexity.

Mentation reports were collected after spontaneous awakenings from morning naps in 18 healthy participants, and associations between sleep stages duration and complexity of recalled mentation were investigated. Participants were continuously recorded with polysomnography and allowed to sleep for a maximum of 2 hr. Mentation reports were classified according to both their complexity (1-6 scale) and their perceived timing of occurrence (Recent or Previous Mentation with respect to the final awakening).

Optimal vaccine allocation for the control of sexually transmitted infections.

The burden of sexually transmitted infections (STIs) poses a challenge due to its large negative impact on sexual and reproductive health worldwide. Besides simple prevention measures and available treatment efforts, prophylactic vaccination is a powerful tool for controlling some viral STIs and their associated diseases. Here, we investigate how prophylactic vaccines are best distributed to prevent and control STIs.

The effect of mixed vaccination rollout strategy: A modelling study.

Vaccines have measurable efficacy obtained first from vaccine trials. However, vaccine efficacy (VE) is not a static measure and long-term population studies are needed to evaluate its performance and impact. COVID-19 vaccines have been developed in record time and the currently licensed vaccines are extremely effective against severe disease with higher VE after the full immunization schedule.