Trans-saccadic integration for object recognition peters out with pre-saccadic object eccentricity as target-directed saccades become more saliency-driven.

Bringing objects from peripheral locations to fovea via saccades facilitates their recognition. Human observers integrate pre- and post-saccadic information for recognition. This integration has only been investigated using instructed saccades to prescribed locations.

A Cluster-Based Deep Learning Model Perceiving Series Correlation for Accurate Prediction of Phonon Spectrum.

The spectral properties are the most prevalent continuous representation for characterizing transport phenomena and excitation responses, yet their accurate predictions remain a challenge due to the inability to perceive series correlations by existing machine learning (ML) models. Herein, a ML model named cluster-based series graph networks (CSGN) is developed based on the dynamical theory of crystal lattices to predict phonon density of states (PDOS) spectrum for crystal materials. The multiple atomic cluster representation is constructed to capture the diverse vibration modes, while the mixture Gaussian process and dynamic time warping mechanism are compiled to project from clusters to PDOS spectrum.

Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.

This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with prostate cancer, differentiating between surgical and non-surgical treatments. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value.

Early-life malnutrition exposure associated with higher osteoporosis risk in adulthood: a large-scale cross-sectional study.

Introduction: Evidence on the association between early-life malnutrition exposure at different developmental stages and the subsequent risk of osteoporosis and fractures in adulthood remains sparse and equivocal. This study sought to elucidate the relationship between malnutrition exposure in early life and the occurrence of osteoporosis and fractures later in life.

Methods: This research is a cross-sectional analysis carried out within the framework of the China Community-based Cohort of Osteoporosis (CCCO), an ongoing community-based cohort study.

Gastroesophageal reflux disease and risk for arrhythmias: a Mendelian randomization analysis.

Background: Clinical observations and epidemiological studies suggest a potential linkage between gastroesophageal reflux disease (GERD) and arrhythmias, yet the underlying mechanism remains elusive. This study investigates the causal relationship between GERD and four types of arrhythmia through a genetic lens, employing Mendelian randomization analysis to elucidate the directionality of these associations.

Methods: Selected single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) data were utilized as instrumental variables.

Polyaptamer-Driven Crystallization of Alendronate for Synergistic Osteoporosis Treatment through Osteoclastic Inhibition and Osteogenic Promotion.

Osteoclastic inhibition using antiresorptive bisphosphonates and osteogenic promotion using antisclerostin agents represent two distinct osteoporosis treatments in clinical practice, each individual treatment suffers from unsatisfactory therapeutic efficacy due to its indirect intervention in osteoclasis and promotion of osteogenesis simultaneously. Although this issue is anticipated to be resolved by drug synergism, a tempting carrier-free dual-medication nanoassembly remains elusive. Herein, we prepare such a nanoassembly made of antiresorptive alendronate (ALN) crystal and antisclerostin polyaptamer (Apt) via a nucleic acid-driven crystallization method.

Acute kidney injury with intravenous colistin sulfate compared with polymyxin B in critically ill patients: A real-world, retrospective cohort study.

Background: Polymyxins have re-emerged as a last-resort therapeutic option for infections caused by carbapenem-resistant gram-negative bacteria. Nephrotoxicity induced by polymyxins is a significant limitation of its use in the clinic. Polymyxin B and colistin sulfate are two widely used active formulations of polymyxins.

Excitation-Inhibition Balance, Neural Criticality, and Activities in Neuronal Circuits.

Neural activities in local circuits exhibit complex and multilevel dynamic features. Individual neurons spike irregularly, which is believed to originate from receiving balanced amounts of excitatory and inhibitory inputs, known as the . The spatial-temporal cascades of clustered neuronal spikes occur in variable sizes and durations, manifested as neural avalanches with scale-free features.

Eye movement evidence for the V1 Saliency Hypothesis and the Central-peripheral Dichotomy theory in an anomalous visual search task.

Typically, searching for a target among uniformly tilted non-targets is easier when this target is perpendicular, rather than parallel, to the non-targets. The V1 Saliency Hypothesis (V1SH) - that V1 creates a saliency map to guide attention exogenously - predicts exactly the opposite in a special case: each target or non-target is a pair of equally-sized disks, a homo-pair of two disks of the same color, black or white, or a hetero-pair of two disks of the opposite color; the inter-disk displacement defines its orientation. This prediction - parallel advantage - was supported by the finding that parallel targets require shorter reaction times (RTs) to report targets' locations.

Programming Injectable DNA Hydrogels Yields Tumor Microenvironment-Activatable and Immune-Instructive Depots for Augmented Chemo-Immunotherapy.

Injectable hydrogels have attracted increasing attention for promoting systemic antitumor immune response through the co-delivery of chemotherapeutics and immunomodulators. However, the biosafety and bioactivity of conventional hydrogel depots are often impaired by insufficient possibilities for post-gelling injection and means for biofunction integration. Here, an unprecedented injectable stimuli-responsive immunomodulatory depot through programming a super-soft DNA hydrogel adjuvant is reported.

Complexity of cortical wave patterns of the wake mouse cortex.

Rich spatiotemporal dynamics of cortical activity, including complex and diverse wave patterns, have been identified during unconscious and conscious brain states. Yet, how these activity patterns emerge across different levels of wakefulness remain unclear. Here we study the evolution of wave patterns utilizing data from high spatiotemporal resolution optical voltage imaging of mice transitioning from barbiturate-induced anesthesia to wakefulness (N = 5) and awake mice (N = 4).

Overexpression of Reduces Resistance against .

Plant triterpenoids play a critical role in plant resistance against de Bary, the causal pathogen of potato and tomato late blight. However, different triterpenoids could have contrasting functions on plant resistance against . In this study, we targeted the key biosynthetic gene of all plant triterpenoids, (), to examine the function of this gene in plant- interactions.

Discrepancy in Sterol Usage between Two Polyphagous Caterpillars, and .

Insects are sterol auxotrophs and typically obtain sterols from food. However, the sterol demand and metabolic capacity vary greatly among species, even for closely related species. The low survival of many insects on atypical sterols, such as cholestanol and cholestanone, raises the possibility of using sterol-modified plants to control insect herbivore pests.

Interfacial and confined molecular-assembly of poly(3-hexylthiophene) and its application in organic electronic devices.

Poly(3-hexylthiophene) (P3HT) is a typical conducting polymer widely used in organic thin-film transistors, polymer solar cells, etc., due to good processability and remarkable charging carrier and hole mobility. It is known that the ordered structure assembled by π-conjugated P3HT chains could promote the performance of electronic devices.

Hyperbolic-Metamaterials-Based SPR Temperature Sensor Enhanced by a Nanodiamond-PDMS Hybrid for High Sensitivity and Fast Response.

A high-performance surface plasmon resonance (SPR) fiber sensor is proposed with hyperbolic metamaterials (HMMs), nanodiamonds (NDs), and polydimethylsiloxane (PDMS) to enhance the temperature sensitivity and response time. The HMM with tunable dispersion can break through the structural limitations of the optical fiber to improve the refractive index (RI) sensitivity, while NDs and PDMS with large thermo-optic coefficients enable to induce significant RI change under varied thermal fields. The ternary composite endows the sensor with a high temperature sensitivity of -9.

Construction and Electrochemical Properties of Solid-state Supercapacitors with Redox Additives.

Adding redox additives to conventional electrolytes is considered to be an effective method to improve electrochemical performance of the supercapacitors, which is ascribed to the additional Farady capacitance derived from the reversible redox reaction. Here, the influence of K Fe(CN) on electrochemical properties for single electrode system and the assembled solid-state supercapacitor are investigated. The carbon felt (CF) electrode in the mixed solution of K Fe(CN) /KCl exhibits remarkable specific capacitance of 2.

Less is more: wiring-economical modular networks support self-sustained firing-economical neural avalanches for efficient processing.

The brain network is notably cost-efficient, while the fundamental physical and dynamic mechanisms underlying its economical optimization in network structure and activity have not been determined. In this study, we investigate the intricate cost-efficient interplay between structure and dynamics in biologically plausible spatial modular neuronal network models. We observe that critical avalanche states from excitation-inhibition balance under modular network topology with less wiring cost can also achieve lower costs in firing but with strongly enhanced response sensitivity to stimuli.

Criticality enhances the multilevel reliability of stimulus responses in cortical neural networks.

Cortical neural networks exhibit high internal variability in spontaneous dynamic activities and they can robustly and reliably respond to external stimuli with multilevel features-from microscopic irregular spiking of neurons to macroscopic oscillatory local field potential. A comprehensive study integrating these multilevel features in spontaneous and stimulus-evoked dynamics with seemingly distinct mechanisms is still lacking. Here, we study the stimulus-response dynamics of biologically plausible excitation-inhibition (E-I) balanced networks.

What county-level factors influence COVID-19 incidence in the United States? Findings from the first wave of the pandemic.

Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases.

AgAu and AgAu: A Model of Cocrystallization in Bimetal Nanoclusters.

The field of cocrystalline nanoclusters stabilized by thiolates is in a period of rapid development. However, the types of cocrystallization have been limited to a few reported until now, so it is of great importance to investigate and understand the novel cocrystallographic structures. Herein, we design and synthesize a new type of cocrystallization, [AgAu(2-EBT)AgAu(2-EBT)][2(PPh)], characterized by thermogravimetric analysis, X-ray photoelectron spectroscopy, and single-crystal X-ray crystallography.

Gamma Oscillations Facilitate Effective Learning in Excitatory-Inhibitory Balanced Neural Circuits.

Gamma oscillation in neural circuits is believed to associate with effective learning in the brain, while the underlying mechanism is unclear. This paper aims to study how spike-timing-dependent plasticity (STDP), a typical mechanism of learning, with its interaction with gamma oscillation in neural circuits, shapes the network dynamics properties and the network structure formation. We study an excitatory-inhibitory (E-I) integrate-and-fire neuronal network with triplet STDP, heterosynaptic plasticity, and a transmitter-induced plasticity.

Hopf Bifurcation in Mean Field Explains Critical Avalanches in Excitation-Inhibition Balanced Neuronal Networks: A Mechanism for Multiscale Variability.

Cortical neural circuits display highly irregular spiking in individual neurons but variably sized collective firing, oscillations and critical avalanches at the population level, all of which have functional importance for information processing. Theoretically, the balance of excitation and inhibition inputs is thought to account for spiking irregularity and critical avalanches may originate from an underlying phase transition. However, the theoretical reconciliation of these multilevel dynamic aspects in neural circuits remains an open question.

Modeling stochastic gene expression: From Markov to non-Markov models.

Gene expression is an inherently noisy process due to low copy numbers of mRNA or protein. The involved reaction events may happen in a Markov fashion but also in a non-Markov manner, depending on waiting-time distributions for the occurrence of reaction events. In recent years, many mechanistic models of stochastic gene expression have been developed to forecast fluctuations in mRNA or protein levels.

Coevolution spreading in complex networks.

The propagations of diseases, behaviors and information in real systems are rarely independent of each other, but they are coevolving with strong interactions. To uncover the dynamical mechanisms, the evolving spatiotemporal patterns and critical phenomena of networked coevolution spreading are extremely important, which provide theoretical foundations for us to control epidemic spreading, predict collective behaviors in social systems, and so on. The coevolution spreading dynamics in complex networks has thus attracted much attention in many disciplines.