Multiple States Research Articles

IP-to-MS: An Unbiased Workflow for Antigen Profiling.

Immunoprecipitation is among the most widely utilized methods in biomedical research, with applications that include the identification of antibody targets and associated proteins. The path to identifying these targets is not straightforward, however, and often requires the use of chemical cross-linking and/or gel electrophoresis to separate targets from an overabundance of immunoglobulin protein. Such experiments are labor intensive and often yield long lists of candidate antibody targets. Here, we describe an unbiased immunoprecipitation-to-mass spectrometry (IP-to-MS) method that relies on a novel protein tag to separate low abundance immunoprecipitated proteins from overwhelmingly abundant immunoglobulins. We demonstrate that the IP-to-MS serotyping workflow is highly reproducible and can be used for the identification of novel, patient-specific antigen targets in multiple disease states. Furthermore, we show that IP-to-MS may outperform conventional methods of antibody detection, including enzyme-linked immunosorbent assay, while also enabling patient stratification beyond what is possible with traditional approaches.

Elastic robotic structures: a multidisciplinary framework for the design and control of shape-morphing elastic system for architectural and design applications

The design of adaptive structures and objects takes place at the intersection of design, architecture, robotics and engineering. Evolving from 1960s cybernetics to today’s interactive projects, technological advancements shape new visions for adaptive systems. A key challenge in this field is developing human-scale, shape-morphing structures. Elastic materials offer a promising solution for creating lightweight systems capable of large transformations with minimal components and energy, unlike conventional rigid systems. This approach requires methodologies for designing and controlling complex material deformations. While architectural and structural design methods focus on large-scale but static elastic structures, soft robotics explores dynamic behaviors. However these approaches are limited for complex shapes and large-scale, as their focus is on specialized applications. To address these issues, this research introduces a multidisciplinary framework for the design and control of shape-morphing elastic system for architectural and design applications. It also presents the concept of elastic robotic structures (ERS), which refers to a body of work developed with the framework. ERS are defined as large-scale elastic systems that are robotically actuated and can achieve multiple geometrical states, interacting with humans and adapting to diverse conditions. The multidisciplinary framework is presented for ERS design, characterization and control, showing how it leverages the integration of architecture, engineering and robotics to overcome the limitations of discipline-specific traditional approaches. The framework is applied in the realization of different types of ERS, which are presented and categorized. Combining the flexibility and interactivity of design methodologies with the reliability of robotic solutions will enable designers and engineers to develop innovative elastic shape-changing systems and program their behaviors.

Biological characterization and clinical significance of cuproptosis-related genes in lung adenocarcinoma

BackgroundLung cancer has high morbidity and mortality rates, which results in a poor prognosis. Cuproptosis is a novel cell death mechanism. The aim of this study was to examine the biological characteristics and clinical significance of genes associated with cuproptosis in lung adenocarcinoma (LUAD), and to understand the molecular mechanisms underlying the occurrence and progression of LUAD.MethodsWe targeted 10 cuproptosis-related genes from previous studies and used the datasets from GEO and TCGA databases to identify differential genes related to cuproptosis; then the data were analyzed by R package, Cytoscape, TISDB, cBioPortal, STRING, CancerSEA, and Disgenet; and finally, the data were detected by immunohistochemistry validation was performed.ResultsCDKN2A and MTF1 were cuproptosis-associated LUAD differential genes and were differentially expressed in immune subtypes. The expression of CDKN2A and MTF1 showed correlation with multiple functional states of LUAD.CDKN2A was negatively correlated with LUAD survival prognosis.ConclusionCDKN2A and MTF1 were correlated with the diagnosis of LUAD, and CDKN2A was negatively correlated with the survival and prognosis of LUAD. CDKN2A has the potential to contribute to the early diagnosis and prognosis analysis of LUAD.

Challenging excited states from adaptive quantum eigensolvers: subspace expansions vs. state-averaged strategies

Abstract The prediction of electronic structure for strongly correlated molecules represents a promising application for near-term quantum computers. Significant attention has been paid to ground state wavefunctions, but excited states of molecules are relatively unexplored. In this work, we consider the ADAPT-VQE algorithm, a single-reference approach for obtaining ground states, and its state-averaged generalization for computing multiple states at once. We demonstrate for both rectangular and linear H2 as well as for BeH2, that this approach, which we call MORE-ADAPT-VQE, can make better use of small excitation manifolds than an analagous method based on a single-reference ADAPT-VQE calculation, q-sc-EOM. In particular, MORE-ADAPT-VQE is able to accurately describe both avoided crossings and crossings between states of different symmetries. In addition to more accurate excited state energies, MORE-ADAPT-VQE can recover accurate transition dipole moments in situations where traditional ADAPT-VQE and q-sc-EOM struggle. These improvements suggest a promising direction toward the use of quantum computers for difficult excited state problems.

Stabilization of stochastic nonlinear systems with multiplicative state sensing noise

Stabilization of stochastic nonlinear systems with multiplicative state sensing noise

Partially observable Markov models inferred using statistical tests reveal context-dependent syllable transitions in Bengalese finch songs.

Generative models have diverse applications, including language processing and birdsong analysis. In this study, we demonstrate how a statistical test, designed to prevent overgeneralization in sequence generation, can be used to infer minimal models for the syllable sequences in Bengalese finch songs. We focus on the partially observable Markov model (POMM), which consists of states and the probabilistic transitions between them. Each state is associated with a specific syllable, with the possibility that multiple states may correspond to the same syllable. This characteristic differentiates the POMM from a standard Markov model, where each syllable is linked to a single state. The presence of multiple states for a syllable suggests that transitions between syllables are influenced by the specific contexts in which these transitions occur. We apply this method to analyze the songs of six adult male Bengalese finches, both before and after they were deafened. Our results indicate that auditory feedback plays a crucial role in shaping the context-dependent syllable transitions characteristic of Bengalese finch songs.Significance statement Generative models are proficient at representing sequences where the order of elements, such as words or birdsong syllables, is context-dependent. In this study, we demonstrate that a probabilistic model, inspired by the neural encoding involved in song production in songbirds, effectively captures the context-dependent transitions of syllables in Bengalese finch songs. Our findings reveal that the absence of auditory input, as observed in deafened Bengalese finches, reduces these context dependencies, indicating that auditory feedback is essential for establishing context-dependent sequencing in their songs. This method can be applied to various behavioral sequences, offering valuable insights into the neural mechanisms underlying the statistical patterns that govern these sequences.

Time-varying quantitative characterization of reservoir microscopic pore structure based on digital core

The reservoir physical parameters (such as porosity, permeability, phase permeability, etc.) will change in the process of water injection development with the continuous flushing effect of high magnification water drive, which may have adverse effects on development if they cannot be accurately characterized. In this paper, we try to quantitative characterize the time -varying features of pore structure from the microscopic perspective. We used high-resolution 3D micro-CT (MCT) images to supplement the analysis of the physical properties of the rocks, and we used 3D pore network modeling technology to generate a 3D model of the rock samples. Then the relevant static micro-pore parameters are derived to study the changes of rock properties in different periods of development. Pore parameters were obtained to study the changes in porosity, permeability and pore size distribution of the rocks under different expulsion multiples, and to visualize the time-varying pattern of the microstructure of the rock samples under different stages of water injection. Under low-multiple water-driven conditions (10 PV), the physical properties of the rock samples did not change significantly, with an average facies change of only 1.98%. When reaching high multiples of water drive (more than 500PV), the change rate reaches more than 15%. And with the increase of water drive multiples, the distribution of pore radius and throat radius of rock samples showed an obvious right-shift trend, and the pores and throats increased, which was consistent with the results of CT scanning photographs. Equation fitting of the simulation results reveals that the core micro-parameters show an overall logarithmic relationship with the change of water drive. In this paper, a new application of Micro CT is provided to quantify the microstructure of water-injected reservoirs. By adopting this method, the effect of water-drive multiplicity on reservoir structure can be illustrated from a microscopic perspective. Meanwhile, compared with previous studies, this paper further investigates the effect of time-variation based on the qualitative analysis of the effect of time-variation of water-driven in reservoirs, and regresses time-variation curves and formulas through the changes in multiple water-driven states, which fills in the gap of the current lack of quantitative research and provides new understanding and optimization of the development of oilfields. The study will provide a new perspective for understanding and optimizing oilfield development.

Spontaneous blinking and brain health in aging: Large-scale evaluation of blink-related oscillations across the lifespan.

Blink-related oscillations (BROs) are newly discovered neurophysiological brainwave responses associated with spontaneous blinking, and represent environmental monitoring and awareness processes as the brain evaluates new visual information appearing after eye re-opening. BRO responses have been demonstrated in healthy young adults across multiple task states and are modulated by both task and environmental factors, but little is known about this phenomenon in aging. To address this, we undertook the first large-scale evaluation of BRO responses in healthy aging using the Cambridge Centre for Aging and Neuroscience (Cam-CAN) repository, which contains magnetoencephalography (MEG) data from a large sample (N = 457) of healthy adults across a broad age range (18-88) during the performance of a simple target detection task. The results showed that BRO responses were present in all age groups, and the associated effects exhibited significant age-related modulations comprising an increase in sensor-level global field power (GFP) and source-level theta and alpha spectral power within the bilateral precuneus. Additionally, the extent of cortical activations also showed an inverted-U relationship with age, consistent with neurocompensation with aging. Crucially, these age-related differences were not observed in the behavioral measures of task performance such as reaction time and accuracy, suggesting that blink-related neural responses during the target detection task are more sensitive in capturing aging-related brain function changes compared to behavioral measures alone. Together, these results suggest that BRO responses are not only present throughout the adult lifespan, but the effects can also capture brain function changes in healthy aging-thus providing a simple yet powerful avenue for evaluating brain health in aging.

Operating principles of interconnected feedback loops driving cell fate transitions

Interconnected feedback loops are prevalent across biological mechanisms, including cell fate transitions enabled by epigenetic mechanisms in carcinomas. However, the operating principles of these networks remain largely unexplored. Here, we identify numerous interconnected feedback loops implicated in cell lineage decisions, which we discover to be the hallmarks of lower- and higher-dimensional state space. We demonstrate that networks having higher centrality nodes have restricted state space while those with lower centrality nodes have higher dimensional state space. The topologically distinct networks with identical node or loop counts have different steady-state distributions, highlighting the crucial influence of network structure on emergent dynamics. Further, regardless of topology, networks with autoregulated nodes exhibit multiple steady states, thereby “liberating” network dynamics from absolute topological control. These findings unravel the design principles of multistable networks implicated in fate decisions and can have crucial implications in engineering or comprehending multi-fate decision circuits.

A new class of higher-order topological insulators that localize energy at arbitrary multiple sites.

Z-classified topological phases lead to a larger-than-unity number of topological states. However, these multiple topological states are only localized at the corners in nonlocal systems. Here, first, we rigorously prove that the multiple topological states of nonlocal Su-Schrieffer-Heeger (SSH) chains can be inherited and realized by local aperiodic chains with only the nearest couplings. Then, we report a new class of higher-order topological insulators constructed with the local aperiodic chains, which can have any integer number of 0D topological states localized at arbitrary positions in the whole domain of the insulators, including within the bulk. The 0D topological states are protected by the local topological marker in each direction, instead of the bulk multipole chiral numbers in existing work. We experimentally demonstrate these multimode topological states in designed acoustic coupled-resonators systems. Our work enables multiple combinations of localized corner-bulk topological states, which leads to programmable lasers and sasers by selecting the excitation sites without altering the structure, and thus opens a new avenue to signal enhancement for computing and sensing.

Thermally responsive spatially programmable soft actuators with multiple response states enabled by Grayscale UV light processing.

Soft actuators hold great promise for applications in biomimetic robots, artificial muscles, and drug delivery systems due to their adaptability in diverse environments. A critical aspect of designing thermally responsive soft actuators is to achieve spatially programmable actuation under a global thermal stimulus. Different local actuation behaviors can be encoded in one actuator to enable complex morphing structures for different tasks. However, it is challenging to achieve programmability beyond one or binary states. This work introduces a new grayscale ultraviolet (UV) light processing method to fabricate soft actuators with spatially tunable Young's modulus, enabling multiple programmable states in one actuator. Together with a liquid crystal elastomer actuation layer and a photothermal heating layer, the LCE programming layer with spatially programmable moduli allows different regions of the soft actuator to bend to controllable extents under a global thermal stimulus. Various shape morphing patterns can be encoded using UV photomasks with spatially controlled grayscales. Additionally, caterpillar-inspired robots capable of bi-directional crawling and octopus-arm-inspired structures for object manipulation are demonstrated. This work represents advancements in the programmability of thermally responsive soft actuators, laying the foundation for their applications in advanced soft robotic systems.

Condition monitoring and multi-fault classification of hydraulic systems using multivariate functional data analysis.

Condition monitoring and fault classification in engineering systems is a critical challenge within the scope of Prognostics and Health Management (PHM). The fault diagnosis of complex nonlinear systems, such as hydraulic systems, has become increasingly important due to advancements in big data analytics, machine learning (ML), Industry 4.0, and Internet of Things (IoT) applications. Multi-sensor data provides opportunities to predict component conditions; however, environments characterized by multiple sensors and diverse fault states across various components complicate the fault classification process. To address these challenges, this study introduces a novel multivariate Functional Data Analysis (FDA) framework based on Multivariate Functional Principal Component Analysis (MFPCA) for classifying failure conditions in hydraulic systems. The proposed method systematically tackles condition-based diagnostics and addresses fundamental issues in multi-fault classification. Experimental results demonstrate that this approach achieves high classification accuracy using raw multi-sensor data, establishing multivariate FDA as a powerful tool for fault diagnosis in complex systems.

Considering Multiecosystem Trade-Offs Is Critical When Leveraging Systematic Conservation Planning for Restoration.

Conservationists are increasingly leveraging systematic conservation planning (SCP) to inform restoration actions that enhance biodiversity. However, restoration frequently drives ecological transformations at local scales, potentially resulting in trade-offs among wildlife species and communities. The Conservation Interactions Principle (CIP), coined more than 15 years ago, cautions SCP practitioners regarding the importance of jointly and fully evaluating conservation outcomes across the landscape over long timeframes. However, SCP efforts that guide landscape restoration have inadequately addressed the CIP by failing to tabulate the full value of the current ecological state. The increased application of SCP to inform restoration, reliance on increasingly small areas to sustain at-risk species and ecological communities, ineffective considerations for the changing climate, and increasing numbers of at-risk species, are collectively intensifying the need to consider unintended consequences when prioritizing sites for restoration. Improper incorporation of the CIP in SCP may result in inefficient use of conservation resources through opportunity costs and/or conservation actions that counteract one another. We suggest SCP practitioners can avoid these consequences through a more detailed accounting of the current ecological benefits to better address the CIP when conducting restoration planning. Specifically, forming interdisciplinary teams with expertise in the current and desired ecosystem states at candidate conservation sites; improving data availability; modeling and computational advancements; and applying structured decision-making approaches can all improve the integration of the CIP in SCP efforts. Improved trade-off assessment, spanning multiple ecosystems or states, can facilitate efficient, proactive, and coordinated SCP applications across space and time. In doing so, SCP can effectively guide the siting of restoration actions capable of promoting the full suite of biodiversity in a region.

Active site-inspired multicopper laccase-like nanozymes for detection of phenolic and catecholamine compounds.

Phenolic compounds are typical organic pollutants which cause severe human health problems due to their teratogenesis, carcinogenesis, neurotoxicity, immunotoxicity and endocrine disruption. Natural laccase is a multicopper oxidase existing in bacteria, plants, and insects, which can accelerate the transformation of phenolic compounds to their less hazardous oxidized products under mild conditions without harmful byproducts. Despite eco-environmentally friendly property of laccase, it still faces constraints of widespread application attribute to its high cost, complex preparation, and vulnerability. Therefore, exploring laccase mimics with high catalytic activity attracts a lot of attention and endeavors. In this research, copper-based nanozymes were prepared with coordination of copper ions and imidazole for mimicking the active sites of natural laccase via solvothermal method. The obtained Cu-based (Cu-Im) nanozymes exhibited multiple redox valence states of Cu and laccase-mimicking coordination structures, which endow Cu-Im with high laccase-like activity. During the process of catalytic oxidation reactions, singlet oxygen and superoxide anions generated from oxygen. Encouraged by the catalytic property, Cu-Im was utilized in degradation and detection of phenolic and catecholamine compounds. The catalytic degradation of compounds by Cu-Im showed good conversion and substrate versatility, which can be used as a kind of potential materials for phenolic pollutant degradation and remediation. Simultaneously, colorimetric sensors of phenols and catecholamines based on Cu-Im in solution system and POCT pad platform were constructed which indicated wide linear range and low limit of detection for both detection strategies. The Cu-Im-based sensor was a promising method for sensitive, fast, convenient, and qualitative-quantitative colorimetric analysis of phenols and catecholamines. The outcomes of this research elucidate Cu-Im is a satisfactory substitute for natural laccase, which will have broad application prospects in laccase-related fields, such as environmental recovery, pollution monitoring, and diagnosis of neurological diseases etc.

Mathematical assessment of the role of temperature on desert locust population dynamics.

This study presents a novel non-autonomous mathematical model to explore the intricate relationship between temperature and desert locust population dynamics, considering the influence of both solitarious and gregarious phases across all life stages. The model incorporates temperature-dependent parameters for key biological processes, including egg development, hopper growth, adult maturation, and reproduction. Theoretical analysis reveals the model's capacity for complex dynamical behaviors, such as multiple stable states and backward bifurcations, suggesting the potential for sudden and unpredictable population shifts. Sensitivity analysis identifies temperature-related parameters as critical drivers of population fluctuations, highlighting the importance of accurate temperature predictions for effective management. Numerical simulations demonstrate the significant impact of temperature on population growth, with optimal conditions promoting rapid development and increased survival, while extreme temperatures can hinder population growth and trigger phase transitions. By providing a deeper understanding of temperature-driven population shifts, this model enhances the ability to predict locust outbreaks, optimize control strategies, and reduce the socio-economic and ecological impacts of locust invasions.

Aromatic-aromatic interactions drive fold switch of GA95 and GB95 with three residue difference.

Proteins typically adopt a single fold to carry out their function, but metamorphic proteins, with multiple folding states, defy this norm. Deciphering the mechanism of conformational interconversion of metamorphic proteins is challenging. Herein, we employed nuclear magnetic resonance (NMR), circular dichroism (CD), and all-atom molecular dynamics (MD) simulations to elucidate the mechanism of fold switching in proteins GA95 and GB95, which share 95% sequence homology. The results reveal that long-range interactions, especially aromatic π-π interactions involving residues F52, Y45, F30, and Y29, are critical for the protein switching from a 3α to a 4β + α fold. This study contributes to understanding how proteins with highly similar sequences fold into distinct conformations and may provide valuable insights into the protein folding code.

Forming and compliance-free operation of low-energy, fast-switching HfOxSy/HfS2 memristors.

We demonstrate low energy, forming and compliance-free operation of a resistive memory obtained by the partial oxidation of a two-dimensional layered van-der-Waals semiconductor: hafnium disulfide (HfS2). Semiconductor-oxide heterostructures are achieved by low temperature (<300 °C) thermal oxidation of HfS2 under dry conditions, carefully controlling process parameters. The resulting HfOxSy/HfS2 heterostructures are integrated between metal contacts, forming vertical crossbar devices. Forming-free, compliance-free resistive switching between non-volatile states is demonstrated by applying voltage pulses and measuring the current response in time. We show non-volatile memory operation with an RON/ROFF of 102, programmable by 80 ns WRITE and ERASE operations. Multiple stable resistance states are achieved by modulating pulse width and amplitude, down to 60 ns, < 20 pJ operation. This demonstrates the capability of these devices for low-energy, fast-switching and multi-state programming. Resistance states were retained without fail at 150 °C over 104 s, showcasing the potential of these devices for long retention times and resilience to ageing. Low-energy resistive switching measurements were repeated under vacuum (8.6 mbar) showing unchanged characteristics and no dependence of the device on surrounding oxygen or water vapour. Using a technology computer-aided design (TCAD) tool, we explore the role of the semiconductor layer in tuning the device conductance and driving gradual resistive switching in 2D HfOx-based devices.

On the Multiple Steady Flow States in Spindle Shaped Geometry of Bridge Foundations

On the Multiple Steady Flow States in Spindle Shaped Geometry of Bridge Foundations

Electronic and magnetic properties of the HfO2 monolayer engineered by doping with transition metals and nonmetal atoms towards spintronic applications.

Doping two-dimensional (2D) materials is a vitally important method to modulate their electronic and magnetic properties. In this work, doping with transition metals (TM = Mn and Fe) and nonmetal atoms (X = B and C) is proposed to engineer the magnetism in the HfO2 monolayer. The pristine monolayer is an intrinsically nonmagnetic insulator with a large band gap of 4.85 (6.43) eV as calculated using the PBE (HSE06) functional. Doping with Mn and Fe atoms induces monolayer magnetization with total magnetic moments of 3.00 and 4.00μ B, respectively. Herein, Mn- and Fe-3d electrons produce mainly magnetic properties and regulate the electronic nature by forming new mid-gap energy states. Similarly, the 2p orbital of impurities plays a key role in determining the electronic and magnetic properties of B- and C-doped systems. Mn and B doping leads to the emergence of magnetic semiconductor nature, while the half-metallicity is obtained by doping with Fe and C atoms. Further, the substitution of the Hf-O pair with the TM-X pair is also studied. In these cases, both TM and X impurities induce the system magnetism, exhibiting an antiparallel spin orientation. Consequently, pair-atom-doped systems have smaller total magnetic moments in comparison with single-atom-doped systems. Interestingly, doping with all four Mn-B, Mn-C, Fe-B, and Fe-C pairs induces a magnetic semiconductor nature, where spin-dependent energy gaps are determined by the doping-induced multiple mid-gap energy states. When incorporated into the HfO2 monolayer lattice, transition metals lose charge, while nonmetal impurities act as charge gainers. This study demonstrates the effectiveness of the doping method to engineer the magnetism in the HfO2 monolayer for spintronic applications.

Unlocking the influence of PNPLA3 mutations on lipolysis: Insights into lipid droplet formation and metabolic dynamics in metabolic dysfunction-associated steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) covers a range of liver conditions marked by the buildup of fat, spanning from simple fatty liver to more advanced stages like metabolic dysfunction-associated steatohepatitis and cirrhosis. Our in-depth analysis of PNPLA3_WT and mutants (I148M (MT1) and C15S (MT2)) provides insights into their structure-function dynamics in lipid metabolism, especially lipid droplet hydrolysis and ABHD5 binding. Employing molecular docking, binding affinity, MD analysis, dissociation constant, and MM/GBSA analysis, we delineated distinct binding characteristics between wild-type and mutants. Structural dynamics analysis revealed that unbound mutants exhibited higher flexibility, increased Rg and SASA values, and broader energy landscapes, indicating multiple inactive states. Mutations, especially in PNPLA3_MT1, reduced the exposure of the catalytic serine, potentially impairing enzymatic activity and LD hydrolysis efficiency. Altered interaction patterns and dynamics, particularly a shift in ABHD5 binding regions towards the C-terminal domain, underscore its role in LD metabolism. Energy dynamics analysis of the protein complexes revealed PNPLA3_WT exhibited multiple low-energy macrostates, whereas the mutants displayed narrower energy landscapes, suggesting a more stable functional state. PNPLA3_MT1 demonstrated the highest affinity towards ABHD5, highlighting the complex interplay between protein structure, dynamics, and lipid metabolism regulation. PNPLA3_MT1 mutant exhibits the highest flexibility and significantly reduced catalytic serine accessibility, leading to impaired lipolysis. Contrarily, PNPLA3_WT maintains stable catalytic efficiency and effective LD hydrolysis, with PNPLA3_MT2 displaying intermediate behavior. Our research provides valuable insights into the metabolic implications of PNPLA3 mutations, offering a path for potential therapeutic interventions in MASLD.