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Serum Proteomics Reveals Diagnostic Biomarkers and Molecular Pathways in Cerebral Palsy
Abstract Cerebral palsy (CP), a prevalent non-progressive neurological disorder in children, lacks reliable biomarkers for early diagnosis, and its molecular mechanisms remain poorly understood. In this study, we conducted serum proteomic profiling of 346 CP patients and 190 healthy controls and developed a 10-protein multi-marker panel for application in diagnosis of CP. The panel was further validated in an independent CP cohort using an orthogonal method, enzyme-linked immunosorbent assay (ELISA). By integrating serum proteomic data with whole-exome sequencing (WES) results, we found that CP patients carrying pathogenic variants exhibited downregulation of synaptic and calcium signaling pathways at the protein level. We also explored the impact of clinical risk factors on the proteome, identifying disruptions in lipid metabolism associated with low birth weight and low gestational age. Additionally, we found a positive correlation between Immunoglobulin Heavy Variable (IGHV) families and higher Gross Motor Function Classification System (GMFCS) levels. Overall, our study provides a valuable tool for early CP diagnosis that complements standard clinical and genomic assessments, and suggests potential molecular mechanisms associated with CP pathogenesis, highlighting the interplay among genetic, environmental, and protein network factors.
A study on the spatial distribution characteristics and influencing factors of forest villages in southwest China based on OPGD
Interplay of coil–globule transitions and aggregation in homopolymer aqueous solutions: Simulation and topological insights
We investigate the structural and topological properties of hydrophobic homopolymer chains in aqueous solutions using molecular dynamics simulations and circuit topology (CT) analysis. By combining geometric observables, such as the radius of gyration and the degree of aggregation, with CT data, we capture the relationship between coil–globule and aggregation transitions, resolving the system’s structural changes with temperature. Our results reveal a temperature-driven collective transition from isolated coiled chains to globular aggregates. At a characteristic transition temperature Tc, each chain in multichain systems undergoes a rapid coil–globule collapse, coinciding with aggregation, in contrast to the gradual collapse observed in single-chain systems at infinite dilution. This collective transition is reflected in geometric descriptors and a reorganization of CT motifs, shifting from intrachain-dominated motifs at low temperatures to a diverse ensemble of multichain motifs at higher temperatures. CT motif enumeration provides contact statistics while offering a topologically detailed view of polymer organization. These findings highlight CT’s utility as a structural descriptor for polymer systems and suggest applications for biopolymer aggregation and folding.
Mapping of HOCl-oxidized RNA identifies abasic sites as major damage and oxidation product of oxo8G
Abstract RNA oxidation is an important yet understudied process, partly because methods to localize oxidized residues in RNA are lacking. We introduce OAbSeq, a deep-sequencing approach that maps oxidized sites with high sensitivity by exploiting aniline-induced strand scission at noncanonical nucleosides to generate unique ligation-competent fragments utilized for library preparation. Applied to yeast RNA, OAbSeq detects widespread signals predominating at purines, especially at guanosines. Exogenous oxidation increased signal intensity but preserved the guanosine-dominated pattern. Parallel quantification of 8-oxoguanosine (oxo 8 G) and abasic sites revealed that abasic sites are more abundant than oxo 8 G following oxidative treatment in vitro and under physiological conditions. These data support a model in which guanosine oxidation proceeds via transient oxo 8 G yielding abasic sites that can be mapped at nucleotide resolution by OAbSeq. Our findings also suggest abasic sites may be a more informative marker of RNA oxidative damage than oxo 8 G, facilitating studies of RNA oxidation dynamics in cells.
An examination of communication mechanism of ancestral hall sacrifice rituals in rural southern China
Study of the properties of nanoconfined EMIMBF4 using polarizable molecular dynamics
We present a molecular dynamics study of the structure and dynamic behavior of the ionic liquid 1-ethyl-3-methylimidazolium tetrafluoroborate under nanoconfinement using a polarizable force field. Two distinct geometries were explored: cylindrical confinement within carbon nanotubes and planar confinement between graphene-like nanoslits, covering a range of confinement sizes. Our results reveal that the geometry and curvature of the confining region play a fundamental role in determining ion layering, molecular orientation, and diffusion. In planar nanoslits, highly ordered interfacial structures form regardless of pore width, while in carbon nanotubes, curvature suppresses such ordering and enhances ionic mobility near the interfaces. For a specific nanotube size, an anomalous behavior emerges where the combination of confinement geometry and pore dimensions promotes the formation of stable ionic layers, which drastically reduce diffusivity. These findings provide insights into the design of electrochemical devices and the optimization of ion transport in confined ionic media.
A mass spectrometry-based strategy allows signature metabolite identification in tear fluid from people with diabetic cataracts
Cutting-edge optimized multi-source data fusion for trusted execution and management of blockchain transactions on the internet of medical things (IoMT) with machine learning
Quantumness of classical-trajectory-based methods for vibrational spectroscopy
Classical-trajectory-based methods calculate the vibrational spectrum of a molecular system as the Fourier transform of an appropriate time correlation function. In this paper, we assess the quantumness of different approaches derived from the path-integral representation of quantum mechanics. We focus on power spectra obtained by means of semiclassical (SC) dynamics, centroid molecular dynamics (CMD), ring polymer molecular dynamics (RPMD), and its thermostatted version (TRPMD). Our calculations also include classical and quasi-classical trajectory (QCT) simulations as examples of results based on a purely classical propagator. Calculations are performed for a three-dimensional anharmonic model system and the non-rotating gas-phase water molecule. We show that typical features of classical calculations, such as sum-of-frequency combination bands and overtones, difference bands, and spectroscopic signals at negative frequencies, are found for classical, QCT, CMD, and (T)RPMD spectra. Conversely, these features are basically absent in semiclassical calculations, which show just a reminiscence of the underlying classical trajectory. The overall accuracy of the results compared to quantum mechanical values is always better for SC methods. Classical results depend on the initial sampling distributions, and their accuracy is of the same order as CMD, RPMD, and TRPMD simulations, i.e., an order of magnitude lower than for semiclassical approaches. Our main conclusion is that when it comes to molecular vibrational spectroscopy calculations, semiclassical methods have a predominant quantum character, being able to include also real-time coherence effects, while CMD, RPMD, and TRPMD are prevalently classical, reproducing just the anharmonicity related to the zero point energy or quantum statistical distribution.
Replay without sharp wave ripples in a spatial memory task
Abstract Sharp-wave ripples and hippocampal replay are widely viewed as inseparable components of episodic memory consolidation, with ripples broadcasting the episodic content carried by replay sequences. Here, we show that in male rats performing an open-field spatial memory task, replay can occur in the absence of ripples. Replays with and without ripples were organized in virtual space: ripples were confined to discrete “ripple fields,” spatially restricted regions defined over the virtual locations depicted during replay and independent of the rat’s location. Ripple fields were direction-independent, stable within sessions, and adapted to environmental changes induced by barriers. Ripple fields were matched across animals exposed to the same environment, revealing a conserved spatial code. These results indicate that ripples and replay are distinct but coordinated processes, with ripples selectively tagging a subset of replays linked to learning or novelty. We propose that this coupling enables targeted broadcast of salient experiences for consolidation.
A genetic screen identifies the E3 ubiquitin ligase MPSR1 as a suppressor of early flowering of the sensitivity to red light reduced 1 mutant
Abstract The timing of floral transition is critical for plants to maximize reproductive success. In Arabidopsis thaliana , SENSITIVITY TO RED LIGHT REDUCED 1 (SRR1) delays the onset of flowering in non-favourable environmental conditions. Furthermore, SRR1 is required for the function of the circadian clock. In a genetic suppressor screen for mutants that alleviate early flowering of srr1-1 mutants, we identified ssm136 ( suppressor of srr1-1 mutant 136 ) that represses srr1-1 early flowering in short photoperiods. Bulk segregant analysis and full-genome sequencing identified MISFOLDED PROTEIN SENSING RING E3 LIGASE 1 ( MPSR1 ) as the causal gene. Outcrossing the mpsr1-ssm allele to wild-type showed that MPSR1 represses flowering independently of SRR1, but the effect is stronger in srr1-1 , suggesting that MPSR1 and SRR1 act together in flowering time control. Co-immunoprecipitation showed that SRR1 and MPSR1 are able to physically interact in vivo. Expression analysis revealed that MPSR1 is regulated by the circadian clock but not required for maintaining the clock itself. Furthermore, MPSR1 expression is repressed by light and induced in short days, consistent with its role in floral repression under noninductive photoperiodic conditions.
Quantifying the transition from single file to Fickian diffusion
Single-file diffusion occurs when diffusing particles are confined to a narrow tube, which prohibits particles from passing one another. Observed in a variety of natural and engineered systems, single-file diffusion is marked by the subdiffusive mean-squared displacement of tracer particles. If the channel is barely wide enough to permit rare passing events, then the mean-squared displacement is subdiffusive at early times and diffusive at late times, and the transition between these two regimes is controlled by the average time it takes a particle to pass its neighbor. In this paper, we study how this so-called “hopping time” depends on confinement geometry, which is a problem previously studied in the chemical physics literature using a variety of theoretical methods, resulting in some conflicting predictions. Our approach leverages the theory of boundary homogenization to describe particle passing in terms of an effective “permeability,” and we use the mathematical theory of strong localized perturbations to obtain explicit formulas for the permeability and hopping time. We confirm our analytical results by kinetic Monte Carlo simulations.
Climate, air quality, and equity benefits from hydrogen substitution for fossil fuels used in process heat
An enhanced bat algorithm based intelligent inspired architecture for resilient macroeconomic prediction
Illuminating non-equilibrium multi-step reaction dynamics with stochastic Marcus state model
Modeling the stochastic reaction dynamics is a significant task to explain the modern measurements of non-equilibrium processes at mesoscopic scales. Marcus’s transition-state theory describes the reaction rate of a single-step reaction event, but how it can enlighten a multi-step stochastic reaction process in a continuous chemical-state space remains elusive. In this paper, we develop a stochastic Marcus state model with continuation methods for different reaction systems. The time-resolved evolutions of the probability density functions are expressed via Fokker–Planck equations where the drift and diffusion coefficients are determined by the free-energy functions and reorganization energy. In a system with infinitesimal-reaction transitions, the model allows a scale-invariant transform that preserves its generic form, and the equation of motion describes the over-damped Langevin dynamics space that follows the fluctuation–dissipation theorem in the chemical-state. We also prove that the Onsager reciprocal relation can be retrieved as long as the free energy obeys Schwarz’s theorem, which reveals its generality in classical closed near-equilibrium systems.
Remodeling of the immune microenvironment is linked to adverse outcome in pediatric T cell acute lymphoblastic leukemia
Biomechanical evaluation of a lower-limb implant model under gait and stumbling conditions using finite element analysis
Mesoscale particle-based simulations of flow in expansion–contraction microchannels at low Reynolds number
We computationally study the flow of Newtonian fluids through sinusoidal expansion–contraction microchannels at low Reynolds numbers. We first use a perturbation method to analytically derive series solutions for the stream function and volumetric flow rate that extend prior work [Kitanidis and Dykaar, Transp. in Porous Media 26, 89–98 (1997)] up to tenth order. We then employ two particle-based mesoscale methods, dissipative particle dynamics (DPD) and multiparticle collision dynamics (MPCD), to simulate the same flows. We find that the fluid velocity at the expansion and contraction points, as well as the volumetric flow rate, are in good agreement between DPD, MPCD, and the fourth-order series solution for a wide range of microchannel geometries. The mesoscale fluid models exhibit some slip at the walls, leading to a small but consistent overprediction of the velocity and volumetric flow rate. The series solution fails for short microchannel lengths and large amplitudes; we identify lengths and amplitudes for which it converges to a given order. Overall, we find that DPD and MPCD are convenient and reasonably accurate methods, particularly for microchannel geometries where the series solution fails or is cumbersome to implement.