Search Results (161)

Syntaxin-1 (Stx1), a core neuronal SNARE protein, regulates membrane docking and fusion during neurotransmitter release. Although Stx1 clustering is widely observed at presynaptic active zones and in neuroendocrine cells, how Stx1 isoforms and lipid interactions organize the plasma membrane prior to fusion remains unclear. Here, we performed MARTINI coarse-grained molecular dynamics (cgMD) simulations of 1–10 copies of the juxtamembrane and transmembrane domains (JMD–TMDs) of Stx1A and Stx1B embedded in plasma membrane models to investigate membrane lipid disorder, Stx1 JMD–TMD clustering dynamics, and regulation by Stx1 TMD palmitoylation and phosphatidylinositol 4,5-bisphosphate (PIP₂). Stx1 JMD–TMD regions induced local lipid disorder associated with hydrophobic mismatch, with Stx1A producing stronger and more spatially extended perturbations than Stx1B. The magnitude of local lipid disorder remained largely independent of clustering and TMD palmitoylation, whereas palmitoylation spatially restricted and PIP₂ depletion broadened the radial extent of membrane perturbation. During clustering, Stx1 JMD–TMDs progressively recruited and redistributed PIP₂ into local membrane domains, resulting in ~7-fold local enrichment relative to the bulk membrane. Together, these findings support a model where hydrophobic mismatch primarily governs membrane disorder, whereas multivalent PIP₂ recruitment and redistribution stabilize higher-order Stx1 oligomers, thereby promoting membrane environments permissive for SNARE-mediated fusion. Full article

The critical binding of quantum states in Screened Coulomb Potentials such as Yukawa/Debye, Hulthén, and ECSC (Exponential Cosine Screened Coulomb) potentials is of perennial interest and relevance in many fields of science, ranging from nuclear and particle physics; plasma physics, astrophysics, cosmology, and nuclear fusion; physical chemistry, condensed matter, and materials physics; to synthetic nanostructures and nanophotonics. The purpose of this paper is to heuristically explore two related mysteries, one new, the other more than 50 years old. The solutions to these mysteries have implications for a much broader class of potentials, those addressed by Klaus and Simon. In our recent paper we presented numerical calculations using the Phase Method (PM), which is accurate to 60 digits and to screening lengths $\mathcal{D}\le {10}^3$ au and l = 0–20 of the critical binding parameters for these potentials and, for Yukawa and ECSC, l = 0–12 to $\mathcal{D}\le {10}^5$ au, at 30 digits. In doing so, we discovered an anomalous period-40 sawtooth structure in the critical parameters of the ECSC potential that is not observed for the Yukawa potential. In this second paper, we quantitatively explain the origin and periodicity of this newly discovered structure. To do so, we use two complementary approaches: a “neoclassical” (NC) variant of conventional semiclassical phase-space quantization and the PM for very precise fully quantum calculations. The observed period-40 sawtooth structure is quantitatively explained in terms of a novel “tick-tock” mechanism. The periodicity is calculated in terms of the ratio of phase-space integrals for the primary and secondary potential wells. A quartic double-well potential is used as a simple model to further illustrate the tick-tock mechanism. Using the NC method, an approximate expression is derived to predict the locations of tick-tock glitches from higher-order wells; it is confirmed by a PM calculation up to $\mathcal{D}\le {10}^6$ au. The second mystery is a strangely linear dependence of the total number of bound states vs. screening length for both the Yukawa and ECSC potentials. Using the PM, we confirm and extend these empirical relations. We show, using the PM, that an approximate trivariate linear relation between the square root of the critical screening length $\sqrt{D_c}$, state number n, and angular momentum l applies to these potentials. This, plus a geometrical state accumulation argument, solve the second mystery. We show these properties derive from the scaling relation between screening length and coupling constant and, as such, are predicted to be applicable to the whole class of potentials. These results are expected to be of both theoretical interest and experimental relevance when interpreting spectra or calculating thermal properties. The significance of these results, and the applicability of these methods and conclusions to a vast array of related potentials, is briefly discussed. Full article

Background: Plasma biomarkers are promoted as scalable tools for the staging of Alzheimer’s disease (AD), yet head-to-head comparisons against the clinical scales used to define diagnostic labels remain scarce. Reported gains from machine learning fusion of clinical and biomarker features may reflect label circularity rather than biological signals, and quantifying this circularity is a central aim of the present work. Methods: From the Alzheimer’s Disease Neuroimaging Initiative (ADNI), we assembled 655 participants (CN = 296, MCI = 168, and AD = 191) with concurrent plasma biomarkers (pT217, A$\beta$42/40, NfL, and GFAP), clinical scales (MMSE, CDR-SB, and FAQ), APOE genotype, and demographics. Three pre-specified feature sets (clinical-only, biomarker plus demographic–genetic, and full fusion) were compared across four classifiers (Logistic Regression, SVM, Random Forest, and XGBoost) using repeated, nested cross-validation (5-fold × 3 outer, 5-fold inner) with balanced class weighting. Because the external Center for Neurodegeneration and Translational Neuroscience (CNTN) cohort ($n=130$) measures pT181 rather than pT217 and lacks A$\beta$42/40, external evaluation used a separate reduced feature panel (NfL, GFAP, APOE, age, sex, and education), not the proposed pT217-inclusive panel. Results: Clinical scales alone reached a three-class AUC-OVR of $0.9539\pm 0.0041$, and fusion reached $0.9559\pm 0.0046$, an indistinguishable gain. Because MMSE, CDR-SB, and FAQ partly determine ADNI diagnostic labels, both estimates are circularity-inflated upper bounds and do not reflect independent classification power. Independent of this circularity, the internal plasma plus demographic–genetic model still achieved AUC-OVR $=0.7455\pm 0.0150$, with pT217 as the dominant contributor. Pairwise discrimination was excellent for CN vs. AD ($1.0000$) and MCI vs. AD ($0.9739$) but markedly weaker for CN vs. MCI ($0.9302$ for fused and $0.6972$ for plasma only). The separate reduced-feature model, which contains neither pT217 nor A$\beta$42/40, transferred to CNTN with AUC-OVR $=0.702$ (95% CI $0.635$–$0.764$). Conclusions: Apparent fusion gains in ADNI are largely a consequence of label circularity. After removing the circular clinical features, the internal pT217-inclusive plasma model supports three-class CN/MCI/AD screening at AUC $\approx 0.74$ and a reduced panel without pT217 transfers to an independent cohort at AUC $\approx 0.70$. These values provide a realistic performance estimate for blood-based AD staging under the current feature set, diagnostic label structure, and cohort design, and richer feature sets or pathology-anchored labels may shift this estimate. MCI detection remains the principal bottleneck. Full article

Drought stress severely impairs crop growth and agricultural productivity. Stomata, specialized structures in the leaf epidermis, play a critical role in gas exchange and transpiration. Therefore, reducing stomatal density to minimize water loss is an effective strategy for enhancing crop drought tolerance. The SDD1 gene was characterized as a negative regulator of stomatal density, and its function has been well characterized in model plants. However, its role in potato remains largely unknown. In this study, we identified a potato SDD1-like gene, StSDD1, which is predominantly expressed in young leaves and induced by drought stress and various hormones. Subcellular localization revealed that the StSDD1 fusion protein localizes to the plasma membrane and cytoplasm. Overexpression of StSDD1 decreased stomatal density and improved water use efficiency, leading to enhanced drought tolerance, whereas knockdown transgenic lines exhibited the opposite phenotype. Additionally, altering StSDD1 expression affected the expression of key stomatal development genes and several physiological and photosynthetic drought-related parameters. Taken together, our results suggest that StSDD1 enhances drought tolerance, potentially by reducing stomatal density. These findings indicate a role for StSDD1 in this process and provide a valuable genetic resource for molecular breeding of drought-resistant crops. Full article

We present a detailed study of the atomic structure and radiative properties of highly charged neon-like selenium (Se XXV), motivated by its importance in plasma diagnostics, fusion research, and astrophysical spectroscopy. We calculated excitation energies and radiative parameters for the 50 lowest levels of fine structure using a fully relativistic multiconfiguration Dirac–Fock approach. We calculated transition wavelengths, radiative transition rates, oscillator strengths, and line strengths for electric dipole, magnetic dipole, electric quadrupole, and magnetic quadrupole transitions among the specified levels. We also evaluated Einstein coefficients for spontaneous and stimulated emission, transition dipole moments, and radiative lifetimes of the low-lying states. To validate the results, we performed independent relativistic calculations using an alternative theoretical method and compared the datasets to examine internal consistency. The calculated excitation energies and radiative parameters agree well with values reported in the National Institute of Standards and Technology database (NIST) and other published theoretical results. The agreement between the independent approaches confirms the consistency of the present dataset. These results provide reliable atomic data for spectral line identification and quantitative plasma modeling in laboratory and astrophysical environments and support ongoing experimental and diagnostic studies of highly charged ions. Full article

Spatially resolved absolute intensities of the atomic lines $H_{\alpha }$, $H_{\beta }$, $H_{\gamma }$, and $H_{\delta }$ have been measured and analyzed in pure hydrogen plasma in the linear plasma device PSI-2. Two regimes have been investigated, with nominal (0.04 Pa) and elevated (0.5 Pa) gas pressure in the sample chamber. The measurements have been compared with local 0D calculations taking into account radiation from $H(n=1)$, $H_2$, and $H_2^{+}$ channels. A baseline plasma chemical mechanism developed in magnetic fusion research was applied to calculate the $H_2^{+}$ density. Both the plasma chemical mechanism and the population factors applied are based on Sawada–Fujimoto collision-radiative model of atomic and molecular hydrogen. The calculations were found to reproduce both the absolute radiation and the line radiation intensity ratios measured in the 0.04 Pa experiment with electron temperature $T_e$ = 2–10 eV and electron density ∼5 × 10¹⁷ m⁻³. An exception is the $H_{\alpha }/H_{\gamma }$ intensity ratio, which tends to be overestimated by the model. The calculations suggest that the majority of the observed Balmer radiation in this regime is due to the $H_2^{+}$ channel. At the same time, both the applied simplified approach without detailed transport modeling and the baseline mechanism were found to be inappropriate for the 0.5 Pa experiment with reduced $T_e$ = 1–5 eV. This experimental regime can serve as a benchmark of more sophisticated hydrogen plasma models. Full article

Background: Protein phosphatase 2Cs (PP2Cs) constitutes the largest phosphatase family in plants, playing a pivotal role in signal transduction. Within this family, the PP2C.D subfamily exerts significant influence on cell elongation and stress adaptation by mediating the ‘SAUR-PP2C.D-H+-ATPase’ regulatory module in the auxin signaling pathway. In rice, OsPP2C61 is a PP2C member whose molecular features and potential regulatory context remain unclear. Methods: Our study conducted a preliminary characterization of OsPP2C61 through integrated bioinformatics analysis, spatiotemporal expression profiling, and subcellular localization experiments in tobacco leaf cell. Results: OsPP2C61 encodes a 377-amino-acid protein predicted to be hydrophilic, basic, and structurally unstable. Secondary-structure prediction identified three major elements with random coils as the predominant component, whereas 3D modeling indicated alternating α-helices and β-sheets consistent with a canonical PP2C fold. Phylogenetic inference placed OsPP2C61 within the PP2C.D clade and revealed conserved motifs shared with OsPP2C25, OsPP2C28, and OsPP2C39. Promoter analysis showed enrichment of abscisic acid (ABA)- and methyl jasmonate (MeJA)-responsive elements along with multiple stress-related cis-regulatory motifs. Spatiotemporal expression analysis showed that OsPP2C61 is highly expressed in roots. Subcellular localization assays further demonstrated that the OsPP2C61-GFP fusion protein localizes to the nucleus and the plasma membrane when transiently expressed in epidermal cells of Nicotiana benthamiana. Conclusions: This work delivers the first comprehensive characterization of OsPP2C61, establishing a foundation for mechanistic studies and positioning OsPP2C61 as a candidate gene for rice improvement. Full article

Osmium is an element of the Periodic Table with an atomic number Z equal to 76. In Tokamaks with divertors made of tungsten ($Z=74$), it is produced in the neutron-induced transmutation of the latter. Therefore one can expect that their sputtering may generate ionic impurities of all possible charge states in the fusion plasma. As a consequence, these could contribute to radiation losses in these controlled nuclear devices. The knowledge of radiative rates in all the spectra of osmium is thus important in this field. In this framework, a multiplatform approach has been used to determine the Os V radiative properties and estimate their accuracy. The transition probabilities have been computed for the 2677 electric dipole (E1) transitions falling in the spectral range from 400 Å to 12,000 Å. Three independent atomic structure models have been considered; one based on the fully relativistic ab initio multiconfiguration Dirac–Hartree–Fock (MCDHF) method and two based on the semi-empirical pseudo-relativistic Hartree–Fock (HFR) method. Full article

The problem of controlling plasma is one of the most essential challenges in the creation of experimental facilities for thermonuclear fusion. In this study, a mathematical model of a two-component Vlasov–Poisson plasma is used to study the stability of spatial dynamic equilibria in this plasma. Applying the direct Lyapunov method, we obtain results that demonstrate that three-dimensional (3D) dynamic equilibrium states of the Vlasov–Poisson plasma are absolutely unstable with respect to small spatial perturbations. The sufficient conditions for linear practical instability are obtained for the 3D dynamic equilibria of a two-component Vlasov–Poisson plasma. An a priori exponential lower estimate is constructed, and initial data are found for small spatial perturbations that grow with time. Finally, analytical examples are presented for exact stationary solutions to the mathematical model of Vlasov–Poisson plasma and the growing small 3D perturbations superimposed on these solutions. Full article

Recombinant human bone morphogenic protein-2 (rhBMP-2) use in spinal fusion is limited by dose-dependent complications. Peptide amphiphile (PA) supramolecular polymers presenting a BMP-2–binding epitope have previously been developed to reduce the rhBMP-2 dose required for successful fusion. We evaluated PA implant biodegradation and tissue clearance in a rat posterolateral spinal fusion model as a prerequisite to clinical safety studies. Twenty-three female Sprague–Dawley rats underwent L4–L5 fusion with gadolinium (Gd)-labeled PA implants. Longitudinal magnetic resonance imaging (MRI) was performed up to 13 weeks postoperatively, while the spine and filter organs were harvested for inductively coupled plasma mass spectrometry (ICP-MS) quantification of Gd at multiple time points. Gd concentration at the fusion site decreased from 71% of maximum to 19.5% at 13 weeks, and MRI showed a complete loss of Gd signal enhancement by 8 weeks. In peripheral organs, peak Gd accumulation was 3% in the liver at 4 weeks, declining to 1.4% at 13 weeks, while Gd remained below 0.05% in the spleen, lung, and blood at all time points. These data indicate PA implant localization, with robust degradation and clearance and minimal off-target accumulation, supporting its translational potential for spinal fusion applications. Full article

Lung cancer remains the leading cause of cancer-related mortality worldwide and is frequently diagnosed at advanced stages, when metastatic dissemination is already present. Tumour hybrid cells (THCs) are rare circulating cells formed through fusion between cancer stem cells with leukocytes, predominantly monocytes. These cells combine traits from both lineages, conferring enhanced migratory, invasive and immune-evasive capacities that could promote metastasis. In parallel, soluble immune checkpoints (sICs) have emerged as minimally invasive biomarkers and indicators of systemic immune dysregulation and tumour-driven immune escape. In this study, 31 patients with lung cancer were prospectively enrolled at La Paz University Hospital (Madrid, Spain). Circulating THCs were quantified by spectral flow cytometry, and plasma sICs concentrations were determined using multiplex immunoassays. Patients were stratified by metastatic status and survival. Variables showing the strongest discriminative capacity were integrated into multivariable logistic regression models. Number of THCs, and levels of sCTLA-4, s-41BB, sLAG-3, and sTIM-3 exhibited the strongest discrimination for metastasis, while THCs, sLAG-3, and sTIM-3 distinguished deceased from surviving patients. Integrating predictive models demonstrated high accuracy, and survival analyses supported their prognostic significance. These findings indicate circulating THCs and selected sICs represent promising liquid biomarkers for monitoring lung cancer progression and patient outcomes. Full article

This paper introduces a novel quantum-inspired algorithm for numerical multiobjective optimization, uniquely integrating the multilevel structure of qudits with principles of controlled thermonuclear fusion. Moving beyond conventional qubit-based approaches, the algorithm leverages the qudit’s higher-dimensional state space to enhance search capabilities. Fusion-inspired dynamics—modeling particle interaction, energy release, and plasma cooling—provide a powerful metaheuristic framework for navigating complex, high-dimensional Pareto fronts. A hybrid quantum-classical version of the algorithm is presented, designed to exploit the complementary strengths of both computational paradigms for improved efficiency in solving dynamic multiobjective problems. Experimental evaluation on standard dynamic multiobjective benchmarks demonstrates clear performance advantages. Both the quantum-inspired and hybrid variants consistently outperform leading classical algorithms such as NSGA-III, MOEA/D and GDE3, as well as the quantum-inspired NSGA-III, in key metrics: identifying a greater number of unique non-dominated solutions, ensuring superior uniformity along the Pareto front, maintaining stable convergence across generations, and achieving higher accuracy in approximating the ideal solution. Full article

The modelling of plasma–wall interactions (PWIs) depends on distributions describing the angle and energy distribution of particles scattered at the first wall of fusion devices. Most PWI codes rely on extensive tables based on data from reflection simulations, employing a Monte Carlo method. At first glance, the uncertainty distribution of the data should be assumed Gaussian. However, in order to obtain the resulting particle distribution, the reflected ions are counted within angle sections of the upper hemisphere, which hints to a Poisson uncertainty distribution. In this paper, we let Bayesian model comparison decide which uncertainty model should be taken. Full article

Charcot–Marie–Tooth disease type 1A (CMT1A) is a hereditary condition caused by the duplication of the PMP22 gene. Overexpression of peripheral myelin protein 22 in Schwann cells leads to myelin sheath defects and axonal loss. We have produced a cell model to facilitate studies of the molecular mechanisms involved in PMP22 accumulation and clearance. Our model is a stably transfected, clonal, immortalised human Schwann cell line with overexpressed levels of PMP22 fusion protein. A control-transfected cell line (vector lacking PMP22) was also produced. PMP22-transfected cells had reduced levels of mitosis, with the PMP22 fusion protein concentrated in punctate aggregates in the cytoplasm and expressed at the plasma membranes, which were often irregular and spindly. In contrast, control cells (control-transfected and parent cell lines) generally had smooth and regular plasma membrane morphology. Culturing in the presence of NRG1 and forskolin lead to upregulation of markers of myelination potential in the control cells. These markers were more variable in the cells stably transfected with PMP22, including decreased levels of transcripts of SOX10, JUN, S100B and NGFR, but increased levels of MPZ and EGR2 compared to controls. Using proximity-dependent biotin identification (BioID2), several hundred proteins were identified in the proximity of the overexpressed PMP22, of which 291 significant proteins were only detected in the proximity of PMP22 and not in that of control pull-downs. Among the most significantly enriched PMP22-interacting proteins were integrins alpha-2 (ITGA2) and alpha-7 (ITGA7), which play a role in myelination via their interactions with the extracellular matrix. The presence of ITGA2 in just the PMP22-transfected fraction was confirmed by western blot. Some of the proteins were associated with several enriched molecular pathways, including molecular transport and protein trafficking, and may represent potential therapeutic targets for CMT1A by promoting the degradation and enhanced trafficking of PMP22. Full article

Magnetic confinement nuclear fusion offers a promising solution to the world’s growing energy demands. The DEMO reactor presented here aims to bridge the gap between laboratory fusion experiments and practical electricity generation, posing unique challenges for magnetic plasma diagnostics due to limited space for diagnostic equipment. This study employs Bayesian inference and Gaussian process modeling to integrate data from pick-up coils, flux loops, and saddle coils, enabling a qualitative estimation of the plasma current density distribution relying on only external magnetic measurements. The methodology successfully infers total plasma current, plasma centroid position, and six plasma–wall gap positions, while adhering to DEMO’s stringent accuracy standards. Additionally, the interchangeability between normal pick-up coils and saddle coils was assessed, revealing a clear preference for saddle coils. Initial steps were taken to utilize Bayesian experimental design for optimizing the orientation (normal or tangential) of pick-up coils within DEMO’s design constraints to improve the diagnostic setup’s inference precision. Our approach indicates the feasibility of Bayesian integrated data analysis in achieving precise and accurate probability distributions of plasma parameter crucial for the successful operation of DEMO. Full article