Beijing Computational Science Research Center

In experiments, the distributions of mRNA or protein numbers in single cells are often fitted to the random telegraph model which includes synthesis and decay of mRNA or protein, and switching of the gene between active and inactive states. While commonly used, this model does not describe how fluctuations are influenced by crucial biological mechanisms such as feedback regulation, non-exponential gene inactivation durations, and multiple gene activation pathways. Here we investigate the dynamical properties of four relatively complex gene expression models by fitting their steady-state mRNA or protein number distributions to the simple telegraph model. We show that despite the underlying complex biological mechanisms, the telegraph model with three effective parameters can accurately capture the steady-state gene product distributions, as well as the conditional distributions in the active gene state, of the complex models. Some effective parameters are reliable and can reflect realistic dynamic behaviors of the complex models, while others may deviate significantly from their real values in the complex models. The effective parameters can also be applied to characterize the capability for a complex model to exhibit multimodality. Using additional information such as single-cell data at multiple time points, we provide an effective method of distinguishing the complex models from the telegraph model. Furthermore, using measurements under varying experimental conditions, we show that fitting the mRNA or protein number distributions to the telegraph model may even reveal the underlying gene regulation mechanisms of the complex models. The effectiveness of these methods is confirmed by analysis of single-cell data for E. coli and mammalian cells. All these results are robust with respect to cooperative transcriptional regulation and extrinsic noise. In particular, we find that faster relaxation speed to the steady state results in more precise parameter inference under large extrinsic noise.

This study aims to investigate the feasibility of using an Artificial Lateral Line system for predicting the real-time position and pose of an undulating swimmer with Carangiform swimming patterns. We established a 3D Computational Fluid Dynamics simulation to replicate the swimming dynamics of a freely swimming mackerel under various motion parameters, calculating the corresponding pressure fields. Using the simulated lateral line data, we trained an artificial neural network to predict the centroid coordinates and orientation of the swimmer. A comprehensive analysis was further conducted to explore the impact of sensor quantity, distribution, noise amplitude and sampling intervals of the Artificial Lateral Line array on predicting performance. Additionally, to quantitatively assess the reliability of the localization network, we trained another neural network to evaluate error magnitudes for different input signals. These findings provide valuable insights for guiding future research on mutual sensing and schooling in underwater robotic fish.

Given that contextuality and coherence are significant resources in quantum physics, exploring the intricate interplay between these two factors presents a compelling avenue for research. Here, an experiment is presented to investigate the nuanced relationship between contextual robustness and coherence in a scenario of state discrimination. Specifically, two types of noises—depolarizing and dephasing—are introduced in the measurement procedure to assess the robustness of contextuality. By varying the overlap between the states to be discriminated, we explore the variations in contextual robustness across different levels of coherence. Importantly, our findings demonstrate that contextuality can persist under any degree of coherence. Notably, when coherence approaches zero (while remaining nonzero), contextuality can still endure under arbitrary amounts of partial dephasing. These results underscore the pivotal role of coherence in contextual phenomena, offering significant insights into the intricate interplay between coherence and contextuality.

Tuning of the magnetic interaction plays the vital role in reducing the clustering of magnetic dopant in diluted magnetic semiconductors (DMS). Due to the not well understood magnetic mechanism and the interplay between different magnetic mechanisms, no efficient and universal tuning strategy is proposed at present. Here, the magnetic interactions and formation energies of isovalent-doped (Mn) and aliovalent (Cr)-doped LiZnAs are studied based on density functional theory (DFT). It is found that the dopant–dopant distance-dependent magnetic interaction is highly sensitive to the carrier concentration and carrier type and can only be explained by the interplay between two magnetic mechanisms, i.e., super-exchange and Zener’s p–d exchange model. Thus, the magnetic behavior and clustering of magnetic dopant can be tuned by the interplay between two magnetic mechanisms. The insensitivity of the tuning effect to U parameter suggests that our strategy could be universal to other DMS.

Allergic diseases, affecting millions worldwide, have shown a progressive increase in recent years. Existing anti-allergy drugs primarily target symptoms and downstream reactions, necessitating the exploration of novel therapeutics addressing the root causes in the allergy pathway. Thymic stromal lymphopoietin (TSLP) and interleukin-33 (IL-33), classified as upstream cytokines, play pivotal roles in initiating type-2 immunity and are implicated in allergic diseases. However, small molecule antagonists for both TSLP and IL-33 proteins are still in early development and not yet available as treatments for allergic diseases. This study focuses on identifying natural small molecules that can inhibit both TSLP and IL-33 proteins. The study employed structure-based virtual screening to identify potential dual inhibitors of TSLP and IL-33 from the ZINC database. Through the use of Autodock Vina in PyRx software, virtual screening was conducted to predict the binding mode and binding affinity of these compounds. Molecular dynamics simulations utilizing GROMACS and binding free energy calculations (MM/PBSA) were performed to evaluate the stability and strength of interactions between the identified compounds and the target proteins. Additionally, bioavailability and toxicity analyses were carried out to evaluate the safety and pharmacokinetic properties of the compounds. The study successfully pinpointed three promising compounds, namely ZINC01105767 and ZINC08764679 (fused heterocyclic compounds), and ZINC33833100 (a limonin analogue), as potential dual inhibitors of both TSLP and IL-33 proteins. Molecular dynamics simulations confirmed the structural stability of these complexes, and the analysis of RMSD, RMSF, Rg, and SASA indicated strong interactions. Furthermore, the bioavailability analysis revealed drug-like properties, and toxicity analysis suggested that the compounds are non-mutagenic and non-tumorigenic. ZINC01105767, ZINC08764679, and ZINC33833100 represent promising lead candidates for the treatment of allergic diseases, particularly being heterocyclic compounds with benzoxalyl coumarin, and chromone moieties, which have shown effectiveness in allergic disease treatment.The comprehensive computational analysis provides valuable insights into the structural stability, structural integrity, compactness, folding properties and safety profiles of these compounds, highlighting their potential as anti-allergy agents. Among three dual candidate inhibitors, based on the MM/PBSA based binding free energy analysis, ZINC01105767 emerged as the most promising dual inhibitor, demonstrating the strongest binding affinity with a binding free energy of −43.31 kcal/mol in case of TSLP and −29.87 kcal/mol in case of IL-33. This suggests a potent interaction with both TSLP and IL-33 proteins, indicating its potential as a dual inhibitor targeting these pathways simultaneously. This study paves the way for further investigations and experimental validations, ultimately contributing to the development of more effective therapies for allergic diseases.

Background A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. Methods We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. Results Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. Conclusions Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

Rechargeable magnesium-metal batteries (RMMBs) are promising next-generation secondary batteries; however, their development is inhibited by the low capacity and short cycle lifespan of cathodes. Although various strategies have been devised to enhance the Mg ²⁺ migration kinetics and structural stability of cathodes, they fail to improve electronic conductivity, rendering the cathodes incompatible with magnesium-metal anodes. Herein, we propose a dual-defect engineering strategy, namely, the incorporation of Mg ²⁺ pre-intercalation defect (P-Mg d ) and oxygen defect (O d ), to simultaneously improve the Mg ²⁺ migration kinetics, structural stability, and electronic conductivity of the cathodes of RMMBs. Using lamellar V 2 O 5 ·nH 2 O as a demo cathode material, we prepare a cathode comprising Mg 0.07 V 2 O 5 ·1.4H 2 O nanobelts composited with reduced graphene oxide (MVOH/rGO) with P-Mg d and O d . The O d enlarges interlayer spacing, accelerates Mg ²⁺ migration kinetics, and prevents structural collapse, while the P-Mg d stabilizes the lamellar structure and increases electronic conductivity. Consequently, the MVOH/rGO cathode exhibits a high capacity of 197 mAh g ⁻¹ , and the developed Mg foil//MVOH/rGO full cell demonstrates an incredible lifespan of 850 cycles at 0.1 A g ⁻¹ , capable of powering a light-emitting diode. The proposed dual-defect engineering strategy provides new insights into developing high-durability, high-capacity cathodes, advancing the practical application of RMMBs, and other new secondary batteries.

Traditional metallic glasses (MGs), based on one or two principal elements, are notoriously known for their lack of tensile ductility at room temperature. Here, we developed a multiprincipal element MG (MPEMG), which exhibits a gigapascal yield strength, significant strain hardening that almost doubles its yield strength, and 2% uniform tensile ductility at room temperature. These remarkable properties stem from the heterogeneous amorphous structure of our MPEMG, which is composed of atoms with significant size mismatch but similar atomic fractions. In sharp contrast to traditional MGs, shear banding in our glass triggers local elemental segregation and subsequent ordering, which transforms shear softening to hardening, hence resulting in shear-band self-halting and extensive plastic flows. Our findings reveal a promising pathway to design stronger, more ductile glasses that can be applied in a wide range of technological fields.

A two-point boundary value problem whose highest-order derivative is a Riemann–Liouville–Caputo derivative of order \(\alpha \in (1,2)\) is considered. A similar problem was considered in Gracia et al. (BIT 60:411–439, 2020) but under a simplifying assumption that excluded singular solutions. In the present paper, this assumption is not imposed; furthermore, the finite difference method of the BIT paper, which was proved to attain 1st-order convergence under a sign restriction on the convective term, is replaced by a piecewise polynomial collocation method which can give any desired integer order of convergence on a suitably graded mesh. An error analysis of the collocation method is given which removes the above sign restriction and numerical results are presented to support our theoretical conclusions. The tools devised for this analysis include new comparison principles for Caputo initial-value problems and weakly singular Volterra integral equations that are of independent interest. Numerical experiments demonstrate the sharpness of our theoretical results.

The Yang-Lee edge singularity was originally studied from the standpoint of mathematical foundations of phase transitions. However, direct observation of anomalous scaling with the negative scaling dimension has remained elusive due to an imaginary magnetic field required for the nonunitary criticality. We experimentally implement an imaginary magnetic field with an open quantum system of heralded single photons, directly measure the partition function, and demonstrate the Yang-Lee edge singularity via the quantum-classical correspondence. We also demonstrate unconventional scaling laws for finite-temperature quantum dynamics.

The layered square-planar nickelates Rn+1NinO2n+2 (R: rare-earth element) hold great promise in realizing cupratelike superconductors. While the appearance of zero resistivity is extremely sensitive to the concentration of hydrogen(x) in infinite-layer Sr0.2Nd0.8NiO2Hx, the configurations of many other Ndn+1NinO2n+2Hx and the general roles of H in these systems are still unknown. Using first-principles calculations, we find that H atoms prefer to form staggered one-dimensional chains along the c axis, which are obstructed by the fluorite layer of Ndn+1NinO2n+2. Importantly, the charge-transfer energy between O 2p and Ni 3d, one of the key factors determining the superconducting temperature in cuprates, is largely and continuously tunable by n and x in nickelates. Further, from the perspective of orbital hybridization and orbital polarization, the quasi-two-dimensional electronic properties are more pronounced for nickelates with smaller n, potentially facilitating superconductivity. These findings shed light on the general roles of H in controlling electronic properties in nickelates and provide valuable guidance for the experimental preparation of superconducting Rn+1NinO2n+2 materials.

Background Klebsiella pneumoniae is a major bacterial and opportunistic human pathogen, increasingly recognized as a healthcare burden globally. The convergence of resistance and virulence in K. pneumoniae strains has led to the formation of hypervirulent and multidrug-resistant strains with dual risk, limiting treatment options. K. pneumoniae clones are known to emerge locally and spread globally. Therefore, an understanding of the dynamics and evolution of the emerging strains in hospitals is warranted to prevent future outbreaks. Methods In this study, we conducted an in-depth genomic analysis on a large-scale collection of 328 multidrug-resistant (MDR) K. pneumoniae strains recovered from 239 patients from a single major hospital in the western coastal city of Jeddah in Saudi Arabia from 2014 through 2022. We employed a broad range of phylogenetic and phylodynamic methods to understand the evolution of the predominant clones on epidemiological time scales, virulence and resistance determinants, and their dynamics. We also integrated the genomic data with detailed electronic health record (EHR) data for the patients to understand the clinical implications of the resistance and virulence of different strains. Results We discovered a diverse population underlying the infections, with most strains belonging to Clonal Complex 14 (CC14) exhibiting dominance. Specifically, we observed the emergence and continuous expansion of strains belonging to the dominant ST2096 in the CC14 clade across hospital wards in recent years. These strains acquired resistance mutations against colistin and extended spectrum β-lactamase (ESBL) and carbapenemase genes, namely blaOXA-48 and blaOXA-232, located on three distinct plasmids, on epidemiological time scales. Strains of ST2096 exhibited a high virulence level with the presence of the siderophore aerobactin (iuc) locus situated on the same mosaic plasmid as the ESBL gene. Integration of ST2096 with EHR data confirmed the significant link between colonization by ST2096 and the diagnosis of sepsis and elevated in-hospital mortality (p-value < 0.05). Conclusions Overall, these results demonstrate the clinical significance of ST2096 clones and illustrate the rapid evolution of an emerging hypervirulent and MDR K. pneumoniae in a clinical setting.

van der Waals (vdW) layered semiconductors exhibiting large nonlinear-optical (NLO) effects have substantial potential for developing nanoscale quantum optical devices. NbOCl2, an ultrathin quantum light source, has recently displayed a large second harmonic effect. However, its small bandgap (∼1.8 eV) impedes transparent light conversion across wide spectral regions, especially when utilizing practical 1-µm lasers. In this paper, we found that MO2X2 (M=W, Mo; X=Cl, Br) effectively widens the bandgap by using W6+ or Mo6+ instead of Nb4+ to eliminate in-gap nonbonding orbitals. Meanwhile, the octahedral [MO4X2] motifs display polar Jahn-Teller distortions as large as [NbO2X4] to demonstrate comparable NLO polarization effects. Based on first-principles calculations, WO2Cl2 and MoO2Br2 are predicted to possess wider bandgaps (2.9 and 2.2 eV), giant birefringence (0.5–0.7), and significant second harmonic and ferroelectric photovoltaic effects competitive with NbOX2. These findings provide strong incentives to explore new vdW materials with superior NLO properties.

Background We previously demonstrated that insulin-like growth factor-1 (IGF-1) regulates sodium/potassium adenosine triphosphatase (Na⁺/K⁺-ATPase) in vascular smooth muscle cells (VSMC) via phosphatidylinositol-3 kinase (PI3K). Taking into account that others’ work show that IGF-1 activates the PI3K/protein kinase B (Akt) signaling pathway in many different cells, we here further questioned if the Akt/mammalian target of rapamycin (mTOR)/ribosomal protein p70 S6 kinase (S6K) pathway stimulates Na⁺/K⁺-ATPase, an essential protein for maintaining normal heart function. Methods and results There were 14 adult male Wistar rats, half of whom received bolus injections of IGF-1 (50 μg/kg) for 24 h. We evaluated cardiac Na⁺/K⁺-ATPase expression, activity, and serum IGF-1 levels. Additionally, we examined the phosphorylated forms of the following proteins: insulin receptor substrate (IRS), phosphoinositide-dependent kinase-1 (PDK-1), Akt, mTOR, S6K, and α subunit of Na⁺/K⁺-ATPase. Additionally, the mRNA expression of the Na⁺/K⁺-ATPase α1 subunit was evaluated. Treatment with IGF-1 increases levels of serum IGF-1 and stimulates Na⁺/K⁺-ATPase activity, phosphorylation of α subunit of Na⁺/K⁺-ATPase on Ser²³, and protein expression of α2 subunit. Furthermore, IGF-1 treatment increased phosphorylation of IRS-1 on Tyr¹²²², Akt on Ser⁴⁷³, PDK-1 on Ser²⁴¹, mTOR on Ser²⁴⁸¹ and Ser²⁴⁴⁸, and S6K on Thr⁴²¹/Ser⁴²⁴. The concentration of IGF-1 in serum positively correlates with Na⁺/K⁺-ATPase activity and the phosphorylated form of mTOR (Ser²⁴⁴⁸), while Na⁺/K⁺-ATPase activity positively correlates with the phosphorylated form of IRS-1 (Tyr¹²²²) and mTOR (Ser²⁴⁴⁸). Conclusion These results indicate that the Akt/mTOR/S6K signalling pathway may be involved in the IGF-1 regulating cardiac Na⁺/K⁺-ATPase expression and activity.

Since charge-carrier radiative recombination is a key process in semiconductors that enables light emission, it is critical to understand its chemical trend and microscopic mechanisms. Using III-nitride semiconductors as prototypical examples, we rigorously study the radiative recombination mechanisms employing first principles. We show that the radiative recombination coefficient is competitively impacted by the band gap, effective masses, and dipole matrix elements, but the band gap plays a dominant role. The radiative recombination coefficient is actually stronger in AlN, as compared to the ones in InN and GaN, despite the fact that AlN-based light-emitting diodes (LEDs) currently exhibit low efficiencies. However, the polarization direction of light emission in AlN is qualitatively different from those in InN and GaN due to valence-band reordering, which may lead to additional complication in light extraction. Our insights pave the way to optimize the optoelectronic performance of wide-band-gap LEDs.

Mg‐ion batteries (MIBs) are promising next‐generation secondary batteries, but suffer from sluggish Mg²⁺ migration kinetics and structural collapse of the cathode materials. Here, an H2O‐Mg²⁺ waltz‐like shuttle mechanism in the lamellar cathode, which is realized by the coordination, adaptive rotation and flipping, and co‐migration of lattice H2O molecules with inserted Mg²⁺, leading to the fast Mg²⁺ migration kinetics, is reported; after Mg²⁺ extraction, the lattice H2O molecules rearrange to stabilize the lamellar structure, eliminating structural collapse of the cathode. Consequently, the demo cathode of Mg0.75V10O24·nH2O (MVOH) exhibits a high capacity of 350 mAh g⁻¹ at a current density of 50 mA g⁻¹ and maintains a capacity of 70 mAh g⁻¹ at 4 A g⁻¹. The full aqueous MIB based on MVOH delivers an ultralong lifespan of 5000 cycles The reported waltz‐like shuttle mechanism of lattice H2O provides a novel strategy to develop high‐performance cathodes for MIBs as well as other multivalent‐ion batteries.