Phosphatidylinositol-5-Phosphate 4-Kinases Regulate Cellular Lipid Metabolism By Facilitating Autophagy.

While the majority of phosphatidylinositol-4, 5-bisphosphate (PI-4, 5-P2) in mammalian cells is generated by the conversion of phosphatidylinositol-4-phosphate (PI-4-P) to PI-4, 5-P2, a small fraction can be made by phosphorylating phosphatidylinositol-5-phosphate (PI-5-P). The physiological relevance of this second pathway is not clear. Here, we show that deletion of the genes encoding the two most active enzymes in this pathway, Pip4k2a and Pip4k2b, in the liver of mice causes a large enrichment in lipid droplets and in autophagic vesicles during fasting. These changes are due to a defect in the clearance of autophagosomes that halts autophagy and reduces the supply of nutrients salvaged through this pathway. Similar defects in autophagy are seen in nutrient-starved Pip4k2a-/-Pip4k2b-/- mouse embryonic fibroblasts and in C. elegans lacking the PI5P4K ortholog. These results suggest that this alternative pathway for PI-4, 5-P2 synthesis evolved, in part, to enhance the ability of multicellular organisms to survive starvation.

MESPool: Molecular Edge Shrinkage Pooling for hierarchical molecular representation learning and property prediction.

Identifying task-relevant structures is important for molecular property prediction. In a graph neural network (GNN), graph pooling can group nodes and hierarchically represent the molecular graph. However, previous pooling methods either drop out node information or lose the connection of the original graph; therefore, it is difficult to identify continuous subtructures. Importantly, they lacked interpretability on molecular graphs. To this end, we proposed a novel Molecular Edge Shrinkage Pooling (MESPool) method, which is based on edges (or chemical bonds). MESPool preserves crucial edges and shrinks others inside the functional groups and is able to search for key structures without breaking the original connection. We compared MESPool with various well-known pooling methods on different benchmarks and showed that MESPool outperforms the previous methods. Furthermore, we explained the rationality of MESPool on some datasets, including a COVID-19 drug dataset.

Twin Strep-Tag Modified CPT1A Mitochondrial Membrane Chromatography in Screening Lipid Metabolism Regulators.

Mitochondrial Membrane Chromatography (MMC) is a bioaffinity chromatography technique developed to study the interaction between target proteins embedded in the mitochondrial membrane and their ligand compounds. However, the MMC stationary phases (MMSP) prepared by chemical immobilization are prone to nonspecific binding in candidate agent screening inevitably. To address these challenges, Twin Strep-Tag/Strep Tactin was employed to establish a specific affinity system in the present study. We prepared a carnitine palmitoyltransferase 1A (CPT1A) MMSP by specifically linking Strep-tactin-modified silica gel with the Twin Strep-Tag on the CPT1A-oriented mitochondrial membrane. This Twin Strep-Tag/Strep Tactin modified CPT1A/MMC method exhibited remarkably better retention behavior, longer stationary phase lifespan, and higher screening specificity compared with previous MMC systems with glutaraldehyde immobilization. We adopted the CPT1A-specific MMC system in screening CPT1A ligands from traditional Chinese medicines, and successfully identified novel candidate ligands: ononin, isoliquiritigenin, and aloe-emodin, from Glycyrrhiza uralensis Fisch and Senna tora (L.) Roxb extracts. Biological assessments illustrated that the compounds screened promote CPT1A enzyme activity without affecting CPT1A protein expression, as well as effectively reduce the lipid droplets and triglyceride levels in the high fat induction HepG2 cells. The results suggest that we have developed an MMC system, which is promising for studying the bioaffinity of mitochondrial membrane proteins to candidate compounds. This system provides a platform for a key step in mitochondrial medicine discovery, especially for bioactive molecule screening from complex herbal extracts.

Tunable-bias based optical neural network for reinforcement learning in path planning.

Owing to the high integration, reconfiguration and strong robustness, Mach-Zehnder interferometers (MZIs) based optical neural networks (ONNs) have been widely considered. However, there are few works adding bias, which is important for neural networks, into the ONNs and systematically studying its effect. In this article, we propose a tunable-bias based optical neural network (TBONN) with one unitary matrix layer, which can improve the utilization rate of the MZIs, increase the trainable weights of the network and has more powerful representational capacity than traditional ONNs. By systematically studying its underlying mechanism and characteristics, we demonstrate that TBONN can achieve higher performance by adding more optical biases to the same side beside the inputted signals. For the two-dimensional dataset, the average prediction accuracy of TBONN with 2 biases (97.1%) is 5% higher than that of TBONN with 0 biases (92.1%). Additionally, utilizing TBONN, we propose a novel optical deep Q network (ODQN) algorithm to complete path planning tasks. By implementing simulated experiments, our ODQN shows competitive performance compared with the conventional deep Q network, but accelerates the computation speed by 2.5 times and 4.5 times for 2D and 3D grid worlds, respectively. Further, a more noticeable acceleration will be obtained when applying TBONN to more complex tasks. Also, we demonstrate the strong robustness of TBONN and the imprecision elimination method by using on-chip training.

Efficacy of 1-hour postload plasma glucose as a suitable measurement in predicting type 2 diabetes and diabetes-related complications: A post hoc analysis of the 30-year follow-up of the Da Qing IGT and Diabetes Study.

AIM: To evaluate whether 1-hour plasma glucose (1hPG) can be a comparable measurement to 2-hour plasma glucose (2hPG) in identifying individuals at high risk of developing diabetes. METHODS: A total of 1026 non-diabetic subjects in the Da Qing IGT and Diabetes Study were included and classified according to baseline postload 1hPG. The participants were followed up and assessed at 6-, 20- and 30year follow-up for outcomes including diabetes, all-cause and cardiovascular mortality, cardiovascular disease (CVD) events, and microvascular disease. We then conducted a proportional hazards analysis in this post hoc study to determine the risks of developing type 2 diabetes and its complications in a '1hPG-normal' group (1hPG <8.6 mmol/L) and a '1hPG-high' group (≥8.6 mmol/L). The predictive values of 1hPG and 2hPG were evaluated using a time-dependent receiver-operating characteristic (ROC) curve. RESULTS: Compared with the 1hPG-normal group, the 1hPG-high group had increased risk of diabetes (hazard ratio [HR] 4.45, 95% CI 3.43-5.79), all-cause mortality (HR 1.46, 95% CI 1.07-2.01), CVD mortality (HR 1.84, 95% CI 1.16-2.95), CVD events (HR 1.39, 95% CI 1.03-1.86) and microvascular disease (HR 1.70, 95% CI: 1.03-2.79) after adjusting for confounders. 1hPG exhibited a higher area under the ROC curve (AUC) for predicting diabetes than 2hPG during the long-term follow-up (AUC [1hPG vs. 2hPG]: 10 years: 0.86 vs. 0.84, p = 0.08; 20 years: 0.88 vs. 0.87, p = 0.04; 30 years: 0.85 vs. 0.82, p = 0.009). CONCLUSIONS: Elevated 1hPG level (≥8.6 mmol/L) was associated with increased risk of developing type 2 diabetes and its long-term complications, and could be considered as a suitable measurement for identifying individuals at high risk of type 2 diabetes.

Molecular Insights into Macromolecules Structure, Function, and Regulation.

Macromolecules exhibit ordered structures and complex functions in an aqueous environment with strong thermodynamic fluctuations [...].

Co-Mutations and Possible Variation Tendency of the Spike RBD and Membrane Protein in SARS-CoV-2 by Machine Learning.

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, SARS-CoV-2 variants capable of breakthrough infections have attracted global attention. These variants have significant mutations in the receptor-binding domain (RBD) of the spike protein and the membrane (M) protein, which may imply an enhanced ability to evade immune responses. In this study, an examination of co-mutations within the spike RBD and their potential correlation with mutations in the M protein was conducted. The EVmutation method was utilized to analyze the distribution of the mutations to elucidate the relationship between the mutations in the spike RBD and the alterations in the M protein. Additionally, the Sequence-to-Sequence Transformer Model (S2STM) was employed to establish mapping between the amino acid sequences of the spike RBD and M proteins, offering a novel and efficient approach for streamlined sequence analysis and the exploration of their interrelationship. Certain mutations in the spike RBD, G339D-S373P-S375F and Q493R-Q498R-Y505, are associated with a heightened propensity for inducing mutations at specific sites within the M protein, especially sites 3 and 19/63. These results shed light on the concept of mutational synergy between the spike RBD and M proteins, illuminating a potential mechanism that could be driving the evolution of SARS-CoV-2.

The Inhibition Effect of Epigallocatechin-3-Gallate on the Co-Aggregation of Amyloid-ß and Human Islet Amyloid Polypeptide Revealed by Replica Exchange Molecular Dynamics Simulations.

Alzheimer's disease and Type 2 diabetes are two epidemiologically linked diseases which are closely associated with the misfolding and aggregation of amyloid proteins amyloid-ß (Aß) and human islet amyloid polypeptide (hIAPP), respectively. The co-aggregation of the two amyloid proteins is regarded as the fundamental molecular mechanism underlying their pathological association. The green tea extract epigallocatechin-3-gallate (EGCG) has been extensively demonstrated to inhibit the amyloid aggregation of Aß and hIAPP proteins. However, its potential role in amyloid co-aggregation has not been thoroughly investigated. In this study, we employed the enhanced-sampling replica exchange molecular dynamics simulation (REMD) method to investigate the effect of EGCG on the co-aggregation of Aß and hIAPP. We found that EGCG molecules substantially diminish the ß-sheet structures within the amyloid core regions of Aß and hIAPP in their co-aggregates. Through hydrogen-bond, π-π and cation-π interactions targeting polar and aromatic residues of Aß and hIAPP, EGCG effectively attenuates both inter-chain and intra-chain interactions within the co-aggregates. All these findings indicated that EGCG can effectively inhibit the co-aggregation of Aß and hIAPP. Our study expands the potential applications of EGCG as an anti-amyloidosis agent and provides therapeutic options for the pathological association of amyloid misfolding disorders.

Corporate political acuity and carbon - efficiency synergies.

RESEARCH QUESTION: In the context of global low-carbon emission reduction, how to achieve green and high-quality development has become a major issue for the Communist Party of China (CPC) and the Chinese government recently. Based on the data of China's listed companies from 2013 to 2020, this paper uses Python to implement text analysis of annual reports, and explores the relationship between political acuity and carbon-efficiency synergies (CES) from the perspective of enterprise initiative. RESEARCH FINDINGS: We found that (1) political acuity positively affects carbon-efficiency synergies. (2) Increased political acuity can reduce carbon emissions, but the effect on economic efficiency is not obvious. That is, low carbon takes the lead in raising the level of carbon-efficiency synergies. (3) Environmental regulations can positively regulate the relationship between political acuity and carbon-efficiency synergies. (4) Political acuity in southern China, carbon neutral and non-state-owned enterprises (NSOEs) will have a more pronounced effect on carbon-efficiency synergies. ACADEMIC IMPLICATIONS: From the perspective of the root causes of political linkages, we find the synergies between formal and informal institutions, and the key factors for policy implementation. POLICY IMPLICATIONS: This paper is helpful for enterprises to improve the synergies of emission reduction and efficiency promotion, and has practical implications for the government to promote green and high-quality development.

MIL-101(CuFe) Nanozymes with Excellent Peroxidase-like Activity for Simple, Accurate, and Visual Naked-Eye Detection of SARS-CoV-2.

The COVID-19 pandemic has spread to every corner of the world and seriously affected our health and daily activities in the past three years; thereby, it is still urgent to develop various simple, quick, and accurate methods for early detection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Nanozymes, a kind of nanomaterial with intrinsic enzyme-mimicking activity, have emerged as a suitable alternative for both therapy and diagnosis of SARS-CoV-2. Here, ultrasensitive and ultrafast MIL-101(CuFe)-CD147 biosensors are established for the detection of SARS-CoV-2 by a simple colorimetric method. A MIL-101(CuFe) metal-organic framework has excellent peroxidase-like activity due to the synergistic effect of Fe and Cu atoms. In addition, the MIL-101(CuFe)-CD147 biosensor shows great potential to detect the various variants of SARS-CoV-2 due to the universal receptor of CD147. The enzyme-based biosensor for the detection of SARS-CoV-2 achieves a very low limit of detection (about 3 PFU/mL) within 30 min. Therefore, the present method provides a new generation of an alternative approach for highly sensitive and visual diagnosis of COVID-19.

Shear polaritons from transformation optics.

Natural in-plane hyperbolic crystals (such as α-MoO3) and natural monoclinic crystals (such as ß-Ga2O3) have recently drawn great research focus. Despite their obvious similarities, however, these two kinds of materials are usually studied as separate topics. In this Letter, we explore the intrinsic relationship between materials like α-MoO3 and ß-Ga2O3 under the framework of transformation optics, providing another perspective to understand the asymmetry of hyperbolic shear polaritons. It is worth mentioning that we demonstrate this novel, to the best of our knowledge, method from theoretical analysis and numerical simulations, which maintain a high degree of consistency. Our work not only combines natural hyperbolic materials with the theory of classical transformation optics, but also opens new avenues for future studies of various natural materials.

A comparative study of H2 sensing performance of stoichiometric polymorphs of titanium carbide MXenes loaded with Pd nanodots.

Although titanium-based MXenes have been widely reported for gas sensing, the effect of crystal stoichiometric variations on the sensing properties has been rarely reported. Herein, stoichiometric polymorphs of titanium carbide MXenes (i.e., Ti3C2Tx and Ti2CTx) loaded with Pd nanodots (NDs) prepared by photochemical reduction were investigated for room-temperature H2 sensing. Interestingly, we found that Pd/Ti2CTx exhibited greatly enhanced sensitivity to H2, along with faster response and recovery rates compared to Pd/Ti3C2Tx. The H2 adsorption induced resistance change in Pd/Ti2CTx was higher than that of Pd/Ti3C2Tx due to the more effective charge transfer at the heterointerface of Pd/Ti2CTx, which was confirmed by shifts of binding energies and theoretical calculation results. We hope this work could be helpful to design more high-performance MXene-based gas sensors.

A distributed-order fractional stochastic differential equation driven by Lévy noise: Existence, uniqueness, and a fast EM scheme.

In this paper, we consider a distributed-order fractional stochastic differential equation driven by Lévy noise. We, first, prove the existence and uniqueness of the solution. A Euler-Maruyama (EM) scheme is constructed for the equation, and its strong convergence order is shown to be min{1-α∗,0.5}, where α∗ depends upon the weight function. Besides, we present a fast EM method and also the error analysis of the fast scheme. In addition, several numerical experiments are carried out to substantiate the mathematical analysis.

Dissecting the Structural Dynamics of Authentic Cholesteryl Ester Transfer Protein for the Discovery of Potential Lead Compounds: A Theoretical Study.

Current structural and functional investigations of cholesteryl ester transfer protein (CETP) inhibitor design are nearly entirely based on a fully active mutation (CETPMutant) constructed for protein crystallization, limiting the study of the dynamic structural features of authentic CETP involved in lipid transport under physiological conditions. In this study, we conducted comprehensive molecular dynamics (MD) simulations of both authentic CETP (CETPAuthentic) and CETPMutant. Considering the structural differences between the N- and C-terminal domains of CETPAuthentic and CETPMutant, and their crucial roles in lipid transfer, we identified the two domains as binding pockets of the ligands for virtual screening to discover potential lead compounds targeting CETP. Our results revealed that CETPAuthentic displays greater flexibility and pronounced curvature compared to CETPMutant. Employing virtual screening and MD simulation strategies, we found that ZINC000006242926 has a higher binding affinity for the N- and C-termini, leading to reduced N- and C-opening sizes, disruption of the continuous tunnel, and increased curvature of CETP. In conclusion, CETPAuthentic facilitates the formation of a continuous tunnel in the "neck" region, while CETPMutant does not exhibit such characteristics. The ligand ZINC000006242926 screened for binding to the N- and C-termini induces structural changes in the CETP unfavorable to lipid transport. This study sheds new light on the relationship between the structural and functional mechanisms of CETP. Furthermore, it provides novel ideas for the precise regulation of CETP functions.

Exploration of the Character Representation of DNA Chiral Conformations and Deformations via a Curved Surface Discrete Frenet Frame.

While undergoing structural deformation, DNA experiences changes in the interactions between its internal base pairs, presenting challenges to conventional elastic methods. To address this, we propose the Discrete Critical State (DCS) model in this paper. This model combines surface discrete frame theory with gauge theory and Landau phase transition theory to investigate DNA's structural deformation, phase transitions, and chirality. Notably, the DCS model considers both the internal interactions within DNA and formulates an overall equation using unified physical and geometric parameters. By employing the discrete frame, we derive the evolution of physical quantities along the helical axis of DNA, including geodesic curvature, geodesic torsion, and others. Our findings indicate that B-DNA has a significantly lower free energy density compared to Z-DNA, which is in agreement with experimental observations. This research reveals that the direction of base pairs is primarily governed by the geodesic curve within the helical plane, aligning closely with the orientation of the base pairs. Moreover, the geodesic curve has a profound influence on the arrangement of base pairs at the microscopic level and effectively regulates the configuration and geometry of DNA through macroscopic-level free energy considerations.

Simultaneous Improvement in the Thermostability and Catalytic Activity of Epoxidase Lsd18 for the Synthesis of Lasalocid A.

Enzymes used in the synthesis of natural products are potent catalysts, capable of efficient and stereoselective chemical transformations. Lsd18 catalyzes two sequential epoxidations during the biosynthesis of lasalocid A, a polyether polyketide natural product. We performed protein engineering on Lsd18 to improve its thermostability and catalytic activity. Utilizing structure-guided methods of FoldX and Rosetta-ddG, we designed 15 mutants of Lsd18. Screening of these mutants using thermal shift assay identified stabilized variants Lsd18-T189M, Lsd18-S195M, and the double mutant Lsd18-T189M-S195M. Trypsin digestion, molecular dynamic simulation, circular dichroism (CD) spectroscopy, and X-ray crystallography provided insights into the molecular basis for the improved enzyme properties. Notably, enhanced hydrophobic interaction within the enzyme core and interaction of the protein with the FAD cofactor appear to be responsible for its better thermostability.

Identification of Potential Lead Compounds Targeting Novel Druggable Cavity of SARS-CoV-2 Spike Trimer by Molecular Dynamics Simulations.

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become an urgent public health problem. Spike (S) protein mediates the fusion between the virus and the host cell membranes, consequently emerging as an important target of drug design. The lack of comparisons of in situ full-length S homotrimer structures in different states hinders understanding the structures and revealing the function, thereby limiting the discovery and development of therapeutic agents. Here, the steady-state structures of the in situ full-length S trimer in closed and open states (Sclosed and Sopen) were modeled with the constraints of density maps, associated with the analysis of the dynamic structural differences. Subsequently, we identified various regions with structure and property differences as potential binding pockets for ligands that promote the formation of inactive trimeric protein complexes. By using virtual screening strategy and a newly defined druggable cavity, five ligands were screened with potential bioactivities. Then molecular dynamic (MD) simulations were performed on apo protein structures and ligand bound complexes to reveal the conformational changes upon ligand binding. Our simulation results revealed that sulforaphane (SFN), which has the best binding affinity, could inhibit the conformational changes of S homotrimer that would occur during the viral membrane fusion. Our results could aid in the understanding of the regulation mechanism of S trimer aggregation and the structure-activity relationship, facilitating the development of potential antiviral agents.

Gold Nanorods/Metal-Organic Framework Hybrids: Photo-Enhanced Peroxidase-Like Activity and SERS Performance for Organic Dyestuff Degradation and Detection.

Metal-organic frameworks (MOFs) are widely used to mimic enzymes for catalyzing chemical reactions; however, low enzyme activity limit their large-scale application. In this work, gold nanorods/metal-organic frameworks (Au NRs/Fe-MOF) hybrids were successfully synthesized for photo-enhanced peroxidase-like catalysis and surface-enhanced Raman spectroscopy (SERS). The enzyme-like activity of Au NRs/Fe-MOF hybrids was significantly enhanced under localized surface plasmon resonance (LSPR), because the hot electrons produced on Au NRs surface were transferred into Fe-MOF, activating the Fenton reaction by Fe3+/Fe2+ conversion and preventing the recombination of hot electrons and holes. This photo-enhanced enzyme-like catalytic performance was investigated by X-ray photoelectron spectrometry (XPS), electrochemical analysis, activation energy measurement, and in situ Raman spectroscopy. Afterward, Methylene Blue (MB) was chosen to demonstrate the photo-enhanced peroxidase-like performance of Au NRs/Fe-MOFs. The Au NRs/Fe-MOF caused chemical and electromagnetic enhancement of Raman signals and exhibited a great potential for the detection of toxic chemicals and biological molecules. The detection limit of MB concentration is 9.3 × 10-12 M. In addition, the Au NRs/Fe-MOF hybrids also showed excellent stability and reproducibility for photo-enhanced peroxidase-like catalysis. These results show that nanohybrids have great potential in many fields, such as sensing, cancer therapy, and energy harvesting.

Deposition of Vertically Aligned Ag/Ag2 S Nanoflakes on EGaIn Particles for Humidity Sensing.

Liquid metals, which possess both good electrical conductivity and liquid-like processability, have drawn much attention recently. They are also capable of acting as synthesis templates to guide the deposition of other functional materials. Herein, through an in-situ galvanic replacement reaction assisted by ultrasonication, core-shell EGaIn/Ag particles composed of EGaIn cores and vertically aligned Ag nanoflakes as shells were prepared; they were further sulfurized to yield ternary EGaIn/Ag/Ag2 S core-shell composite particles. A humidity sensor based on EGaIn/Ag/Ag2 S particles showed much higher sensing response than EGaIn and EGaIn/Ag. Such superior performance could be attributed to the n-type semiconducting character of Ag2 S allowing it to receive electrons from water molecules at low humidity, and its highly hydrophilic surface allowing it to absorb more water molecules at higher humidity so as to enable the formation of ion-conductive paths.

Mechanism of Glycans Modulating Cholesteryl Ester Transfer Protein: Unveiled by Molecular Dynamics Simulation.

Inhibition of the cholesteryl ester transfer protein (CETP) has been considered as a promising way for the treatment of cardiovascular disease (CVD) for three decades. However, clinical trials of several CETP inhibitors with various potencies have been marginally successful at best, raising doubts on the target drugability of CETP. The in-depth understanding of the glycosylated CETP structure could be beneficial to more definitive descriptions of the CETP function and the underlying mechanism. In this work, large-scale molecular dynamics simulations were performed to thoroughly explore the mechanism of glycans modulating CETP. Here, the extensive simulation results intensely suggest that glycan88 tends to assist CETP in forming a continuous tunnel throughout interacting with the upper-right region of the N-barrel, while it also could prevent the formation of a continuous tunnel by swinging toward the right-rear of the N-barrel. Furthermore, glycan240 formed stable H-bonds with Helix-B and might further stabilize the central cavity of CETP. Furthermore, the nonspecific involvement of the hydroxyl groups from the various glycans with protein core interactions and the similar influence of different glycans trapped at similar regions on the protein structure suggest that physiological glycan may lead to a similar effect. This study would provide valuable insights into devising novel methods for CVD treatment targeting CETP and functional studies about glycosylation for other systems.