Characteristics and outcomes associated with sarcomere mutations in patients with hypertrophic cardiomyopathy: A systematic review and meta-analysis.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is an inherited heart disease that can lead to sudden cardiac death. Impact of genetic testing for the prognosis and treatment of patients with HCM needs to be improved. We conducted a systematic review and meta-analysis to investigate the characteristics and outcomes associated with sarcomere genotypes in index patients with HCM. METHODS: A systematic search was conducted in Medline, Embase, and Cochrane Library up to Dec 31, 2023. Data on clinical characteristics, morphological and imaging features, outcomes and interventions were collected from published studies and pooled using a random-effects meta-analysis. RESULTS: A total of 30 studies with 10,825 HCM index patients were included in the pooled analyses. The frequency of sarcomere genes in HCM patients was 41%. Sarcomere mutations were more frequent in women (p < 0.00001), and were associated with lower body mass index (26.1 ± 4.7 versus 27.5 ± 4.3; p = 0.003) and left ventricular ejection fraction (65.7% ± 10.1% vs. 67.1% ± 8.6%; p = 0.03), less apical hypertrophy (6.5% vs. 20.1%; p < 0.0001) and left ventricular outflow tract obstruction (29.1% vs. 33.2%; p = 0.03), greater left atrial volume index (43.6 ± 21.1 ml/m2 vs. 37.3 ± 13.0 ml/m2; p = 0.02). Higher risks of ventricular tachycardia (23.4% vs. 14.1%; p < 0.0001), syncope (18.3% vs. 10.9%; p = 0.01) and heart failure (17.3% vs. 14.6%; p = 0.002) were also associated with sarcomere mutations. CONCLUSIONS: Sarcomere mutations are more frequent in women, and are associated with worse clinical characteristics and poor outcomes.

A prediction model for CO2/CO adsorption performance on binary alloys based on machine learning.

Despite the rapid development of computational methods, including density functional theory (DFT), predicting the performance of a catalytic material merely based on its atomic arrangements remains challenging. Although quantum mechanics-based methods can model 'real' materials with dopants, grain boundaries, and interfaces with acceptable accuracy, the high demand for computational resources no longer meets the needs of modern scientific research. On the other hand, Machine Learning (ML) method can accelerate the screening of alloy-based catalytic materials. In this study, an ML model was developed to predict the CO2 and CO adsorption affinity on single-atom doped binary alloys based on the thermochemical properties of component metals. By using a greedy algorithm, the best combination of features was determined, and the ML model was trained and verified based on a data set containing 78 alloys on which the adsorption energy values of CO2 and CO were calculated from DFT. Comparison between predicted and DFT calculated adsorption energy values suggests that the extreme gradient boosting (XGBoost) algorithm has excellent generalization performance, and the R-squared (R2) for CO2 and CO adsorption energy prediction are 0.96 and 0.91, respectively. The errors of predicted adsorption energy are 0.138 eV and 0.075 eV for CO2 and CO, respectively. This model can be expected to advance our understanding of structure-property relationships at the fundamental level and be used in large-scale screening of alloy-based catalysts.

Advancements in defect engineering of two-dimensional nanomaterial-based membranes for enhanced gas separation.

The advent of two-dimensional nanomaterials, a revolutionary class of materials, is marked by their atomic-scale thickness, superior aspect ratios, robust mechanical attributes, and exceptional chemical stability. These materials, producible on a large scale, are emerging as the forefront candidates in the domain of membrane-based gas separation. The concept of defect engineering in 2D nanomaterials has introduced a novel approach in their application for membrane separation, offering an effective technique to augment the performance of these membranes. Nonetheless, the development of customized microstructures in gas separation membranes via defect engineering remains nascent. Hence, this review is designed to serve as a comprehensive guide for the application of defect engineering in 2D nanomaterial-based membranes. It delves into the most recent developments in this field, encompassing the synthesis methodologies of defective 2D nanomaterials and the mechanisms underlying gas transport. Special emphasis is placed on the utilization of defect-engineered 2D nanomaterial-based membranes in gas capture applications. Furthermore, the paper encapsulates the burgeoning challenges and prospective advancements in this area. In essence, defect engineering emerges as a promising avenue for enhancing the efficacy of 2D nanomaterial-based membranes in gas separation, offering significant potential for advancements in membrane-based gas separation technologies.

A molecular dynamics study on adsorption mechanisms of polar, cationic, and anionic polymers on montmorillonite.

Adsorption of polymers on clay in aqueous solutions has wide applications in environmental, medical, and energy-related areas, but the interactions between polymers and clay under varied conditions are still not fully understood. In this study, we investigated the adsorption mechanisms of four polymers belonging to different categories, namely anionic poly(acrylic acid) (poly-AA), cationic poly(diallyldimethylammonium chloride) (poly-DADMAC), nonionic polyacrylamide (poly-AM), and the copolymer of AA and DADMAC (poly-AADADMAC). By using molecular dynamics simulations, we compared the desorption kinetics of these polymers at different temperatures and found that poly-AA and poly-AM have the weakest and strongest adsorption abilities, respectively. Polymer adsorptions are slightly more stable at higher pressures, and high salinity favors the adsorption of charged polymers. Further analysis suggests that the adsorption of anionic poly-AA is less stable than that of cationic poly-DADMAC because the latter is attracted to the negatively charged surface by direct coulombic forces, and poly-AM is stabilized by van der Waals forces and hydrogen bonds. This study provides insights on how to enhance the adsorption affinity of polymers on a clay surface and may help the design or improvement of polymer/clay nanocomposite materials.

A preorganization oriented computational method for de novo design of Kemp elimination enzymes.

A preorganization oriented computational strategy for de novo enzyme design based on computational enzyme design tool PRODA was developed and demonstrated by the creation of Kemp elimination enzymes. A pre-organized active site model of proton transfer from carbon with a low energy barrier was proposed and then anchored into the scaffold 3AOF, the endoglucanase from Thermotoga maritima, which was selected from the protein structural database. The low-energy amino acid sequences at the binding pocket to stabilize the catalytic productive geometry were computationally generated via the iterative protein redesign and molecular dynamics simulation. The designed variant (3AOF-KE03) bearing 17 mutations was experimentally confirmed to afford catalytic activity (kcat/KM=14.04M-1s-1) towards Kemp elimination, with measured rate (kcat=0.033s-1) enhancement of up to 104-fold. This computational strategy is general, and we anticipate the creation of a wide range of artificial enzymes to catalyze reactions with industrial significance in the future.

A General Strategy for Kilogram-Scale Preparation of Highly Crystal-line Covalent Triazine Frameworks.

Scalable and eco-friendly synthesis of crystalline porous covalent triazine frameworks (CTFs) is essential to realize their broad industrial applications but remains a great challenge, which requires the fundamental understanding of the two-dimensional polymerization mechanism. Herein, we report a universal polyphosphoric acid (H6 P4 O13 )-catalyzed nitrile trimerization route to synthesize a series of highly crystalline CTFs with high specific surface areas. This new strategy enables the cost-effective large-scale fabrication of crystalline CTFs at kilogram level for the first time. Through density functional theory calculation and detailed controlled experiments, we reveal that the polyphosphate acid show much higher catalytic activity for trimerization reaction than its analogues such as P2 O5 and H3 PO4 . Furthermore, the crystalline CTFs with regular porosity and abundant triazine groups exhibit ultrahigh removal efficiency of micropollutants, indicating its great potential in environment remediation.

Synergistic anticancer effects of everolimus (RAD001) and Rhein on gastric cancer cells via phosphoinositide-3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway.

Everolimus (RAD001) is a mTOR inhibitor and is widely used for the treatment of gastric cancer (GC). Evidence suggests that Rhein has anticancer effect on GC. But the synergistic effect and mechanism of RAD001 and Rhein combination on GC is not clear. The current study aims to clarify the combination of RAD001 and Rhein in GC treatment. We found Rhein dose-dependently repressed MGC-803 cell viability (50% inhibition concentration (IC50) value = 94.26 µM). Rhein (80 µM) significantly suppressed GC cell proliferation and invasion. RAD001 dose-dependently repressed MGC-803 cells viability (IC50 value = 45.41 nM). The combination of Rhein and RAD001 repressed MGC-803 cells viability, invasion, and proliferation compared to the administration of Rhein or RAD001 alone. Protein levels of epithelial-mesenchymal transition (EMT)-related molecules E-cadherin, N-cadherin and Vimentin expressions were significantly affected by the combination of Rhein and RAD001. The combination of Rhein and RAD001 significantly facilitated cell apoptosis and up-regulated expressions of cell apoptosis and cycle-related protein p53, cyclin-dependent kinase 4 (CDK4) and cyclin D1 compared to the administration of Rhein or RAD001 alone. Moreover, the combination of Rhein and RAD001 repressed the expressions of phosphorylation-phosphoinositide-3-kinase (p-PI3K), p-protein kinase B (p-AKT) and p-mammalian target of rapamycin (p-mTOR). Finally, the combination of RAD001 and Rhein significantly decreased tumor weight and volume, suppressed the expressions of p-PI3K, p-Akt and p-mTOR, and repressed cell proliferation marker Ki-67 expression, which exerted synergistic cancer prevention in GC in vivo. Overall, the combination of Rhein and RAD001 exert synergistic cancer prevention in GC via PI3K/Akt/mTOR pathway.

Early Fault Diagnosis Method for Batch Process Based on Local Time Window Standardization and Trend Analysis.

The products of a batch process have high economic value. Meanwhile, a batch process involves complex chemicals and equipment. The variability of its operation leads to a high failure rate. Therefore, early fault diagnosis of batch processes is of great significance. Usually, the available information of the sensor data in batch processing is obscured by its noise. The multistage variation of data results in poor diagnostic performance. This paper constructed a standardized method to enlarge fault information as well as a batch fault diagnosis method based on trend analysis. First, an adaptive standardization based on the time window was created; second, utilizing quadratic fitting, we extracted a data trend under the window; third, a new trend recognition method based on the Euclidean distance calculation principle was composed. The method was verified in penicillin fermentation. We constructed two test datasets: one based on an existing batch, and one based on an unknown batch. The average diagnostic rate of each group was 100% and 87.5%; the mean diagnosis time was the same; 0.2083 h. Compared with traditional fault diagnosis methods, this algorithm has better fault diagnosis ability and feature extraction ability.

Ultrathin Crystalline Covalent-Triazine-Framework Nanosheets with Electron Donor Groups for Synergistically Enhanced Photocatalytic Water Splitting.

Ultrathin nanosheets have great potential for photocatalytic applications, however, suffer from enlarged band gap and narrowed visible-light-responsive range due to the quantum confinement effect. Herein, we report a novel redox strategy for efficient preparation of ultrathin crystalline amide-functionalized covalent-triazine-framework nanosheets (CTF NSs) with enhanced visible light absorption. The CTF NSs exhibited photocatalytic hydrogen (512.3 µmol h-1 ) and oxygen (12.37 µmol h-1 ) evolution rates much higher than that of pristine bulk CTF. Photocatalytic overall water splitting could be achieved with efficient stoichiometric H2 (5.13 µmol h-1 ) and O2 (2.53 µmol h-1 ) evolution rates under visible light irradiation. Experimental and theoretical analysis revealed that introduction of amide groups as electron donor optimized the band structure and improve its visible-light absorption, hydrophilicity and carrier separation efficiency, thus resulting in the enhanced photocatalytic performance. The well-dispersed CTF NSs could be easily cast onto a support as a thin film device and demonstrate excellent photocatalytic activity (25.7 mmol h-1 m-2 for hydrogen evolution).

High-Voltage-Tolerant Covalent Organic Framework Electrolyte with Holistically Oriented Channels for Solid-State Lithium Metal Batteries with Nickel-Rich Cathodes.

By introducing lithiophilic groups and electrochemically stable quinolyl aromatic ring linkages, we prepared covalent organic frameworks (COFs) exhibiting a large band gap with an ultralow HOMO value (-6.2 eV under vacuum) and oxidative stability up to 5.6 V (versus Li+ /Li) as solid-state electrolytes (SSEs). The obtained flexible COF SSE thin films showed a holistically oriented arrangement along the (001) facet with remarkable ionic conductivity up to 1.5×10-4  S cm-1 at 60 °C and excellent mechanical strength with a high Young's modulus of 10.5 GPa. Molecular dynamic simulations showed that lithium ions are transmitted in this COF SSE by directional hopping paths with fast drift velocity. The COF SSE film was used to assemble all-solid-state lithium metal batteries with nickel-rich cathodes (NMC811). The batteries demonstrated stable cycling performance over 400 cycles, high coulombic efficiency (>99 %), and could also withstand abuse tests, such as folding.

Integrated Diagnostic Framework for Process and Sensor Faults in Chemical Industry.

This study considers the problem of distinguishing between process and sensor faults in nonlinear chemical processes. An integrated fault diagnosis framework is proposed to distinguish chemical process sensor faults from process faults. The key idea of the framework is to embed the cycle temporal algorithm into the dynamic kernel principal component analysis to improve the fault detection speed and accuracy. It is combined with the fault diagnosis method based on the reconstruction-based contribution graph to diagnose the fault variables and then distinguish the two fault types according to their characteristics. Finally, the integrated fault diagnosis framework is applied to the Tennessee Eastman process and acid gas absorption process, and its effectiveness is proved.

The Role of Surface Termination in Halide Perovskites for Efficient Photocatalytic Synthesis.

Halide perovskites have received attention in the field of photocatalysis owing to their excellent optoelectronic properties. However, the semiconductor properties of halide perovskite surfaces and the influence on photocatalytic performance have not been systematically clarified. Now, the conversion of triose (such as 1,3-dihydroxyacetone (DHA)) is employed as a model reaction to explore the surface termination of MAPbI3 . By rational design of the surface termination for MAPbI3 , the production rate of butyl lactate is substantially improved to 7719 µg g-1 cat. h-1 under visible-light illumination. The MAI-terminated MAPbI3 surface governs the photocatalytic performance. Specially, MAI-terminated surface is susceptible to iodide oxidation, which thus promotes the exposure of PbII as active sites for this photocatalysis process. Moreover, MAI-termination induces a p-doping effect near the surface for MAPbI3 , which facilitates carrier transport and thus photosynthesis.

Photo-Fenton removal of tetracycline hydrochloride using LaFeO3 as a persulfate activator under visible light.

In this work, LaFeO3 nanoparticles were fabricated by a facile sol-gel method and applied to degrade tetracycline hydrochloride (TC-HCl) through heterogeneous activation of persulfate under visible-light illumination. The structure, compositions, photocatalytic properties, and morphological features of the as-obtained sample were investigated by XRD, XPS, DRS, and FESEM techniques. Optimizations of dosage of LaFeO3 (0-0.4 g/L), dosage of PS (0-4 g/L), concentration of TC-HCl (10 ppm-80 ppm), and pH of initial solution (2.09-9.59) were conducted. Radical trapping experiments indicated that SO4- was the dominant radical for TC-HCl removal while OH was also involved. In addition, LaFeO3 was proved with excellent stability and reusability in degrading TC-HCl molecules in the Vis/LaFeO3/PS system. The findings of this work revealed the potential application of the Vis/LaFeO3/PS system toward degrading organic pollutants in wastewater.

Coalbed methane diffusion and water blocking effects investigated by mesoscale all-atom molecular dynamic simulations.

In coalbed methane extraction processes, the water blocking effect (WBE) is a formation damage that limits the extraction efficiency. To investigate WBE mechanisms at the molecular level, realistic coal models must be developed to simulate the interplay between methane and liquid phase water in a coal matrix's mesopores and macropores. This study built a massive and highly scalable coal tube model with accurate all-atom force fields. Based on this model, we investigated the adsorption and diffusion of methane and liquid water in the mesopores of coal. We found that methane forms multiple layers of adsorption on the coal surface, and the diffusivity of methane strongly depends on pore sizes and the presence of water. When both methane and liquid water were loaded in the coal tube, the liquid phase formed a nearly impenetrable barrier that prevented methane diffusion. This work provides insights into the mechanism of the WBE and can facilitate further studies on WBE alleviating strategies.

Emodin inhibits zinc-induced neurotoxicity in neuroblastoma SH-SY5Y cells.

Emodin is a natural anthraquinone derivative with numerous beneficial effects, including antioxidant properties, anti-tumor activities, and protecting the nerves. Zinc-induced neurotoxicity plays a crucial role in the pathogenesis of vascular dementia (VD) and Parkinson's disease (PD). Here, the protective activity of emodin inhibiting zinc-induced neurotoxicity and its molecular mechanisms such as cellular Zn2+ influx and zinc-induced gene expression were examined using human neuroblastoma cells (SH-SY5Y cells). Our findings showed that emodin obviously enhanced cell viability and reduced cell apoptosis and lactate dehydrogenase release. Bedsides, we detected a decrease of intracellular Zn2+ concentration after SH-SY5Y cells were pretreated with emodin. Simultaneously, the expression of zinc transporter-1, metallothionein-1, and metallothionein-2 were weakened in emodin-pretreated SH-SY5Y cells. In addition, emodin prevented the depletion of NAD+ and ATP induced by zinc. Emodin also reduced intracellular reactive oxygen species and endoplasmic reticulum-stress levels. Strikingly, emodin elevated SH-SY5Y cell viability and inhibited cell apoptosis caused by AMP-activated protein kinase signaling pathway activation. Thus, emodin could protect against neurotoxicity induced by Zn2+ in neuroblastoma SH-SY5Y cells. It is expected to have future therapeutic potential for VD or PD and other neurodegenerative diseases.

Water adsorption on olivine(010) surfaces: Effect of alkali and transition metal cation doping.

Dopants have the potential to locally modify water-olivine interactions, which can impact geological processes, such as weathering, CO2 sequestration, and abiotic hydrocarbon generation. As a first step in understanding the role of dopants on the water structure and chemistry at water-olivine interfaces, water monomer adsorption on alkaline earth (AE) and transition metal (TM) doped forsterite(010) [Mg2SiO4(010)] surfaces was studied using density functional theory (DFT). Dopants that occur in olivine minerals were considered and consisted of Ca, Sr, and Ba for the AE dopants and Cr, Mn, Fe, Co, and Ni for the TM dopants. The water molecule adsorbs on the olivine surface through a metal-water bond (Me-Ow) and a hydrogen bond with an adjacent surface lattice oxygen (Ox-Hw). A frontier orbital analysis reveals that the 1b2, 3a1, and 1b1 (HOMO) of the water molecule are involved in the bonding. All of the TM dopants show strong net Me-Ow covalent bonding between 3a1 and 1b1 water orbitals and TM d states, while the AE dopants except for Mg2SiO4(010) show negligible Me-Ow covalent bonding. Both the AE and TM dopants show similar hydrogen bonding features involving both the 1b2 and 3a1 orbitals. While the AE cations show an overall lower Me-Ow covalent interaction, the AE dopants have strong electrostatic interactions between the positive metal cation and the negatively charged water dipole. A bonding model incorporating a linear combination of the covalent Me-Ow bond, the Ox-Hw hydrogen bond, the electrostatic interaction between the dopant cation and the H2O molecule, and the surface distortion energy is needed to capture the variation in the DFT adsorption energies on the olivine surfaces. The bonding analysis is able to identify the dominant contributions to water-dopant interactions and can serve as a basis for future studies of more realistic water-olivine interfaces.

Dimeric [Mo2 S12 ](2-) Cluster: A Molecular Analogue of MoS2 Edges for Superior Hydrogen-Evolution Electrocatalysis.

Proton reduction is one of the most fundamental and important reactions in nature. MoS2 edges have been identified as the active sites for hydrogen evolution reaction (HER) electrocatalysis. Designing molecular mimics of MoS2 edge sites is an attractive strategy to understand the underlying catalytic mechanism of different edge sites and improve their activities. Herein we report a dimeric molecular analogue [Mo2 S12 ](2-) , as the smallest unit possessing both the terminal and bridging disulfide ligands. Our electrochemical tests show that [Mo2 S12 ](2-) is a superior heterogeneous HER catalyst under acidic conditions. Computations suggest that the bridging disulfide ligand of [Mo2 S12 ](2-) exhibits a hydrogen adsorption free energy near zero (-0.05 eV). This work helps shed light on the rational design of HER catalysts and biomimetics of hydrogen-evolving enzymes.

Poisoning effect of adsorbed CO during CO2 electroreduction on late transition metals.

Copper cathodes, at sufficiently negative potentials, are selective for hydrocarbon production during the electrochemical reduction of carbon dioxide. Other metals, such as Pt, Fe, Ni and Co, produce low to zero hydrocarbons. We employ density functional theory to examine the coverage of reaction intermediates under CO2 electroreduction conditions. A detailed thermodynamic analysis suggests that a high coverage of adsorbed CO at relevant reduction potentials blocks the metal surface sites for H adsorption, preventing C-H bond formation. The potential-dependent energetics of H adsorption and CO formation are highly sensitive to the surface coverage of the adsorbed species. The formation of surface carbon as a competing adsorption intermediate is also explored at relevant reduction potentials. CO2 electroreduction to hydrocarbons over metals active for the thermal reduction process (Fe, Ni, Co, Pt) would require a H supply for C-H bond formation that is competitive with CO* and C* at the surface.

A matching algorithm for catalytic residue site selection in computational enzyme design.

A loop closure-based sequential algorithm, PRODA_MATCH, was developed to match catalytic residues onto a scaffold for enzyme design in silico. The computational complexity of this algorithm is polynomial with respect to the number of active sites, the number of catalytic residues, and the maximal iteration number of cyclic coordinate descent steps. This matching algorithm is independent of a rotamer library that enables the catalytic residue to take any required conformation during the reaction coordinate. The catalytic geometric parameters defined between functional groups of transition state (TS) and the catalytic residues are continuously optimized to identify the accurate position of the TS. Pseudo-spheres are introduced for surrounding residues, which make the algorithm take binding into account as early as during the matching process. Recapitulation of native catalytic residue sites was used as a benchmark to evaluate the novel algorithm. The calculation results for the test set show that the native catalytic residue sites were successfully identified and ranked within the top 10 designs for 7 of the 10 chemical reactions. This indicates that the matching algorithm has the potential to be used for designing industrial enzymes for desired reactions.

A fast protein-ligand docking algorithm based on hydrogen bond matching and surface shape complementarity.

With the rapid development of structural determination of target proteins for human diseases, high throughout virtual screening based drug discovery is gaining popularity gradually. In this paper, a fast docking algorithm (H-DOCK) based on hydrogen bond matching and surface shape complementarity was developed. In H-DOCK, firstly a divide-and-conquer strategy based enumeration approach is applied to rank the intermolecular modes between protein and ligand by maximizing their hydrogen bonds matching, then each docked conformation of the ligand is calculated according to the matched hydrogen bonding geometry, finally a simple but effective scoring function reflecting mainly the van der Waals interaction is used to evaluate the docked conformations of the ligand. H-DOCK is tested for rigid ligand docking and flexible one, the latter is implemented by repeating rigid docking for multiple conformations of a small molecule and ranking all together. For rigid ligands, H-DOCK was tested on a set of 271 complexes where there is at least one intermolecular hydrogen bond, and H-DOCK achieved success rate (RMSD<2.0 A) of 91.1%. For flexible ligands, H-DOCK was tested on another set of 93 complexes, where each case was a conformation ensemble containing native ligand conformation as well as 100 decoy ones generated by AutoDock, and the success rate reached 81.7%. The high success rate of H-DOCK indicates that the hydrogen bonding and steric hindrance can grasp the key interaction between protein and ligand. H-DOCK is quite efficient compared with the conventional docking algorithms, and it takes only about 0.14 seconds for a rigid ligand docking and about 8.25 seconds for a flexible one on average. According to the preliminary docking results, it implies that H-DOCK can be potentially used for large scale virtual screening as a pre-filter for a more accurate but less efficient docking algorithm.