Recent Submissions

  • Bone-Marrow-Derived Mesenchymal Stem Cells, Their Conditioned Media, Protect against Cyclophosphamide-Induced Infertility in Rats

    Ibrabim, Dalia; Abozied, Nadia; Maboud, Samar Abdel; Alzamami, Ahmad; Alturki, Norah; Jaremko, Mariusz; Alanazi, Maram Khalil; Seddek, Asmaa (Frontiers in Pharmacology, Frontiers Media, 2023-03-22) [Article]
    Cancer is a deadly disease characterized by abnormal cell proliferation. Chemotherapy is one tech-nique of cancer treatment. Cyclophosphamide (CYP) is the most powerful chemotherapy medication, yet it has serious adverse effects. It is an antimitotic medicine that regulates cell proliferation and primarily targets quickly dividing cells, and it has been related to varying levels of infertility in hu-mans. In the current study, we assessed the biochemical, histological, and microscopic evaluations of testicular damage following CYP administration. Further, we have explored the potential protective impact of mesenchymal stem cell (MSCs) transplantation. The biochemical results revealed that ad-ministration of CYP increased serum concentrations of follicle-stimulating hormone (FSH) and lu-teinizing hormone (LH), while it decreased serum concentrations of free testosterone hormone (TH), testicular FSH, LH, and free TH concentrations, testicular total antioxidant capacity (TAC), and testicular activity of superoxide dismutase (SOD) enzyme. The histology and sperm examinations revealed that CYP induced destruction to the architectures of several tissues in the testes, which drastically reduced the Johnsen score as well as the spermatogenesis process. Surprisingly, trans-plantation of MSCs after CYP administration altered the deterioration effect of CYP injury on the testicular tissues, as demonstrated by biochemical and histological analysis. Our results indicated alleviation of serum and testicular sex hormones, as well as testicular oxidative stress markers (TAC and SOD activity), and nearly restored the normal appearance of the testicular tissues, Johnsen score, and spermatogenesis process. In conclusion, our work emphasizes the protective pharmacological use of MSCs to mitigate the effects of CYP on testicular tissues that impair the spermatogenesis process following chemotherapy. These findings indicate that transferring MSCs to chemotherapy patients could significantly improve spermatogenesis
  • Physics-Constrained Neural Network (PcNN): Phase Behavior Modeling for Complex Reservoir Fluids

    Li, Yiteng; He, Xupeng; Zhang, Zhen; AlSinan, Marwa; Kwak, Hyung; Hoteit, Hussein (SPE, 2023-03-21) [Conference Paper]
    The highly nonlinear nature of equation-of-state-based (EOS-based) flash calculations encages high-fidelity compositional simulation, as most of the CPU time is spent on detecting phase stability and calculating equilibrium phase amounts and compositions. With the rapid development of machine learning (ML) techniques, they are growing to substitute classical iterative solvers for speeding up flash calculations. However, conventional data-driven neural networks fail to account for physical constraints, like chemical potential equilibrium (equivalent to fugacity equality in the PT flash formulation) and interphase/intraphase mass conservation. In this work, we propose a physics-constrained neural network (PcNN) that first conserves both fugacity equality and mass balance constraints. To ease the inclusion of fugacity equality, it is reformulated in terms of equilibrium ratios and then introduced with a relaxation parameter such that phase split calculations are extended to the single-phase regime. This makes it technologically feasible to incorporate the fugacity equality constraint into the proposed PcNN model without any computational difficulty. The workflow for the development of the proposed PcNN model includes four steps. Step 1: Perform the constrained Latin hypercube sampling (LHS) to generate representative mixtures covering a variety of fluid types, including wet gas, gas condensate, volatile oil, and black oil. Step 2: Conduct PT flash calculations using the Peng-Robinson (PR) EOS for each fluid mixture. A wide range of reservoir pressures and temperatures are considered, from which we sample the training data for each fluid mixture through grid search. Step 3: Build an optimized PcNN model by including the fugacity equality and mass conservation constraints in the loss function. Bayesian optimization is used to determine the optimal hyperparameters. Step 4: Validate the PcNN model. In this step, we conduct blind validation by comparing it with the iterative PT flash algorithm.
  • Parameter Inversion in Geothermal Reservoir Using Markov Chain Monte Carlo and Deep Learning

    Zhang, Zhen; He, Xupeng; Li, Yiteng; AlSinan, Marwa; Kwak, Hyung; Hoteit, Hussein (SPE, 2023-03-21) [Conference Paper]
    Traditional history-matching process suffers from non-uniqueness solutions, subsurface uncertainties, and high computational cost. This work proposes a robust history-matching workflow utilizing the Bayesian Markov Chain Monte Carlo (MCMC) and Bidirectional Long-Short Term Memory (BiLSTM) network to perform history matching under uncertainties for geothermal resource development efficiently. There are mainly four steps. Step 1: Identifying uncertainty parameters. Step 2: The BiLSTM is built to map the nonlinear relationship between the key uncertainty parameters (e.g., injection rates, reservoir temperature, etc.) and time series outputs (temperature of producer). Bayesian optimization is used to automate the tuning process of the hyper-parameters. Step 3: The Bayesian MCMC is performed to inverse the uncertainty parameters. The BiLSTM is served as the forward model to reduce the computational expense. Step 4: If the errors of the predicted response between the high-fidelity model and Bayesian MCMC are high, we need to revisit the accuracy of the BiLSTM and the prior information on the uncertainty parameters. We demonstrate the proposed method using a 3D fractured geothermal reservoir, where the cold water is injected into a geothermal reservoir, and the energy is extracted by producing hot water in a producer. Results show that the proposed Bayesian MCMC and BiLSTM method can successfully inverse the uncertainty parameters with narrow uncertainties by comparing the inversed parameters and the ground truth. We then compare its superiority with models like PCE, Kriging, and SVR, and our method achieves the highest accuracy. We propose a Bayesian MCMC and BiLSTM-based history matching method for uncertainty parameters inversion and demonstrate its accuracy and robustness compared with other models. This approach provides an efficient and practical history-matching method for geothermal extraction with significant uncertainties.
  • Impact of Evanescence Process on Three-Dimensional Sub-Diffusion based Molecular Communication Channel

    Briantceva, Nadezhda; Chouhan, Lokendra; Parsani, Matteo; Alouini, Mohamed-Slim (IEEE Transactions on NanoBioscience, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-21) [Article]
    In most of the existing works of molecular communication (MC), the standard diffusion environment is taken into account where the mean square displacement (MSD) of an information molecule (IM) scales linearly with time. On the contrary, this work considers the sub-diffusion motion that appears in crowded and complex (porous or fractal) environments (movement of the particles in the living cells) where the particle’s MSD scales as a fractional order power law in time. Moreover, we examine an additional evanescence process resulting from which the molecules can degrade before hitting the boundary of the receiver (RX). Thus, in this work, we present a 3D MC system with a point transmitter (TX) and the spherical RX with the sub-diffusive behavior of an IM along with its evanescence. Furthermore, an IM’s closed-form expressions for the arrival probability and the first passage time density (FPTD) are emulated in the above context. Additionally, we investigate the performance of MC by using the concentration-based modulation technique in a sub-diffusion channel. Finally, the considered MC channel is exploited in terms of the probability of detection, probability of false alarm, and probability of error for different parameters such as the reaction rate, fractional power, and radius of the RX.
  • 3D-Printed disposable nozzles for cost-efficient extrusion-based 3D bioprinting

    Albalawi, Hamed I.; Khan, Zainab N.; H. Rawas, Ranim; U. Valle-Pérez, Alexander; Abdelrahman, Sherin; Hauser, Charlotte (Materials Science in Additive Manufacturing, AccScience Publishing, 2023-03-21) [Article]
    3D bioprinting has significantly impacted tissue engineering with its capability to create intricate structures with complex geometries that were difficult to replicate through traditional manufacturing techniques. Extrusion-based 3D bioprinting methods tend to be limited when creating complex structures using bioinks of low viscosity. However, the capacity for creating multi-material structures that have distinct properties could be unlocked through the mixture of two solutions before extrusion. This could be used to generate architectures with varying levels of stiffness and hydrophobicity, which could be utilized for regenerative medicine applications. Moreover, it allows for combining proteins and other biological materials in a single 3D-bioprinted structure. This paper presents a standardized fabrication method of disposable nozzle connectors (DNC) for 3D bioprinting with hydrogel-based materials. This method entails 3D printing connectors with dual inlets and a single outlet to mix the material internally. The connectors are compatible with conventional Luer lock needles, offering an efficient solution for nozzle replacement. IVZK (Ac-Ile-Val-Cha-Lys-NH2) peptide-based hydrogel materials were used as a bioink with the 3D-printed DNCs. Extrusion-based 3D bioprinting was employed to print shapes of varying complexities, demonstrating potential in achieving high print resolution, shape fidelity, and biocompatibility. Post-printing of human neonatal dermal fibroblasts, cell viability, proliferation, and metabolic activity were observed, which demonstrated the effectiveness of the proposed design and process for 3D bioprinting using low-viscosity bioinks.
  • Experimental and Computational Fluid Dynamics Investigation of Mechanisms of Enhanced Oil Recovery via Nanoparticle-Surfactant Solutions

    Yekeen, Nurudeen; Ali Elakkari, Ali Masoud; Khan, Javed Akbar; Ali, Muhammad; Al-Yaseri, Ahmed; Hoteit, Hussein (Energy & Fuels, American Chemical Society (ACS), 2023-03-21) [Article]
    The enhancement in surfactant performance at downhole conditions in the presence of nanomaterials has fascinated researchers’ interest regarding the applications of nanoparticle-surfactant (NPS) fluids as novel enhanced oil recovery (EOR) techniques. However, the governing EOR mechanisms of hydrocarbon recovery using NPS solutions are not yet explicit. Pore-scale visualization experiments clarify the dominant EOR mechanisms of fluid displacement and trapped/residual oil mobilization using NPS solutions. In this study, the influence of multiwalled carbon nanotubes (MWCNTs), silicon dioxide (SiO2), and aluminum oxide (Al2O3) nanoparticles on the EOR properties of a conventional surfactant (sodium dodecyl benzene sulfonate, SDBS) was investigated via experimental and computational fluid dynamics (CFD) simulation approaches. Oil recovery was reduced with increased temperatures and micromodel heterogeneity. Adding nanoparticles to SDBS solutions decreases the fingering and channeling effect and increases the recovery factor. The simulation prediction results agreed with the experimental results, which demonstrated that the lowest amount of oil (37.84%) was retained with the micromodel after MWCNT-SDBS flooding. The oil within the micromodel after Al2O3-SDBS and SiO2-SDBS flooding was 58.48 and 43.42%, respectively. At 80 °C, the breakthrough times for MWCNT-SDBS, Al2O3-SDBS, and SiO2-SDBS displacing fluids were predicted as 32.4, 29.3, and 21 h, respectively, whereas the SDBS flooding and water injections at similar situations were at 12.2 and 6.9 h, respectively. The higher oil recovery and breakthrough time with MWCNTs could be attributed to their cylindrical shape, promoting the MWCNT-SDBS orientation at the liquid–liquid and solid–liquid interfaces to reduce the oil–water interfacial tension and contact angles significantly. The study highlights the prevailing EOR mechanisms of NPS.
  • AB-Gen: Antibody Library Design with Generative Pre-trained Transformer and Deep Reinforcement Learning

    Xu, Xiaopeng; Xu, Tiantian; Zhou, Juexiao; Liao, Xingyu; Zhang, Ruochi; Wang, Yu; Zhang, Lu; Gao, Xin (Cold Spring Harbor Laboratory, 2023-03-21) [Preprint]
    Antibody leads must fulfill multiple desirable properties to be clinical candidates. Primarily due to the low throughput in the experimental procedure, the need for such multi-property optimization causes the bottleneck in preclinical antibody discovery and development, because addressing one issue usually causes another. We developed a reinforcement learning (RL) method, named AB-Gen, for antibody library design using a generative pre-trained Transformer (GPT) as the policy network of the RL agent. We showed that this model can learn the antibody space of heavy chain complementarity determining region 3 (CDRH3) and generate sequences with similar property distributions. Besides, when using HER2 as the target, the agent model of AB-Gen was able to generate novel CDRH3 sequences that fulfill multi-property constraints. 509 generated sequences were able to pass all property filters and three highly conserved residues were identified. The importance of these residues was further demonstrated by molecular dynamics simulations, which consolidated that the agent model was capable of grasping important information in this complex optimization task. Overall, the AB-Gen method is able to design novel antibody sequences with an improved success rate than the traditional propose-then-filter approach. It has the potential to be used in practical antibody design, thus empowering the antibody discovery and development process.
  • Observation of cnoidal wave localization in nonlinear topolectric circuits

    Hohmann, Hendrik; Hofmann, Tobias; Helbig, Tobias; Imhof, Stefan; Brand, Hauke; Upreti, Lavi K.; Stegmaier, Alexander; Fritzsche, Alexander; Müller, Tobias; Schwingenschlögl, Udo; Lee, Ching Hua; Greiter, Martin; Molenkamp, Laurens W.; Kießling, Tobias; Thomale, Ronny (Physical Review Research, American Physical Society (APS), 2023-03-21) [Article]
    We observe a localized cnoidal (LCn) state in an electric circuit network. Its formation derives from the interplay of nonlinearity and the topology inherent to a Su-Schrieffer-Heeger (SSH) chain of inductors. Varicap diodes act as voltage-dependent capacitors, and create a nonlinear on-site potential. For a sinusoidal voltage excitation around midgap frequency, we show that the voltage response in the nonlinear SSH circuit follows the Korteweg-de Vries equation. The topological SSH boundary state, which relates to a midgap impedance peak in the linearized limit is distorted into the LCn state in the nonlinear regime, where the cnoidal eccentricity decreases from edge to bulk.
  • A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics

    Li, Haoyang; Zhou, Juexiao; Li, Zhongxiao; Chen, Siyuan; Liao, Xingyu; Zhang, Bin; Zhang, Ruochi; Wang, Yu; Sun, Shiwei; Gao, Xin (Nature Communications, Springer Science and Business Media LLC, 2023-03-21) [Article]
    Spatial transcriptomics technologies are used to profile transcriptomes while preserving spatial information, which enables high-resolution characterization of transcriptional patterns and reconstruction of tissue architecture. Due to the existence of low-resolution spots in recent spatial transcriptomics technologies, uncovering cellular heterogeneity is crucial for disentangling the spatial patterns of cell types, and many related methods have been proposed. Here, we benchmark 18 existing methods resolving a cellular deconvolution task with 50 real-world and simulated datasets by evaluating the accuracy, robustness, and usability of the methods. We compare these methods comprehensively using different metrics, resolutions, spatial transcriptomics technologies, spot numbers, and gene numbers. In terms of performance, CARD, Cell2location, and Tangram are the best methods for conducting the cellular deconvolution task. To refine our comparative results, we provide decision-tree-style guidelines and recommendations for method selection and their additional features, which will help users easily choose the best method for fulfilling their concerns.
  • Visualization of Surface Charge Carrier Diffusion Lengths in Different Perovskite Crystal Orientations Using 4D Electron Imaging

    Nughays, Razan O.; Yang, Chen; Nematulloev, Sarvarkhodzha; Yin, Jun; Harrison, George; Zhao, Jianfeng; Fatayer, Shadi P.; Bakr, Osman; Mohammed, Omar F. (Advanced Optical Materials, Wiley, 2023-03-20) [Article]
    Understanding charge carrier dynamics on the surface of materials at the nanometer and femtosecond scales is one of the key elements to optimizing the performance of light-conversion devices, including solar cells. Unfortunately, most of the pump-probe characterization techniques are surface-insensitive and obtain information from the bulk due to the large penetration depth of the pulses. However, ultrafast scanning electron microscopy (USEM) is superior in visualizing carrier dynamics at the surface with high spatial-temporal resolution. Here, the authors successfully used USEM to uncover the tremendous effect of surface orientations and termination on the charge carrier of MAPbI3 perovskite single crystals. Time-resolved secondary electrons snapshots and density functional theory calculations clearly demonstrate that charge carrier diffusion, surface trap density, surface work function, and carrier concentration are strongly facet-dependent. The results display a diffusion length of 22 micrometers within 6.0 nanoseconds along (001) orientation. While (100) facet forms defect states that prevent carrier diffusion and shows an increase in the surface work function leading to dark contrast and fast charge carrier recombination. These findings provide a new key component to optimizing the surface of perovskites, thus paving the way for even more efficient and stable solar-cell devices based on perovskite single crystals.
  • The effects of chemical and mechanical interactions on the thermodynamic pressure for mineral solid solutions

    Clavijo, Santiago P; Espath, Luis; Calo, Victor M (Authorea, Inc., 2023-03-20) [Preprint]
    We use a coupled thermodynamically-consistent framework to model reactive chemo-mechanical responses of solid solutions. Specifically, we focus on chemically active solid solutions that are subject to mechanical effects due to heterogeneous stress distributions. The stress generation process is driven solely by volume changes associated with the chemical processes. We use this model to describe the underlying physics during standard geological processes. Furthermore, simulation results of a three-species solid solution provide insights into the phenomena and verify the interleaving between mechanical and chemical responses in the solid. In particular, we show the evolution of the thermodynamic pressure as the system goes to a steady state.
  • Engineering grain boundaries in monolayer molybdenum disulfide for an efficient water/ion separation

    Han, Yu; Shen, Jie; Aljarb, Areej; Cai, Yichen; Liu, Xing; Min, Jiacheng; Wang, Yingge; Zhang, Chenhui; Chen, Cailing; Hakami, Marim; Fu, Jui-Han; Zhang, Hui; Li, Guanxing; Wang, Xiaoqian; Chen, Zhuo; Li, Jiaqiang; Dong, Xinglong; Tung, Vincent; Shi, Guosheng; Pinnau, Ingo; Li, Lain-Jong (Research Square Platform LLC, 2023-03-20) [Preprint]
    Atomically thin two-dimensional (2D) materials have long been considered as ideal platforms for developing separation membranes. However, it is difficult to generate uniform subnanometer pores over large areas on 2D materials. Herein, we report that the well-defined defect structure of monolayer MoS2, namely, eight-membered ring (8-MR) pores typically formed at the boundaries of two antiparallel grains, can serve as molecular sieves for efficient water/ion separation. The 8-MR pores (4.2 × 2.4 Å) in monolayer MoS2 allow rapid single-file water transport while rejecting various hydrated ions. Further, the density of grain boundaries and, consequently, the density of pores can be tuned by regulating the nucleation density and size of MoS2 grains during the chemical vapor deposition process. The optimized MoS2 membrane exhibited an ultrahigh water/NaCl selectivity of ~6.5 × 104 at a water permeance of 232 mol m−2 h−1 bar−1, outperforming the state-of-the-art desalination membranes. When used for direct hydrogen production from seawater by combining the forward osmosis and electrochemical water splitting processes, the membrane achieved ~40 times the energy conversion efficiency of commercial polymeric membranes. It also exhibited a rapid and selective proton transport behavior desirable for fuel cells and electrolysis. The bottom-up approach of creating precise pore structures on atomically thin films via grain boundary engineering presents a promising route for producing large-area membranes suitable for various applications.
  • Multimode Free-Vibration Decay Column: Small-Strain Stiffness and Attenuation

    Noh, Dong-Hwa; Park, Junghee; Santamarina, Carlos; Kwon, Tae-Hyuk (Journal of Geotechnical and Geoenvironmental Engineering, American Society of Civil Engineers (ASCE), 2023-03-20) [Article]
    This study presents a simplified resonant column testing method to obtain small-strain dynamic properties of soils in both torsional and flexural vibrations. The method exploits free vibration decay responses of the system produced by manual excitation while the specimen is subjected to an isotropic effective confining stress produced by a vacuum pressure. This method is readily applicable to standard resonant column and torsional shear devices and triaxial cells by attaching a metal bar with one or two accelerometers for manual excitation, but not using an electromagnetic driving plate. This paper describes the apparatus design, test procedure, system calibration, and data analyses, as well as the test results of dynamic properties of a dry sand, including small-strain elastic moduli and damping ratios obtained from the torsional and flexural modes. The results confirm that the suggested method can capture strain-dependent characteristics up to the strains of ∼10−4 beyond typical elastic threshold strains, although the isotropic effective confining stress is limited to ∼90 kPa. This unique testing method provides remarkably consistent and reliable measurement for the dynamic properties of soils, and it avoids any possible bias from the counterelectromotive force.
  • Computationally Budgeted Continual Learning: What Does Matter?

    Prabhu, Ameya; Hammoud, Hasan Abed Al Kader; Dokania, Puneet; Torr, Philip H. S.; Lim, Ser-Nam; Ghanem, Bernard; Bibi, Adel (arXiv, 2023-03-20) [Preprint]
    Continual Learning (CL) aims to sequentially train models on streams of incoming data that vary in distribution by preserving previous knowledge while adapting to new data. Current CL literature focuses on restricted access to previously seen data, while imposing no constraints on the computational budget for training. This is unreasonable for applications in-the-wild, where systems are primarily constrained by computational and time budgets, not storage. We revisit this problem with a large-scale benchmark and analyze the performance of traditional CL approaches in a compute-constrained setting, where effective memory samples used in training can be implicitly restricted as a consequence of limited computation. We conduct experiments evaluating various CL sampling strategies, distillation losses, and partial fine-tuning on two large-scale datasets, namely ImageNet2K and Continual Google Landmarks V2 in data incremental, class incremental, and time incremental settings. Through extensive experiments amounting to a total of over 1500 GPU-hours, we find that, under compute-constrained setting, traditional CL approaches, with no exception, fail to outperform a simple minimal baseline that samples uniformly from memory. Our conclusions are consistent in a different number of stream time steps, e.g., 20 to 200, and under several computational budgets. This suggests that most existing CL methods are particularly too computationally expensive for realistic budgeted deployment.
  • Ti3C2Tx MXene van der Waals gate contact for GaN high electron mobility transistors

    Wang, Chuanju; Xu, Xiangming; Tyagi, Shubham; Rout, Paresh Chandra; Schwingenschlögl, Udo; Sarkar, Biplab; Khandelwal, Vishal; Liu, Xinke; Gao, Linfei; Hedhili, Mohamed N.; Alshareef, Husam N.; Li, Xiaohang (Advanced Materials, Wiley, 2023-03-20) [Article]
    Gate controllability is a key factor that determines the performance of GaN high electron mobility transistors (HEMTs). However, at traditional metal-GaN interface, direct chemical interaction between metal and GaN can result in fixed charges and traps, which can significantly deteriorate the gate controllability. In this study, Ti3C2Tx MXene films were integrated into GaN HEMTs as the gate contact, wherein van der Waals heterojunctions were formed between MXene films and GaN without direct chemical bonding. The GaN HEMTs with enhanced gate controllability exhibited an extremely low off-state current (IOFF) of 10−7 mA/mm, a record high ION/IOFF current ratio of ∼1013 (which is six orders of magnitude higher than conventional Ni/Au contact), a high off-state drain breakdown voltage of 1085 V, and a near-ideal subthreshold swing of 61 mV/dec. This work shows the great potential of MXene films as gate electrodes in wide-bandgap semiconductor devices.
  • Generalization of the Orthodiagonal Involutive Type of Kokotsakis Flexible Polyhedra

    Aikyn, Alisher; Liu, Yang; Lyakhov, Dmitry; Pottmann, Helmut; Michels, Dominik L. (arXiv, 2023-03-19) [Preprint]
    In this paper we introduce and study a remarkable class of mechanisms formed by a 3×3 arrangement of rigid and skew quadrilateral faces with revolute joints at the common edges. These Kokotsakis-type mechanisms with a quadrangular base and non-planar faces are a generalization of Izmestiev's orthodiagonal involutive type of Kokotsakis polyhedra formed by planar quadrilateral faces. Our algebraic approach yields a complete characterization of all complexes of the orthodiagonal involutive type. It is shown that one has 8 degrees of freedom to construct such mechanisms. This is illustrated by several examples, including cases that are not possible with planar faces.
  • Sintering-free catalytic ammonia cracking by vertically standing 2D porous framework supported Ru nanocatalysts

    Kim, Seok-Jin; Nguyen, Thien Si; Mahmood, Javeed; Yavuz, Cafer T. (Chemical Engineering Journal, Elsevier BV, 2023-03-18) [Article]
    Catalytic ammonia decomposition enables ammonia to be a hydrogen gas carrier for a carbon-free fuel economy. The challenge is to obtain high conversion yields and rates at low temperatures for a prolonged time. A promising approach is to engineer a catalyst support to minimize deleterious effects like sintering. Here, we compared a conventional 2D planar porous framework support with a vertically standing 2D structure to ascertain the effects of support geometry on the catalytic performance. The catalysts were made by loading ruthenium (Ru) nanoparticles onto the structures, and the catalytic activities were monitored by varying the ammonia (NH3) feeding rate and reaction temperature. Unlike the planar version, the vertically standing 2D support prevented nanoparticle aggregation, retained the original nanoparticle size, and showed an excellent hydrogen production rate (95.17 mmol gRu-1min-1) at a high flow rate of 32,000 ml gcat-1h-1 at a temperature of 450 ℃.
  • A universal framework for single-cell multi-omics data integration with graph convolutional networks

    Gao, Hongli; Zhang, Bin; Liu, Long; Li, Shan; Gao, Xin; Yu, Bin (Briefings in bioinformatics, Oxford University Press (OUP), 2023-03-17) [Article]
    Single-cell omics data are growing at an unprecedented rate, whereas effective integration of them remains challenging due to different sequencing methods, quality, and expression pattern of each omics data. In this study, we propose a universal framework for the integration of single-cell multi-omics data based on graph convolutional network (GCN-SC). Among the multiple single-cell data, GCN-SC usually selects one data with the largest number of cells as the reference and the rest as the query dataset. It utilizes mutual nearest neighbor algorithm to identify cell-pairs, which provide connections between cells both within and across the reference and query datasets. A GCN algorithm further takes the mixed graph constructed from these cell-pairs to adjust count matrices from the query datasets. Finally, dimension reduction is performed by using non-negative matrix factorization before visualization. By applying GCN-SC on six datasets, we show that GCN-SC can effectively integrate sequencing data from multiple single-cell sequencing technologies, species or different omics, which outperforms the state-of-the-art methods, including Seurat, LIGER, GLUER and Pamona.
  • miProBERT: identification of microRNA promoters based on the pre-trained model BERT.

    Wang, Xin; Gao, Xin; Wang, Guohua; Li, Dan (Briefings in bioinformatics, Oxford University Press (OUP), 2023-03-17) [Article]
    Accurate prediction of promoter regions driving miRNA gene expression has become a major challenge due to the lack of annotation information for pri-miRNA transcripts. This defect hinders our understanding of miRNA-mediated regulatory networks. Some algorithms have been designed during the past decade to detect miRNA promoters. However, these methods rely on biosignal data such as CpG islands and still need to be improved. Here, we propose miProBERT, a BERT-based model for predicting promoters directly from gene sequences without using any structural or biological signals. According to our information, it is the first time a BERT-based model has been employed to identify miRNA promoters. We use the pre-trained model DNABERT, fine-tune the pre-trained model on the gene promoter dataset so that the model includes information about the richer biological properties of promoter sequences in its representation, and then systematically scan the upstream regions of each intergenic miRNA using the fine-tuned model. About, 665 miRNA promoters are found. The innovative use of a random substitution strategy to construct a negative dataset improves the discriminative ability of the model and further reduces the false positive rate (FPR) to as low as 0.0421. On independent datasets, miProBERT outperformed other gene promoter prediction methods. With comparison on 33 experimentally validated miRNA promoter datasets, miProBERT significantly outperformed previously developed miRNA promoter prediction programs with 78.13% precision and 75.76% recall. We further verify the predicted promoter regions by analyzing conservation, CpG content and histone marks. The effectiveness and robustness of miProBERT are highlighted.
  • Poly(heptazine imide) ligand exchange enables remarkable low catalyst loadings in heterogeneous metallaphotocatalysis

    Xing, Liuzhuang; Yang, Qian; Zhu, Chen; Bai, Yilian; Tang, Yurong; Rueping, Magnus; Cai, Yunfei (Nature Communications, Springer Science and Business Media LLC, 2023-03-17) [Article]
    The development of heterogeneous metallaphotocatalysis is of great interest for sustainable organic synthesis. The rational design and controllable preparation of well-defined (site-isolated) metal/photo bifunctional solid catalysts to meet such goal remains a critical challenge. Herein, we demonstrate the incorporation of privileged homogeneous bipyridyl-based Ni-catalysts into highly ordered and crystalline potassium poly(heptazine imide) (K-PHI). A variety of PHI-supported cationic bipyridyl-based Ni-catalysts (LnNi-PHI) have been prepared and fully characterized by various techniques including NMR, ICP-OES, XPS, HAADF-STEM and XAS. The LnNi-PHI catalysts exhibit exceptional chemical stability and recyclability in diverse C−P, C−S, C−O and C−N cross-coupling reactions. The proximity and cooperativity effects in LnNi-PHI significantly enhances the photo/Ni dual catalytic activity, thus resulting in low catalyst loadings and high turnover numbers.

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