Machine Learning Empowering Drug Discovery: Applications, Opportunities and Challenges.

Drug discovery plays a critical role in advancing human health by developing new medications and treatments to combat diseases. How to accelerate the pace and reduce the costs of new drug discovery has long been a key concern for the pharmaceutical industry. Fortunately, by leveraging advanced algorithms, computational power and biological big data, artificial intelligence (AI) technology, especially machine learning (ML), holds the promise of making the hunt for new drugs more efficient. Recently, the Transformer-based models that have achieved revolutionary breakthroughs in natural language processing have sparked a new era of their applications in drug discovery. Herein, we introduce the latest applications of ML in drug discovery, highlight the potential of advanced Transformer-based ML models, and discuss the future prospects and challenges in the field.

Small variation induces a big difference: the effect of polymerization kinetics of graphitic carbon nitride on its photocatalytic activity.

Graphitic carbon nitride (g-CN) has emerged as a promising visible-light-responsive photocatalyst, and its activity is highly sensitive to synthesis conditions. In this work, we attempt to correlate the photocatalytic activity of g-CN with its production yield, which is kinetically determined by the specific condensation process. Bulk g-CN samples were synthesized by the conventional condensation procedure, but in static air and flowing air, respectively. The one synthesized in static air showed a lower production yield with an increased specific surface area and preferential surface chemical states, corresponding to a significantly improved activity for photocatalytic hydrogen evolution (PHE) and dye degradation. We further synthesized a series of g-CN samples by merely changing the synthetic atmosphere, the ramping rate, and the loading amount of the precursor, and the difference in their PHE performance was found to be as high as 7.05 times. The notable changes in their production yields as well as the photocatalytic activities have been discussed from the point of view of polymerization reaction kinetics, and the self-generated NH3 atmosphere plays a crucial role.

Tumor-associated macrophages in colorectal cancer metastasis: molecular insights and translational perspectives.

Metastasis is the leading cause of high mortality in colorectal cancer (CRC), which is not only driven by changes occurring within the tumor cells, but is also influenced by the dynamic interaction between cancer cells and components in the tumor microenvironment (TME). Currently, the exploration of TME remodeling and its impact on CRC metastasis has attracted increasing attention owing to its potential to uncover novel therapeutic avenues. Noteworthy, emerging studies suggested that tumor-associated macrophages (TAMs) within the TME played important roles in CRC metastasis by secreting a variety of cytokines, chemokines, growth factors and proteases. Moreover, TAMs are often associated with poor prognosis and drug resistance, making them promising targets for CRC therapy. Given the prognostic and clinical value of TAMs, this review provides an updated overview on the origin, polarization and function of TAMs, and discusses the mechanisms by which TAMs promote the metastatic cascade of CRC. Potential TAM-targeting techniques for personalized theranostics of metastatic CRC are emphasized. Finally, future perspectives and challenges for translational applications of TAMs in CRC development and metastasis are proposed to help develop novel TAM-based strategies for CRC precision medicine and holistic healthcare.

Deciphering the functional roles of transporter proteins in subcellular metal transportation of plants.

MAIN CONCLUSION: The role of transporters in subcellular metal transport is of great significance for plants in coping with heavy metal stress and maintaining their proper growth and development. Heavy metal toxicity is a serious long-term threat to plant growth and agricultural production, becoming a global environmental concern. Excessive heavy metal accumulation not only damages the biochemical and physiological functions of plants but also causes chronic health hazard to human beings through the food chain. To deal with heavy metal stress, plants have evolved a series of elaborate mechanisms, especially a variety of spatially distributed transporters, to strictly regulate heavy metal uptake and distribution. Deciphering the subcellular role of transporter proteins in controlling metal absorption, transport and separation is of great significance for understanding how plants cope with heavy metal stress and improving their adaptability to environmental changes. Hence, we herein introduce the detrimental effects of excessive common essential and non-essential heavy metals on plant growth, and describe the structural and functional characteristics of transporter family members, with a particular emphasis on their roles in maintaining heavy metal homeostasis in various organelles. Besides, we discuss the potential of controlling transporter gene expression by transgenic approaches in response to heavy metal stress. This review will be valuable to researchers and breeders for enhancing plant tolerance to heavy metal contamination.

Decoding Connectivity Map-based drug repurposing for oncotherapy.

The rising global burden of cancer has driven considerable efforts into the research and development of effective anti-cancer agents. Fortunately, with impressive advances in transcriptome profiling technology, the Connectivity Map (CMap) database has emerged as a promising and powerful drug repurposing approach. It provides an important platform for systematically discovering of the associations among genes, small-molecule compounds and diseases, and elucidating the mechanism of action of drug, contributing toward efficient anti-cancer pharmacotherapy. Moreover, CMap-based computational drug repurposing is gaining attention because of its potential to overcome the bottleneck constraints faced by traditional drug discovery in terms of cost, time and risk. Herein, we provide a comprehensive review of the applications of drug repurposing for anti-cancer drug discovery and summarize approaches for computational drug repurposing. We focus on the principle of the CMap database and novel CMap-based software/algorithms as well as their progress achieved for drug repurposing in the field of oncotherapy. This article is expected to illuminate the emerging potential of CMap in discovering effective anti-cancer drugs, thereby promoting efficient healthcare for cancer patients.

Prognostic Roles of ceRNA Network-Based Signatures in Gastrointestinal Cancers.

Gastrointestinal cancers (GICs) are high-incidence malignant tumors that seriously threaten human health around the world. Their complexity and heterogeneity make the classic staging system insufficient to guide patient management. Recently, competing endogenous RNA (ceRNA) interactions that closely link the function of protein-coding RNAs with that of non-coding RNAs, such as long non-coding RNA (lncRNA) and circular RNA (circRNA), has emerged as a novel molecular mechanism influencing miRNA-mediated gene regulation. Especially, ceRNA networks have proven to be powerful tools for deciphering cancer mechanisms and predicting therapeutic responses at the system level. Moreover, abnormal gene expression is one of the critical breaking events that disturb the stability of ceRNA network, highlighting the role of molecular biomarkers in optimizing cancer management and treatment. Therefore, developing prognostic signatures based on cancer-specific ceRNA network is of great significance for predicting clinical outcome or chemotherapy benefits of GIC patients. We herein introduce the current frontiers of ceRNA crosstalk in relation to their pathological implications and translational potentials in GICs, review the current researches on the prognostic signatures based on lncRNA or circRNA-mediated ceRNA networks in GICs, and highlight the translational implications of ceRNA signatures for GICs management. Furthermore, we summarize the computational approaches for establishing ceRNA network-based prognostic signatures, providing important clues for deciphering GIC biomarkers.

Surface Magnetism in Pristine α Rhombohedral Boron and Intersurface Exchange Coupling Mechanism of Boron Icosahedra.

We report intrinsic surface magnetism in pristine α rhombohedral boron (α-boron) using first-principles calculations. Semiconducting α-boron has been cleaved along the (001), (102̅), and (101) planes to produce icosahedral-based non-van der Waals face-boron, t-face-boron, and edge-boron structures, respectively. Face-boron is found to be metallic, while t-face-boron and edge-boron show semiconducting features. In particular, edge-boron exhibits layer-dependent magnetism with a transition from an overall antiferromagnetic (AFM) state with AFM surfaces to either an AFM or a ferromagnetic (FM) state with FM surfaces as the number of layers increases. The magnetism in edge-boron arises from the spin polarization of boron atoms with unsaturated bonds at the edge sites in the upper and lower surfaces, and magnetic exchange coupling can be mediated via adjacent boron icosahedra by up to a maximum of 8.4 Å. These findings deepen our understanding of icosahedral-based boron and boron-rich materials, which may be useful in potential spintronics applications.

From Triazine to Heptazine: Origin of Graphitic Carbon Nitride as a Photocatalyst.

Graphitic carbon nitride (g-CN) has emerged as a promising metal-free photocatalyst, while the catalytic mechanism for the photoinduced redox processes is still under investigation. Interestingly, this heptazine-based polymer optically behaves as a "quasi-monomer". In this work, we explore upstream from melem (the heptazine monomer) to the triazine-based melamine and melam and present several lines of theoretical/experimental evidence where the catalytic activity of g-CN originates from the electronic structure evolution of the C-N heterocyclic cores. Periodic density functional theory calculations reveal the strikingly different electronic structures of melem from its triazine-based counterparts. Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy also provide consistent results in the structural and chemical bonding variations of these three relevant compounds. Both melam and melem were found to show stable photocatalytic activities, while the photocatalytic activity of melem is about 5.4 times higher than that of melam during the degradation of dyes under UV-visible light irradiation. In contrast to melamine and melam, the frontier electronic orbitals of the heptazine unit in melem are uniformly distributed and well complementary to each other, which further determine the terminal amines as primary reduction sites. These appealing electronic features in both the heterocyclic skeleton and the terminated functional groups can be inherited by the polymeric but quasi-monomeric g-CN, leading to its pronounced photocatalytic activity.

Bifidobacterium pseudolongum reduces triglycerides by modulating gut microbiota in mice fed high-fat food.

Obesity has become a growing concern around the world. The purpose of this study was to investigate the potential benefit of Bifidobacterium pseudolongum (B. pseudolongum) on obesity, gut microbiota, and its physiological mechanism. The obese mice model was established with a high-fat diet (HFD), and the treatment were used the strain B. pseudolongum. We investigated the changes in fat content, plasma metabolites and gut microbiota on obese mice and B. pseudolongum treated obese mice. We found that B. pseudolongum treatment significantly decreased the body mass (about 12 %), plasma triglycerides (about 12.4 %), gross energy intake (about 12.8 %), and visceral fat (about 26.5 %) in obese mice. Further, High-throughput pyrosequencing of the 16S rRNA demonstrated that B. pseudolongum treatment markedly recovered the gut microbiota dysbiosis in obese mice, including the diversity of microbiota and the ratio of Firmicutes to Bacteroidetes. B. pseudolongum treatment increased the abundance of the bacterial genus Butyricimonas and Bifidobacterium. Therefore, B. pseudolongum may have therapeutic potential for the treatment of diet-induced obesity (DIO). B. pseudolongum treatment could change host gut microbiota and provide benefits to host digestive processes that mitigate metabolic diseases.

A P/N type silicon semiconductor loaded with silver nanoparticles used as a SERS substrate to selectively drive the coupling reaction induced by surface plasmons.

Semiconductor materials are favoured in the field of photocatalysis due to their unique optoelectronic properties. When a semiconductor is excited by external energy, electrons will transition through the band gap, providing electrons or holes for the reaction. This is similar to the chemical enhancement mode of a catalytic reaction initiated by the rough noble metal on the surface excited by plasmon resonance. In this study, different types of semiconductor silicon loaded with silver nanoparticles were used as SERS substrates. SERS detection of p-aminothiophenol (PATP) and p-nitrothiophenol (PNTP) probe molecules was performed using typical surface plasmon-driven coupling reactions, and the mechanism of optical drive charge transfer in semiconductor-metal-molecular systems was investigated. Scanning electron microscopy and plasmon luminescence spectroscopy were used to characterize the silver deposited on the substrate surface. Mapping technology and electrochemistry were used to characterize the photocatalytic reaction of the probe molecules. This study proposed a mechanism for the coupling reaction of "hot electrons" and "hot holes" on the surface of plasmon-driven molecules and provides a method for preparing a stable SERS substrate.

Solvent-controlled plasmon-assisted surface catalysis reaction of 4-aminothiophenol dimerizing to p,p'-dimercaptoazobenzene on Ag nanoparticles.

A large number of literatures have investigated the selective photocatalytic reaction of 4-aminothiophenol (PATP) to p,p'-dimercaptoazobenzene (DMAB). Most of them mainly study the contribution of substrate, excitation wavelength, exposure time, pH and added cations to plasmon-assisted surface catalytic reactions. However, we mainly study focuses on the effects of solvents on the dimerization of PATP to DMAB under the action of Ag nanoparticles (NPs). In experiments, a variety of diols was selected as solvents for the probe molecule PATP, and power-dependent SERS spectra were obtained at an excitation wavelength of 532 nm. From the laser-dependent SERS spectrum, we found that the characteristic peak enhancement effect of the product DMAB in different solvents is significantly different. That is, different solvents could regulate the rate at which DMAB is produced from PATP. Based on the experimental results, we further explored how different diol solvents regulate the response of PATP to DMAB. Our conclusion is that the solvent in the system can quickly capture the hot electrons generated by the decay of the plasmon, so that the remaining holes can oxidize PATP to form DMAB. The ability to trap hot electrons is different due to the difference in the position of the functional groups in the solvent, so that the photocatalytic reaction rate of the hole-oxidized PATP is different. The ability to capture electrons varies depending on the position of the functional groups in the solvent, so the oxidation rate of the photocatalytic reaction is also different. This work not only deepens our understanding of the mechanism of hole-driven surface catalysis oxidation reaction, but also provides a convenient method for regulating the rate of catalytic oxidation.

Cluster-model DFT simulations of the infrared spectra of triazine-based molecular crystals.

Understanding the intermolecular interactions in the context of crystal packing is of fundamental significance in molecular materials science. Infrared (IR) spectroscopy can provide complementary structural information; however, it still remains a great challenge to accurately predict the molecular IR vibrations in the crystalline phase. Here we report a cluster-model approach to simulate the IR spectra of triazine-based molecular crystals via density functional theory (DFT) calculations. In the properly designed cluster models, the molecular IR vibrations are expressed by a representative unit, while the nearest-neighbouring molecules are treated as a "frozen shell" to mimic the surrounding crystallographic environments. Much smaller clusters can be built by considering the crystallographic equivalence in the unit cell, which are able to perform DFT calculations on more complicated crystal structures with endurable computational costs. The simulated spectra show excellent consistencies with the experimental ones, particularly providing an in-depth understanding of the vibrational modes closely related to hydrogen bonding. Most importantly, the selectively built clusters based on the crystallographically independent molecules in the unit cell allow us to perform specific IR-spectral simulations, by which their distinct hydrogen-bonding environments have been clearly revealed for the first time.

Stacking sequences of black phosphorous allotropes and the corresponding few-layer phosphorenes.

Possible bulk black phosphorus (BP) allotropes are constructed based on single-layer BP with various stacking sequences. Our stacking algorithm shows that there are eight possible allotropes with two stacking layers in their unit cells possessing relatively high symmetries, and six of them are retained after structural relaxation using a van der Waals correction of optB88-vdW. The AF, AG, and AH bulk structures are presented for the first time. The structural relationship of these configurations has been explained via an interlayer slipping process. The total energy of the AF allotrope is closest to the most stable bulk BP structure (AB stacking) among all explored 2-layer stacked bulk structures. The calculated band structure of the AF allotrope using HSE06 shows a direct band gap of 0.48 eV with anisotropic electronic structures. We also presented six possible BP allotropes with three stacking layers in their unit cells. The newly reported AAF and ABC stacked structures show semiconducting and metallic features, respectively. After the bulk structures were explored, we further built the corresponding few-layer phosphorene structures and investigated their electronic properties. The results show that all the few-layer phosphorenes show semiconducting features. The AE, AAE, and AEA phosphorenes have indirect band gaps while the other explored phosphorenes possess direct band gaps located at the Γ point.

Plasmon-driven surface catalytic reaction of 4-ethynylaniline in a liquid environment.

There is much evidence that surface plasmon photocatalytic reactions can occur on organic molecules on metal surfaces. In this paper, we focus on the photocatalytic reaction of 4-ethynylaniline (PEAN) on silver nanoparticles (Ag NPs) in a liquid environment by surface-enhanced Raman spectroscopy (SERS). Our experiments used SERS to characterize p,p'-diynylazobenzene produced from PEAN via a selective catalytic coupling reaction on Ag NPs. This discovery not only achieved the expected results but also broadens the known plasmon-driven surface catalytic reaction system. In our work, we also regulated the photocatalytic coupling reaction conditions of PEAN on Ag NPs by laser power-dependent and time-dependent SERS spectra.

Tuning the Photocatalytic Activity of Graphitic Carbon Nitride by Plasma-Based Surface Modification.

In this study, we demonstrate that plasma treatment can be a facile and environmentally friendly approach to perform surface modification of graphitic carbon nitride (g-CN), leading to a remarkable modulation on its photocatalytic activity. The bulk properties of g-CN, including the particle size, structure, composition, and electronic band structures, have no changes after being treated by oxygen or nitrogen plasma; however, its surface composition and specific surface area exhibit remarkable differences corresponding to an oxygen functionalization induced by the plasma post-treatment. The introduced oxygen functional groups play a key role in reducing the recombination rate of the photoexcited charge carries. As a consequence, the oxygen-plasma-treated sample shows a much superior photocatalytic activity, which is about 4.2 times higher than that of the pristine g-CN for the degradation of rhodamine B (RhB) under visible light irradiation, while the activity of nitrogen-plasma-treated sample exhibits a slight decrease. Furthermore, both of the plasma-treated samples are found to possess impressive photocatalytic stabilities. Our results suggest that plasma treatment could be a conventional strategy to perform surface modification of g-CN in forms of both powders and thin films, which holds broad interest not only for developing g-CN-based high-performance photocatalysts but also for constructing photoelectrochemical cells and photoelectronic devices with improved energy conversion efficiencies.

Combinatorial Vibration-Mode Assignment for the FTIR Spectrum of Crystalline Melamine: A Strategic Approach toward Theoretical IR Vibrational Calculations of Triazine-Based Compounds.

Although polymeric graphitic carbon nitride (g-C3N4) has been widely studied as metal-free photocatalyst, the description of its structure still remains a great challenge. Fourier transform infrared (FTIR) spectroscopy can provide complementary structural information. In this paper, we reconsider the representative crystalline melamine and develop a strategic approach to theoretically calculate the IR vibrations of this triazine-based nitrogen-rich system. IR calculations were based on three different models: a single molecule, a 4-molecule unit cell, and a 32-molecule cluster, respectively. By this comparative study the contribution of the intermolecular weak interactions were elucidated in detail. An accurate and visualized description on the experimental FTIR spectrum has been further presented by a combinatorial vibration-mode assignment based on the calculated potential energy distribution of the 32-molecule cluster. The theoretical approach reported in this study opens the way to the facile and accurate assignment for IR vibrational modes of other complex triazine-based compounds, such as g-C3N4.

Functionalization of single-wall carbon nanotubes with chromophores of opposite internal dipole orientation.

We report the functionalization of carbon nanotubes with two azobenzene-based chromophores with large internal dipole moments and opposite dipole orientations. The molecules are attached to the nanotubes noncovalently via a pyrene tether. A combination of characterization techniques shows uniform molecular coverage on the nanotubes, with minimal aggregation of excess chromophores on the substrate. The large on/off ratios and the subthreshold swings of the nanotube-based field-effect transistors (FETs) are preserved after functionalization, and different shifts in threshold voltage are observed for each chromophore. Ab initio calculations verify the properties of the synthesized chromophores and indicate very small charge transfer, confirming a strong, noncovalent functionalization.

Luminescence enhancement of pyrene/dispersant nanoarrays driven by the nanoscale spatial effect on mixing.

This work presents a simple method to generate ordered chromophore/dispersant nanoarrays through a pore-filling process for a nanoporous polymer template to enhance chromophore luminescence. Fluorescence results combining with the morphological evolution examined by scanning probe microscopy reveal that the enhanced luminescence intensity reaches the maximum intensity as the nanopores of the template are completely filled by the chromophore/dispersant mixture. The variation is attributed to nanoscale spatial effect on the enhanced mixing efficiency of chromophore and dispersant, that is, the alleviation of self-quenching problem, as evidenced by the results of attenuated total reflection Fourier transform IR spectroscopy combining with grazing incident wide-angle X-ray diffraction. The enhanced luminescence of the chromophore/dispersant nanoarrays driven by the nanoscale spatial effect is highly promising for use in designing luminescent nanodevices.

Growth and electrical properties of zinc oxide nanowires.

Zinc oxide nanowires were grown on molybdenum grids with a simple chemical vapor transport and deposition method through thermal evaporation of zinc powder at a temperature of 600 degrees C. These nanowires are 20-50 nm in diameter and over ten microns in length. High resolution transmission electron microscopy studies show that the as-grown nanowires are single crystal of wurtzite structure and grow along the (0001) direction. The growth process was explained with a vapor-solid mechanism under zinc-rich conditions. We further patterned electrodes on individual ZnO nanowires by e-beam lithography and studied thier electrical properties.

Surface-enhanced/normal Raman scattering studies on an isolated and individual single-walled carbon nanotube.

In this paper, we report the surface-enhanced Raman scattering and normal Raman scattering from different parts of one individual single-walled carbon nanotube. We found that the intensity of radial breathing mode can be remarkably enhanced for surface-enhanced Raman scattering. And no frequency shift of the radial breathing mode has been observed. For the tangential mode at approximately 1590 cm(-1), the peak becomes slightly narrower for surface-enhanced Raman scattering. Both semiconducting and metallic nanotubes can be identified based on the line shape of tangential mode. Meanwhile, the intensities of tangential mode depend on laser excitation energies sensitively, which can be explained by different resonant transitional conditions.