Electrospinning-derived transition metal/carbon nanofiber composites as electrocatalysts for Zn-air batteries.

The sluggish kinetics of the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) significantly impede the broader implementation of Zn-air batteries (ZABs), underscoring the necessity for advanced high-efficiency materials to catalyze these electrochemical processes. Recent advancements have highlighted the potential of transition metal/carbon nanofiber (TM/CNF) composite materials, synthesized via electrospinning technology, due to their expansive surface area, profusion of active sites, and elevated catalytic efficacy. This review comprehensively examines the structural characteristics of TM/CNFs, with a particular emphasis on the pivotal role of electrospinning technology in fabricating diverse structural configurations. Additionally, it delves into the mechanistic underpinnings of various strategies aimed at augmenting the catalytic activity of TM/CNFs. A meticulous discourse is also presented on the application scope of TM/CNFs in the realm of electrocatalysis, with a special focus on their impact on the performance of assembled ZABs. Lastly, this review encapsulates the challenges and future prospects in the development of TM/CNF composite materials via electrospinning, aiming to provide an exhaustive understanding of the current state of research in this domain and to foster further advancements in the commercialization of ZABs.

Structural and compositional analysis of MOF-derived carbon nanomaterials for the oxygen reduction reaction.

The development of low-cost and efficient cathode catalysts is crucial for the advancement of fuel cells, as the oxygen reduction reaction (ORR) on the cathode is constrained by expensive commercial Pt/C catalysts and a significant energy barrier. Metal-organic frameworks (MOFs) are considered excellent precursors for synthesizing carbon nanomaterials due to their simple synthesis, rich structure and composition. MOF-derived carbon nanomaterials (MDCNM) inherit the morphology of their precursors at low dimensional scales, providing abundant edge defects, larger specific surface area, and excellent electron transport paths. Furthermore, the rich composition of MOFs enables the carbon nanomaterials derived from them to exhibit various physicochemical properties, including stronger electron gaining ability, oxygen affinity, and a higher degree of graphitization, resulting in excellent ORR activity. However, a more detailed analysis is necessary to understand the advantages and mechanisms of MDCNM in the field of the ORR. This review classifies and summarizes the structure and different chemical compositions of MDCNM in low dimensions, and provides an in-depth analysis of the reasons for their improved ORR activity. Additionally, the recent practical applications of MDCNM as cathode material in fuel cells are introduced and analyzed in detail, with a focus on the enhanced electrochemical performance.

DeepFusion: A deep bimodal information fusion network for unraveling protein-RNA interactions using in vivo RNA structures.

RNA-binding proteins (RBPs) are key post-transcriptional regulators, and the malfunctions of RBP-RNA binding lead to diverse human diseases. However, prediction of RBP binding sites is largely based on RNA sequence features, whereas in vivo RNA structural features based on high-throughput sequencing are rarely incorporated. Here, we designed a deep bimodal information fusion network called DeepFusion for unraveling protein-RNA interactions by incorporating structural features derived from DMS-seq data. DeepFusion integrates two sub-models to extract local motif-like information and long-term context information. We show that DeepFusion performs best compared with other cutting-edge methods with only sequence inputs on two datasets. DeepFusion's performance is further improved with bimodal input after adding in vivo DMS-seq structural features. Furthermore, DeepFusion can be used for analyzing RNA degradation, demonstrating significantly different RBP-binding scores in genes with slow degradation rates versus those with rapid degradation rates. DeepFusion thus provides enhanced abilities for further analysis of functional RNAs. DeepFusion's code and data are available at http://bioinfo.org/deepfusion/.

Metal oxide nanomaterials based electrochemical and optical biosensors for biomedical applications: Recent advances and future prospectives.

The amalgamation of nanostructures with modern electrochemical and optical techniques gave rise to interesting devices, so-called biosensors. A biosensor is an analytical tool that incorporates various biomolecules with an appropriate physicochemical transducer. Over the past few years, metal oxide nanomaterials (MONMs) have significantly stimulated biosensing research due to their desired functionalities, versatile chemical stability, and low cost along with their unique optical, catalytic, electrical, and adsorption properties that provide an attractive platform for linking the biomolecules, for example, antibodies, nucleic acids, enzymes, and receptor proteins as sensing elements with the transducer for the detection of signals or signal amplifications. The signals to be measured are in direct proportionate to the concentration of the bioanalyte. Because of their simplicity, cost-effectiveness, portability, quick analysis, higher sensitivity, and selectivity against a broad range of biosamples, MONMs-based electrochemical and optical biosensing platforms are exhaustively explored as powerful early-diagnosis tools for point of care applications. Herein, we made a bibliometric analysis of past twenty years (2004-2023) on the application of MONMs as electrochemical and optical biosensing units using Web of Science database and the results of which clearly reveal the increasing number of publications since 2004. Geographical area distribution analysis of these publications shows that China tops the list followed by the United States of America and India. In this review, we first describe the electrochemical and optical properties of MONMs that are crucial for the creation of extremely stable, specific, and sensitive sensors with desirable characteristics. Then, the biomedical applications of MONMs-based bare and hybrid electrochemical and optical biosensing frameworks are highlighted in the light of recent literature. Finally, current limitations and future challenges in the field of biosensing technology are addressed.

Recent advances and promise of MXene-based composites as electrode materials for sodium-ion and potassium-ion batteries.

With the increasing demand for sustainable energy and concerns about the scarcity of lithium resources, sodium and potassium ion batteries have emerged as promising alternative energy storage technologies. MXene, as a novel two-dimensional material, possesses exceptional electrical conductivity, high surface area, and tunable structural features that make it an ideal candidate for high-performance electrode materials. However, its limited theoretical capacity hinders its widespread application. To overcome this limitation, MXene has been combined with other materials through synergistic effects between different components to enhance the overall electrochemical performance and expand its application in sodium/potassium ion batteries. Recently, substantial advancements have been realized in the exploration of MXene-based composites as energy storage materials, encompassing their synthesis, design, and the comprehension of charge storage mechanisms. This paper aims to propose a comprehensive summary of the latest developments in MXene-based composites as electrode materials for sodium ion batteries and potassium ion batteries, with a particular emphasis on the enhanced physicochemical properties resulting from composite formation. Moreover, the challenges faced by MXene materials in sodium ion batteries and potassium ion batteries are thoroughly discussed, and future research directions to further advance this field are proposed.

Corrigendum to "TREAT: Therapeutic RNAs exploration inspired by artificial intelligence technology" [Comput Struct Biotechnol J 20 (2022) 5680-5689].

[This corrects the article DOI: 10.1016/j.scr.2023.103115.].

TREAT: Therapeutic RNAs exploration inspired by artificial intelligence technology.

Recent advances in RNA engineering have enabled the development of RNA-based therapeutics for a broad spectrum of applications. Developing RNA therapeutics start with targeted RNA screening and move to the drug design and optimization. However, existing target screening tools ignore noncoding RNAs and their disease-relevant regulatory relationships. And designing therapeutic RNAs encounters high computational complexity of multi-objective optimization to overcome the immunogenicity, instability and inefficient translational production. To unlock the therapeutic potential of noncoding RNAs and enable one-stop screening and design of therapeutic RNAs, we have built the platform TREAT. It incorporates 43,087,953 regulatory relationships between coding and noncoding genes from 81 biological networks under different physiological conditions. TREAT introduces graph representation learning with Random Walk Diffusions to perform disease-relevant target screening, in addition to the commonly utilized Topological Degree and PageRank algorithms. Design and optimization of large RNAs or interfering RNAs are both available. To reduce the computational complexity of multi-objective optimization for large RNA, we stratified the features into local and global features. The local features are evaluated on the fixed-length or dynamic-length local bins, whereas the latter are inspired by AI language models of protein sequence. Then the global assessment is performed on refined candidates, thus reducing the enormous search space. Overall, TREAT is a one-stop platform for the screening and designing of therapeutic RNAs, with particular attention to noncoding RNAs and cutting-edge AI technology embedded, leading the progress of innovative therapeutics for challenging diseases. TREAT is freely accessible at https://rna.org.cn/treat.

A review on the toxicity of silver nanoparticles against different biosystems.

Despite significant progress made in the past two decades, silver nanoparticles (AgNPs) have not yet made it to the clinical trials. In addition, they showed both positive and negative effects in their toxicity from unicellular organism to well-developed multi-organ system, for example, rat. Although it is generally accepted that capped (bio)molecules have synergistic bioactivities and diminish the toxicity of metallic Ag core, convincing evidence is completely lacking. Therefore, in this review, we first highlight the recent in vivo toxicity studies of chemically manufactured AgNPs, biologically synthesized AgNPs and reference AgNPs of European Commission. Then, their toxic effects are compared with each other and the overlooked factors leading to the potential conflict of obtained toxicity results are discussed. Finally, suggestions are given to better design and conduct the future toxicity studies and to fast-track the successful clinical translation of AgNPs as well.

Electrospun Nanofibers of Polycaprolactone/Collagen as a Sustained-Release Drug Delivery System for Artemisinin.

The application of artemisinin (ART) in the treatment of malaria has been restricted to a certain degree due to its inherent limitations, such as short half-life, poor solubility, limited bioavailability, and re-crystallization. Electrospun nanofibers loaded with ART provide an excellent solution to these limitations and yield sustained drug release as well as inhibition of drug re-crystallization. In this study, ART-loaded polycaprolactone (PCL)/collagen (Col) nanofibers with different proportions of polymers were prepared. ART-loaded PCL/Col nanofibers were characterized, and further ART anti-crystallization and release behaviors were studied. SEM was used to observe the morphology of PCL/Col nanofibers. X-ray diffraction (XRD) was used to characterize the physical state of ART in ART-loaded PCL/Col nanofibers. Fourier transform infrared spectroscopy (FTIR), water contact angle measurement, weight loss, degree of swelling, and drug release experiments can verify the differences in performance of ART-loaded PCL/Col nanofibers due to different polymer ratios. The release curve was analyzed by kinetics, showing sustained release for up to 48 h, and followed the Fickian release mechanism, which was shown by the diffusion index value obtained from the Korsmeyer-Peppas equation.

KOBAS-i: intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis.

Gene set enrichment (GSE) analysis plays an essential role in extracting biological insight from genome-scale experiments. ORA (overrepresentation analysis), FCS (functional class scoring), and PT (pathway topology) approaches are three generations of GSE methods along the timeline of development. Previous versions of KOBAS provided services based on just the ORA method. Here we presented version 3.0 of KOBAS, which is named KOBAS-i (short for KOBAS intelligent version). It introduced a novel machine learning-based method we published earlier, CGPS, which incorporates seven FCS tools and two PT tools into a single ensemble score and intelligently prioritizes the relevant biological pathways. In addition, KOBAS has expanded the downstream exploratory visualization for selecting and understanding the enriched results. The tool constructs a novel view of cirFunMap, which presents different enriched terms and their correlations in a landscape. Finally, based on the previous version's framework, KOBAS increased the number of supported species from 1327 to 5944. For an easier local run, it also provides a prebuilt Docker image that requires no installation, as a supplementary to the source code version. KOBAS can be freely accessed at http://kobas.cbi.pku.edu.cn, and a mirror site is available at http://bioinfo.org/kobas.

ncFANs v2.0: an integrative platform for functional annotation of non-coding RNAs.

Increasing evidence proves the essential regulatory roles of non-coding RNAs (ncRNAs) in biological processes. However, characterizing the specific functions of ncRNAs remains a challenging task, owing to the intensive consumption of the experimental approaches. Here, we present an online platform ncFANs v2.0 that is a significantly enhanced version of our previous ncFANs to provide multiple computational methods for ncRNA functional annotation. Specifically, ncFANs v2.0 was updated to embed three functional modules, including ncFANs-NET, ncFANs-eLnc and ncFANs-CHIP. ncFANs-NET is a new module designed for data-free functional annotation based on four kinds of pre-built networks, including the co-expression network, co-methylation network, long non-coding RNA (lncRNA)-centric regulatory network and random forest-based network. ncFANs-eLnc enables the one-stop identification of enhancer-derived lncRNAs from the de novo assembled transcriptome based on the user-defined or our pre-annotated enhancers. Moreover, ncFANs-CHIP inherits the original functions for microarray data-based functional annotation and supports more chip types. We believe that our ncFANs v2.0 carries sufficient convenience and practicability for biological researchers and facilitates unraveling the regulatory mechanisms of ncRNAs. The ncFANs v2.0 server is freely available at http://bioinfo.org/ncfans or http://ncfans.gene.ac.

FangNet: Mining herb hidden knowledge from TCM clinical effective formulas using structure network algorithm.

The use of herbs to treat various human diseases has been recorded for thousands of years. In Asia's current medical system, numerous herbal formulas have been repeatedly verified to confirm their effectiveness in different periods, which is a great resource for drug innovation and discovery. Through the mining of these clinical effective formulas by network pharmacology and bioinformatics analysis, important biologically active ingredients derived from these natural products might be discovered. As modern medicine requires a combination of multiple drugs for the treatment of complex diseases, previously clinical formulas are also combinations of various herbs according to the main causes and accompanying symptoms. However, the herbs that play a major role in the treatment of diseases are always unclear. Therefore, how to rank each herb's relative importance and determine the core herbs, is the first step to assisting herb selection for active ingredients discovery. To solve this problem, we built the platform FangNet, which ranks all herbs on their relative topological importance using the PageRank algorithm, based on the constructed symptom-herb network from a collection of clinical empirical prescriptions. Three types of herb hidden knowledge, including herb importance rank, herb-herb co-occurrence, and associations to symptoms, were provided in an interactive visualization. Moreover, FangNet has designed role-based permission for teams to store, analyze, and jointly interpret their clinical formulas, in an easy and secure collaboration environment, aiming at creating a central hub for massive symptom-herb connections. FangNet can be accessed at http://fangnet.org or http://fangnet.herb.ac.cn.

HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine.

Pharmacotranscriptomics has become a powerful approach for evaluating the therapeutic efficacy of drugs and discovering new drug targets. Recently, studies of traditional Chinese medicine (TCM) have increasingly turned to high-throughput transcriptomic screens for molecular effects of herbs/ingredients. And numerous studies have examined gene targets for herbs/ingredients, and link herbs/ingredients to various modern diseases. However, there is currently no systematic database organizing these data for TCM. Therefore, we built HERB, a high-throughput experiment- and reference-guided database of TCM, with its Chinese name as BenCaoZuJian. We re-analyzed 6164 gene expression profiles from 1037 high-throughput experiments evaluating TCM herbs/ingredients, and generated connections between TCM herbs/ingredients and 2837 modern drugs by mapping the comprehensive pharmacotranscriptomics dataset in HERB to CMap, the largest such dataset for modern drugs. Moreover, we manually curated 1241 gene targets and 494 modern diseases for 473 herbs/ingredients from 1966 references published recently, and cross-referenced this novel information to databases containing such data for drugs. Together with database mining and statistical inference, we linked 12 933 targets and 28 212 diseases to 7263 herbs and 49 258 ingredients and provided six pairwise relationships among them in HERB. In summary, HERB will intensively support the modernization of TCM and guide rational modern drug discovery efforts. And it is accessible through http://herb.ac.cn/.

Electrospun Nanofibers of Natural and Synthetic Polymers as Artificial Extracellular Matrix for Tissue Engineering.

Many types of polymer nanofibers have been introduced as artificial extracellular matrices. Their controllable properties, such as wettability, surface charge, transparency, elasticity, porosity and surface to volume proportion, have attracted much attention. Moreover, functionalizing polymers with other bioactive components could enable the engineering of microenvironments to host cells for regenerative medical applications. In the current brief review, we focus on the most recently cited electrospun nanofibrous polymeric scaffolds and divide them into five main categories: natural polymer-natural polymer composite, natural polymer-synthetic polymer composite, synthetic polymer-synthetic polymer composite, crosslinked polymers and reinforced polymers with inorganic materials. Then, we focus on their physiochemical, biological and mechanical features and discussed the capability and efficiency of the nanofibrous scaffolds to function as the extracellular matrix to support cellular function.

Preparation of Lutein-Loaded PVA/Sodium Alginate Nanofibers and Investigation of Its Release Behavior.

This investigation aims to study the characteristics and release properties of lutein-loaded polyvinyl alcohol/sodium alginate (PVA/SA) nanofibers prepared by electrospinning. In order to increase PVA/SA nanofibers' water-resistant ability for potential biomedical applications, the electrospun PVA/SA nanofibers were cross-linked with a mixture of glutaraldehyde and saturated boric acid solution at room temperature. The nanofibers were characterized using scanning electron microscopy (SEM) and X-ray diffractometer (XRD). Disintegration time and contact angle measurements testified the hydrophilicity change of the nanofibers before and after cross-linking. The lutein release from the nanofibers after cross-linking was measured by an ultraviolet absorption spectrophotometer, which showed sustained release up to 48 h and followed anomalous (non-Fickian) release mechanism as indicated by diffusion exponent value obtained from the Korsmeyer-Peppas equation. The results indicated that the prepared lutein-loaded PVA/SA nanofibers have great potential as a controlled release system.

Formulation Strategies for Folate-Targeted Liposomes and Their Biomedical Applications.

The folate receptor (FR) is a tumor-associated antigen that can bind with folic acid (FA) and its conjugates with high affinity and ingests the bound molecules inside the cell via the endocytic mechanism. A wide variety of payloads can be delivered to FR-overexpressed cells using folate as the ligand, ranging from small drug molecules to large DNA-containing macromolecules. A broad range of folate attached liposomes have been proven to be highly effective as the targeted delivery system. For the rational design of folate-targeted liposomes, an intense conceptual understanding combining chemical and biomedical points of view is necessary because of the interdisciplinary nature of the field. The fabrication of the folate-conjugated liposomes basically involves the attachment of FA with phospholipids, cholesterol or peptides before liposomal formulation. The present review aims to provide detailed information about the design and fabrication of folate-conjugated liposomes using FA attached uncleavable/cleavable phospholipids, cholesterol or peptides. Advances in the area of folate-targeted liposomes and their biomedical applications have also been discussed.

Antibacterial Properties of Graphene-Based Nanomaterials.

Bacteria mediated infections may cause various acute or chronic illnesses and antibiotic resistance in pathogenic bacteria has become a serious health problem around the world due to their excessive use or misuse. Replacement of existing antibacterial agents with a novel and efficient alternative is the immediate demand to alleviate this problem. Graphene-based materials have been exquisitely studied because of their remarkable bactericidal activity on a wide range of bacteria. Graphene-based materials provide advantages of easy preparation, renewable, unique catalytic properties, and exceptional physical properties such as a large specific surface area and mechanical strength. However, several queries related to the mechanism of action, significance of size and composition toward bacterial activity, toxicity criteria, and other issues are needed to be addressed. This review summarizes the recent efforts that have been made so far toward the development of graphene-based antibacterial materials to face current challenges to combat against the bacterial targets. This review describes the inherent antibacterial activity of graphene-family and recent advances that have been made on graphene-based antibacterial materials covering the functionalization with silver nanoparticles, other metal ions/oxides nanoparticles, polymers, antibiotics, and enzymes along with their multicomponent functionalization. Furthermore, the review describes the biosafety of the graphene-based antibacterial materials. It is hoped that this review will provide valuable current insight and excite new ideas for the further development of safe and efficient graphene-based antibacterial materials.

Atomic Force Microscopy Based Tip-Enhanced Raman Spectroscopy in Biology.

Most biological phenomena occur at the nanometer scale, which is not accessible by the conventional optical techniques because of the optical diffraction limitation. Tip-enhanced Raman spectroscopy (TERS), one of the burgeoning probing techniques, not only can provide the topography characterization with high resolution, but also can deliver the chemical or molecular information of a sample beyond the optical diffraction limitation. Therefore, it has been widely used in various structural analyses pertaining to materials science, tissue engineering, biological processes and so on. Based on the different feedback mechanisms, TERS can be classified into three types: atomic force microscopy based TERS system (AFM-TERS), scanning tunneling microscopy based TERS system (STM-TERS) and shear force microscopy based TERS system (SFM-TERS). Among them, AFM-TERS is the most widely adopted feedback system by live biosamples because it can work in liquid and this allows the investigation of biological molecules under native conditions. In this review, we mainly focus on the applications of AFM-TERS in three biological systems: nucleic acids, proteins and pathogens. From the TERS characterization to the data analysis, this review demonstrates that AFM-TERS has great potential applications to visually characterizing the biomolecular structure and crucially detecting more nano-chemical information of biological systems.

Ethanol Diffusion on Rutile TiO2(110) Mediated by H Adatoms.

We have studied the diffusion of ethanol on rutile TiO2(110)-(1 × 1) by high-resolution scanning tunneling microscopy (STM) measurements and density functional theory (DFT) calculations. Time-lapsed STM images recorded at ∼200 K revealed the diffusion of ethanol molecules both parallel and perpendicular to the rows of surface Ti atoms. The diffusion of ethanol molecules perpendicular to the rows of surface Ti atoms was found to be mediated by H adatoms in the rows of bridge-bonded O (Obr) atoms similarly to previous results obtained for water monomers. In contrast, the diffusion of H adatoms across the Ti rows, mediated by ethanol molecules, was observed only very rarely and exclusively on fully hydrogenated TiO2(110) surfaces. Possible reasons why the diffusion of H adatoms across the Ti rows mediated by ethanol molecules occurs less frequently than the cross-row diffusion of ethanol molecules mediated by H adatoms are discussed.

The importance of bulk Ti3+ defects in the oxygen chemistry on titania surfaces.

The role of bulk defects in the oxygen chemistry on reduced rutile TiO(2)(110)-(1 × 1) has been studied by means of temperature-programmed desorption spectroscopy and scanning tunneling microscopy measurements. Following O(2) adsorption at 130 K, the amount of O(2) desorbing at ∼410 K initially increased with increasing density of surface oxygen vacancies but decreased after further reduction of the TiO(2)(110) crystal. We explain these results by withdrawal of excess charge (Ti(3+)) from the TiO(2)(110) lattice to oxygen species on the surface and by a reaction of Ti interstitials with O adatoms upon heating. Important consequences for the understanding of the O(2)-TiO(2) interaction are discussed.