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The interactions between nucleic acids and proteins are important in diverse biological processes. The high-quality prediction of nucleic-acid-binding sites continues to pose a significant challenge. Presently, the predictive efficacy of sequence-based methods is constrained by their exclusive consideration of sequence context information, whereas structure-based methods are unsuitable for proteins lacking known tertiary structures. Though protein structures predicted by AlphaFold2 could be used, the extensive computing requirement of AlphaFold2 hinders its use for genome-wide applications. Based on the recent breakthrough of ESMFold for fast prediction of protein structures, we have developed GLMSite, which accurately identifies DNA- and RNA-binding sites using geometric graph learning on ESMFold predicted structures. Here, the predicted protein structures are employed to construct protein structural graph with residues as nodes and spatially neighboring residue pairs for edges. The node representations are further enhanced through the pre-trained language model ProtTrans. The network was trained using a geometric vector perceptron, and the geometric embeddings were subsequently fed into a common network to acquire common binding characteristics. Finally, these characteristics were input into two fully connected layers to predict binding sites with DNA and RNA, respectively. Through comprehensive tests on DNA/RNA benchmark datasets, GLMSite was shown to surpass the latest sequence-based methods and be comparable with structure-based methods. Moreover, the prediction was shown useful for inferring nucleic-acid-binding proteins, demonstrating its potential for protein function discovery. The datasets, codes, and trained models are available at https://github.com/biomed-AI/nucleic-acid-binding. [ABSTRACT FROM AUTHOR]

Determining intrinsically disordered regions of proteins is essential for elucidating protein biological functions and the mechanisms of their associated diseases. As the gap between the number of experimentally determined protein structures and the number of protein sequences continues to grow exponentially, there is a need for developing an accurate and computationally efficient disorder predictor. However, current single-sequence-based methods are of low accuracy, while evolutionary profile-based methods are computationally intensive. Here, we proposed a fast and accurate protein disorder predictor LMDisorder that employed embedding generated by unsupervised pretrained language models as features. We showed that LMDisorder performs best in all single-sequence-based methods and is comparable or better than another language-model-based technique in four independent test sets, respectively. Furthermore, LMDisorder showed equivalent or even better performance than the state-of-the-art profile-based technique SPOT-Disorder2. In addition, the high computation efficiency of LMDisorder enabled proteome-scale analysis of human, showing that proteins with high predicted disorder content were associated with specific biological functions. The datasets, the source codes, and the trained model are available at https://github.com/biomed-AI/LMDisorder. [ABSTRACT FROM AUTHOR]

[Display omitted] • Air-cathode structure design constitutes a promising target for single-chamber microbial fuel cells. • Mechanisms and pathways of oxygen reduction reaction (ORR) at the air-cathodes are discussed. • Impact of excessive biofilm proliferation on ORR mass transport kinetics at the cathode interface is elucidated. • Progress of existing catalysts and possible antimicrobial mechanisms are highlighted. • It indicates the potential directions and implications for the development of air–cathode catalysts. Microbial fuel cells (MFCs), a potential game-changer in sustainable energy production, exploit bacterial metabolic activity to transduce organic waste into electrical power. Nevertheless, MFCs' performance hinges on a delicate interplay between anode and cathode. Given that cathodes are a primary site for power losses, their refinement becomes imperative. This review scrutinizes the intricate world of air–cathode composition and architecture, as well as the evolution and roles of oxygen reduction reaction (ORR) catalysts. It elaborates on the transition from carbon-based to metallic substrates, with stainless steel mesh emerging as a preferred material for cathodes, and also emphasizes the indispensable role of binders in cathode assembly. The discourse extends to the crucial functions of catalysts in hastening ORR, evaluating the shift from the high-performing yet cost-prohibitive Pt to more economical alternatives. Performances of various catalysts including metal monolithic, alloy, metal oxides/oxide analogues, macrocyclic metal complexes and single-atom catalysts are highlighted. The discussions, however, does not shy away from acknowledging the extant challenges in cathode development-durability, operational stability, and economic and environmental ramifications. Despite the many hurdles of air–cathode technology, ongoing research initiatives can anticipate breakthroughs that can hasten the transition of MFCs applications from the laboratory to real-world environments. [ABSTRACT FROM AUTHOR]

Indexes provide a method to access data in databases quickly. It can improve the response speed of subsequent queries by building a complete index in advance. However, it also leads to a huge overhead of the continuous updating during creating the index. An in-memory database usually has a higher query processing performance than disk databases and is more suitable for real-time query processing. Therefore, there is an urgent need to reduce the index creation and update cost for in-memory databases. Database cracking technology is currently recognized as an effective method to reduce the index initialization time. However, conventional cracking algorithms are focused on simple column data structure rather than those complex index structures for in-memory databases. In order to show the feasibility of in-memory database index cracking and promote to future more extensive research, this paper conducted a case study on the Adaptive Radix Tree (ART), a popular tree index structure of in-memory databases. On the basis of carefully examining the ART index construction overhead, an algorithm using auxiliary data structures to crack the ART index is proposed. This makes it possible to build up an ART index step by step with incessant queries, and hence avoids the poor instant availability of a complete index which is constructed once and for all, but is time consuming. Furthermore, updating a cracking ART index is considered as well. Extensive experiments show that the average initialization time of the ART cracker index is reduced by 75%, and the query response time gradually approaches the original ART algorithm with the coming queries. • In-memory database indexes have more extensive research and application space. • Database Cracking is used as a method applied to in-memory database indexes. • The algorithm has better performance advantages under random queries. [ABSTRACT FROM AUTHOR]

Manipulating electronic structure and defects is crucial to achieve on‐demand functionalities of bimetallic sulfide catalysts for oxygen reduction/evolution reactions (ORR/OER). Here, via a vulcanization strategy, defects‐abundant NiCo2S4 needles obtained from sea urchin‐like NiCo2O4 are anchored on surface of hollow carbon‐sphere (NiCo2S4/HCS). NiCo2S4 nanoneedles (≈7.5 nm) are radially grown on shell of HCS with a cavity (254.5 m2 g−1), and their surface becomes rougher after vulcanization due to anion exchange reaction. As‐marked NiCo2S4/HCS‐3 exhibits better ORR activity (half‐wave potential of 0.89 V) and methanol tolerance than Pt/C (0.86 V). NiCo2S4/HCS‐3 shows a lower OER overpotential (310 mV) than RuO2 and retains 90.9% of initial activity after 9 h. Notably, zinc–air battery with NiCo2S4/HCS‐3 reveals highly‐stable charging/discharging voltages of 2.11/1.16 V with a negligible fading for 200 h. NiCo2S4 grown on outer/inner surfaces of HCS expands spatial distribution of active sites to enhance reactants‐electrode contact and charge transfer. Theoretical calculation shows that Co‐site with an electronic state near Fermi energy level is chiefly‐responsible for ORR, while Ni‐site mainly affords high OER activity. Bader charge analyses reveal that S doping increases the charge density and redox active sites in NiCo2S4. It sheds light on the understanding of electrocatalytic mechanisms on bimetallic sulfides for electronic device. [ABSTRACT FROM AUTHOR]

• Relationship of reactivity and cytotoxicity needs to be clarified for nZVI materials. • Encapsulation of nZVI/Fe 3 C heterojunction in PGC skeleton enhances the air stability. • nZVI/Fe 3 C/PGC-700 exhibits a RhB removal efficiency of 89.2 % within 10 min at pH = 3. • Fe 3 C-bonded nZVI with a stable reactivity has high biocompatibility and low toxicity. • It reveals how the Fe 3 C-bonded nZVI can enhance its stability and lower its toxicity. Nano zero-valent iron (nZVI) as an active species for environmental applications usually suffers from its poor stability by corrosion and strong toxicity to microbes. To relieve the fast surface passivation and cytotoxicity (for Escherichia coli, E. coli), in-situ modification of nZVI with iron species may be a feasible strategy for strengthening the stability/reactivity and biocompatibility of nZVI-based materials. Here, nZVI/iron carbide heterojunctions are in situ embedded in partly-graphitized carbon (nZVI/Fe 3 C/PGC) using a one-step carbothermal synthesis method. nZVI/Fe 3 C/PGC-700 (700 °C) with a specific surface area of 126.04 m2/g exhibits a promising Rhodamine B (15 mg/L) removal efficiency of 89.2 % within 10 min at pH = 3. After 15 d storage in air or the 4th use, the crystalline structure and morphology of nZVI/Fe 3 C/PGC-700 remain basically unchanged. Due to the in-situ binding of nZVI and Fe 3 C with mixed valence, the surface oxidation is quite difficult to occur, thereby stabilizing the reducing capacity of nZVI. The encapsulation of nZVI/Fe 3 C heterojunctions in PGC structure also contributes to the structural stability. Although nZVI/Fe 3 C/PGC-700 can influence the metabolic functions of E. coli cells and the integrity of cell structure, this Fe 3 C-bonded nZVI exhibits a lower bacterial cytotoxicity than bare nZVI and nZVI@SiO 2 as indicated by lactate dehydrogenase and reduced superoxide dismutase assays. This novel strategy provides an interesting option for design of carbides-stabilized nZVI with balanced reactivity and cytotoxicity. [ABSTRACT FROM AUTHOR]

[Display omitted] • BT was preferred to occupy the P-hollow site, while naphthalene was preferentially adsorbed at the Ni-hollow site on the Ni(I) surface. • Fe atom doped was beneficial to improve the adsorption capacity of probe molecules. • Fe atom doped reduced the energy barrier of the rate-control step of BT HYD path. • Fe atom doped improved the selectivity of naphthalene ring-opening products. The competitive adsorption and reaction mechanism of benzothiophene (BT) and naphthalene at the active sites on the Ni 2 P (0 0 1) surfaces were systematically explored using density function theory (DFT) calculations. In the competitive adsorption process under reaction conditions, BT was preferred to occupy the P-hollow site and Ni-top site, while naphthalene was preferentially adsorbed at the Ni-hollow site on the Ni(I) structure surface. Fe atom doped was beneficial to improve the adsorption ability of probe molecules, in which the Ni-top site exhibited the highest adsorption ability for BT during competitive adsorption. In addition, the dominant reaction pathway of BT was HYD with the preferential cleavage route of the aryl C 4 -S bond, and the naphthalene tended to form tetralin and further saturated products through hydrogenation on the Ni(I) structure surface. Notably, the energy barrier for the C-S bond scission of BT, which was the rate control step, was significantly reduced after Fe atom doped on the Ni(I) structure surface (1.28 eV vs 1.05 eV). Meanwhile, the energy barrier for the cycloalkyl C–C bond scission of tetralin was also obviously decreased on the Fe-Ni(I) structure surface (2.02 eV vs 1.65 eV). Overall, Fe atom doped on the Ni(I) structure surface was of great significance to further improve the hydrogenation reactions activity and the selectivity of ring-opening products. [ABSTRACT FROM AUTHOR]

[Display omitted] • NiMo CA(x)/Al-TUD-1 modified with citric acid (CA) were successfully synthesized. • CA modification can enhance B/L ratio of NiMoCA(x)/AT catalysts. • CA modification improve the sulfidation and dispersion degree of active metals. • B/L and S-edge/Mo-edge ratios are beneficial to the isomerization route. • NiMoCA(2)/AT presents superior DBT and 4,6-DMDBT HDS performance. Low-cost pure aluminum-based Al-TUD-1 mesoporous materials (AT) were successfully synthesized and the corresponding NiMo/AT catalysts were modified with Citric acid (CA), which were utilized for dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophene (4,6-DMDBT) hydrodesulfurization (HDS) reactions. CA could effectively modulate the acidity and metal-support-interaction (MSI) of NiMoCA(x)/AT catalysts, which were in favor of generating more MoS 2 active species with higher sulfurization degree and higher dispersion degree. The morphology of the MoS 2 active phase of NiMoCA(x)/AT catalysts was changed after the addition of CA. The NiMoCA(2)/AT catalyst showed the higher B/L ratio and higher S-edge/M-edge ratio, which was conducive to the isomerization (ISO) route selectivity (81%) of 4,6-DMDBT HDS, thus resulting the improvement of HDS activity of the NiMoCA(2)/AT catalyst. The NiMoCA(2)/AT exhibited the maximal DBT and 4,6-DMDBT HDS efficiency of 99.0% and 95.5% as well as maximal k HDS and TOF values of 4,6-DMDBT HDS (13.4 × 10−4 mol⋅g−1⋅h−1, 4.7 h−1) among other series NiMoCA(x)/AT catalysts and reference commercial NiMo/Al 2 O 3 catalyst at the Weight hour space velocity (WHSV) of 10 h−1. [ABSTRACT FROM AUTHOR]