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Abstract To unveil the nature of amorphous states, single‐element amorphous metals have been the perfect research subject due to the simplest composition. However, the extreme crystal nucleation and growth rate in single‐element metal make the synthesis of single‐element amorphous metals seemingly impossible in the past. Fortunately, benefited by several delicate synthetic strategies developed recently, the single‐element amorphous metals have been successfully demonstrated. This review aims to provide a systematic overview of the synthesis of single‐element amorphous metals covering the challenges in physics and recent achievements. In addition, current understanding of the atomic and electronic structures of single‐element amorphous metal has also been included. Finally, the challenges that worth further investigation are discussed. By identifying the potential avenues for further exploration, this review aims to contribute valuable insights that will propel the cognition of single‐element amorphous metals.

Fast and precise identification of microorganisms in the early diagnosis of sepsis is crucial for enhancing patient outcomes. Digital PCR (dPCR) is a highly sensitive approach for absolute quantification that can be utilized as a culture-independent molecular technique for diagnosing sepsis pathogens. We performed a retrospective investigation on 69 ICU patients suspected of sepsis. Our findings showed that a multiplex dPCR diagnostic kit outperformed blood culture in detecting the 15 most frequent bacteria that cause sepsis. Ninety-two bacterial strains were identified using dPCR at concentrations varying from 34 copies/mL to 105,800 copies/mL. The detection rate of dPCR was much greater than that of BC, with 27.53% (19/69) versus 73.91% (51/69). The sensitivity of dPCR was 63.2%. Our research indicated that dPCR outperforms blood culture in the early detection of sepsis-causing microorganisms. The diagnostic kit can detect a greater variety of pathogens with quantitative data, including polymicrobial infections, and has a quicker processing time. DPCR is a valuable technique that could aid in the proper management of sepsis.

International students play a crucial role in China’s talent development strategy. Thus, predicting overseas talent mobility is essential for formulating scientifically reasonable talent introduction policies, optimizing talent cultivation systems, and fostering international talent cooperation. In this study, we proposed a novel fractional-order grey model based on the Multi-Layer Perceptron (MLP) and Grey Wolf Optimizer (GWO) algorithm to forecast the movement of overseas talent, namely MGDFGM(1,1). Compared to the traditional grey model FGM(1,1), which utilizes the same fractional order at all time points, the proposed MGDFGM(1,1) model dynamically adjusts the fractional-order values based on the time point. This dynamic adjustment enables our model to better capture the changing trends in the data, thereby enhancing the model’s fitting capability. To validate the effectiveness of the MGDFGM(1,1) model, we primarily utilize Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) as the evaluation criteria for the prediction accuracy, as well as standard deviation (STD) as an indicator of the model stability. Furthermore, we perform experimental analysis to evaluate the predictive performance of the MGDFGM(1,1) model in comparison to NAÏVE, ARIMA, GM(1,1), FGM(1,1), LSSVR, MLP, and LSTM. The research findings demonstrate that the MGDFGM(1,1) model achieves a remarkably high level of prediction accuracy and stability for forecasting overseas talent mobility in China. The implications of this study offer valuable insights and assistance to government departments involved in overseas talent management.

Amorphous nanocatalysts have attracted significant attention due to their outstanding catalytic performance. Recent research has indicated that the performance of amorphous nanocatalysts is closely related to the short-to-medium-range order. This perspective aims to provide a comprehensive summary of the latest advances in understanding the significance of short-to-medium-range order in amorphous nanocatalysts and its correlation with catalytic performance. This perspective commences by presenting advanced methods employed for characterizing the short-to-medium-range order of amorphous nanocatalysts, including nanobeam electron diffraction, scanning transmission electron microscopy, atomic electron tomography, pair distribution function, and X-ray absorption fine structure spectroscopy. Next, the effect of short-to-medium-range order in determining the properties of amorphous nanocatalysts is discussed. Current challenges faced in amorphous nanocatalysts are eventually summarized with several prospective research directions. By identifying the obstacles and potential avenues for further exploration, this perspective aims to contribute valuable insights that will propel the development of high-efficient amorphous nanocatalysts.

SspABCD–SspE is a phosphorothioation-sensing bacterial defence system. Here, authors find that SspE exploits DNA phosphorothioation-binding preference to modulate its biochemical activities for the self/nonself discrimination and phage resistance.

While inducing strain to noble metal nanomaterials can modulate catalytic activities, the strain is often spatially dependent. Here, authors manipulate the planar strain in noble metal nanosheets for hydrogen evolution electrocatalysis by constructing amorphous–crystalline phase boundaries.

Abstract The conversion of CO2 into fuels and valuable chemicals is one of the central topics to combat climate change and meet the growing demand for renewable energy. Herein, we show that the formate dehydrogenase from Clostridium ljungdahlii (ClFDH) adsorbed on electrodes displays clear characteristic voltammetric signals that can be assigned to the reduction and oxidation potential of the [4Fe‐4S]2+/+ cluster under nonturnover conditions. Upon adding substrates, the signals transform into a specific redox center that engages in catalytic electron transport. ClFDH catalyzes rapid and efficient reversible interconversion between CO2 and formate in the presence of substrates. The turnover frequency of electrochemical CO2 reduction is determined as 1210 s−1 at 25 °C and pH 7.0, which can be further enhanced up to 1786 s−1 at 50°C. The Faradaic efficiency at −0.6 V (vs. standard hydrogen electrode) is recorded as 99.3% in a 2‐h reaction. Inhibition experiments and theoretical modeling disclose interesting pathways for CO2 entry, formate exit, and OCN− competition, suggesting an oxidation‐state‐dependent binding mechanism of catalysis. Our results provide a different perspective for understanding the catalytic mechanism of FDH and original insights into the design of synthetic catalysts.

Every generation of wireless technologies needs to bring a set of new system capabilities to enable future applications and services, the sixth generation mobile system (6G) is no exception. This paper provides an overview of the technology transformation from the communication-centric the forth generation mobile system (4G) and the fifth generation mobile system (5G) to the compute-centric 6G with the cloud-native system framework as the foundation of the next generation technologies. We explain what 6G plans to achieve, the fundamental reasons for this technology transformation, the architecture framework and enabling technologies to achieve 6G cloud-native technology objectives. This paper intends to provide a technical deep dive on the 6G cloud-native system to trigger more discussions, innovations and bring the technology transformation from concept to reality.

The SARS-CoV-2 Omicron outbreak is ongoing in Shanghai, home to 25 million population. Here, we presented a novel mathematical model to evaluate the Omicron spread and Zero-COVID strategy. Our model provided important parameters, the average quarantine ratio, the detection interval from being infected to being tested positive, and the spreading coefficient to understand the epidemic progression better. Moreover, we found that the key to a relatively accurate long-term forecast was to take the variation/relaxation of the parameters into consideration based on the flexible execution of the quarantine policy. This allowed us to propose the criteria for estimating the parameters and outcome for the ending stage that is likely to take place in late May. Altogether, this model helped to give a correct mathematical appraisal of the SARS-CoV-2 Omicron outbreak under the strict Zero-COVID policy in China.

ABSTRACT The compositional and physiological responses of autotrophic microbiotas to salinity in lakes remain unclear. In this study, the community composition and carbon fixation pathways of autotrophic microorganisms in lacustrine sediments with a salinity gradient (82.6 g/L to 0.54 g/L) were investigated by using metagenomic analysis. A total of 117 metagenome-assembled genomes (MAGs) with carbon fixation potentially belonging to 20 phyla were obtained. The abundance of these potential autotrophs increased significantly with decreasing salinity, and the variation of sediment autotrophic microbial communities was mainly affected by salinity, pH, and total organic carbon. Notably, along the decreasing salinity gradient, the dominant lineage shifted from Desulfobacterota to Proteobacteria. Meanwhile, the dominant carbon fixation pathway shifted from the Wood-Lungdahl pathway to the less-energy-efficient Calvin-Benson-Bassham cycle, with glycolysis shifting from the Embden-Meyerhof-Parnas pathway to the less-exergonic Entner-Doudoroff pathway. These results suggest that the physiological efficiency of autotrophic microorganisms decreased when the environmental salinity became lower. Metabolic inference of these MAGs revealed that carbon fixation may be coupled to the oxidation of reduced sulfur compounds and ferrous iron, dissimilatory nitrate reduction at low salinity, and dissimilatory sulfate reduction in hypersaline sediments. These results extend our understanding of metabolic versatility and niche diversity of autotrophic microorganisms in saline environments and shed light on the response of autotrophic microbiomes to salinity. These findings are of great significance for understanding the impact of desalination caused by climate warming on the carbon cycle of saline lake ecosystems. IMPORTANCE The Qinghai-Tibetan lakes are experiencing water increase and salinity decrease due to climate warming. However, little is known about how the salinity decrease will affect the composition of autotrophic microbial populations and their carbon fixation pathways. In this study, we used genome-resolved metagenomics to interpret the dynamic changes in the autotrophic microbial community and metabolic pathways along a salinity gradient. The results showed that desalination drove the shift of the dominant microbial lineage from Desulfobacterota to Proteobacteria, enriched autotrophs with lower physiological efficiency pathways, and enhanced coupling between the carbon cycle and other element cycles. These results can predict the future response of microbial communities to lake desalination and improve our understanding of the effect of climate warming on the carbon cycle in saline aquatic ecosystems.

ABSTRACT Phosphorothioate (PT) modification, a sequence-specific modification that replaces the nonbridging oxygen atom with sulfur in a DNA phosphodiester through the gene products of dndABCDE or sspABCD, is widely distributed in prokaryotes. DNA PT modification functions together with gene products encoded by dndFGH, pbeABCD, or sspE to form defense systems that can protect against invasion by exogenous DNA particles. While the functions of the multiple enzymes in the PT system have been elucidated, the exact role of DndE in the PT process is still obscure. Here, we solved the crystal structure of DndE from the haloalkaliphilic archaeal strain Natronorubrum bangense JCM10635 at a resolution of 2.31 Å. Unlike the tetrameric conformation of DndE in Escherichia coli B7A, DndE from N. bangense JCM10635 exists in a monomeric conformation and can catalyze the conversion of supercoiled DNA to nicked or linearized products. Moreover, DndE exhibits preferential binding affinity to nicked DNA by virtue of the R19- and K23-containing positively charged surface. This work provides insight into how DndE functions in PT modification and the potential sulfur incorporation mechanism of DNA PT modification. IMPORTANCE DndABCDE proteins have been demonstrated to catalyze DNA PT modification with the nonbridging oxygen in the DNA sugar-phosphate backbone replaced by sulfur. In the PT modification pathway, DndA exerts cysteine desulfurase activity capable of catalyzing the mobilization of sulfur from l-cysteine, which involves the ion-sulfur cluster assembly of DndC. This is regarded as the initial step of the DNA PT modification. Moreover, DndD has ATPase activity in vitro, which is believed to provide energy for the oxygen-sulfur swap, while the function of DndE is unknown. However, the exact function of the key enzyme DndE remains to be elucidated. By determining the structure of DndE from the haloalkaliphilic strain Natronorubrum bangense JCM10635, we showed that the archaeal DndE adopts a monomer conformation. Notably, DndE can introduce nicks to supercoiled DNA and exhibits a binding preference for nicked DNA; the nicking is believed to be the initial step for DNA to facilitate the sulfur incorporation.

The balance between anabolism and catabolism is disrupted with aging, with the rate of anabolism being faster than that of catabolism. Therefore, mTOR, whose major function is to enhance anabolism and inhibit catabolism, has become a potential target of inhibition for anti-aging therapy. Interestingly, it was found that the downregulation of the mTOR signaling pathway had a lifespan-extending effect resembling calorie restriction. In addition, the mTOR signaling pathway promotes cell proliferation and has been regarded as a potential anti-cancer target. Rapamycin and rapalogs, such as everolimus, have proven to be effective in preventing certain tumor growth. Here, we reviewed the basic knowledge of mTOR signaling, including both mTORC1 and mTORC2. Then, for anti-aging, we cited a lot of evidence to discuss the role of targeting mTOR and its anti-aging mechanism. For cancer therapy, we also discussed the role of mTOR signaling in different types of cancers, including idiopathic pulmonary fibrosis, tumor immunity, etc. In short, we discussed the research progress and both the advantages and disadvantages of targeting mTOR in anti-aging and anti-cancer therapy. Hopefully, this review may promote more ideas to be generated for developing inhibitors of mTOR signaling to fight cancer and extend lifespan.

Summary: Achieving high selectivity and activity with the oxygen reduction reaction (ORR) is significant for developing efficient energy conversion techniques and chemical production. Here, we report that selective ORRs can be achieved by tuning short-range order in amorphous and crystalline NiO nanosheets (a-NiO NSs and c-NiO NSs, respectively). X-ray absorption spectroscopy analysis reveals that the short-range order of a-NiO NSs and c-NiO NSs mainly adopt the NiO5 pyramidal and NiO6 octahedral structures, respectively. The a-NiO NSs for electrochemical H2O2 production in 0.1 M KOH exhibits both high selectivity over 90% and high activity (1 mA cm−2 at 0.66 V versus RHE), while c-NiO NSs tends to catalyze ORRs through 4-electron pathways to generate H2O. Theoretical calculations indicate that the changed short-range order of a-NiO NSs leads to alteration of Ni d-orbital states, which can regulate the adsorption orientation and strength of ∗OOH intermediates to achieve high selectivity and activity of 2-electron ORRs.

Overseas students constitute the paramount talent resource for China, and, hence, overseas talent mobility prediction is crucial for the formulation of China’s talent strategy. This study proposes a new model for predicting the number of students studying abroad and returning students, based on the grey system theory, owing to the limited data and uncertainty of the influencing factors. The proposed model introduces change-point detection to determine the number of modeling time points, based on the fractional-order grey prediction model. We employed a change-point detection method to find the change points for determining the model length, based on the principle of new information priority, and used a fractional order accumulated generating operation to construct a grey prediction model. The two real data sets, the annual number of students studying abroad and returning students, were employed to verify the superiority of the proposed model. The results showed that the proposed model outperformed other benchmark models. Furthermore, the proposed model has been employed to predict the tendencies of overseas talent mobility in China by 2025. Further, certain policy recommendations for China’s talent strategy development have been proposed, based on the prediction results.

The lymphatic system is crucial for the regeneration of many tissues due to its fundamental role in immune cell trafficking, protein transport, and tissue homeostasis maintenance. Strategies stimulating lymphangiogenesis can provide new therapeutic approaches for tissue repair and regeneration (e.g., chronic wound healing). Here, we explored the effects of cerium-containing mesoporous bioactive glass nanoparticles (Ce-MBGNs) on lymphangiogenesis. The results showed that the extracts of Ce-MBGNs (1, 5, or 10 wt/v%) were non-cytotoxic toward lymphatic endothelial cells (LECs), while they enhanced the proliferation of LECs. Moreover, as evidenced by the scratch wound healing and Transwell migration assays, conditioned media containing the extract of Ce-MBGNs (1 wt/v%) could enhance the migration of LECs in comparison to the blank control and the media containing vascular endothelial growth factor-C (VEGF-C, 50 ng/mL). Additionally, a tube-formation assay using LECs showed that the extract of Ce-MBGNs (1 wt/v%) promoted lymphatic vascular network formation. Western blot results suggested that Ce-MBGNs could induce lymphangiogenesis probably through the HIF-1α/VEGFR-3 pathway. Our study for the first time showed the effects of Ce-MBGNs on stimulating lymphangiogenesis in vitro, highlighting the potential of Ce-MBGNs for wound healing.

Eukaryotic cells coordinate growth under different environmental conditions via mechanistic target of rapamycin complex 1 (mTORC1). In the amino-acid-sensing signalling pathway, the GATOR2 complex, containing five evolutionarily conserved subunits (WDR59, Mios, WDR24, Seh1L and Sec13), is required to regulate mTORC1 activity by interacting with upstream CASTOR1 (arginine sensor) and Sestrin2 (leucine sensor and downstream GATOR1 complex). GATOR2 complex utilizes β-propellers to engage with CASTOR1, Sestrin2 and GATOR1, removal of these β-propellers results in substantial loss of mTORC1 capacity. However, structural information regarding the interface between amino acid sensors and GATOR2 remains elusive. With the recent progress of the AI-based tool AlphaFold2 (AF2) for protein structure prediction, structural models were predicted for Sentrin2-WDR24-Seh1L and CASTOR1-Mios β-propeller. Furthermore, the effectiveness of relevant residues within the interface was examined using biochemical experiments combined with molecular dynamics (MD) simulations. Notably, fluorescence resonance energy transfer (FRET) analysis detected the structural transition of GATOR2 in response to amino acid signals, and the deletion of Mios β-propeller severely impeded that change at distinct arginine levels. These findings provide structural perspectives on the association between GATOR2 and amino acid sensors and can facilitate future research on structure determination and function. [ABSTRACT FROM AUTHOR]