Cobalt selenide has been proposed to be an effective low‐cost electrocatalyst toward the oxygen evolution reaction (OER) due to its well‐suited electronic configuration. However, pure cobalt selenide ...has by far still exhibited catalytic activity far below what is expected. Herein, this paper for the first time reports the synthesis of new monoclinic Co3Se4 thin nanowires on cobalt foam (CF) via a facile one‐pot hydrothermal process using selenourea. When used to catalyze the OER in basic solution, the conditioned monolithic self‐supported Co3Se4/CF electrode shows an exceptionally high catalytic current of 397 mA cm−2 at a low overpotential (η) of 320 mV, a small Tafel slope of 44 mV dec−1, a turnover frequency of 6.44 × 10−2 s−1 at η = 320 mV, and excellent electrocatalytic stability at various current densities. Furthermore, an electrolyzer is assembled using two symmetrical Co3Se4/CF electrodes as anode and cathode, which can deliver 10 and 20 mA cm−2 at low cell voltages of 1.59 and 1.63 V, respectively. More significantly, the electrolyzer can operate at 10 mA cm−2 over 3500 h and at 100 mA cm−2 for at least 2000 h without noticeable degradation, showing extraordinary operational stability.
Thin Co3Se4 nanowires are grown on porous Co foam (CF) via hydrothermal selenization, forming an integrated Co3Se4/CF electrode, which exhibits outstanding catalytic performance for oxygen evolution with a high current of 397 mA cm‐2 at an overpotential of 320 mV. An electrolyzer comprising two symmetrical Co3Se4/CF can operate at 10 mA cm−2 under 1.59 V over 3500 h without degradation.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
2D layered materials have sparked great interest from the perspective of basic physics and applied science in the past few years. Extraordinarily, many novel stacked structures that bring versatile ...properties and applications can be artificially assembled, as exemplified by vertical van der Waals (vdW) heterostructures, twisted multilayer 2D materials, hybrid dimensional structures, etc. Compared with the ordinary synthesis process, the stacking technique is a powerful strategy to achieve high‐quality and freely controlled 2D material stacked structures with atomic accuracy. This review highlights the most advanced stacking techniques involving the preparation, transfer, and stacking of high‐quality single crystal 2D materials. Apart from the 2D–2D stacked structures, 2D–0D, 2D–1D, and 2D–3D structures offer a prospective platform for the increasing application of 2D materials. The assembly strategy and physical properties of these stacked structures strongly depend on the factors in the stacking process, including the surface quality, angle control, and sample size. In addition, comparative analysis tables on the techniques involved are also available. The summary of these strategies and techniques will hopefully provide a valuable reference for relevant work.
2D stacked structures are being rapidly developed. However, the assembly and integration techniques of 2D material‐based devices are still subject to many restrictions, seriously hindering the design and development of new functional devices. As one of the most important aspects, 2D material stacking techniques are systematically summarized and analyzed in this review.
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•Eu doping could enhance the SO2 resistance of Mn/TiO2 catalyst for SCR reaction.•The addition of Eu on Mn/TiO2 catalyst inhibited the formation of surface sulfate.•The SCR reaction ...(with SO2) over MnEu/TiO2 catalyst took place through L-H pathway.
Mn/TiO2 catalyst is a promising candidate for future utilization in low-temperature NH3-SCR reaction, but its bad resistance to SO2 is still a great challenge for practical application. In this study, Eu was successfully used as the additive to improve its resistance to SO2 under SCR conditions, while the pretreatment of Mn/TiO2 and MnEu/TiO2 catalyst by SO2 + O2 had a strong deactivation effect on them. In situ DRIFT study clarified that the deactivation of Mn/TiO2-S (SCR + SO2), Mn/TiO2-S (SO2 + O2) and MnEu/TiO2-S (SO2+O2) were mainly originated from the inhibited adsorption of NH3 and NOx species, as well as the formation of a large amount surface sulfate species on them, which had a strong blacking effect on the SCR reactions over the three catalysts via both E-R and L-H routes. After the addition of Eu, SCR reaction over MnEu/TiO2 catalyst with the existence of SO2 took place through L-H pathway, accompanied by the generation of less surface sulfate species, which brought about the excellent SO2 tolerance of MnEu/TiO2 catalyst under SCR conditions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Small data are often used in scientific and engineering research due to the presence of various constraints, such as time, cost, ethics, privacy, security, and technical limitations in data ...acquisition. However, big data have been the focus for the past decade, small data and their challenges have received little attention, even though they are technically more severe in machine learning (ML) and deep learning (DL) studies. Overall, the small data challenge is often compounded by issues, such as data diversity, imputation, noise, imbalance, and high-dimensionality. Fortunately, the current big data era is characterized by technological breakthroughs in ML, DL, and artificial intelligence (AI), which enable data-driven scientific discovery, and many advanced ML and DL technologies developed for big data have inadvertently provided solutions for small data problems. As a result, significant progress has been made in ML and DL for small data challenges in the past decade. In this review, we summarize and analyze several emerging potential solutions to small data challenges in molecular science, including chemical and biological sciences. We review both basic machine learning algorithms, such as linear regression, logistic regression (LR), k-nearest neighbor (KNN), support vector machine (SVM), kernel learning (KL), random forest (RF), and gradient boosting trees (GBT), and more advanced techniques, including artificial neural network (ANN), convolutional neural network (CNN), U-Net, graph neural network (GNN), Generative Adversarial Network (GAN), long short-term memory (LSTM), autoencoder, transformer, transfer learning, active learning, graph-based semi-supervised learning, combining deep learning with traditional machine learning, and physical model-based data augmentation. We also briefly discuss the latest advances in these methods. Finally, we conclude the survey with a discussion of promising trends in small data challenges in molecular science.
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IJS, KILJ, NUK, PNG, UL, UM
The mitochondrial serine hydroxymethyltransferase SHMT2, which catalyzes the rate-limiting step in serine catabolism, drives cancer cell proliferation, but how this role is regulated is undefined. ...Here, we report that the sirtuin SIRT5 desuccinylates SHMT2 to increase its activity and drive serine catabolism in tumor cells. SIRT5 interaction directly mediated desuccinylation of lysine 280 on SHMT2, which was crucial for activating its enzymatic activity. Conversely, hypersuccinylation of SHMT2 at lysine 280 was sufficient to inhibit its enzymatic activity and downregulate tumor cell growth
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Notably, SIRT5 inactivation led to SHMT2 enzymatic downregulation and to abrogated cell growth under metabolic stress. Our results reveal that SHMT2 desuccinylation is a pivotal signal in cancer cells to adapt serine metabolic processes for rapid growth, and they highlight SIRT5 as a candidate target for suppressing serine catabolism as a strategy to block tumor growth.
These findings reveal a novel mechanism for controlling cancer cell proliferation by blocking serine catabolism, as a general strategy to impede tumor growth.
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Using a method optimized in hepatocellular carcinoma (HCC), we established patient‐derived xenograft (PDX) models with an increased take rate (42.2%) and demonstrated that FBS +10% dimethyl sulfoxide ...exhibited the highest tumor take rate efficacy. Among 254 HCC patients, 103 stably transplantable xenograft lines that could be serially passaged, cryopreserved and revived were established. These lines maintained the diversity of HCC and the essential features of the original specimens at the histological, transcriptome, proteomic and genomic levels. Tumor engraftment was associated with lack of encapsulation, poor tumor differentiation, large size and overexpression of cancer stem cell biomarkers, and was an independent predictor for overall survival and tumor recurrence after resection. To confirm the preclinical value of the PDX model in HCC treatment, several antitumor agents were tested in 16 selected PDX models. The results revealed a high degree of pharmacologic heterogeneity in the cohort, as well as heterogeneity to different agents in the same individual. The sorafenib responses observed between HCC patients and the corresponding PDXs were also consistent. After molecular characterization of the PDX models, we explored the predictive markers for sorafenib response and found that mitogen‐activated protein kinase kinase kinase 1 (MAP3K1) might play an important role in sorafenib resistance and sorafenib response is impaired in patients with MAP3K1 downexpression. Our results indicated that PDX models could accurately reproduce patient tumors biology and could aid in the discovery of new treatments to advance in precision medicine.
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Patient‐derived xenografts (PDX) models offer a promising preclinical tool. Here, the authors established the largest bank of hepatocellular carcinoma (HCC) PDX models with a high and stable tumor take rate that recapitulated the key clinical and molecular characteristics of primary tumors. The tumor take rate was associated with expression of cancer stem cell proteins, lack of tumor encapsulation, poor differentiation, advanced stage, overall survival, and time to recurrence in patients. The models were used to identify MAP3K1 expression as an indicator of patient response to sorafenib treatment. PDX models are valuable surrogates for HCC patients and could facilitate translational research.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), coronavirus disease 2019 (COVID‐19) has shown extensive lung manifestations in vulnerable individuals, putting lung imaging and ...monitoring at the forefront of early detection and treatment. Magnetic particle imaging (MPI) is an imaging modality, which can bring excellent contrast, sensitivity, and signal‐to‐noise ratios to lung imaging for the development of new theranostic approaches for respiratory diseases. Advances in MPI tracers would offer additional improvements and increase the potential for clinical translation of MPI. Here, a high‐performance nanotracer based on shape anisotropy of magnetic nanoparticles is developed and its use in MPI imaging of the lung is demonstrated. Shape anisotropy proves to be a critical parameter for increasing signal intensity and resolution and exceeding those properties of conventional spherical nanoparticles. The 0D nanoparticles exhibit a 2‐fold increase, while the 1D nanorods have a > 5‐fold increase in signal intensity when compared to VivoTrax. Newly designed 1D nanorods displayed high signal intensities and excellent resolution in lung images. A spatiotemporal lung imaging study in mice revealed that this tracer offers new opportunities for monitoring disease and guiding intervention.
Magnetic particle imaging (MPI) offers high contrast, sensitivity, and signal‐to‐noise ratios for lung imaging, enhancing theranostic strategies in respiratory disease. Innovations in MPI tracers promise further gains, bolstering clinical applicability. This work introduces a superior nanotracer, leveraging magnetic nanoparticle shape anisotropy, elevating sensitivity and resolution beyond conventional spherical counterparts for lung MPI.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Distant metastasis is the main cause of breast cancer-related death; however, effective therapeutic strategies targeting metastasis are still scarce. This is largely attributable to the ...spatiotemporal intratumor heterogeneity during metastasis. Here we show that protein deacetylase SIRT7 is significantly downregulated in breast cancer lung metastases in human and mice, and predicts metastasis-free survival. SIRT7 deficiency promotes breast cancer cell metastasis, while temporal expression of Sirt7 inhibits metastasis in polyomavirus middle T antigen breast cancer model. Mechanistically, SIRT7 deacetylates and promotes SMAD4 degradation mediated by β-TrCP1, and SIRT7 deficiency activates transforming growth factor-β signaling and enhances epithelial-to-mesenchymal transition. Significantly, resveratrol activates SIRT7 deacetylase activity, inhibits breast cancer lung metastases, and increases survival. Our data highlight SIRT7 as a modulator of transforming growth factor-β signaling and suppressor of breast cancer metastasis, meanwhile providing an effective anti-metastatic therapeutic strategy.Metastatic disease is the major reason for breast cancer-related deaths; therefore, a better understanding of this process and its players is needed. Here the authors report the role of SIRT7 in inhibiting SMAD4-mediated breast cancer metastasis providing a possible therapeutic avenue.
The potential threat of antibiotics to the environment and human health has raised significant concerns in recent years. The consumption and production of antibiotics in China are the highest in the ...world due to its rapid economic development and huge population, possibly resulting in the high detection frequencies and concentrations of antibiotics in aquatic environments of China. As a water resource, lakes in China play an important role in sustainable economic and social development. Understanding the current state of antibiotics in lakes in China is important. Closed and semi-closed lakes provide an ideal medium for the accumulation of antibiotics and antibiotic resistance genes (ARGs). This review summarizes the current levels of antibiotic exposure in relevant environmental compartments in lakes. The ecological and health risks of antibiotics are also evaluated. This review concludes that 39 antibiotics have been detected in the aquatic environments of lakes in China. The levels of antibiotic contamination in lakes in China is relatively high on the global scale. Antibiotic contamination is higher in sediment than water and aquatic organisms. Quinolone antibiotics (QNs) pose the greatest risks. The contents of antibiotics in aquatic organisms are far lower than their maximum residual limits (MRLs), with the exception of the organisms in Honghu Lake. The lakes experience high levels of ARG contamination. A greater assessment of ARG presence and antibiotic exposure are urgent.
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•39 antibiotics are detected in aquatic environment of lakes in China•The quinolone antibiotics are predominant risk and pollution factors in aquatic environment of lakes.•All Lakes experience ARGs pollution with high detection frequencies of sulfonamide and tetracycline resistance genes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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