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To explore novel electrode materials with in-depth elucidation of initial coulombic efficiency (ICE), kinetics, and charge storage mechanisms is of great challenge for Na-ion storage. Herein, a novel 3D antiperovskite carbide Ni3ZnC0.7@rGO anode coupled with ether-based electrolyte is reported for fast Na-ion storage, exhibiting superior performance than ester-based electrolyte. Electrochemical tests and density functional theory (DFT) calculations show that Ni3ZnC0.7@rGO anode with ether-based electrolyte can promote charge/ion transport and lower Na+ diffusion energy barrier, thereby improving ICE, reversible capacity, rate, and cycling performance. Cross-sectional-morphology and depth profiling surface chemistry demonstrate that not only a thinner and more homogeneous reaction interface layer with less side effects but also a superior solid electrolyte interface (SEI) film with a high proportion of inorganic components are formed in the ether-based electrolyte, which accelerates Na+ transport and is the significant reason for the improvement of ICE and other electrochemical properties. Meanwhile, electrochemical and ex situ measurements have revealed conversion, alloying, and co-intercalation hybrid mechanisms of the Ni3ZnC0.7@rGO anode based on ether electrolyte. Interestingly, the Na-ion capacitors (SICs) designed by pairing with activated carbon (AC) cathode exhibit favorable electrochemical performance. Overall, this work provides deep insights on developing advanced materials for fast Na-ion storage.
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Developing high electroactivity ruthenium (Ru)-based electrocatalysts for pH-universal hydrogen evolution reaction (HER) is challenging due to the strong bonding strengths of key RuâH/RuâOH intermediates and sluggish water dissociation rates on active Ru sites. Herein, a semi-ionic F-modified N-doped porous carbon implanted with ruthenium nanoclusters (Ru/FNPC) is introduced by a hydrogel sealing-pyrolying-etching strategy toward highly efficient pH-universal hydrogen generation. Benefiting from the synergistic effects between Ru nanoclusters (Ru NCs) and hierarchically F, N-codoped porous carbon support, such synthesized catalyst displays exceptional HER reactivity and durability at all pH levels. The optimal 8Ru/FNPC affords ultralow overpotentials of 17.8, 71.2, and 53.8 mV at the current density of 10 mA cm-2 in alkaline, neutral, and acidic media, respectively. Density functional theory (DFT) calculations elucidate that the F-doped substrate to support Ru NCs weakens the adsorption energies of H and OH on Ru sites and reduces the energy barriers of elementary steps for HER, thus enhancing the intrinsic activity of Ru sites and accelerating the HER kinetics. This work provides new perspectives for the design of advanced electrocatalysts by porous carbon substrate implanted with ultrafine metal NCs for energy conversion applications.
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Owing to the increasing resistance to most existing antimicrobial drugs, research has shifted towards developing novel antimicrobial agents with mechanisms of action distinct from those of current clinical options. Pleuromutilins are antibiotics known for their distinct mechanism of action, inhibiting bacterial protein synthesis by binding to the peptidyl transferase center of the ribosome. Recent studies have revealed that pleuromutilin derivatives can disrupt bacterial cell membranes, thereby enhancing antibacterial efficacy. Both marketed pleuromutilin derivatives and those in clinical trials have been developed by structurally modifying the pleuromutilin C14 side chain to improve their antimicrobial activity. Therefore, this review aims to review advancement in the chemical structural characteristics, antibacterial activities, and structure-activity relationship studies of pleuromutilins, specifically focusing on modifications made to the C14 side chain in recent years. These findings provide a valuable reference for future research and development of pleuromutilins.
Assuntos
Diterpenos , Compostos Policíclicos , Pleuromutilinas , Antibacterianos/farmacologia , Antibacterianos/química , Diterpenos/farmacologia , Diterpenos/química , Compostos Policíclicos/farmacologia , Relação Estrutura-Atividade , Testes de Sensibilidade MicrobianaRESUMO
Sequential recommendation typically utilizes deep neural networks to mine rich information in interaction sequences. However, existing methods often face the issue of insufficient interaction data. To alleviate the sparsity issue, self-supervised learning is introduced into sequential recommendation. Despite its effectiveness, we argue that current self-supervised learning-based (i.e., SSL-based) sequential recommendation models have the following limitations: (1) using only a single self-supervised learning method, either contrastive self-supervised learning or generative self-supervised learning. (2) employing a simple data augmentation strategy in either the graph structure domain or the node feature domain. We believe that they have not fully utilized the capabilities of both self-supervised methods and have not sufficiently explored the advantages of combining graph augmentation schemes. As a result, they often fail to learn better item representations. In light of this, we propose a novel multi-task sequential recommendation framework named Adaptive Self-supervised Learning for sequential Recommendation (ASLRec). Specifically, our framework combines contrastive and generative self-supervised learning methods adaptively, simultaneously applying different perturbations at both the graph topology and node feature levels. This approach constructs diverse augmented graph views and employs multiple loss functions (including contrastive loss, generative loss, mask loss, and prediction loss) for joint training. By encompassing the capabilities of various methods, our model learns item representations across different augmented graph views to achieve better performance and effectively mitigate interaction noise and sparsity. In addition, we add a small proportion of random uniform noise to item representations, making the item representations more uniform and mitigating the inherent popularity bias in interaction records. We conduct extensive experiments on three publicly available benchmark datasets to evaluate our model. The results demonstrate that our approach achieves state-of-the-art performance compared to 14 other competitive methods: the hit rate (HR) improved by over 14.39%, and the normalized discounted cumulative gain (NDCG) increased by over 18.67%.
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Purpose: The purpose of this retrospective study was to analyze the imaging and pathological features, treatment, and prognosis of patients with primary intraventricular lymphomas (PIL) in order to enhance physicians' understanding of the diagnosis and treatment of PIL. Methods: A retrospective analysis was conducted on 13 cases of PIL that were hospitalized in our institution. Clinical and imaging data of the patients were collected and compared with the pathology data to summarize and analyze the qualitative diagnostic value of magnetic resonance (MR) features. Results: Among the enrolled patients, there were nine males and four females, with an average age of (56 ± 9.0) years. The major clinical features observed in PIL patients were headache and dizziness. All 13 patients underwent plain and contrast-enhanced MR scans, revealing multiple foci in 7 cases and single foci in 6 cases. The lesions were located in the lateral ventricle in 10 cases, the third ventricle in 4 cases, and the fourth ventricle in 4 cases. Plain MR scans demonstrated an isointense or slightly hypointense signal on T1-weighted imaging (T1WI) and an isointense or slightly hyperintense signal on T2-weighted imaging (T2WI). Contrast-enhanced scans showed uniform and consistent enhancement of the tumors. Surgical treatment was performed in all patients, and postoperative pathology confirmed the presence of diffuse large B-cell lymphoma. Conclusions: PIL exhibits specific imaging and pathological features, with diffuse large B-cell lymphoma being the main pathological type. Pathological examination and immunophenotype analysis serve as the gold standards for PIL diagnosis.
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Single-atom (SA) catalysts with nearly 100% atom utilization have been widely employed in electrolysis for decades, due to the outperforming catalytic activity and selectivity. However, most of the reported SA catalysts are fixed through the strong bonding between the dispersed single metallic atoms with nonmetallic atoms of the substrates, which greatly limits the controllable regulation of electrocatalytic activity of SA catalysts. In this work, Pt-Ni bonded Pt SA catalyst with adjustable electronic states was successfully constructed through a controllable electrochemical reduction on the coordination unsaturated amorphous Ni(OH)2 nanosheet arrays. Based on the X-ray absorption fine structure analysis and first-principles calculations, Pt SA was bonded with Ni sites of amorphous Ni(OH)2, rather than conventional O sites, resulting in negatively charged Ptδ-. In situ Raman spectroscopy revealed that the changed configuration and electronic states greatly enhanced absorbability for activated hydrogen atoms, which were the essential intermediate for alkaline hydrogen evolution reaction. The hydrogen spillover process was revealed from amorphous Ni(OH)2 that effectively cleave the H-O-H bond of H2O and produce H atom to the Pt SA sites, leading to a low overpotential of 48 mV in alkaline electrolyte at -1000 mA cm-2 mg-1Pt, evidently better than commercial Pt/C catalysts. This work provided new strategy for the controllable modulation of the local structure of SA catalysts and the systematic regulation of the electronic states.
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Background and objectives: The neutrophil-to-lymphocyte ratio (NLR) is a widely recognized marker of inflammation in peripheral blood. However, its specific role in neuronal intranuclear inclusion disease (NIID) has not been reported. This study aims to investigate the relationship between NIID and NLR. Methods: A multicenter database was collected, including 157 NIID patients from seven hospitals (The Affiliated Hospital of Xuzhou Medical University, Yantai Yuhuangding Hospital, Tengzhou Central People's Hospital,The Affiliated Brain Hospital of Nanjing Medical University, Liaocheng People's Hospital,The Second Hospital of Shandong University, Inner Mongolia People's Hospital, Xuanwu Hospital Capital Medical University,The First Affiliated Hospital of USTC), along with 157 age- and gender-matched healthy control subjects. White blood cell counts (including neutrophils, lymphocytes, monocytes, eosinophils, and basophils) were obtained, and the NLR was calculated. Additionally, cognitive impairment was assessed using clinical evaluation scores. Results: NIID patients exhibited significantly higher NLR values compared to the healthy control group (p < 0.001). The plasma NLR levels in NIID patients showed a weak positive correlation with disease duration (r = 0.219, p = 0.016). However, no significant correlations were found between NLR and age of onset or cognitive impairment (p > 0.05). Conclusion: There is a significant association between NLR and NIID, suggesting a potential role of peripheral blood inflammation in the pathogenesis of NIID.
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Objectives This study aimed to identify the association between lactate dehydrogenase (LDH) levels and 30-day mortality in patients with intracranial hemorrhage (ICH) with acute leukemia during the induction phase. Methods This cohort study included patients with acute leukemia with ICH during induction. We evaluated serum LDH levels upon admission. Multivariable Cox regression analyzed the LDH 30-day mortality association. Interaction and stratified analyses based on factors like age, sex, albumin, white blood cell count, hemoglobin level, and platelet count were conducted. Results We selected 91 patients diagnosed with acute leukemia and ICH. The overall 30-day mortality rate was 61.5%, with 56 of the 91 patients succumbing. Among those with LDH levels ≥ 570 U/L, the mortality rate was 74.4% (32 out of 43), which was higher than the 50% mortality rate of the LDH < 570 U/L group (24 out of 48) ( p = 0.017). In our multivariate regression models, the hazard ratios and their corresponding 95% confidence intervals for Log2 and twice the upper limit of normal LDH were 1.27 (1.01, 1.58) and 2.2 (1.05, 4.58), respectively. Interaction analysis revealed no significant interactive effect on the relationship between LDH levels and 30-day mortality. Conclusions Serum LDH level was associated with 30-day mortality, especially in patients with LDH ≥ 570 U/L.