Magnetic superhydrophobic cellulose nanofibril based aerogel with rope-ladder like structure incorporating both superelasticity and excellent oil absorption.

Achieving an equilibrium between exceptional oil absorption and remarkable elasticity has emerged as a formidable challenge for magnetic porous materials designed for oil absorption. Here, we propose an original, magnetic and superhydrophobic cellulose nanofibril (CNF) based aerogel system with a rope-ladder like skeleton by to greatly improve the issue. Within this system, CNF as the skeleton was combined with multiwalled carbon nanotubes (MWCNT)@Fe3O4 as the magnetic and enhanced component, both methyltrimethoxysilane (MTMS) and acetonitrile-extracted lignin (AEL) as the soft-hard associating constituents. The resultant CNF based aerogel shows a rope-ladder like pore structure to contribute to high elasticity and excellent oil absorption (28.34-61.09 g/g for various oils and organic solvents) under the synergistic effect of Fe3O4@MWCNT, AEL and MTMS, as well as good specific surface area (27.97 m2/g), low density (26.4 mg/cm3). Notably, despite the introduced considerable proportion (0.5 times of mass-CNF) of Fe3O4@MWCNT, the aerogel retained an impressive compression-decompression rate (88%) and the oil absorption efficiency of above 87% for various oils due to the soft-hard associating structure supported by both MTMS and AEL. This study provides a prospective strategy to balance between high elasticity and excellent oil absorption of CNF based aerogel doping inorganic particles.

Preparation of highly elastic superhydrophobic CNF/Fe3O4 based materials modified in aqueous phase for oil-water separation.

Magnetic superhydrophobic materials have broad application prospect in oil-water separation. In this study, a magnetic and superhydrophobic aerogel with lamellar structure was successfully prepared using cellulose nanofibrils (CNF) as the skeleton, Fe3O4 as the magnetic ion, 1H, 1H, 2H, 2H trialkylfluorooctane triethoxysilane (FS) and 3-(2-aminoethyl amino)-propyl trimethoxysilane (AS) as the combined modifier. The prepared aerogel shows lower density (38.63 mg/cm3), excellent magnetic (15.13 emu/g), high elasticity and good oil sorption properties (21 g/g). In addition, FS/AS also exhibits excellent mechanical properties and superhydrophobic ability (water contact angle (WCA) of 151.9 ± 1.4°), as it provides sufficient toughness and low surface energy for the layer-branch structure. It should be noted that the entire preparation process is carried out in the aqueous phase, without the use of any organic solvents, providing a green oil-water separation strategy.

Synergistic enhancement of electrocatalytic nitroarene hydrogenation over Mo2C@MoS2 heteronanorods with dual active-sites.

Electrocatalytic hydrogenation (ECH) enables the sustainable production of chemicals under ambient conditions, in which catalysts catering for the different chemisorption of reactants/intermediates are desired but still challenging. Here, Mo2C@MoS2 heteronanorods with dual active-sites are developed to accomplish efficient nitroarene ECH according to our theoretical prediction that the binding of atomic H and nitro substrates would be synergistically strengthened on Mo2C-MoS2 interfaces. They afford high faradaic efficiency (>85%), yield (>78%) and selectivity (>99%) for the reduction of 4-nitrostyrene (4-NS) to 4-vinylaniline (4-VA) in neutral electrolytes, outperforming not only the single-component counterparts of Mo2C nanorods and MoS2 nanosheets, but also recently reported noble-metals. Accordingly, in situ Raman spectroscopy combined with electrochemical tests clarifies the rapid ECH of 4-NS on Mo2C-MoS2 interfaces due to the facilitated elementary steps, quickly refreshing active sites for continuous electrocatalysis. Mo2C@MoS2 further confirms efficient and selective ECH toward functional anilines with other well-retained reducible groups in wide substrate scope, underscoring the promise of dual-site engineering for exploring catalysts.

Enhancing Low-Potential Electrosynthesis of 2,5-Furandicarboxylic Acid on Monolithic CuO by Constructing Oxygen Vacancies.

Electrosynthesis of 2,5-furandicarboxylic acid (FDCA) from the biomass-derived 5-hydroxymethylfurfural (HMF) is one of the most potential means to produce a bioplastic monomer. Copper oxide (CuO) catalyst shows promising prospects due to its high surface activity, conductivity, and stability, but relatively poor capability of oxygen evolution; however, the weak adsorption of substrates and the lack of facile synthetic strategies largely restrict its practical application. Here, a novel facile in situ method, alternate cycle voltammetry (denoted as c) and potentiostatic electrolysis (denoted as p), was proposed to prepare a monolithic cpc-CuO/Cu-foam electrocatalyst. Along with the increment of CuO and its surficial oxygen vacancies (OV), the FDCA yield, productivity, and Faradaic efficiency can reach up to ∼98.5%, ∼0.2 mmol/cm2, and ∼94.5% under low potential of 1.404 VRHE. Such an efficient electrosynthesis system can be easily scaled up to afford pure FDCA powders. In a combinatory analysis via electron paramagnetic resonance spectroscopy, H2 temperature-programmed reduction, open circuit potential, infrared spectroscopy, zeta potential, electrochemical measurement, and theoretical calculation, we found that the CuO was the active phase and OV generated on CuO surface can dramatically enhance the adsorption of *HMF and *OH (* denotes an active site), accounting for its superior FDCA production. This work offers an excellent paradigm for enhancing biomass valorization on CuO catalysts by constructing surficial defects.

JAK/STAT in leukemia: a clinical update.

Over the past three decades, considerable efforts have been expended on understanding the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway in leukemia, following the identification of the JAK2V617F mutation in myeloproliferative neoplasms (MPNs). The aim of this review is to summarize the latest progress in our understanding of the involvement of the JAK/STAT signaling pathway in the development of leukemia. We also attempt to provide insights into the current use of JAK/STAT inhibitors in leukemia therapy and explore pertinent clinical trials in this field.

MFG-E8 promotes M2 polarization of macrophages and is associated with poor prognosis in patients with gastric cancer.

Background: Milk Fat Globule-Epidermal Growth Factor 8 (MFG-E8) has been reported to play an oncogenic role in a variety of tumors. However, its involvement in gastric cancer (GC) development has not been described. Methods: The cancer genome atlas (TCGA) and the gene expression omnibus database (GEO) databases were used to analyze the expression of MFG-E8 in GC. These findings were further validated using immunohistochemistry (IHC) and western blotting assay (WB). Kaplan-Meier method, univariate logistic regression, and Christopher Cox regression were used to study the relationship between MFG-E8 and clinical pathology. In addition, the potential signaling pathways involved in MFG-E8 and its potential correlation with levels of immune cell infiltration were investigated. Finally, the biological function of MFG-E8 in GC cells was revealed. Results: MFG-E8 was highly expressed in GC patients and cells, and the high level of MFG-E8 was associated with poor overall survival (OS). KEGG analysis indicated that MFG-E8 may play an important role in the cAMP signaling pathway. The expression of MFG-E8 was positively correlated with the infiltration of M2 macrophages. The patients with high MFG-E8 were easy to develop chemotherapy resistance. Furthermore, the knockdown of MFG-E8 significantly inhibited the proliferation and invasion of GC cells. Conclusion: MFG-E8 in GC may serve as a prognostic marker and a potential immunotherapy target for GC.

Directional Electrosynthesis of Adipic Acid and Cyclohexanone by Controlling the Active Sites on NiOOH.

Dicarboxylic acids and cyclic ketones, such as adipic acid (AA) and cyclohexanone (CHN), are essential compounds for the chemical industry. Although their production by electrosynthesis using electricity is considered one of the most promising strategies, the application of such processes has been hampered by a lack of efficient catalysts as well as a lack of understanding of the mechanism. Herein, a series of monolithic msig/ea-NiOOH-Ni(OH)2/NF were prepared by means of self-dissolution of metal matrix components, interface growth, and electrochemical activation (denoted as msig/ea). The as-synthesized catalysts have three-dimensional cuboid-like structures formed by interconnecting nanosheets composed of NiOOH. By theoretically guided regulation of the amounts of Ni3+ and oxygen vacancies (OV), a 96.5% yield of CHN from cyclohexanol (CHA) dehydrogenation and a 93.6% yield of AA from CHN oxidation were achieved. A combined experimental and theoretical study demonstrates that CHA dehydrogenation and CHN oxidation were promoted by the formation of Ni3+ and the peroxide species (*OOH) on OV. This work provides a promising approach for directional electrosynthesis of high-purity chemicals with in-depth mechanistic insights.

Influence of bio-coupling agent on interfacial interlocking compatibility and toughness of ultrafine bamboo charcoal/polylactic acid composite film.

Applications for polylactic acid (PLA) are significantly impacted by its poor mechanical properties and lack of thermal stability. The goal of this work is to bridge the gap of poor compatibility among the components and enhance their interface interlocking capability to improve the toughness and thermal stability. Ultrafine bamboo charcoal (UFBC) was treated through deep eutectic solvent (DES) method to deposit sodium lignosulfonate (LS) on its surface. LS was used with PLA as a bio-coupling agent to create an eco-friendly PLA composite film with a wide range of characteristics. Benefiting from the penetration of PLA to the internal pores in UFBC, the resultant L-UFBC/PLA film has a good mechanical interlocking structure. Ls can increase the compatibility and strengthen the interface interlocking capability through DES method, which greatly improves the mechanical properties of the system. In comparison to pure PLA one, the elongation at break was 136.24 % greater, and the crystallinity (Xc) increased from 1.09 % to 3.33 %. Furthermore, the thermal stability of the system was also improved, and the residual at 600 °C rose by 4.83 %. These characteristics offer the prepared L-UFBC/PLA film a wide range of potential applications in the packaging, medical, agricultural, and other sectors.

Activating Commercial Nickel Foam to a Highly Efficient Electrocatalyst for Oxygen Evolution Reaction through a Three-Step Surface Reconstruction.

It is highly desired to directly use commercial nickel foam (CNF) as an electrocatalyst for the oxygen evolution reaction (OER) via simple surface reconstruction. In our research, a simple three-step preactivation process was proposed to reconstruct CNF as an efficient OER catalyst, including calcination, high-voltage treatment, and immersing in electrolyte. The optimal CNF after three-step activation reaches an excellent OER performance of 228 and 267 mV at η10 and η100 in alkaline media and can tolerate long-term tests under a large current density of 500 mA·cm-2. The promotion of each step was explored. The calcination step leads to a reconstructive surficial morphology with an enlarged active surface, providing a prerequisite for the following construction steps. The high-voltage treatment changes the valence of surface Ni species, generating phases with higher catalytic activity, and the immersing process introduces Fe heteroatoms into the surface of CNF, boosting the catalytic performance of CNF through Ni-Fe interactions. This research provides a simple method of making high-performance catalysts with accessible nickel foam, a potential for large-scale application in practical industry, and new thinking for the manipulation of Ni-based catalysts.

Bioinformatic Analysis of the Mechanism of Action of COL3A1 in Pan-Cancer and Design of Specific Inhibitors for Its Conformation.

In this study, we investigated the mechanism of action of COL3A1 in various types of cancers by bioinformatics analysis and designed some specific inhibitors aimed at the treatment of this gene. We found that COL3A1 was highly expressed in several cancer types and correlated with tumor progression and prognosis. Through systems biology analysis, we identified a central role for COL3A1 in cancer development, including cell proliferation, metastasis and invasion. We also used molecular dynamics simulations and drug screening techniques to design anticancer drugs with potential COL3A1 inhibitory functions. These results provide a strong rationale for the development and use of COL3A1 as a therapeutic target.

Simultaneous identification of strong and weak interactions with Pauli energy, Pauli potential, Pauli force, and Pauli charge.

Strong and weak interatomic interactions in chemical and biological systems are ubiquitous, yet how to identify them on a unified theoretical foundation is still not well established. Recently, we proposed employing Pauli energy-based indexes, such as strong covalent interaction and bonding and noncovalent interaction indexes, in the framework of density functional theory for the purpose. In this work, we extend our previous theoretical work by directly employing Pauli energy, Pauli potential, Pauli force, and Pauli charge to simultaneously identify both strong covalent bonding and weak noncovalent interactions. Our results from this work elucidate that using their signature isosurfaces, we can identify different types of interactions, either strong or weak, including single, double, triple, and quadruple covalent bonds, ionic bond, metallic bond, hydrogen bonding, and van der Waals interaction. We also discovered strong linear correlations between Pauli energy derived quantities and different covalent bond orders. These qualitative and quantitative results from our present study solidify the viewpoint that a unified approach to simultaneously identify both strong and weak interactions is possible. In our view, this work signifies one step forward towards the goal of establishing a density-based theory of chemical reactivity in density functional theory.

Does dual-layer spectral detector CT provide added value in predicting spread through air spaces in lung adenocarcinoma? A preliminary study.

OBJECTIVES: To examine the predictive value of dual-layer spectral detector CT (DLCT) for spread through air spaces (STAS) in clinical lung adenocarcinoma. METHODS: A total of 225 lung adenocarcinoma cases were retrospectively reviewed for demographic, clinical, pathological, traditional CT, and spectral parameters. Multivariable logistic regression analysis was carried out based on three logistic models, including a model using traditional CT features (traditional model), a model using spectral parameters (spectral model), and an integrated model combining traditional CT and spectral parameters (integrated model). Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to assess these models. RESULTS: Univariable analysis showed significant differences between the STAS and non-STAS groups in traditional CT features, including nodule density (p < 0.001), pleural indentation types (p = 0.006), air-bronchogram sign (p = 0.031), the presence of spiculation (p < 0.001), long-axis diameter of the entire nodule (LD) (p < 0.001), and consolidation/tumor ratio (CTR) (p < 0.001). Multivariable analysis revealed that LD > 20 mm (odds ratio [OR] = 2.271, p = 0.025) and CTR (OR = 24.208, p < 0.001) were independent predictors in the traditional model, while electronic density (ED) in the venous phase was an independent predictor in the spectral (OR = 1.062, p < 0.001) and integrated (OR = 1.055, p < 0.001) models. The area under the curve (AUC) for the integrated model (0.84) was the highest (spectral model, 0.83; traditional model, 0.80), and the difference between the integrated and traditional models was statistically significant (p = 0.015). DCA showed that the integrated model had superior clinical value versus the traditional model. CONCLUSIONS: DLCT has added value for STAS prediction in lung adenocarcinoma. CLINICAL RELEVANCE STATEMENT: Spectral CT has added value for spread through air spaces prediction in lung adenocarcinoma so may impact treatment planning in the future. KEY POINTS: • Electronic density may be a potential spectral index for predicting spread through air spaces in lung adenocarcinoma. • A combination of spectral and traditional CT features enhances the performance of traditional CT for predicting spread through air spaces.

Chlorine-mediated electrodeposition of hierarchical and hydrophobic copper electrocatalysts for efficient CO2 electroreduction to ethylene.

Hierarchical Cu dendrites fabricated via Cl-mediated electrodeposition afford high C2H4 efficiency (58% faradaic efficiency at -0.9 V vs. RHE) for CO2 electroreduction thanks to not only the optimal hydrophobicity/aerophilicity, but also the dominant distribution of active (100) and (110) facets.

Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma.

OBJECTIVES: To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. METHODS: A total of 542 patients with clinical stage 0-I peripheral LUAD and with preoperative CT data of 1-mm slice thickness were included. Maximal solid size on axial image (MSSA) was evaluated by two chest radiologists. MSSA, volume of solid component (SV), and mass of solid component (SM) were evaluated by DL. Consolidation-to-tumor ratios (CTRs) were calculated. For ground glass nodules (GGNs), solid parts were extracted with different density level thresholds. The prognosis prediction efficacy of DL was compared with that of manual measurements. Multivariate Cox proportional hazards model was used to find independent risk factors. RESULTS: The prognosis prediction efficacy of T-staging (TS) measured by radiologists was inferior to that of DL. For GGNs, MSSA-based CTR measured by radiologists (RMSSA%) could not stratify RFS and OS risk, whereas measured by DL using 0HU (2D-AIMSSA0HU%) could by using different cutoffs. SM and SV measured by DL using 0 HU (AISM0HU% and AISV0HU%) could effectively stratify the survival risk regardless of different cutoffs and were superior to 2D-AIMSSA0HU%. AISM0HU% and AISV0HU% were independent risk factors. CONCLUSION: DL algorithm can replace human for more accurate T-staging of LUAD. For GGNs, 2D-AIMSSA0HU% could predict prognosis rather than RMSSA%. The prediction efficacy of AISM0HU% and AISV0HU% was more accurate than of 2D-AIMSSA0HU% and both were independent risk factors. CLINICAL RELEVANCE STATEMENT: Deep learning algorithm could replace human for size measurements and could better stratify prognosis than manual measurements in patients with lung adenocarcinoma. KEY POINTS: • Deep learning (DL) algorithm could replace human for size measurements and could better stratify prognosis than manual measurements in patients with lung adenocarcinoma (LUAD). • For GGNs, maximal solid size on axial image (MSSA)-based consolidation-to-tumor ratio (CTR) measured by DL using 0 HU could stratify survival risk than that measured by radiologists. • The prediction efficacy of mass- and volume-based CTRs measured by DL using 0 HU was more accurate than of MSSA-based CTR and both were independent risk factors.

Promoting Amination of Furfural to Furfurylamine by Metal-Support Interactions on Pd/MoO3-x Catalysts.

The reductive amination of carbonyl compounds is one of the most straightforward protocols to construct C-N bonds, but highly desires active and selective catalysts. Herein, Pd/MoO3-x catalysts are proposed for furfural amination, in which the interactions between Pd nanoparticles and MoO3-x supports can be easily ameliorated by varying the preparation temperature toward efficient catalytic turnover. Thanks to the synergistic cooperation of MoV -rich MoO3-x and highly dispersed Pd, the optimal catalysts afford the high yield of furfurylamine (84 %) at 80 °C. Thereinto, MoV species not only acts as the acidic promoter to facilitate the activation of carbonyl groups, but also interacts with Pd nanoparticles to promote the subsequent hydrogenolysis of Schiff base N-furfurylidenefurfurylamine and its germinal diamine. The good efficiency of Pd/MoO3-x within a broad substrate scope further highlights the key contribution of metal-support interactions to the refinery of biomass feedstocks.

CT-based decision tree model for predicting EGFR mutation status in synchronous multiple primary lung cancers.

Background: The current study aimed to construct a computed tomography (CT)-based decision tree algorithm (DTA) model to predict the epidermal growth factor receptor (EGFR) mutation status in synchronous multiple primary lung cancers (SMPLCs). Methods: The demographic and CT findings of 85 patients with molecular profiling for surgically resected SMPLCs were reviewed retrospectively. Least absolute shrinkage and selection operator (LASSO) regression was used to select the potential predictors of EGFR mutation, and a CT-DTA model was developed. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to assess the performance of this CT-DTA model. Results: The CT-DTA model was applied to predict the EGFR mutant that had ten binary split, of which eight parameters to accurately categorize the lesions as follows: the presence of bubble-like vacuole sign (19.4% importance in the development of the model), presence of air bronchogram sign (17.4% importance), smoking status (15.7% importance), types of the lesions (14.8% importance), histology (12.6% importance), presence of pleural indentation sign (7.6% importance), gender (6.9% importance), and presence of lobulation sign (5.6% importance). The ROC analysis achieved an area under the curve (AUC) of 0.854. Multivariate logistic regression analysis demonstrated that this CT-DTA model was an independent predictor of EGFR mutation (P<0.001). Conclusions: CT-DTA model is a simple tool to predict the status of EGFR mutation in SMPLC patients and could be considered for treatment decision-making.

Roughness-Dependent Electro-Reductive Coupling of Nitrobenzenes and Aldehydes on Copper Electrodes.

The electro-reductive coupling of nitro and carbonyl compounds enables a facile, environmentally friendly and energy benign transformation toward value-added nitrones or imines, but the selectivity is still challenging. Here, the surface roughness of Cu electrodes is introduced for the first time as the determinant to switch products from nitrones to imines owing to the controllable reduction of nitroarenes to hydroxylamines or amines on tailored CuI /Cu0 interfaces. The roughness-dependent selectivity, that is the decrease of nitrones and the increase of imines with enhanced roughness, is visible in the electro-reductive coupling of nitrobenzene and furfural. Thus, the high selectivity of nitrone (98 %) and imine (80 %) can be achieved on a surface smooth Cu foil and the one electrochemically roughened in the presence of I- , respectively. Such roughness-dependence of nitrone/imine selectivity on Cu electrodes is further verified in a wide substrate scope, highlighting the promise of surface/interfacial engineering for electrochemical synthesis.

Promoted electrocatalytic hydrogenation of furfural in a bi-phasic system.

The promoted electrocatalytic hydrogenation of biomass-derived furfural to 2-methylfuran is for the first time identified in a water/oil bi-phasic system, in which the oil phase can quickly separate hydrophobic products from the electrode/electrolyte interfaces, resulting in a beneficial equilibrium toward hydrodeoxygenation.

A Novel Prognostic Score Based on Multiple Quantitative Parameters of Chest CT for Patients with Synchronous Multiple Primary Lung Cancer: Is Solid Component Size a Better Prognostic Indicator?

BACKGROUND: There is no simple and definitive way to predict the prognosis of synchronous multiple primary lung cancer (SMPLC). In this study, we developed a clinical prognostic score for predicting the survival of patients with SMPLC. PATIENTS AND METHODS: This study included 206 patients with SMPLC between 2011 and 2020 at three hospitals. Kaplan-Meier analysis was used to determine the optimal cutoff values for the quantitative chest computed tomography (CT) parameters. Multivariable Cox proportional hazards regression was carried out to identify independent prognostic factors for predicting overall survival (OS) and disease-free survival (DFS). The time-dependent receiver operating characteristic curve was analyzed to evaluate the prognostic performance. RESULTS: A CT-based prognostic score (CTPS) comprising six chest CT parameters was developed. Compared with T stage, CTPS had a higher prediction accuracy for OS and DFS. All C-indices of the model reached a satisfactory level in both the development and validation cohorts. Significant differences in the OS and DFS curves were observed when the patients were stratified into different risk groups. The high-risk group (CTPS of 5-6) had poorer survival than the low-risk group (CTPS of 0-4). CONCLUSIONS: The developed CTPS and the corresponding risk stratification system are valid for predicting the survival of patients with SMPLC.