α-MnO2 Cathode with Oxygen Vacancies Accelerated Affinity Electrolyte for Dual-Ion Co-Encapsulated Aqueous Aluminum Ion Batteries.

Aluminum batteries (ABs) are identified as one of the most promising candidates for the next generation of large-scale energy storage elements because of their efficient three-electron reaction. Compared to ionic electrolytes, aqueous aluminum-ion batteries (AAIBs) are considered safer, less costly, and more environmentally friendly. However, considerable cycling performance is a key issue limiting the development of AAIBs. Stable, efficient, and electrolyte-friendly cathodes are most desirable for AAIBs. Herein, a rod-shaped defect-rich α-MnO2 is designed as a cathode, which is capable to deliver high performance with stable cycling for 180 cycles at 500 mA g-1 and maintains a discharge specific capacity of ≈100 mAh g-1. In addition, the infiltrability simulation is effectively utilized to corroborate the rapid electrochemical reaction brought about by the defective mechanism. With the formation of oxygen vacancies, the dual embedding of protons and metal ions is activated. This work provides a brand-new design for the development and characterization of cathodes for AAIBs.

Correlating the Experimentally Determined CO Adsorption Enthalpy with the Electrochemical CO Reduction Performance on Cu Surfaces.

CO binding energy has been widely employed as a descriptor for effective catalysts in the electrochemical CO2 and CO reduction reactions (CO(2) RR), however, it has yet to be determined experimentally at electrochemical interfaces due to the lack of suitable techniques. In this work, we developed a method to determine the standard adsorption enthalpy of CO on Cu surfaces with quantitative surface enhanced infrared absorption spectroscopy. On dendritic Cu at -0.75 V vs. SHE, the standard adsorption enthalpy, entropy and Gibbs free energy were determined to 1.5±0.5 kJ mol-1 , ≈37.9±13.4 J/(mol K), and ≈-9.8±4.0 kJ mol-1 , respectively. Comparison of the standard adsorption enthalpy of oxide-derived Cu and dendritic Cu, as well as their CORR activities, suggests the presence of stronger binding sites on OD Cu, which could favor multicarbon products. The method developed in this work will help establish the correlation between the CO binding energy and the CO(2) RR activity.

Cobalt-promoted synthesis of sulfurated oxindoles via radical annulation of N-arylacrylamides with disulfides.

An efficient radical annulation of N-arylacrylamides with disulfides is developed for the synthesis of sulfurated oxindoles. The reaction occurs in a facile manner using CoBr2 as both an initiator and a promoter for the first time and (NH4)2S2O8 as the oxidant. By controlling the CoBr2/(NH4)2S2O8 ratio, a wide range of sulfurated and brominated/sulfurated oxindoles are selectively prepared in good to excellent yields. The present protocol is simple and highly atom economical, and can tolerate a broad range of substrates.

The nonlinear dynamics and fluctuations of mRNA levels in cell cycle coupled transcription.

Gene transcription is a noisy process, and cell division cycle is an important source of gene transcription noise. In this work, we develop a mathematical approach by coupling transcription kinetics with cell division cycles to delineate how they are combined to regulate transcription output and noise. In view of gene dosage, a cell cycle is divided into an early stage [Formula: see text] and a late stage [Formula: see text]. The analytical forms for the mean and the noise of mRNA numbers are given in each stage. The analysis based on these formulas predicts precisely the fold change r* of mRNA numbers from [Formula: see text] to [Formula: see text] measured in a mouse embryonic stem cell line. When transcription follows similar kinetics in both stages, r* buffers against DNA dosage variation and r* ∈ (1, 2). Numerical simulations suggest that increasing cell cycle durations up-regulates transcription with less noise, whereas rapid stage transitions induce highly noisy transcription. A minimization of the transcription noise is observed when transcription homeostasis is attained by varying a single kinetic rate. When the transcription level scales with cellular volume, either by reducing the transcription burst frequency or by increasing the burst size in [Formula: see text], the noise shows only a minor variation over a wide range of cell cycle stage durations. The reduction level in the burst frequency is nearly a constant, whereas the increase in the burst size is conceivably sensitive, when responding to a large random variation of the cell cycle durations and the gene duplication time.

Jatrorrhizine Hydrochloride Suppresses RANKL-Induced Osteoclastogenesis and Protects against Wear Particle-Induced Osteolysis.

Wear particle-induced aseptic prosthetic loosening is a major complication associated with total joint arthroplasty (TJA). A growing body of evidence suggests that receptor activator of nuclear factor κ-B ligand (RANKL)-stimulated osteoclastogenesis and bone resorption are responsible for peri-implant loosening. Thus, agents which attenuate excessive osteoclast differentiation and function have been considered to offer therapeutic potential for prolonging the life of TJA implants. Jatrorrhizine hydrochloride (JH), a major protoberberine alkaloid isolated from the traditional Chinese herb Coptis chinensis, has been reported to have antimicrobial, antitumor, and antihypercholesterolemic and neuroprotective activities. However, its effects on osteoclast biology remain unknown. Here, we found that JH inhibited RANKL-induced osteoclast formation and bone resorption in vitro and exerted protection against titanium (Ti) particle-induced osteolysis in vivo. Biochemical analysis demonstrated that JH suppressed RANKL-induced activation of MAPKs (p38 and ERK) which down-regulated the production of NFATc1 and NFATc1-regulated osteoclastic marker genes, such as TRAP, CTR and CTSK. Collectively, our findings suggest that JH may be a promising anti-osteoclastogenesis agent for treating periprosthetic osteolysis or other osteoclast-related osteolytic diseases.

The nonlinear dynamics and fluctuations of mRNA levels in cross-talking pathway activated transcription.

Gene transcription is a stochastic process, and is often activated by multiple signal transduction pathways. In this work, we study gene transcription activated randomly by two cross-talking pathways, with the messenger RNA (mRNA) molecules being produced in a simple birth and death process. We derive the analytical formulas for the mean and the second moment of mRNA copy numbers and characterize the nature of transcription noise. We find that the stationary noise strength Φ is close to its baseline limit 1 when the mRNA level is high due to strong activation or stable transcription, or the mRNA level is low due to unstable transcription or ineffective mRNA production. If Φ stays well above 1, then the gene is infrequently active but mRNAs are accumulated rapidly once it is active. In this case, the system generates a transcriptional bursting, and the mean mRNA level peaks at a finite time. By examining the nonlinear dependance of Φ on transcriptional efficiency, we show that the maximum noise strength is attained only when the gene is silent in the majority of cells as observed in recent experiments. By comparing the current findings with our previous results in sequential pathway model, we come up with a profound conclusion that parallel, cross-talking pathways tend to increase transcription noise, whereas sequential pathways tend to reduce transcription noise. A further study on gene transcription activated by entangling pathways may help us reveal the subtle connection between the characteristics of transcription noise and the topology of genetic network.

Can feature structure improve model's precision? A novel prediction method using artificial image and image identification.

Objectives: This study aimed to develop an approach to enhance the model precision by artificial images. Materials and Methods: Given an epidemiological study designed to predict 1 response using f features with M samples, each feature was converted into a pixel with certain value. Permutated these pixels into F orders, resulting in F distinct artificial image sample sets. Based on the experience of image recognition techniques, appropriate training images results in higher precision model. In the preliminary experiment, a binary response was predicted by 76 features, the sample set included 223 patients and 1776 healthy controls. Results: We randomly selected 10 000 artificial sample sets to train the model. Models' performance (area under the receiver operating characteristic curve values) depicted a bell-shaped distribution. Conclusion: The model construction strategy developed in the research has potential to capture feature order related information and enhance model predictability.

Dual-Salt Mixed Electrolyte for High Performance Aqueous Aluminum Batteries.

A dual-salt electrolyte with 5 M Al(OTF)3 and 0.5 M LiOTF is proposed for aqueous aluminum batteries, which can effectively prevent the corrosion caused by the hydrogen evolution reaction. With the addition of LiOTF in the electrolyte, the solvation phenomenon has changed with the coordination mode of Al3+ conversion from an all octahedral structure to a mixed octahedral and tetrahedral structure. This change can reduce the hydrogen bond between water molecules, which will minimize the occurrence of hydrogen evolution reactions. Moreover, the new electrolyte improves the cycle life of the battery. With MnO as the cathode, 2.1 V high charging platform and 1.5 V high discharge platform can be obtained. The electrochemical stability window (ESW) has been improved to 3.8 V. The first cycle capacity is up to 437 mAh g-1, which can be maintained at 103 mAh g-1 after 100 cycles. This work provides solutions for the future development of electrolyte for aqueous aluminum batteries.

Design, Synthesis, Formulation, and Bioevaluation of Trisubstituted Triazines as Highly Selective mTOR Inhibitors for the Treatment of Human Breast Cancer.

The aberrant activation of the PI3K/mTOR signaling pathway is implicated in various human cancers. Thus, the development of inhibitors targeting mTOR has attracted considerable attention. In this study, we used a structure-based drug design strategy to discover a highly potent and kinase-selective mTOR inhibitor 24 (PT-88), which demonstrated an mTOR inhibitory IC50 value of 1.2 nM without obvious inhibition against another 195 kinases from the kinase profiling screening. PT-88 displayed selective inhibition against MCF-7 cells (IC50: 0.74 µM) with high biosafety against normal cells, in which autophagy induced by mTOR inhibition was implicated. After successful encapsulation in a lipodisc formulation, PT-88 demonstrated favorable pharmacokinetic and biosafety profiles and exerted a large antitumor effect in an MCF-7 subcutaneous bearing nude mice model. Our study shows the discovery of a highly selective mTOR inhibitor using a structure-based drug discovery strategy and provides a promising antitumor candidate for future study and development.

Self-Aggregated Nanoscale Metal-Organic Framework for Targeted Pulmonary Decorporation of Uranium.

The limited availability of effective agents for removing actinides from the lungs significantly restricts the effectiveness of medical treatments for nuclear emergencies. Inhalation is the primary route of internal contamination in 44.3% of actinide-related accidents, leading to the accumulation of radionuclides in the lungs and resulting in infections and potential tumor formation (tumorigenesis). This study focuses on the synthesis of a nanometal-organic framework (nMOF) material called ZIF-71-COOH, which is achieved by post-synthetic carboxyl functionalization of ZIF-71. The material demonstrates high and selective adsorption of uranyl, while also exhibiting increased particle size (≈2100 nm) when it aggregates in the blood, enabling passive targeting of the lungs through mechanical filtration. This unique property facilitates the rapid enrichment and selective recognition of uranyl, making nano ZIF-71-COOH highly effective in removing uranyl from the lungs. The findings of this study highlight the potential of self-aggregated nMOFs as a promising drug delivery system for targeted uranium decorporation in the lungs.

Temporal profile of gene transcription noise modulated by cross-talking signal transduction pathways.

Gene transcription is a central cellular process and is stochastic in nature. The stochasticity has been studied in real cells and in theory, but often for the transcription activated by a single signaling pathway at steady-state. As transcription of many genes is involved with multiple pathways, we investigate how the transcription efficiency and noise is modulated by cross-talking pathways. We model gene transcription as a renewal process for which the gene can be turned on by different pathways. We determine the transcription efficiency by solving a system of differential equations, and obtain the mathematical formula of the noise strength by the Laplace transform and standard techniques in renewal theory. Our numerical examples demonstrate that cross-talking pathways are capable of inducing more cells to transcribe than the steady-state level after a short time period of signal transduction, and creating exceedingly high stationary transcription noise strength. In contrast, it is shown that one signaling pathway alone is unable to do so. Very strikingly, it is observed that the noise strength varies gradually over most values of the system parameters, but changes abruptly over a narrow range in the neighborhoods of some critical parameter values.

Modulation of gene transcription noise by competing transcription factors.

Sequence specific transcription factors (TFs) are critical to ensuring that genes are transcribed in the right cell at the right time. Often, the gene promoter is flanked by multiple binding sites, some of which can be bound by different types of TFs in the cell. To investigate how the transcription noise is modulated by the competition of these TFs at their shared binding sites, we model gene transcription as a renewal process where the time spent in each transcription cycle is assumed to be independently and identically distributed. With the help of the elementary renewal theorem and the central limit theorem, we prove that the stationary noise strength Φ of transcription frequency equals the noise η (2) of the time spent in a single transcription cycle. Subsequent analysis shows that competitive TF binding could produce an unbounded spectrum of Φ, in sharp contrast to the estimate 1/3 ≤ Φ < for single binding pattern activated transcription. We predict several mechanisms by which genes could stay away from abnormally noisy transcription while living with multiple binding patterns. The most efficient one is to maintain a relatively long engaged time by transcription pausing, interrupting, or other means. Alternatively, high noise strength is prevented if all binding patterns activate transcription strongly. When some binding patterns activate transcription weakly, low noise strength is ensured if the binding pattern with the weakest activation strength is utilized frequently.

Uniqueness and stability of periodic solutions for an interactive wild and Wolbachia-infected male mosquito model.

We investigate a mosquito population suppression model, which includes the release of Wolbachia-infected males causing incomplete cytoplasmic incompatibility (CI). The model consists of two sub-equations by considering the density-dependent birth rate of wild mosquitoes. By assuming the release waiting period T is larger than the sexual lifespan T¯ of Wolbachia-infected males, we derive four thresholds: the CI intensity threshold sh∗, the release amount thresholds g∗ and c∗, and the waiting period threshold T∗. From a biological view, we assume sh>sh∗ throughout the paper. When g∗T∗, which is globally asymptotically stable. Our theoretical results are confirmed by numerical simulations.

Effective mitigation of gadolinium deposition using the bidentate hydroxypyridinone ligand Me-3,2-HOPO.

With the extensive usage of gadolinium-based contrast agents (GBCAs) in magnetic resonance imaging (MRI), gadolinium deposition has been observed in the brain, kidneys, liver, etc., and this is also closely related to the development of nephrogenic systemic fibrosis (NSF) in patients with renal dysfunction. Chelation, thereby promoting the elimination of deposited Gd(III), seems to be promising for alleviating these problems. Despite many ligands suitable for chelation therapy having been studied, the decorporation of transition metals (e.g. iron, copper, lead, etc.) and actinides (e.g. uranium, plutonium, etc.) has long been a primary concern, whereas the study of Gd(III) has been extremely limited. Due to their excellent metal binding abilities in vivo and therapeutic effects toward neurodegenerative diseases, bidentate hydroxypyridinone ligands are expected to be able to remove Gd(III) from the brain, kidneys, bones, and liver. Herein, the Gd(III) decorporation efficacy of a bidentate hydroxypyridinone ligand (Me-3,2-HOPO) has been evaluated. The complexation behavior between Me-3,2-HOPO and Gd(III) in solution and solid states was characterized with the assistance of potentiometric titration and X-ray diffraction techniques, respectively. Solution-based thermodynamic studies illustrate that the dominant species of complex between Gd(III) and Me-3,2-HOPO (HL) is GdL2+ (log ß120 = 11.8 (3)) at pH 7.4. The structure of the Gd-Me-3,2-HOPO crystal obtained from a room temperature reaction reveals the formation of a Gd(III) dimer that is chelated by four ligands as a result of metal ion hydration and ligand complexation. Cellular Gd(III) removal assays illustrate that Me-3,2-HOPO could effectively reduce final amounts of gadolinium by 77.6% and 66.1% from rat renal proximal tubular epithelial (NRK-52E) cells and alpha mouse liver 12 (AML-12) cells, respectively. Our current results suggest the potential of bidentate HOPO ligands as an effective approach to treat patients suffering from Gd(III) toxicity.

Boosting Simultaneous Uranium Decorporation and Reactive Oxygen Species Scavenging Efficiency by Lacunary Polyoxometalates.

The chemical toxicity and the oxidative stress induced by the internal exposure of uranium is responsible for the long-term adverse effect of in vivo contamination of uranium. An agent with simultaneous removal capability of uranium and excess reactive oxygen species (ROS) is highly desired. Herein, the lacunary Keggin-type polyoxometalate (POM) is demonstrated to selectively bind with uranyl ions in the presence of excess essential divalent ions and exhibits a compelling ROS scavenging efficiency of 78.8%. In vivo uranium decorporation assays illustrate the uranium sequestration efficiencies of 74.0%, 49.4%, and 37.1% from kidneys by prophylactic, prompt, and delayed administration of lacunary POM solution, respectively. The superior ROS quenching and uranium removal performance in comparison with all reported bifunctional agents endow lacunary polyoxometalates as novel agents to effectively protect people from injuries caused by the internal exposure of actinides.

Direct Conversion of Syngas to Light Olefins through Fischer-Tropsch Synthesis over Fe-Zr Catalysts Modified with Sodium.

Fe-Zr-Na catalysts synthesized by coprecipitation and impregnation methods were implemented to investigate the promoting effects of Na and Zr on the iron-based catalyst for high-temperature Fischer-Tropsch synthesis (HTFT). The catalysts were characterized by Ar adsorption-desorption, X-ray diffraction, scanning electron microscopy, transmission electron microscopy, CO temperature-programmed desorption, H2 temperature-programmed desorption, X-ray photoelectron spectroscopy, and Mössbauer spectroscopy (MES). The results indicated that Na changed the active sites on the catalyst surface for the CO and hydrogen adsorption, owing to the electron migration from Na to Fe atoms, which resulted in an enhanced CO dissociative adsorption and a decrease in hydrogen adsorption on the metallic Fe surface. The decreased H/C ratio on the catalyst surface accounted for the increased chain propagation and weakened hydrogenation of light olefins. Besides, Na could also facilitate the carbonization of catalysts and protect the iron carbide against oxidation, which provides more active sites for HTFT reaction and is beneficial to the C-C coupling. Zr could decrease the hematite crystallite size and stabilize the active phase to improve the HTFT activity. At an optimal Na loading of 1.0 wt %, the Fe-Zr-1.0Na catalyst exhibited the highest light olefin selectivity of 35.8% in the hydrocarbon distribution at a CO conversion of 95.2%.

Recent Achievements in Noble Metal Catalysts with Unique Nanostructures for Liquid Fuel Cells.

In recent years, research efforts have been focused on the design and fabrication of highly efficient catalysts for liquid fuel cells, because the use of these cells is an important approach for alleviating environmental pollution and energy crises. However, the limitations of the catalytic performance of industrial Pt/C have strongly hindered the development of these fuel cells. The catalyst morphology has a strong impact on its performance; nanostructured catalysts are preferred as they offer large specific surface area and more exposed active centers. In view of this, many catalysts with unique structures have been synthesized in recent years, all of which show excellent catalytic performance characteristics. Despite these achievements, few efforts have been made to survey this field comprehensively. Herein, the recent advances in catalysts for liquid fuel cells are summarized, with a focus on noble metal catalysts with unique morphologies such as nanowires, nanosheets, and assembly structures. Their formation mechanisms are discussed critically. The relationship between the unique morphologies and excellent performance of these catalysts is also explored. This work may provide guidelines for the further development of liquid fuel cells.

Adoption of Machine Learning in Intelligent Terrain Classification of Hyperspectral Remote Sensing Images.

To overcome the difficulty of automating and intelligently classifying the ground features in remote-sensing hyperspectral images, machine learning methods are gradually introduced into the process of remote-sensing imaging. First, the PaviaU, Botswana, and Cuprite hyperspectral datasets are selected as research subjects in this study, and the objective is to process remote-sensing hyperspectral images via machine learning to realize the automatic and intelligent classification of features. Then, the basic principles of the support vector machine (SVM) and extreme learning machine (ELM) classification algorithms are introduced, and they are applied to the datasets. Next, by adjusting the parameter estimates using a restricted Boltzmann machine (RBM), a new terrain classification model of hyperspectral images that is based on a deep belief network (DBN) is constructed. Next, the SVM, ELM, and DBN classification algorithms for hyperspectral image terrain classification are analysed and compared in terms of accuracy and consistency. The results demonstrate that the average detection accuracies of ELM on the three datasets are 89.54%, 96.14%, and 96.28%, and the Kappa coefficient values are 0.832, 0.963, and 0.924; the average detection accuracies of SVM are 88.90%, 92.11%, and 91.68%, and the Kappa coefficient values are 0.768, 0.913, and 0.944; the average detection accuracies of the DBN classification model are 92.36%, 97.31%, and 98.84%, and the Kappa coefficient values are 0.883, 0.944, and 0.972. The results also demonstrate that the classification accuracy of the DBN algorithm exceeds those of the previous two methods because it fully utilizes the spatial and spectral information of hyperspectral remote-sensing images. In summary, the DBN algorithm that is proposed in this study has high application value in object classification for remote-sensing hyperspectral images.

Study of the Fischer-Tropsch synthesis on nano-precipitated iron-based catalysts with different particle sizes.

Nano iron-based catalysts with different particle sizes were prepared by a co-precipitated method and characterized by XRD, N2 adsorption, SEM, Mössbauer spectroscopy, XPS, H2-TPR, CO-TPD, H2-TPD and TGA. The CO-TPD results revealed that large particle sizes of catalysts were not conducive to the adsorption of CO, and exhibited low activity of FTS. The decrease of catalyst particle size enhanced the interaction between Fe and Mn, and promoted the CO chemical adsorption and the formation of Fe5C2, but the hydrogenation reaction was inhibited as confirmed by H2-TPD. When the particle size continued to decrease, Mössbauer spectroscopy showed that MnFe2O4 appeared in the catalyst phase, which hindered the reduction of catalysts and the adsorption of feed gas. Overall, the sample FeMnSm-600 showed the highest C[double bond, length as m-dash] 2-4 selectivity of 33% at the highest CO conversion of 79% during the reaction conditions of 300 °C, 1.0 MPa, 12 000 mL (g h)-1, and H2/CO = 2.

Associations of CXCL1 gene 5'UTR variations with ovarian cancer.

BACKGROUND: There are about 2.4 hundred thousand new cases and 1.5 hundred thousand deaths of ovarian cancer (OC) annually in the world. Chronic inflammation is a risk factor for OC. C-X-C motif chemokine ligand 1 (CXCL1) defects may facilitate inflammation and transactivate EGFR in ovarian cancer, but the precise haplotypes associated with the potential diseases remained largely unknown. In this work, we characterized CXCL1 gene variations to elucidate their possible associations with OC. METHODS: We analyzed the CXCL1 gene for 300 OC patients with 400 healthy participants as controls. The statistical analyses and Hardy-Weinberg equilibrium tests of the patients and control populations were conducted using the SPSS software (version 19.0) and Plink (version 1.9). RESULTS: The variants rs11547681, rs201090116, rs199791199, rs181868085, rs4074 and rs1814092 within or near the CXCL1 gene were characterized. The genetic heterozygosity of rs11547681 and rs4074 was very high. Statistical analysis showed that the variant rs11547681 in the gene was closely associated with the risk of OC in the Chinese Han population, although this variant was not associated with FIGO stages or pathological grades of the patients. CONCLUSIONS: Rs11547681 in CXCL1 gene was associated with the risk of OC in the Chinese Han population.