Three-Dimensional Bimetallic Ammonium K-Eu Nitrate with a Rare (6,6)-Connected Ion Topology Exhibiting Structural Phase Transition and Photoluminescence Properties.

A K-Eu bimetallic ammonium metal-nitrate three-dimensional (3D) framework incorporating R-N-methyl-3-hydroxyquinuclidine, (RM3HQ)2KEu(NO3)6 (RM3HQ = R-N-methyl-3-hydroxyquinuclidine, 1), was characterized and reported. Distinguishing from the former hybrid rare-earth double perovskites, 1 adopts a mixed corner- and face-sharing K+/Eu3+-centered polyhedral connectivity to form a 3D inorganic framework, showing a rare (6, 6)-connected ion topology with a 66 framework. Notably, 1 exhibits clear phase transition, and the switchable thermodynamic behavior is confirmed by variable-temperature dielectric measurements and second-harmonic generation response. Moreover, 1 also shows photoluminescence properties. The activator Eu3+ plays a crucial role in this process, leading to a significant narrow emission at 592 nm with a photoluminescence quantum yield (PLQY) of 20.76%. The fluorescence lifetime (FLT) of 1 is 4.32 ms. This finding enriches the bimetallic hybrid system for potential electronic and/or luminescence applications.

Gas-Liquid Interface Route to Hybrid Copper Bromine Perovskite Single-Crystal Membrane with Dielectric Transitions and Ferromagnetic Exchanges.

Single-crystal membranes (SCMs) show great promise in the fields of sensors, light-emitting diodes, and photodetection. However, the growth of a large-area single-crystal membranes is challenging. We report a new organic-inorganic SCMs [HCMA]2CuBr4 (HCMA = cyclohexanemethylamine) crystallized at the gas-liquid interface. It also has low-temperature ferromagnetic order, high-temperature dielectric anomalies, and narrow band gap indirect semiconductor properties. Specifically, the reversible phase transition of the compound occurs at 350/341 K on cooling/heating and exhibits dielectric anomalies and stable switching performance near the phase transition temperature. The ferromagnetic exchange interaction in the inorganic octahedra and the organic layer enables ferromagnetic ordering at low-temperature 10 K. Finally, the single crystal exhibits an indirect semiconducting property with a narrow band gap of 0.99 eV. Such rich multichannel physical properties make it a potential application in photodetection, information storage and sensors.

A phosphoglycerate mutase 1 allosteric inhibitor overcomes drug resistance to EGFR-targeted therapy via disrupting IL-6/JAK2/STAT3 signaling pathway in lung adenocarcinoma.

Resistance to epidermal growth factor receptor (EGFR) inhibitors, from the first-generation erlotinib to the third generation osimertinib, is a clinical challenge in the treatment of patients with EGFR-mutant lung adenocarcinoma. Our previous work found that a novel allosteric inhibitor of phosphoglycerate mutase 1 (PGAM1), HKB99, restrains erlotinib resistance in lung adenocarcinoma cells. However, the role of HKB99 in osimertinib resistance and its underlying molecular mechanism remains to be elucidated. Herein, we found that IL-6/JAK2/STAT3 signaling pathway is aberrantly activated in both erlotinib and osimertinib resistant cells. Importantly, HKB99 significantly blocks the interaction of PGAM1 with JAK2 and STAT3 via the allosteric sites of PGAM1, which leads to inactivation of JAK2/STAT3 and thereby disrupts IL-6/JAK2/STAT3 signaling pathway. Consequently, HKB99 remarkably restores EGFR inhibitor sensitivity and exerts synergistic tumoricidal effect. Additionally, HKB99 alone or in combination with osimertinib down-regulated the level of p-STAT3 in xenograft tumor models. Collectively, this study identifies PGAM1 as a key regulator in IL-6/JAK2/STAT3 axis in the development of resistance to EGFR inhibitors, which could serve as a therapeutic target in lung adenocarcinoma with acquired resistance to EGFR inhibitors.

Electrochemical Detection of Flutamide by the Composite of Complex Based on Thiacalix[4]arene Derivatives and Reduced Graphene Oxide.

In this paper, a thiacalix[4]arene complex [Zn2(TIT4A)L2]·4DMF·2CH3OH (H2L = 4,4'-oxybisbenzoic acid) (Zn-TIT4A-L) was synthesized by a solvothermal method. The composites were prepared by combining Zn-TIT4A-L with reduced graphene oxide (RGO), mesoporous carbon (MC), and multi-walled carbon nanotubes (MWCNTs), respectively. Three representative composites are Zn-TIT4A-L@RGO(1:1), Zn-TIT4A-L@MC(1:2), and Zn-TIT4A-L@MWCNT(1:2). X-ray diffraction and scanning electron microscopy characterized their structures and morphologies. The results showed that three composites were successfully prepared, and the crystals of the complex remained in the composites. The electrochemical properties of the composites were characterized by electrochemical impedance spectroscopy and cyclic voltammetry. The results indicated that they had good electrocatalytic activity and conductivity. Among them, Zn-TIT4A-L@RGO(1:1) had the best performance and was used for the quantitative detection of flutamide (FTA). The linear range of detection is 0.1-200 µM, and the limit of detection is 0.015 µM. At the same time, the sensor also had good reproducibility, anti-interference, and stability. The sensor was also used for the detection of FTA in lake water, human urine, and serum with a satisfactory recovery rate. The possible mechanism of electrochemical detection of FTA was also discussed.

An allosteric PGAM1 inhibitor effectively suppresses pancreatic ductal adenocarcinoma.

Glycolytic enzyme phosphoglycerate mutase 1 (PGAM1) plays a critical role in cancer metabolism by coordinating glycolysis and biosynthesis. A well-validated PGAM1 inhibitor, however, has not been reported for treating pancreatic ductal adenocarcinoma (PDAC), which is one of the deadliest malignancies worldwide. By uncovering the elevated PGAM1 expressions were statistically related to worse prognosis of PDAC in a cohort of 50 patients, we developed a series of allosteric PGAM1 inhibitors by structure-guided optimization. The compound KH3 significantly suppressed proliferation of various PDAC cells by down-regulating the levels of glycolysis and mitochondrial respiration in correlation with PGAM1 expression. Similar to PGAM1 depletion, KH3 dramatically hampered the canonic pathways highly involved in cancer metabolism and development. Additionally, we observed the shared expression profiles of several signature pathways at 12 h after treatment in multiple PDAC primary cells of which the matched patient-derived xenograft (PDX) models responded similarly to KH3 in the 2 wk treatment. The better responses to KH3 in PDXs were associated with higher expression of PGAM1 and longer/stronger suppressions of cancer metabolic pathways. Taken together, our findings demonstrate a strategy of targeting cancer metabolism by PGAM1 inhibition in PDAC. Also, this work provided "proof of concept" for the potential application of metabolic treatment in clinical practice.

Heteroexpression and biochemical characterization of thermostable citrate synthase from the cyanobacteria Anabaena sp. PCC7120.

The present study recombinantly expressed a citrate synthase from cyanobacteria Anabaena sp. PCC7120 (AnCS) in Escherichia coli and characterized its enzymatic activity. The molecular mass of native AnCS was 88,533.1 Da containing two 44,162.7 Da subunits. Recombinant AnCS revealed the highest activity at pH 9.0 and 25 °C. AnCS displayed high thermal stability with a half-life time (t1/2) of approximately 6.5 h at 60 °C, which was more thermostable than most CS from general organisms, but less than those from hyperthermophilic bacteria. The Km values of oxaloacetate and acetyl-CoA were 138.50 and 18.15 µM respectively, suggesting a higher affinity to acetyl-CoA than oxaloacetate. Our inhibition assays showed that AnCS activity was not severely affected by most metal ions, but was strongly inhibited by Cu2+ and Zn2+. Treatments with ATP, ADP, AMP, NADH, and DTT depressed the AnCS activity. Overall, our results provide information on the enzymatic properties of AnCS, which contributes to the basic knowledge on CS selection for industrial utilizations.

[Study on the Visualization of the Biomass of Chlorella sp., Isochrysis galbana, and Spirulina sp. Based on Hyperspectral Imaging Technique].

Effective cultivation of the microalgae is the key issue for microalgal bio-energy utilization. In nutrient rich culture conditions, the microalge have a fast growth rate, but they are more susceptible to environmental pollution and influence. So to monitor the the growth process of microalgae is significant during cultivating. Hyperspectral imaging has the advantages of both spectra and image analysis. The spectra contain abundant material quality signal and the image contains abundant spatial information of the material about the chemical distribution. It can achieve the rapid information acquisition and access a large amount of data. In this paper, the authors collected the hyperspectral images of forty-five samples of Chlorella sp., Isochrysis galbana, and Spirulina sp., respectively. The average spectra of the region of interest (ROI) were extracted. After applying successive projection algorithm (SPA), the authors established the multiple linear regression (MLR) model with the spectra and corresponding biomass of 30 samples, 15 samples were used as the prediction set. For Chlorella sp., Isochrysis galbana, and Spirulina sp., the correlation coefficient of prediction (r(pre)) are 0.950, 0.969 and 0.961, the root mean square error of prediction (RMSEP) for 0.010 2, 0.010 7 and 0.007 1, respectively. Finally, the authors used the MLR model to predict biomass for each pixel in the images of prediction set; images displayed in different colors for visualization based on pseudo-color images with the help of a Matlab program. The results show that using hyperspectral imaging technique to predict the biomass of Chlorella sp. and Spirulina sp. were better, but for the Isochrysis galbana visualization needs to be further improved. This research set the basis for rapidly detecting the growth of microalgae and using the microalgae as the bio-energy.

[Identification of Microalgae Species Using Visible/Near Infrared Transmission Spectroscopy].

At present, the identification and classification of the microalgae and its biochemical analysis have become one of the hot spots on marine biology research. Four microalgae species, including Chlorella vulgaris, Chlorella pyrenoidosa, Nannochloropsis oculata, Chlamydomonas reinhardtii, were chosen as the experimental materials. Using an established spectral acquisition system, which consists of a portable USB 4000 spectrometer having transmitting and receiving fiber bundles connected by a fiber optic probe, a halogen light source, and a computer, the Vis/NIR transmission spectral data of 120 different samples of the microalgae with different concentration gradients were collected, and the spectral curves of fourmicroalgae species were pre-processed by different pre-treatment methods (baseline filtering, convolution smoothing, etc. ). Based on the pre-treated effects, SPA was applied to select effective wavelengths (EWs), and the selected EWs were introduced as inputs to develop and compare PLS, Least Square Support Vector Machines (LS-SVM), Extreme Learning Machine (ELM)models, so as to explore the feasibility of using Vis/NIR transmission spectroscopy technology for the rapid identification of four microalgae species in situ. The results showed that: the effect of Savitzky-Golay smoothing was much better than the other pre-treatment methods. Six EWs selected in the spectraby SPA were possibly relevant to the content of carotenoids, chlorophyll in the microalgae. Moreover, the SPA-PLS model obtained better performance than the Full-Spectral-PLS model. The average prediction accuracy of three methods including SPA-LV-SVM, SPA-ELM, and SPA-PLS were 80%, 85% and 65%. The established method in this study may identify four microalgae species effectively, which provides a new way for the identification and classification of the microalgae species. The methodology using Vis/NIR spectroscopy with a portable optic probe would be applicable to a diverse range of microalgae species and proves to be a rapid, real-time, non-destructive, precise method for the physiological and biochemical detection for microalgae.

[Study on the Nondestructive Detection Methods for Dynamica Change of Lipid Content in Chlorella sp.].

Microalgae based biodiesel production requires a large amount of lipid accumulation in the cells, and the accumulation is greatly influenced by the environment. Therefore, it is necessary to find fast and non-destructive methods for lipid change detection. In this paper, Chlorella sp. was adopted as the objective, which was cultured under different light condition consisted of red and blue lights with different proportion. We applied the visible near-infrared spectroscopy (Vis/NIRs) technique to detect the dynamic change of lipid during the microalgae growth processes and utilized hyperspectral imaging technology for visualization of lipid distribution in the suspension. The transmittance and reflectance spectra of microalgae were acquired with Vis/NIRs and hyper-spectroscopy, respectively. In the comparison of the transmittance and reflectance spectra, they showed some different characteristics. Meanwhile it also varied in terms of the number and the area of feature wavelengths obtained by successive projections algorithm (SPA) based on the different spectra. But the established multiple linear regression (MLR) model for lipid content prediction had similar results with rpre of 0.940, RMSEP of 0.003 56 and rpre of 0.932, RMSEP of 0.004 23, respectively. Based on the predictive model, we obtained the spectra and analyzed the lipid dynamic change in microalgae in one life cycle. In the life cycle, the lipid content in Chlorella sp. was relatively stable from the beginning of inoculation to exponential phase, the increase and accumulation of lipid phenomenon occurred in the late exponential phase. Combined with the MLR model and the hypersepctral images, we studied the visualization result of microalgae suspension in the steady phase. The stimulated images showed that the microalgae with higher lipid content appeared gathering. This study compared the difference and the feasibility of the Vis/NIRs and hyperspectral imaging technique in lipid content detection applied in microalgae growing microalgae. The results are meaningful for the fast and non-destructive detection of the growth information of microalgae. It has boththeoretical and practical significance for developing microalgal culture and harvest strategy in practice.

[Microalgae Species Identification Study with Raman Microspectroscopy Technology].

Identification and classification of microalgae are basis and premise in the study of physiological and biochemical characteristics for microalgae. Microalgae cells mainly consist of five kinds of biological molecules, including proteins, carbonhydrates, lipids, nucleic acids and pigments. These five kinds of biological molecules contents with different ratio in microalgae cells can be utilized to identify microalgae species as a supplement method. This paper investigated the application of Raman microspectroscopy technology in the field of rapid identification on different algae species such as aschlorella sp. and chlamydomonas sp. . Cultivated in the same conditions of culture medium, illumination duration and intensity, these two kinds of species of microalgae cells were immobilized by using agar, and then the samples were placed under 514. 5 nm Raman laser to collect Raman spectra of different growth periods of different species. An approach to remove fluorescence background in Raman spectra called Rolling Circle Filter (RCF) algorithm was adopted to remove the fluorescent background, and then some preprocessing methods were used to offset the baseline and smooth method of Savitzky-Golay was tried to make the spectra curves of total 80 samples smoother. Then 50 samples were randomly extracted from 80 samples for modeling, and the remaining 30 samples for independent validation. This paper adopted different pretreatment methods, and used the partial least squares (PLS) to establish model between the spectral data and the microalgae species, then compared the effects of different pretreatment methods. The results showed that with Raman microspectroscopy technology, the pretreatment method of max-peak ratio standardization was a more effective identification approach which utilizes the different content ratios of pigments of different microalgae species. This method could efficiently eliminate the influence on Raman signal due to different growth stages of microalgae and decomposition of pigments contents of microalgae in vivo. Compared with other traditional classification methods, this method had significant advantages like simpler procedure and shorter testing time, and it can also avoid some subjective measurement errors caused by unskilled operations. If the threshold was set to +/- 0.5, the prediction accuracy can reach 100%, and when the threshold was +/- 0.2, the prediction accuracy reached 86.67%, which proves the proposed new method can be a good approach to identify different algae varieties.

[Identification of transmission fluid based on NIR spectroscopy by combining sparse representation method with manifold learning].

An identification method based on sparse representation (SR) combined with autoencoder network (AN) manifold learning was proposed for discriminating the varieties of transmission fluid by using near infrared (NIR) spectroscopy technology. NIR transmittance spectra from 600 to 1 800 nm were collected from 300 transmission fluid samples of five varieties (each variety consists of 60 samples). For each variety, 30 samples were randomly selected as training set (totally 150 samples), and the rest 30 ones as testing set (totally 150 samples). Autoencoder network manifold learning was applied to obtain the characteristic information in the 600-1800 nm spectra and the number of characteristics was reduced to 10. Principal component analysis (PCA) was applied to extract several relevant variables to represent the useful information of spectral variables. All of the training samples made up a data dictionary of the sparse representation (SR). Then the transmission fluid variety identification problem was reduced to the problem as how to represent the testing samples from the data dictionary (training samples data). The identification result thus could be achieved by solving the L-1 norm-based optimization problem. We compared the effectiveness of the proposed method with that of linear discriminant analysis (LDA), least squares support vector machine (LS-SVM) and sparse representation (SR) using the relevant variables selected by principal component analysis (PCA) and AN. Experimental results demonstrated that the overall identification accuracy of the proposed method for the five transmission fluid varieties was 97.33% by AN-SR, which was significantly higher than that of LDA or LS-SVM. Therefore, the proposed method can provide a new effective method for identification of transmission fluid variety.

Protective effects of the secondary metabolites from Quercus salicina Blume against gentamicin-induced nephrotoxicity in zebrafish (Danio rerio) model.

To reveal the protective effect on the nephrotoxicity of Quercus salicina Blume(QS), a traditional medicine for the treatment of urolithiasis, the 50 % ethanol extract from the branches and leaves of QS was chemically studied by systematic solvent extraction and HPLC chromatography. Two phenolic acids and three flavonoids were identified by nuclear magnetic resonance spectroscopy, namely Ferulic acid (1), p-Hydroxycinnamic acid (2), Hesperidin (3), Formononetin (4), and Quercetin (5). At the same time, the gentamicin-induced nephrotoxicity of zebrafish was used as a model for the first time. The antioxidant activity of these derivatives with good antioxidant activity screened from free radical scavenging experiments in vitro (DPPH and ABTS) was evaluated in vivo, including protein levels (LPO, NO, GSH, and SOD), kidney injury factor (KIM-1), zebrafish kidney pathology and real-time PCR. The results showed that metabolites 1, 3, and 5 had strong antioxidant activity, and oxidative stress in renal tissue was significantly reduced; KIM-1, TNF-α, and IL-6 mRNA expression in a dose-dependent manner, which preliminarily revealed the protective effect of the secondary metabolites of QS on nephrotoxicity, and preliminarily discussed the structure-activity relationship. This study provides an experimental basis for further exploring the mechanism of QS in the kidney.

Enzymatic Characterization and Coenzyme Specificity Conversion of a Novel Dimeric Malate Dehydrogenase from Bacillus subtilis.

Malate is an important material to various industrials and clinical applications. Bacillus subtilis is a widely used biocatalyst tool for chemical production. However, the specific enzymatic properties of malate dehydrogenase from Bacillus subtilis (BsMDH) remain largely unknown. In the present study, BsMDH was cloned, recombinantly expressed and purified to test its enzymatic properties. The molecular weight of single unit of BsMDH was 34,869.7 Da. Matrix-Assisted Laser-Desorption Ionization-Time-of-Flight Mass Spectrometry and gel filtration analysis indicated that the recombinant BsMDH could form dimers. The kcat/Km values of oxaloacetate and NADH were higher than those of malate and NAD+, respectively, indicating a better catalysis in the direction of malate synthesis than the reverse. Furthermore, six BsMDH mutants were constructed with the substitution of amino acids at the coenzyme binding site. Among them, BsMDH-T7 showed a greatly higher affinity and catalysis efficiency to NADPH than NADH with the degree of alteration of 2039, suggesting the shift of the coenzyme dependence from NADH to NADPH. In addition, BsMDH-T7 showed a relatively lower Km value, but a higher kcat and kcat/Km than NADPH-dependent MDHs from Thermus flavus and Corynebacterium glutamicum. Overall, these results indicated that BsMDH and BsMDH-T7 mutant might be promising enzymes for malate production.

Reduced electron relaxation time of perovskite films via g-C3N4 quantum dot doping for high-performance perovskite solar cells.

Perovskite film-quality is a crucial factor to improve the photovoltaic properties of perovskite solar cells, which is closely related to the morphology of crystallization grain size of the perovskite layer. However, defects and trap sites are inevitably generated on the surface and at the grain boundaries of the perovskite layer. Here, we report a convenient method for preparing dense and uniform perovskite films, employing g-C3N4 quantum dots doped into the perovskite layer by regulating proper proportions. This process produces perovskite films with dense microstructures and flat surfaces. As a result, the higher fill factor (0.78) and a power conversion efficiency of 20.02% are obtained by the defect passivation of g-C3N4QDs.

Nomogram for Prediction of Postoperative Delirium after Deep Brain Stimulation of Subthalamic Nucleus in Parkinson's Disease under General Anesthesia.

Introduction: Postoperative delirium can increase cognitive impairment and mortality in patients with Parkinson's disease. The purpose of this study was to develop and internally validate a clinical prediction model of delirium after deep brain stimulation of the subthalamic nucleus in Parkinson's disease under general anesthesia. Methods: We conducted a retrospective observational cohort study on the data of 240 patients with Parkinson's disease who underwent deep brain stimulation of the subthalamic nucleus under general anesthesia. Demographic characteristics, clinical evaluation, imaging data, laboratory data, and surgical anesthesia information were collected. Multivariate logistic regression was used to develop the prediction model for postoperative delirium. Results: A total of 159 patients were included in the cohort, of which 38 (23.90%) had postoperative delirium. Smoking (OR 4.51, 95% CI 1.56-13.02, p < 0.01) was the most important risk factor; other independent predictors were orthostatic hypotension (OR 3.42, 95% CI 0.90-13.06, p=0.07), inhibitors of type-B monoamine oxidase (OR 3.07, 95% CI 1.17-8.04, p=0.02), preoperative MRI with silent brain ischemia or infarction (OR 2.36, 95% CI 0.90-6.14, p=0.08), Hamilton anxiety scale score (OR 2.12, 95% CI 1.28-3.50, p < 0.01), and apolipoprotein E level in plasma (OR 1.48, 95% CI 0.95-2.29, p=0.08). The area under the receiver operating characteristic curve (AUC) was 0.76 (95% CI 0.66-0.86). A nomogram was established and showed good calibration and clinical predictive capacity. After bootstrap for internal verification, the AUC was 0.74 (95% CI 0.66-0.83). Conclusion: This study provides evidence for the independent inducing factors of delirium after deep brain stimulation of the subthalamic nucleus in Parkinson's disease under general anesthesia. By predicting the development of delirium, our model may identify high-risk groups that can benefit from early or preventive intervention.

[Determination of dynamic viscosity of automobile lubricant using visible and near infrared spectroscopy].

Visible and near infrared (Vis/NIR) spectroscopy was applied for the fast determination of dynamic viscosity of automobile lubricant. One hundred fifty samples from 5 brands were collected for Vis/NIR spectral scanning. Partial least squares (PLS) analysis was applied as calibration method after preprocessing stage as well as a way to extract the first 6 principal components which were used as the input data matrix of least squares-support vector machine (LS-SVM) to develop the LS-SVM models. Radial basis function was used as core function with gamma equal to 27.3212 and sigma2 equal to 3.2295. The calibration set was composed of 125 samples, whereas 25 samples were in the validation set. The results indicated that LS-SVM model achieved the best prediction performance. A new process is proposed in this paper for determination of dynamic viscosity of automobile lubricant.

[Non-invasive measurement of water content in engine lubricant using visible and near infrared spectroscopy].

Visible and near-infrared reflectance spectroscopy (Vis-NIRS) was applied to non-invasively measurement of water content in engine lubricant. Based on measured spectra, several spectral calibration algorithms were adopted to improve accuracy and simply calculation. Principal component analysis (PCA) and successive projections algorithm (SPA) were separately used to reduce variables of spectral model. Nine effective variables, 476, 483, 544, 925, 933, 938, 952, 970 and 974 nm, were selected by SPA, and were inputted into partial least square regression (PLSR) and multivariable linear regression (MLR) models. Both the two models obtained better results than full-spectra-PLSR model and PCA-PLSR model. It shows that SPA does not select uninformative but effective variables from full-spectrum. Least-square support vector machine (LS-SVM) was operated to improve Vis-NIRS's ability based on full-spectrum and SPA, separately. High coefficients of determination for prediction set (Rp(2)) up to 0.9 were obtained by both full-spectrum-LS-SVM and SPA-LS-SVM models. SPA-LS-SVM is better than full-spectrum-LS-SVM. The value of Rp(2) of SPA-LS-SVM is 0.983 and residual predictive deviation (RPD) is 6.963. It is concluded that Vis-NIRS can be used in the non-invasive measurement of water content in engine lubricant, and SPA is a feasible and efficient algorithm for the spectral variable selection.

Expression and characterization of a thermostable citrate synthase from Microcystis aeruginosa PCC7806.

Citrate synthase (CS) is an important enzyme in energy conversion and material circulation, participating in many important biochemical processes. In the present study, CS from Microcystis aeruginosa PCC7806 (MaCS) was cloned and expressed in Escherichia coli Rosetta (DE3). The recombinant MaCS was purified and its enzymological properties were characterized. The results showed that MaCS formed dimers in native status. The optimum temperature and pH of MaCS was 30°C and 8.2, respectively. MaCS displayed relative high thermal stability. Treatment at 50°C for 20 min only decreased 11.30% activity of MaCS and the half-life of MaCS was approximately 35 min at 55°C. The kcat and Km of acetyl-CoA and oxaloacetic acid were 17.133 s-1 (kcat) and 11.62 µM (Km), 24.502 s-1 and 103.00 µM, respectively. MaCS activity was not drastically inhibited by monovalent ions and NADH but depressed by divalent ions and some small molecular compounds, especially Mg2+, Zn2+, Co2+ and DTT. Overall, these data contributed to further understanding of energy metabolism in cyanobacteria and also provided basic information for industrial application of CS.

[Comparison of short-term clinical effect and assessment of influencial factors around single-tooth in the aesthetic area: immediate implant placement versus delayed implant placement].

PURPOSE: To compare the short-term clinical effect and to assess the influencial factors of immediate implant placement and delayed implant placement around single-tooth implant in the aesthetic area. METHODS: A total of 114 patients requiring a single-tooth implant in the aesthetic area were reviewed at Center for Implant Dentistry of Stomatological Hospital of China Medical University. They were divided into immediate implant group and delayed implant group. The patients were followed up for 1 year after upper structure rehabilitation, and the pink esthetic score and the marginal bone absorption around the implants were measured. Statistical analysis was performed using SPSS 17.0 software package. RESULTS: After 1 year of upper structure rehabilitation, 114 implants were stable and the marginal bone absorption around the implants of the immediate implant group was (0.36±0.39) mm,significantly smaller than the delayed implant group [(0.79±0.67)mm, P<0.001]. The difference in PES score between the two groups were not statistically significant on the day of rehabilitation and 1 year after upper structure rehabilitation（P>0.05）. Significant improvement of PES on the day of rehabilitation and 1 year after upper structure rehabilitation and marginal bone absorption was found with flapless surgery. SLA and DAE surface treatment methods had no significant impact on PES and marginal bone absorption (P>0.05). Graft procedure had an unfavorable effect on PES value both on the day of rehabilitation and 1 year after upper structure rehabilitation. CONCLUSIONS: Under appropriate indications, immediate implant placement and immediate repair could reduce the time of missing teeth. The marginal bone absorption of immediate implant group is smaller than delayed implant group. Flapless surgery avoids damage to gingival tissue, reduces postoperative reaction and improves the aesthetic outcomes after repair.

A Novel Allosteric Inhibitor of Phosphoglycerate Mutase 1 Suppresses Growth and Metastasis of Non-Small-Cell Lung Cancer.

Phosphoglycerate mutase 1 (PGAM1) plays a pivotal role in cancer metabolism and tumor progression via its metabolic activity and interaction with other proteins like α-smooth muscle actin (ACTA2). Allosteric regulation is considered to be an innovative strategy to discover a highly selective and potent inhibitor targeting PGAM1. Here, we identified a novel PGAM1 allosteric inhibitor, HKB99, via structure-based optimization. HKB99 acted to allosterically block conformational change of PGAM1 during catalytic process and PGAM1-ACTA2 interaction. HKB99 suppressed tumor growth and metastasis and overcame erlotinib resistance in non-small-cell lung cancer (NSCLC). Mechanistically, HKB99 enhanced the oxidative stress and altered multiple signaling pathways including the activation of JNK/c-Jun and suppression of AKT and ERK. Collectively, the study highlights the potential of PGAM1 as a therapeutic target in NSCLC and reveals a distinct mechanism by which HKB99 inhibits both metabolic activity and nonmetabolic function of PGAM1 by allosteric regulation.