A close quasar pair in a disk-disk galaxy merger at z = 2.17.

Galaxy mergers produce pairs of supermassive black holes (SMBHs), which may be witnessed as dual quasars if both SMBHs are rapidly accreting. The kiloparsec (kpc)-scale separation represents a physical regime sufficiently close for merger-induced effects to be important1 yet wide enough to be directly resolvable with the facilities currently available. Whereas many kpc-scale, dual active galactic nuclei-the low-luminosity counterparts of quasars-have been observed in low-redshift mergers2, no unambiguous dual quasar is known at cosmic noon (z ≈ 2), the peak of global star formation and quasar activity3,4. Here we report multiwavelength observations of Sloan Digital Sky Survey (SDSS) J0749 + 2255 as a kpc-scale, dual-quasar system hosted by a galaxy merger at cosmic noon (z = 2.17). We discover extended host galaxies associated with the much brighter compact quasar nuclei (separated by 0.46″ or 3.8 kpc) and low-surface-brightness tidal features as evidence for galactic interactions. Unlike its low-redshift and low-luminosity counterparts, SDSS J0749 + 2255 is hosted by massive compact disk-dominated galaxies. The apparent lack of stellar bulges and the fact that SDSS J0749 + 2255 already follows the local SMBH mass-host stellar mass relation, suggest that at least some SMBHs may have formed before their host stellar bulges. While still at kpc-scale separations where the host-galaxy gravitational potential dominates, the two SMBHs may evolve into a gravitationally bound binary system in around 0.22 Gyr.

A novel design of targeted endocrine and cytokine therapy for breast cancer.

The aim of this study is to combine endocrine therapy [human prolactin (hPRL) antagonist, G129R] and immune therapy [interleukin 2 (IL2)] in the design of a fusion protein, G129R-IL2, to treat human breast cancer. This novel approach uses the specific interaction between the G129R and hPRL receptors (PRLRs), thus directly targeting the fusion protein to the malignant breast tissues that have previously been shown to contain high levels of PRLR. The localized bifunctional fusion protein is designed to block signal transduction induced by hPRL as well as to activate T lymphocytes near the tumor site. A bacterial expression system was used to produce G129R-IL2 fusion protein that maintained both G129R and IL2 activities as demonstrated by cell-based assays such as signal transducer(s) and activator(s) of transcription (STAT)5 phosphorylation, breast cancer cell proliferation, and T-cell proliferation. The antitumor activities of G129R-IL2 were demonstrated in vivo using a syngeneic model system with BALB/c mice and EMT6-hPRLR breast cancer cells. After daily injection (i.p.) of G129R-IL2 (100 microg/mouse) for 18 days, the tumor growth in the G129R-IL2-treated group was only one-third the size as compared with that of the control group. The growth rate in the G129R-IL2-treated group is also significantly slower than that of the group treated with G129R alone (200 microg/mouse/day). We hope that this novel bifunctional protein will contribute significantly to human breast cancer therapy.

Using support vector classification for SAR of fentanyl derivatives.

AIM: To discriminate between fentanyl derivatives with high and low activities. METHODS: The support vector classification (SVC) method, a novel approach, was employed to investigate structure-activity relationship (SAR) of fentanyl derivatives based on the molecular descriptors, which were quantum parameters including DeltaE [energy difference between highest occupied molecular orbital energy (HOMO) and lowest empty molecular orbital energy (LUMO)], MR (molecular refractivity) and M(r) (molecular weight). RESULTS: By using leave-one-out cross-validation test, the accuracies of prediction for activities of fentanyl derivatives in SVC, principal component analysis (PCA), artificial neural network (ANN) and K-nearest neighbor (KNN) models were 93%, 86%, 57%, and 71%, respectively. The results indicated that the performance of the SVC model was better than those of PCA, ANN, and KNN models for this data. CONCLUSION: SVC can be used to investigate SAR of fentanyl derivatives and could be a promising tool in the field of SAR research.

Hyper-polyhedron model applied to molecular screening of guanidines as Na/H exchange inhibitors.

AIM: To investigate structure-activity relationships of N-(3-Oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-carbonyl) guanidines in Na/H exchange inhibitory activities and probe into a new method of the computer-aided molecular screening. METHODS: The hyper-polyhedron model (HPM) was proposed in our lab. RESULTS: The samples with probably higher activities could be determined in such a way that their representing points should be in the hyper-polyhedron region where all known samples with high activities were distributed. And the predictive ability of different methods available was tested by the cross-validation experiment. CONCLUSION: The accurate rate of molecular screening of N-(3-Oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-carbonyl) guanidines by HPM was much higher than that obtained by PCA (principal component analysis) and Fisher methods for the data set available here. Therefore, HPM could be used as a powerful tool for screening new compounds with probably higher activities.

Semiempirical quantum chemical method and artificial neural networks applied for lambdamax computation of some azo dyes.

The maximum absorption wavelengths of 31 azo dyes have been calculated by two comprehensive methods using the semiempirical quantum chemical method, PM3, and the weight decay based artificial neural network (WD-ANN) or the early stopping based artificial neural network (ES-ANN). The average absolute errors of WD-ANN and that of ES-ANN are 10.07 nm and 12.40 nm, respectively. These results are much better than the results using ZINDO/S with the default value (0.585) only.