Suppressing Protodeboronation in Cu-Mediated 19F/18F-Fluorination of Arylboronic Acids: A Mechanistically Guided Approach Towards Optimized PET Probe Development.

Fluorinated arenes play a crucial role in drug discovery, specialty materials, and medical imaging. Although several variants for Cu-mediated nucleophilic fluorination of arylboronic acids and derivatives have been developed, these protocols rarely address the occurrence and control of protodeboronation, which greatly complicates product separation and can compromise the effectiveness of a radiotracer for in vivo imaging. Consequently, simpler and more efficient procedures are needed to allow rapid 18F/19F-fluorination of both arylboronic acids and esters while minimizing protodeboronation. Mechanistic controls revealed that in addition to a high temperature, strong donor ligands such as acetonitrile and pyridine accentuate a Cu-mediated protodeboronation. This observation guided the optimization of a ligandless procedure with t-BuOH as solvent to enhance the nucleophilicity of fluoride under milder conditions at lower temperatures minimizing protodeboronation. Additionally, a new copper salt, Cu(ONf)2 was employed to further improve the fluorination efficiency. A large range of functional groups are tolerated under the new procedure, which is complete within 30 minutes at a temperature of 60 °C, and affords fluorinated arenes and heteroarenes in 39% to 84% yield. With minimal modifications, the protocol can also be applied in 18F-radiofluorination, affording radiochemical conversions (RCCs) between 17-54% with minimal protodeboronation compared to previously established protocols.

DTDNet: Dynamic Target Driven Network for pedestrian trajectory prediction.

Predicting the trajectories of pedestrians is an important and difficult task for many applications, such as robot navigation and autonomous driving. Most of the existing methods believe that an accurate prediction of the pedestrian intention can improve the prediction quality. These works tend to predict a fixed destination coordinate as the agent intention and predict the future trajectory accordingly. However, in the process of moving, the intention of a pedestrian could be a definite location or a general direction and area, and may change dynamically with the changes of surrounding. Thus, regarding the agent intention as a fixed 2-d coordinate is insufficient to improve the future trajectory prediction. To address this problem, we propose Dynamic Target Driven Network for pedestrian trajectory prediction (DTDNet), which employs a multi-precision pedestrian intention analysis module to capture this dynamic. To ensure that this extracted feature contains comprehensive intention information, we design three sub-tasks: predicting coarse-precision endpoint coordinate, predicting fine-precision endpoint coordinate and scoring scene sub-regions. In addition, we propose a original multi-precision trajectory data extraction method to achieve multi-resolution representation of future intention and make it easier to extract local scene information. We compare our model with previous methods on two publicly available datasets (ETH-UCY and Stanford Drone Dataset). The experimental results show that our DTDNet achieves better trajectory prediction performance, and conducts better pedestrian intention feature representation.

MDST-DGCN: A Multilevel Dynamic Spatiotemporal Directed Graph Convolutional Network for Pedestrian Trajectory Prediction.

Pedestrian trajectory prediction is an essential but challenging task. Social interactions between pedestrians have an immense impact on trajectories. A better way to model social interactions generally achieves a more accurate trajectory prediction. To comprehensively model the interactions between pedestrians, we propose a multilevel dynamic spatiotemporal digraph convolutional network (MDST-DGCN). It consists of three parts: a motion encoder to capture the pedestrians' specific motion features, a multilevel dynamic spatiotemporal directed graph encoder (MDST-DGEN) to capture the social interaction features of multiple levels and adaptively fuse them, and a motion decoder to produce the future trajectories. Experimental results on public datasets demonstrate that our model achieves state-of-the-art results in both long-term and short-term predictions for both high-density and low-density crowds.

Dkk3/REIC Deficiency Impairs Spermiation, Sperm Fibrous Sheath Integrity and the Sperm Motility of Mice.

The role of Dickkopf-3 (Dkk3)/REIC (The Reduced Expression in Immortalized Cells), a Wnt-signaling inhibitor, in male reproductive physiology remains unknown thus far. To explore the functional details of Dkk3/REIC in the male reproductive process, we studied the Dkk3/REIC knock-out (KO) mouse model. By examining testicular sections and investigating the sperm characteristics (count, vitality and motility) and ultrastructure, we compared the reproductive features between Dkk3/REIC-KO and wild-type (WT) male mice. To further explore the underlying molecular mechanism, we performed RNA sequencing (RNA-seq) analysis of testicular tissues. Our results showed that spermiation failure existed in seminiferous tubules of Dkk3/REIC-KO mice, and sperm from Dkk3/REIC-KO mice exhibited inferior motility (44.09 ± 8.12% vs. 23.26 ± 10.02%, p < 0.01). The Ultrastructure examination revealed defects in the sperm fibrous sheath of KO mice. Although the average count of Dkk3/REIC-KO epididymal sperm was less than that of the wild-types (9.30 ± 0.69 vs. 8.27 ± 0.87, ×106), neither the gap (p > 0.05) nor the difference in the sperm vitality rate (72.83 ± 1.55% vs. 72.50 ± 0.71%, p > 0.05) were statistically significant. The RNA-seq and GO (Gene Oncology) enrichment results indicated that the differential genes were significantly enriched in the GO terms of cytoskeleton function, cAMP signaling and calcium ion binding. Collectively, our research demonstrates that Dkk3/REIC is involved in the process of spermiation, fibrous sheath integrity maintenance and sperm motility of mice.

Repurposing of posaconazole as a hedgehog/SMO signaling inhibitor for embryonal rhabdomyosarcoma therapy.

Posaconazole (POS) is a novel antifungal agent, which has been repurposed as an anti-tumor drug for its potential inhibition of Hedgehog signaling pathway. Hedgehog pathway is reported to be abnormally activated in embryonal rhabdomyosarcoma (ERMS), this study aimed to reveal whether POS could inhibit Hedgehog signaling pathway in ERMS. Following POS treatment, XTT viability assay was used to determine the cell proliferation of ERMS cell lines. Protein changes related to Hedgehog signaling, cell cycle and autophagy were detected by Western blot. The cell cycle distribution was analyzed by flow cytometry. Moreover, a subcutaneous tumor mouse model of ERMS was established to assess the anti-tumor effect of POS. POS was found to inhibit tumor progression by inducing G0/G1 arrest and autophagy of RD, RMS-YM, and KYM-1 cells dose-dependently. Western blot demonstrated that POS downregulated the expressions of SMO, Gli1, c-Myc, CDK4, and CDK6, while upregulated the expressions of autophagy-related proteins. Immunofluorescence microscopy revealed a significant increase of LC3B puncta in POS-treated ERMS cells. Furthermore, POS treatment led to a significant inhibition of tumor growth in mice bearing ERMS. Our findings could provide a theoretical basis and have important clinical implications in developing POS as a promising agent against ERMS by targeting Hedgehog pathway.

The Cell Cycle Checkpoint Gene, RAD17 rs1045051, Is Associated with Prostate Cancer Risk.

Human RAD17, as an agonist of checkpoint signaling, plays an essential role in mediating DNA damage. This hospital-based case-control study aimed to explore the association between RAD17 rs1045051, a missense sin-gle nucleotide polymorphism (SNP), and prostate cancer risk. Subjects were 358 prostate cancer patients and 314 cancer-free urology patients undergoing treatment at the Zhujiang Hospital of Southern Medical University in China. RAD17 gene polymorphism rs1045051 was evaluated by the SNaPshot method. Compared with the RAD17 gene polymorphism rs1045051 AA genotype, there was a higher risk of prostate cancer for the CC gen-otype (adjusted odds ratio [AOR] = 1.731, 95% confidence interval [95%CI] = 1.031-2.908, p = 0.038). Compared with the A allele, the C allele was significantly associated with the disease status (AOR = 1.302, 95%CI = 1.037-1.634, p = 0.023). All these findings indicate that in the SNP rs1045051, both the CC genotype and C allele may have a substantial influence on the prostate cancer risk.

Discovery and Validation of Nitroxoline as a Novel STAT3 Inhibitor in Drug-resistant Urothelial Bladder Cancer.

Repeated cycles of first-line chemotherapy drugs such as doxorubicin (DOX) and cisplatin (CIS) trigger frequent chemoresistance in recurrent urothelial bladder cancer (UBC). Nitroxoline (NTX), an antibiotic to treat urinary tract infections, has been recently repurposed for cancer treatment. Here we aimed to investigate whether NTX suppresses drug-resistant UBC and its molecular mechanism. The drug-resistant cell lines T24/DOX and T24/CIS were established by continual exposure of parental cell line T24 to DOX and CIS, respectively. T24/DOX and T24/CIS cells were resistant to DOX and CIS, respectively, but they were sensitive to NTX time- and dose-dependently. Overexpressions of STAT3 and P-glycoprotein (P-gp) were identified in T24/DOX and T24/CIS, which could be reversed by NTX. Western blot revealed that NTX downregulated p-STAT3, c-Myc, Cyclin D1, CDK4, CDK6, Bcl-xL, Mcl-1, and Survivin, which were further confirmed by Stattic, a selective STAT3 inhibitor. In vivo, NTX exhibited the significant anti-tumor effect in T24/DOX and T24/CIS tumor-bearing mice. These results suggested that NTX-induced P-gp reversal, G0/G1 arrest, and apoptosis in drug-resistant UBC were mediated by inhibition of STAT3 signaling. Our findings repurpose NTX as a novel STAT3 inhibitor to induce P-gp reversal, G0/G1 arrest, and apoptosis in drug-resistant UBC.

The role of Wnt signaling in male reproductive physiology and pathology.

Accumulating evidence has shown that Wnt signaling is deeply involved in male reproductive physiology, and malfunction of the signal path can cause pathological changes in genital organs and sperm cells. These abnormalities are diverse in manifestation and have been constantly found in the knockout models of Wnt studies. Nevertheless, most of the research solely focused on a certain factor in the Wnt pathway, and there are few reports on the overall relation between Wnt signals and male reproductive physiology. In our review, Wnt findings relating to the reproductive system were sought and summarized in terms of Wnt ligands, Wnt receptors, Wnt intracellular signals and Wnt regulators. By sorting out and integrating relevant functions, as well as underlining the controversies among different reports, our review aims to offer an overview of Wnt signaling in male reproductive physiology and pathology for further mechanistic studies.

Multicomponent Spatial-Temporal Graph Attention Convolution Networks for Traffic Prediction with Spatially Sparse Data.

Predicting traffic data on traffic networks is essential to transportation management. It is a challenging task due to the complicated spatial-temporal dependency. The latest studies mainly focus on capturing temporal and spatial dependencies with spatially dense traffic data. However, when traffic data become spatially sparse, existing methods cannot capture sufficient spatial correlation information and thus fail to learn the temporal periodicity sufficiently. To address these issues, we propose a novel deep learning framework, Multi-component Spatial-Temporal Graph Attention Convolutional Networks (MSTGACN), for traffic prediction, and we successfully apply it to predicting traffic flow and speed with spatially sparse data. MSTGACN mainly consists of three independent components to model three types of periodic information. Each component in MSTGACN combines dilated causal convolution, graph convolution layer, and the weight-shared graph attention layer. Experimental results on three real-world traffic datasets, METR-LA, PeMS-BAY, and PeMSD7-sparse, demonstrate the superior performance of our method in the case of spatially sparse data.

Nitroxoline inhibits bladder cancer progression by reversing EMT process and enhancing anti-tumor immunity.

Nitroxoline is considered to be an effective treatment for the urinary tract infections. Recently, it has been found to be effective against several cancers. However, few studies have examined the anti-tumor activity of nitroxoline in bladder cancer. The purpose of the study was to reveal the possible mechanisms how nitroxoline inhibited bladder cancer progression. In vitro assay, we demonstrated that nitroxoline inhibited bladder cancer cell growth and migration in a concentration-related manner. Western blot analysis demonstrated that nitroxoline downregulated the expressions of epithelial mesenchymal transition (EMT)-related proteins. Furthermore, treatment with nitroxoline in the C3H/He mice bladder cancer subcutaneous model resulted in significant inhibition of tumor growth. Moreover, the percentage of myeloid-derived suppressor cells (MDSC) in peripheral blood cells significantly decreased after treatment of nitroxoline. Taken together, our results suggested that nitroxoline may be used as a potential drug for bladder cancer.

One-Pot Generation of Functionalized Benzynes from Readily Available 2-Hydroxyphenylboronic Acids.

We developed a one-pot method for the generation of benzynes from a range of readily available 2-hydroxyphenylboronic acids. This method features the in situ activation of both boronic acid and hydroxyl groups of the substrate to enhance benzyne generation at 60 °C. Such mild conditions facilitate the generation of functionalized benzynes that immediately react with diverse arynophiles to produce multisubstituted fused benzenes.