Direct Synthesis of α- and ß-2'-Deoxynucleosides with Stereodirecting Phosphine Oxide via Remote Participation.

2'-Deoxynucleosides and analogues play a vital role in drug development, but their preparation remains a significant challenge. Previous studies have focused on ß-2'-deoxynucleosides with the natural ß-configuration. In fact, their isomeric α-2'-deoxynucleosides also exhibit diverse bioactivities and even better metabolic stability. Herein, we report that both α- and ß-2'-deoxynucleosides can be prepared with high yields and stereoselectivity using a remote directing diphenylphosphinoyl (DPP) group. It is particularly efficient to prepare α-2'-deoxynucleosides with an easily accessible 3,5-di-ODPP donor. Instead of acting as a H-bond acceptor on a 2-(diphenylphosphinoyl)acetyl (DPPA) group in our previous studies for syn-facial O-glycosylation, the phosphine oxide moiety here acts as a remote participating group to enable highly antifacial N-glycosylation. This proposed remote participation mechanism is supported by our first characterization of an important 1,5-briged P-heterobicyclic intermediate via variable-temperature NMR spectroscopy. Interestingly, antiproliferative assays led to a α-2'-deoxynucleoside with IC50 values in the low micromole range against central nervous system tumor cell lines SH-SY5Y and LN229, whereas its ß-anomer exhibited no inhibition at 100 µM. Furthermore, the DPP group significantly enhanced the antitumor activities by 10 times.

WSGMB: weight signed graph neural network for microbial biomarker identification.

The stability of the gut microenvironment is inextricably linked to human health, with the onset of many diseases accompanied by dysbiosis of the gut microbiota. It has been reported that there are differences in the microbial community composition between patients and healthy individuals, and many microbes are considered potential biomarkers. Accurately identifying these biomarkers can lead to more precise and reliable clinical decision-making. To improve the accuracy of microbial biomarker identification, this study introduces WSGMB, a computational framework that uses the relative abundance of microbial taxa and health status as inputs. This method has two main contributions: (1) viewing the microbial co-occurrence network as a weighted signed graph and applying graph convolutional neural network techniques for graph classification; (2) designing a new architecture to compute the role transitions of each microbial taxon between health and disease networks, thereby identifying disease-related microbial biomarkers. The weighted signed graph neural network enhances the quality of graph embeddings; quantifying the importance of microbes in different co-occurrence networks better identifies those microbes critical to health. Microbes are ranked according to their importance change scores, and when this score exceeds a set threshold, the microbe is considered a biomarker. This framework's identification performance is validated by comparing the biomarkers identified by WSGMB with actual microbial biomarkers associated with specific diseases from public literature databases. The study tests the proposed computational framework using actual microbial community data from colorectal cancer and Crohn's disease samples. It compares it with the most advanced microbial biomarker identification methods. The results show that the WSGMB method outperforms similar approaches in the accuracy of microbial biomarker identification.

Thermal Dynamics of Charge Density Wave Pinning in ZrTe_{3}.

Impurity pinning has long been discussed to have a profound effect on the dynamics of an incommensurate charge density wave (CDW), which would otherwise slide through the lattice without resistance. Here, we visualize the impurity pinning evolution of the CDW in ZrTe_{3} using the variable temperature scanning tunneling microscopy. At low temperatures, we observe a quasi-1D incommensurate CDW modulation moderately correlated to the impurity positions, indicating a weak impurity pinning. As we raise the sample temperature, the CDW modulation gets progressively weakened and distorted, while the correlation with the impurities becomes stronger. Above the CDW transition temperature, short-range modulations persist with the phase almost all pinned by impurities. The evolution from weak to strong impurity pinning through the CDW transition can be understood as a result of losing phase rigidity.

Surface geometric and electronic structures of BaFe2As2(001).

BaFe2As2 exhibits properties that are characteristic of the parent compounds of the newly discovered iron (Fe)-based high-T(C) superconductors. By combining real-space imaging of scanning tunneling microscopy and spectroscopy (STM+STS) with momentum-space quantitative low-energy electron diffraction (LEED), we have identified the surface plane of cleaved BaFe2As2 crystals as the As terminated Fe-As layer-the plane where superconductivity occurs. LEED and STM+STS data on the BaFe2As2(001) surface indicate an ordered arsenic (As) terminated metallic surface without reconstruction or lattice distortion. It is surprising that STM images the different Fe-As orbitals associated with the orthorhombic structure, but not the As atoms in the surface plane.