A topological nodal line semi-metal with a negative Poisson's ratio in a three-dimensional carbon network with sp2 hybridization.

In carbon allotropes, a series of topological semi-metals have been predicted, but both novel electronic properties and mechanical characteristics, e.g., a negative Poisson's ratio (NPR), are rarely discovered in the same sp2 type system. Here, a new three-dimensional carbon network, named WZGN, constructed from distorted one-dimensional zigzag graphene nanoribbons is proposed. The stability of the system is fully ensured by the phonon dispersion, AIMD simulation, and binding energy calculations. Besides, it is found that the system holds both topologically protected nodal line semi-metal properties together with an NPR property. Especially, the value of the NPR can exceed -0.36 when 21% uniaxial tensile strain along the c'-direction is applied. Our findings point out that nodal line semi-metals can be compatible with intrinsic NPR properties in a wide strain range in carbon systems with sp2 hybridization, suggesting possible applications in mechanical and electronics fields.

De novo design of dual-target JAK2, SMO inhibitors based on deep reinforcement learning, molecular docking and molecular dynamics simulations.

Triple-negative breast cancer (TNBC) and HER2-positive breast cancer are particularly aggressive and the effectiveness of current therapies for them is limited. TNBC lacks effective therapies and HER2-positive cancer is often resistant to HER2-targeted drugs after an initial response. The recent studies have demonstrated that the combination of JAK2 inhibitors and SMO inhibitors can effectively inhibit the growth and metastasis of TNBC and HER2-positive drug resistant breast cancer cells. In this study, deep reinforcement learning was used to learn the characteristics of existing small molecule inhibitors of JAK2 and SMO, and to generate a novel library of small molecule compounds that may be able to inhibit both JAK2 and SMO. Subsequently, the molecule library was screened by molecular docking and a total of 7 compounds were selected out as dual inhibitors of JAK2 and SMO. Molecular dynamics simulations and binding free energies showed that the top three compounds stably bound to both JAK2 and SMO proteins. The binding free energies and hydrogen bond occupancy of key amino acids indicate that A8976 and A10625 has good properties and could be a potential dual-target inhibitor of JAK2 and SMO.

Evidence of Magnon-Mediated Orbital Magnetism in a Quasi-2D Topological Magnon Insulator.

We explore spin dynamics in Cu(1,3-bdc), a quasi-2D topological magnon insulator. The results show that the thermal evolution of the Landé g factor (g) is anisotropic: gin-plane decreases while gout-of-plane increases with increasing temperature T. Moreover, the anisotropy of the g factor (Δg) and the anisotropy of saturation magnetization (ΔMs) are correlated below 4 K, but they diverge above 4 K. We show that the electronic orbital moment contributes to the g anisotropy at lower T, while the topological orbital moment induced by thermally excited spin chirality dictates the g anisotropy at higher T. Our work suggests an interplay among topology, spin chirality, and orbital magnetism in Cu(1,3-bdc).

Machine learning predicts cancer-associated deep vein thrombosis using clinically available variables.

PURPOSE: To develop and validate machine learning (ML) models for cancer-associated deep vein thrombosis (DVT) and to compare the performance of these models with the Khorana score (KS). METHODS: We randomly extracted data of 2100 patients with cancer between Jan. 1, 2017, and Oct. 31, 2019, and 1035 patients who underwent Doppler ultrasonography were enrolled. Univariate analysis and Lasso regression were applied to select important predictors. Model training and hyperparameter tuning were implemented on 70% of the data using a ten-fold cross-validation method. The remaining 30% of the data were used to compare the performance with seven indicators (area under the receiver operating characteristic curve [AUC], sensitivity, specificity, accuracy, balanced accuracy, Brier score, and calibration curve), among all five ML models (linear discriminant analysis [LDA], logistic regression [LR], classification tree [CT], random forest [RF], and support vector machine [SVM]), and the KS. RESULTS: The incidence of cancer-associated DVT was 22.3%. The top five predictors were D-dimer level, age, Charlson Comorbidity Index (CCI), length of stay (LOS), and previous VTE (venous thromboembolism) history according to RF. Only LDA (AUC = 0.773) and LR (AUC = 0.772) outperformed KS (AUC = 0.642), and combination with D-dimer showed improved performance in all models. A nomogram and web calculator https://webcalculatorofcancerassociateddvt.shinyapps.io/dynnomapp/ were used to visualize the best recommended LR model. CONCLUSION: This study developed and validated cancer-associated DVT predictive models using five ML algorithms and visualized the best recommended model using a nomogram and web calculator. The nomogram and web calculator developed in this study may assist doctors and nurses in evaluating individualized cancer-associated DVT risk and making decisions. However, other prospective cohort studies should be conducted to externally validate the recommended model.

Design of SARS-CoV-2 Mpro, PLpro dual-target inhibitors based on deep reinforcement learning and virtual screening.

Background: Since December 2019, SARS-CoV-2 has continued to spread rapidly around the world. The effective drugs may provide a long-term strategy to combat this virus. The main protease (Mpro) and papain-like protease (PLpro) are two important targets for the inhibition of SARS-CoV-2 virus replication and proliferation. Materials & methods: In this study, deep reinforcement learning, covalent docking and molecular dynamics simulations were used to identify novel compounds that have the potential to inhibit both Mpro and PLpro. Results & conclusion: Three compounds were identified that can effectively occupy the Mpro protein cavity with the PLpro protein cavity and form high-frequency contacts with key amino acid residues (Mpro: His41, Cys145, Glu166; PLpro: Cys111). These three compounds can be further investigated as potential lead compounds for SARS-CoV-2 inhibitors.

Two-dimensional magnetic metal-organic frameworks with the Shastry-Sutherland lattice.

Inspired by the successful synthesis of Fe/Cu-5,5'-bis(4-pyridyl)(2,2'-bipirimidine) (PBP), a family of two-dimensional (2D) metal-organic frameworks (MOFs) with the Shastry-Sutherland lattice, i.e., transition metal (TM)-PBP (TM = Cr, Mn, Fe, Co, Ni, Cu, Zn) has been systematically investigated by means of first-principles density functional theory calculations and Monte Carlo simulations. Mn-PBP is discovered to be the first ferromagnetic 2D MOF with the Shastry-Sutherland lattice and the Curie temperature is predicted to be about 105 K, while Fe-PBP, TM-PBP (TM = Cr, Co, Ni) and TM-PBP (TM = Cu, Zn) are found to be stripe-order antiferromagnetic, magnetic-dimerized and nonmagnetic, respectively. The electronic structure calculations reveal that TM-PBP MOFs are semiconductors with band gaps ranging from 0.12 eV to 0.85 eV, which could be easily modulated by various methods. Particularly, Mn-PBP would exhibit half-metallic behavior under compressive strain or appropriate electron/hole doping and a Mn-PBP based spintronic device has been proposed. This study not only improves the understanding of the geometric, electronic and magnetic properties of the 2D TM-PBP MOF family, but also provides a novel spin lattice playground for the research of 2D magnetic systems, which has diverse modulating possibilities and rich potential applications.

Diverse anisotropy of phonon transport in two-dimensional group IV-VI compounds: A comparative study.

New classes of two-dimensional (2D) materials beyond graphene, including layered and non-layered, and their heterostructures, are currently attracting increasing interest due to their promising applications in nanoelectronics, optoelectronics and clean energy, where thermal transport is a fundamental physical parameter. In this paper, we systematically investigated the phonon transport properties of the 2D orthorhombic group IV-VI compounds of GeS, GeSe, SnS and SnSe by solving the Boltzmann transport equation (BTE) based on first-principles calculations. Despite their similar puckered (hinge-like) structure along the armchair direction as phosphorene, the four monolayer compounds possess diverse anisotropic properties in many aspects, such as phonon group velocity, Young's modulus and lattice thermal conductivity (κ), etc. Especially, the κ along the zigzag and armchair directions of monolayer GeS shows the strongest anisotropy while monolayer SnS and SnSe show almost isotropy in phonon transport. The origin of the diverse anisotropy is fully studied and the underlying mechanism is discussed in details. With limited size, the κ could be effectively lowered, and the anisotropy could be effectively modulated by nanostructuring, which would extend the applications to nanoscale thermoelectrics and thermal management. Our study offers fundamental understanding of the anisotropic phonon transport properties of 2D materials, and would be of significance for further study, modulation and applications in emerging technologies.

Tinselenidene: a Two-dimensional Auxetic Material with Ultralow Lattice Thermal Conductivity and Ultrahigh Hole Mobility.

By means of extensive ab initio calculations, a new two-dimensional (2D) atomic material tin selenide monolayer (coined as tinselenidene) is predicted to be a semiconductor with an indirect gap (~1.45 eV) and a high hole mobility (of order 10000 cm(2)V(-1)S(-1)), and will bear an indirect-direct gap transition under a rather low strain (<0.5 GPa). Tinselenidene has a very small Young's modulus (20-40 GPa) and an ultralow lattice thermal conductivity (<3 Wm(-1)K(-1) at 300 K), making it probably the most flexible and most heat-insulating material in known 2D atomic materials. In addition, tinseleniden has a large negative Poisson's ratio of -0.17, thus could act as a 2D auxetic material. With these intriguing properties, tinselenidene could have wide potential applications in thermoelectrics, nanomechanics and optoelectronics.

GRP78 upregulation-induced increase in cisplatin sensitivity of SPCA1 lung cancer cells.

BACKGROUND: Glucose regulated protein 78 (GRP78), an endoplasmic reticulum (ER) chaperone, plays a critical role in chemotherapy resistance in a variety of cancers. In this study, we investigated the up-regulation of GRP78 induced by A23187 and its association with the chemotherapeutical sensibility to cisplatin in human lung cancer cell line SPCA1. METHODS: SPCA1 cells were pretreated with A23187 at different concentrations. The expression of GRP78 at the mRNA level was analyzed by RT-PCR; the expression of GRP78 at the protein level was determined by Western blotting and immunofluorescence assay. Cell survival was determined by MTT assay. Cell apoptosis was analyzed by flow cytometry. RESULTS: The expression of GRP78 at both the mRNA and protein levels was obviously induced by A23187 in SPCA1 cells, with an elevation of GRP78 by 2.1-fold at the mRNA level and by 3.8-fold at the protein level compared to the control. There was a dose-dependent response. Survival curve analysis demonstrated that A23187 induction caused a significant reduction of survival for the cells subjected to cisplatin treatment (P < 0.05). After treatment by cisplatin, the percentage of apoptotic cells in the A23187 pretreated group increased about three fold compared with the control group ((27.53 ± 4.32)% vs. (9.25 ± 3.64)%, P < 0.05). CONCLUSIONS: A23187 treatment was fairly effective for the induction of GRP78 in SPCA1 cells at both the mRNA and protein levels. To a certain extent, GRP78 up-regulation by A23187 was associated with the enhancement of drug sensitivity to cisplatin in human lung cancer cell line SPCA1.