Diffusion-Weighted Magnetic Resonance Imaging and Morphological Characteristics Evaluation for Outcome Prediction of Primary Debulking Surgery for Advanced High-Grade Serous Ovarian Carcinoma.

BACKGROUND: Preoperative assessment of whether a successful primary debulking surgery (PDS) can be performed in patients with advanced high-grade serous ovarian carcinoma (HGSOC) remains a challenge. A reliable model to precisely predict resectability is highly demanded. PURPOSE: To investigate the value of diffusion-weighted MRI (DW-MRI) combined with morphological characteristics to predict the PDS outcome in advanced HGSOC patients. STUDY TYPE: Prospective. SUBJECTS: A total of 95 consecutive patients with histopathologically confirmed advanced HGSOC (ranged from 39 to 77 years). FIELDS STRENGTH/SEQUENCE: A 3.0 T, readout-segmented echo-planar DWI. ASSESSMENT: The MRI morphological characteristics of the primary ovarian tumor, a peritoneal carcinomatosis index (PCI) derived from DWI (DWI-PCI) and histogram analysis of the primary ovarian tumor and the largest peritoneal carcinomatosis were assessed by three radiologists. Three different models were developed to predict the resectability, including a clinicoradiologic model combing MRI morphological characteristic with ascites and CA125 level; DWI-PCI alone; and a fusion model combining the clinical-morphological information and DWI-PCI. STATISTICAL TESTS: Multivariate logistic regression analyses, receiver operating characteristic (ROC) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI) were used. A P < 0.05 was considered to be statistically significant. RESULTS: Sixty-seven cases appeared as a definite mass, whereas 28 cases as an infiltrative mass. The morphological characteristics and DWI-PCI were independent factors for predicting the resectability, with an AUC of 0.724 and 0.824, respectively. The multivariable predictive model consisted of morphological characteristics, CA-125, and the amount of ascites, with an incremental AUC of 0.818. Combining the application of a clinicoradiologic model and DWI-PCI showed significantly higher AUC of 0.863 than the ones of each of them implemented alone, with a positive NRI and IDI. DATA CONCLUSIONS: The combination of two clinical factors, MRI morphological characteristics and DWI-PCI provide a reliable and valuable paradigm for the noninvasive prediction of the outcome of PDS. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Development and validation of MRI-based radiomics model to predict recurrence risk in patients with endometrial cancer: a multicenter study.

OBJECTIVES: To develop a fusion model based on clinicopathological factors and MRI radiomics features for the prediction of recurrence risk in patients with endometrial cancer (EC). METHODS: A total of 421 patients with histopathologically proved EC (101 recurrence vs. 320 non-recurrence EC) from four medical centers were included in this retrospective study, and were divided into the training (n = 235), internal validation (n = 102), and external validation (n = 84) cohorts. In total, 1702 radiomics features were respectively extracted from areas with different extensions for each patient. The extreme gradient boosting (XGBoost) classifier was applied to establish the clinicopathological model (CM), radiomics model (RM), and fusion model (FM). The performance of the established models was assessed by the discrimination, calibration, and clinical utility. Kaplan-Meier analysis was conducted to further determine the prognostic value of the models by evaluating the differences in recurrence-free survival (RFS) between the high- and low-risk patients of recurrence. RESULTS: The FMs showed better performance compared with the models based on clinicopathological or radiomics features alone but with a reduced tendency when the peritumoral area (PA) was extended. The FM based on intratumoral area (IA) [FM (IA)] had the optimal performance in predicting the recurrence risk in terms of the ROC, calibration curve, and decision curve analysis. Kaplan-Meier survival curves showed that high-risk patients of recurrence defined by FM (IA) had a worse RFS than low-risk ones of recurrence. CONCLUSIONS: The FM integrating intratumoral radiomics features and clinicopathological factors could be a valuable predictor for the recurrence risk of EC patients. CLINICAL RELEVANCE STATEMENT: An accurate prediction based on our developed FM (IA) for the recurrence risk of EC could facilitate making an individualized therapeutic decision and help avoid under- or over-treatment, therefore improving the prognosis of patients. KEY POINTS: • The fusion model combined clinicopathological factors and radiomics features exhibits the highest performance compared with the clinicopathological model and radiomics model. • Although higher values of area under the curve were observed for all fusion models, the performance tended to decrease with the extension of the peritumoral region. • Identifying patients with different risks of recurrence, the developed models can be used to facilitate individualized management.

Blockade of Indoleamine 2,3-Dioxygenase attenuates lipopolysaccharide-induced kidney injury by inhibiting TLR4/NF-κB signaling.

Blockade of indoleamine 2,3-dioxygenase (IDO) has been shown to alleviate lipopolysaccharide (LPS)-induced endotoxic shock and reduce sepsis mortality, but its effect on LPS-induced kidney damage has not been reported. Herein, we established a mouse kidney injury model by intraperitoneal injection of 10 mg/kg LPS and established an in vitro renal tubular epithelial cell injury model by stimulating TCMK-1 cells with 10 mg/L LPS. We found that pretreatment with 1-methyl tryptophan (1-MT), an IDO inhibitor, significantly improved LPS-induced mouse survival, and IDO knockout (KO) mice also had higher survival rates after LPS exposure than wild-type mice. At the same time, IDO KO or pretreatment with 1-MT not only reduced serum creatinine, blood urea nitrogen, renal tubular injury pathological score, but also inflammatory factors and oxidative stress status in serum or kidney of LPS-exposed mice. In vitro, blockade of IDO with 1-MT significantly inhibited LPS-induced apoptosis, inflammation and oxidative stress in TCMK-1 cells. In addition, blockade of IDO significantly inhibited LPS-activated TLR4/NF-κB signaling pathway in kidney of mice or in TCMK-1 cells. In conclusion, our results suggested that blockade of IDO attenuated kidney inflammation, apoptosis and oxidative stress to protect against LPS-induced septic kidney injury via inhibiting the TLR4/NF-κB signaling pathway.

Ethanol-Induced Hydrogen Insertion in Ultrafine IrPdH Boosts pH-Universal Hydrogen Evolution.

Engineering Pt-free catalysts for hydrogen evolution reaction (HER) with high activity and stability is of great significance in electrochemical hydrogen production. Herein, in situ chemical H intercalation into ultrafine Pd to activate this otherwise HER-inferior material to form the ultrafine IrPdH hydride as an efficient and stable HER electrocatalyst is proposed. The formation of PdIrH depends on a new hydrogenation strategy via using ethanol as the hydrogen resource. It is demonstrated that H atoms in IrPdH originate from the OH and CH2  of ethanol, which fills the gap of ethanol as the hydrogen source for the preparation of Pd hydride. Thanks to the incorporation of H/Ir atoms and ultrafine structure, the IrPdH exhibits superior HER activity and stability in the whole pH range. The IrPdH delivers very low overpotentials of 14, 25 and 60 mV at a current density of 10 mA cm-2 respectively in 0.5 m H2 SO4 , 1 m KOH, and 1 m PBS electrolytes, which are much better than those of commercial Pt/C and most reported noble metal electrocatalysts. Theoretical calculations confirm that interstitial hydrogen availably refines the electronic density of Pd and Ir sites, which optimizes the adsorption of *H and leads to the significant enhancement of HER performance.

Clinical Features and Prognosis Analysis of Hormone Receptor-Positive, HER2-Negative Breast Cancer with Differential Expression Levels of Estrogen and Progesterone Receptors: A 10-Year Retrospective Study.

Background: Estrogen and progesterone receptor status can predict breast cancer patient prognosis and treatment sensitivity, but research on low ER and PR levels and expression balance remains limited. Methods: From January 2010 to October 2016, 283 ER+/PR+/HER2-breast cancer patients who met the inclusion criteria were enrolled and divided into the H group (ER > 10%, N = 261) and the L group (1% ≤ ER ≤ 10%, N = 22). Groups were further divided into the HH group (ER > 10%/PR > 20%, N = 201), the HL group (ER > 10%/ER 1% ≤ PR ≤ 20% PR, N = 60), the LH group (1% ≤ ER ≤ 10%/PR > 20%, N = 5), and the LL group (1% ≤ ER ≤ 10%/1% ≤ PR ≤ 20%, N = 17). The LH group was excluded due to its small size, leaving the clinical and prognostic characteristics of 2 large groups and 3 subgroups to be analyzed. Results: L group patients had significantly more stage N2 axillary lymph nodes than H group patients (31.8% vs. 9.2%, P = 0.007). Age (P = 0.011), menopause status (P = 0.001), and tumor size (P = 0.024) were significantly different in the HL vs. HH and LL groups. Five-year DFS (94.6% vs. 77.0%, P < 0.001) and 5-year OS (97.2% vs. 85.8%, P = 0.001) rates significantly differed between HH and HL. No significant differences in 5-year DFS (77.0% vs. 81.9%, P = 0.564) or 5-year OS (85.8% vs. 87.8%, P = 0.729) rates were observed between HL and LL; the OS rates of HL and LL were similar. Conclusion: In the group of ER+/PR+/HER2-patients, there was no significant prognostic difference between ER-low positive and ER-high positive groups, but low PR expression was significantly associated with a worse prognosis. The role of ER and PR balance in breast cancer progression and individualized treatment requires further investigation.

How to Look for Compounds: Predictive Screening and in†situ Studies in Na-Zn-Bi System.

Here, the combination of theoretical computations followed by rapid experimental screening and in situ diffraction studies is demonstrated as a powerful strategy for novel compounds discovery. When applied for the previously "empty" Na-Zn-Bi system, such an approach led to four novel phases. The compositional space of this system was rapidly screened via the hydride route method and the theoretically predicted NaZnBi (PbClF type, P4/nmm) and Na11 Zn2 Bi5 (Na11 Cd2 Sb5 type, P 1 ‾ ) phases were successfully synthesized, while other computationally generated compounds on the list were rejected. In addition, single crystal X-ray diffraction studies of NaZnBi indicate minor deviations from the stoichiometric 1 : 1 : 1 molar ratio. As a result, two isostructural (PbClF type, P4/nmm) Zn-deficient phases with similar compositions, but distinctly different unit cell parameters were discovered. The vacancies on Zn sites and unit cell expansion were rationalized from bonding analysis using electronic structure calculations on stoichiometric "NaZnBi". In-situ synchrotron powder X-ray diffraction studies shed light on complex equilibria in the Na-Zn-Bi system at elevated temperatures. In particular, the high-temperature polymorph HT-Na3 Bi (BiF3 type, Fm 3 ‾ m) was obtained as a product of Na11 Zn2 Bi5 decomposition above 611 K. HT-Na3 Bi cannot be stabilized at room temperature by quenching, and this type of structure was earlier observed in the high-pressure polymorph HP-Na3 Bi above 0.5 GPa. The aforementioned approach of predictive synthesis can be extended to other multinary systems.

Ternary Zinc Antimonides Unlocked Using Hydride Synthesis.

Three new sodium zinc antimonides Na11Zn2Sb5, Na4Zn9Sb9, and NaZn3Sb3 were synthesized utilizing sodium hydride NaH as a reactive sodium source. In comparison to the synthesis using sodium metal, salt-like NaH can be ball-milled, leading to the easy and uniform mixing of precursors in the desired stoichiometric ratios. Such comprehensive compositional control enables a fast screening of the Na-Zn-Sb system and identification of new compounds, followed by their preparation in bulk with high purity. Na11Zn2Sb5 crystallizes in the triclinic P1 space group (No. 2, Z = 2, a = 8.8739(6) Å, b = 10.6407(7) Å, c = 11.4282(8) Å, α = 103.453(2)°, ß = 96.997(2)°, γ = 107.517(2)°) and features polyanionic [Zn2Sb5]11- clusters with unusual 3-coordinated Zn atoms. Both Na4Zn9Sb9 (Z = 4, a = 28.4794(4) Å, b = 4.47189(5) Å, c = 17.2704(2) Å, ß = 98.3363(6)°) and NaZn3Sb3 (Z = 8, a = 32.1790(1) Å, b = 4.51549(1) Å, c = 9.64569(2) Å, ß = 98.4618(1)°) crystallize in the monoclinic C2/m space group (No. 12) and have complex new structure types. For both compounds, their frameworks are built from ZnSb4 distorted tetrahedra, which are linked via edge-, vertex-sharing, or both, while Na cations fill in the framework channels. Due to the complex structures, Na4Zn9Sb9 and NaZn3Sb3 compounds exhibit low thermal conductivities (0.97-1.26 W·m-1 K-1) at room temperature, positive Seebeck coefficients (19-32 µV/K) suggestive of holes as charge carriers, and semimetallic electrical resistivities (∼1.0-2.3 × 10-4 Ω·m). Na4Zn9Sb9 and NaZn3Sb3 decompose into the equiatomic NaZnSb above ∼800 K, as determined by in situ synchrotron powder X-ray diffraction. The discovery of multiple ternary compounds highlights the importance of judicious choice of the synthetic method.

lncRNA Eif4g2 improves palmitate-induced dysfunction of mouse ß-cells via modulation of Nrf2 activation.

Chronic oxidative stress resulting from hyperlipidemia is thought to be a key pathogenic driver of pancreatic ß-cell dysfunction in leading to the onset of type 2 diabetes mellitus (T2DM). Long non-coding RNAs (lncRNAs) have been increasingly recognized to regulate dysfunction within pancreatic ß-cells in the context of T2DM. In the present study, we sought to comprehensively analyze the roles of lncRNAs in dysfunctional ß-cells and mouse islets. Analyses of INS-1E cells were performed by RNA-seq and qRT-PCR after treating with or without 0.5 mM palmitate for 4 days, leading us to identify the novel lncRNA Eif4g2 (lncEif4g2) as a functional regulator within these cells. When we overexpressed lncEif4g2 in INS-1E ß-cells and mouse islets, this was sufficient for the reversal of palmitate-mediated reductions in cell viability, insulin production, ATP production by mitochondria, and creation of intracellular reactive oxygen species (ROS) and the dysfunction of mouse islets, with nuclear factor erythroid 2 related factor 2 (Nrf2) activation also being observed. In contrast, when lncEif4g2 was knocked down this led INS-1E cells and mouse islets to become more sensitive to palmitate-induced dysfunction, with reduced Nrf2 nuclear translocation also being detected. When antioxidants were used to treat INS-1E cells and mouse islets, however, these negative effects were reversed. Additional functional analyses revealed lncEif4g2 to be capable of directly binding to miR-3074-5p in ß-cells, with the expression of lncEif4g2 and miR-3074-5p being negatively correlated with one another. We further found that cAMP-responsive element binding-protein (CREB) was a miR-3074-5p target gene in these cells, thus at least in part serving as a functional mediator of the lncEif4g2/miR-3074-5p axis within dysfunctional ß-cells. In summary, our results thus reveal that lncEif4g2 is able to indirectly regulate the expression of CREB via targeting miR-3074-5p in INS-1E cells and mouse islets, thereby leading to enhanced Nrf2 activation.

Identifying potential functional lncRNAs in metabolic syndrome by constructing a lncRNA-miRNA-mRNA network.

The metabolic syndrome (MS) is a cluster of interrelated risk factors including diabetes mellitus, abdominal obesity, high cholesterol, and hypertension, which can significantly increase mortality and disability. Accumulating evidence suggest that long non-coding RNAs (lncRNAs) are involved in the pathogenesis of human metabolic diseases. However, little is known about the regulatory role of lncRNAs in MS. In this work, we proposed a method for identifying potential MS-associated lncRNAs by constructing an lncRNA-miRNA-mRNA network (LMMN). Firstly, we constructed LMMN by integrating MS-associated genes, miRNA-mRNA interactions, miRNA-lncRNA interactions and mRNA/miRNA expression profiles in patients with MS. Then, we predicted potential MS-associated lncRNAs based on the topological properties of LMMN. As a result, we identified XIST as the most important lncRNA in LMMN. Furthermore, we focused on XIST/miR-214-3p and mir-181a-5p/PTEN axis and validated their expression in MS using real-time quantitative polymerase chain reaction (RT-qPCR). The RT-qPCR results showed that the expression of XIST and PTEN was significantly decreased (P < 0.05) while the expression of miR-214-3p was significantly increased (P < 0.05) in peripheral blood mononuclear cells (PBMCs) of patients with MS, compared with healthy controls. In addition, correlation analysis showed that XIST was negatively correlated with serum C peptide and PTEN was positively correlated with BMI of MS patients. Our findings provided new evidence for further exploring the regulatory role of XIST and other lncRNAs in MS.

Stabilizing the crystal structures of NaFePO4 with Li substitutions.

Due to the high cost and insufficient resources of lithium, alternative sodium-ion batteries have been widely investigated for large-scale applications. NaFePO4 has the highest theoretical capacity of 154 mA h g-1 among the iron-based phosphates, which makes it an attractive cathode material for Na-ion batteries. Experimentally, LiFePO4 has been highly successful as a cathode material in Li-ion batteries because its olivine crystal structure provides a stable framework during battery cycling. In NaFePO4, maricite replaces olivine as the most stable phase. However, the maricite phase is experimentally found to be electrochemically inactive under normal battery operating voltages (0-4.5 V). We found that partial substitutions of Na with Li stabilize the olivine structure and may be a way to improve the performance of NaFePO4 cathodes. Using the previously developed structural LiFePO4 database, we examined the low-energy crystal structures in the system when we replace Li with Na. The known maricite and olivine NaFePO4 phases are reconfirmed and an unreported phase with energy between them is identified by our calculations. Besides, the Li-doped olivine type compound LixNa1-xFePO4 with mixed alkali ions retains better energetic stability compared with the other two types of structures of the same composition, as long as the proportion of Li exceeds 0.25. The thermodynamic stability of o-type LixNa1-xFePO4 can be further improved at finite temperatures. The primary limitation of the calculations is that we mainly focus on the zero-temperature condition; however, the relative stability of the structures may vary depending on the ambient temperature.

Catalytic Effect of Hydrogen Bond on Oxhydryl Dehydrogenation in Methanol Steam Reforming on Ni(111).

Dehydrogenation of H3COH and H2O are key steps of methanol steam reforming on transition metal surfaces. Oxhydryl dehydrogenation reactions of HxCOH (x = 0-3) and OH on Ni (111) were investigated by DFT calculations with the OptB88-vdW functional. The transition states were searched by the climbing image nudged elastic band method and the dimer method. The activation energies for the dehydrogenation of individual HxCOH* are 68 to 91 kJ/mol, and reduced to 12-17 kJ/mol by neighboring OH*. Bader charge analysis showed the catalysis role of OH* can be attributed to the effect of hydrogen bond (H-bond) in maintaining the charge of oxhydryl H in the reaction path. The mechanism of H-bond catalysis was further demonstrated by the study of OH* and N* assisted dehydrogenation of OH*. Due to the universality of H-bond, the H-bond catalysis shown here, is of broad implication for studies of reaction kinetics.

Fe-Si networks and charge/discharge-induced phase transitions in Li2FeSiO4 cathode materials.

Structural phase transitions of electrode materials are responsible for poor reversibility during charge/discharge cycling in Li-ion batteries. Using previously developed structural databases, we investigate a structural landscape for LixFeSiO4 systems at x = 1. Starting with low-energy Li2FeSiO4 crystal structures, we explore the crystal structures of the material in different states of charge. The as-prepared Li2FeSiO4 materials adopt low energy structures characterized by two-dimensional (2D) Fe-Si networks. After the removal of one Li per formula unit to form LiFeSiO4, the structures with three-dimensional (3D) diamond-like Fe-Si networks become more energetically favorable without a significant impact on the charge capacity, which agrees with previous experimental and theoretical work. However, we reveal that the structure with a 3D diamond-like Fe-Si network can further transform into a new structure at x = 1. And the Li atom is hard to reinsert into these new structures. Consequently the system is prevented from returning to the Li2FeSiO4 state. We believe that the formation of this new structure plays an important role in the loss of reversible capacity of Li2FeSiO4 electrode materials.

Construction of competitive endogenous RNA network reveals regulatory role of long non-coding RNAs in type 2 diabetes mellitus.

Increasing epidemic of type 2 diabetes mellitus (T2DM) and its comorbidities makes it urgent to understand the pathogenesis and regulatory mechanism. However, little is known about the regulatory role of lncRNAs in diabetes. Here, we constructed a T2DM-related competitive endogenous RNA (ceRNA) network (DMCN) to explore biological function of lncRNAs during the development of diabetes mellitus. This network contained 351 nodes including 98 mRNAs, 86 microRNAs and 167 lncRNAs. Functional analysis showed that the mRNAs in DMCN were annotated into some diabetes-related pathways. Furthermore, mTOR-centred subnetwork was extracted and ncRNA-involved mTOR pathway was established. Finally, we validated that NEAT1 was potentially communicated with mTOR signalling target protein mLST8 via the association with miR-181b. These findings provide significant insight into lncRNA regulatory network in T2DM.

A genetic algorithm encoded with the structural information of amino acids and dipeptides for efficient conformational searches of oligopeptides.

The genetic algorithm (GA) is an intelligent approach for finding minima in a highly dimensional parametric space. However, the success of GA searches for low energy conformations of biomolecules is rather limited so far. Herein an improved GA scheme is proposed for the conformational search of oligopeptides. A systematic analysis of the backbone dihedral angles of conformations of amino acids (AAs) and dipeptides is performed. The structural information is used to design a new encoding scheme to improve the efficiency of GA search. Local geometry optimizations based on the energy calculations by the density functional theory are employed to safeguard the quality and reliability of the GA structures. The GA scheme is applied to the conformational searches of Lys, Arg, Met-Gly, Lys-Gly, and Phe-Gly-Gly representative of AAs, dipeptides, and tripeptides with complicated side chains. Comparison with the best literature results shows that the new GA method is both highly efficient and reliable by providing the most complete set of the low energy conformations. Moreover, the computational cost of the GA method increases only moderately with the complexity of the molecule. The GA scheme is valuable for the study of the conformations and properties of oligopeptides. © 2016 Wiley Periodicals, Inc.

Electronic structures of intermolecular hydrogen bond contacts with solute in aqueous solution: glycine as a working prototype.

The intermolecular hydrogen bond (H-bond) interactions play vital roles in many biological systems. Despite continued interest, the nature of their electronic structures has remained elusive. Based on the unique features of aqueous solution, a simple model depicting the H-bond electronic states by orbital hybridizations is developed. The model is demonstrated by reproducing the experimental IR data and yielding favorable solute-solvent interactions for the prototype glycine. The H-bond state for solute H, O and N atoms is found to be characterized by sp(1), sp(2), and sp(3) hybridizations, respectively. The model provides a new way for probing the intricate solute-solvent contacts.

Theoretical spectroscopic studies on chemical and electronic structures of arginylglycine.

The energy differences between canonical and zwitterionic isomers of arginylglycine (ArgGly) at the CCSD/aug-cc-pVDZ level are too small (less than 1 kcal mol(-1)) to determine the dominant form in the gas phase from the energetic point of view. First-principles simulations have been performed for near-edge X-ray absorption fine-structure (NEXAFS) spectra and X-ray photoelectron spectra (XPS) at C, N and O K-edges, as well as for infrared (IR) spectra of neutral ArgGly. Noticeable spectral differences were found which enable the unambiguous identification of different neutral groups. We thus demonstrate X-ray spectroscopy as a powerful technique to study the conformation dependent chemical and electronic properties of neutral ArgGly.

Interleaved imaging of cerebral hemodynamics and blood flow index to monitor ischemic stroke and treatment in rat by volumetric diffuse optical tomography.

Diffuse optical tomography (DOT) has been used by several groups to assess cerebral hemodynamics of cerebral ischemia in humans and animals. In this study, we combined DOT with an indocyanine green (ICG)-tracking method to achieve interleaved images of cerebral hemodynamics and blood flow index (BFI) using two middle cerebral artery occlusion (MCAO) rat models. To achieve volumetric images with high-spatial resolution, we first integrated a depth compensation algorithm (DCA) with a volumetric mesh-based rat head model to generate three-dimensional (3D) DOT on a rat brain atlas. Then, the experimental DOT data from two rat models were collected using interleaved strategy for cerebral hemodynamics and BFI during and after ischemic stroke, with and without a thrombolytic therapy for the embolic MCAO model. The acquired animal data were further analyzed using the integrated rat-atlas-guided DOT method to form time-evolving 3D images of both cerebral hemodynamics and BFI. In particular, we were able to show and identify therapeutic outcomes of a thrombolytic treatment applied to the embolism-induced ischemic model. This paper demonstrates that volumetric DOT is capable of providing high-quality, interleaved images of cerebral hemodynamics and blood perfusion in small animals during and after ischemic stroke, with excellent 3D visualization and quantifications.

Atlas-guided volumetric diffuse optical tomography enhanced by generalized linear model analysis to image risk decision-making responses in young adults.

Diffuse optical tomography (DOT) is a variant of functional near infrared spectroscopy and has the capability of mapping or reconstructing three dimensional (3D) hemodynamic changes due to brain activity. Common methods used in DOT image analysis to define brain activation have limitations because the selection of activation period is relatively subjective. General linear model (GLM)-based analysis can overcome this limitation. In this study, we combine the atlas-guided 3D DOT image reconstruction with GLM-based analysis (i.e., voxel-wise GLM analysis) to investigate the brain activity that is associated with risk decision-making processes. Risk decision-making is an important cognitive process and thus is an essential topic in the field of neuroscience. The Balloon Analog Risk Task (BART) is a valid experimental model and has been commonly used to assess human risk-taking actions and tendencies while facing risks. We have used the BART paradigm with a blocked design to investigate brain activations in the prefrontal and frontal cortical areas during decision-making from 37 human participants (22 males and 15 females). Voxel-wise GLM analysis was performed after a human brain atlas template and a depth compensation algorithm were combined to form atlas-guided DOT images. In this work, we wish to demonstrate the excellence of using voxel-wise GLM analysis with DOT to image and study cognitive functions in response to risk decision-making. Results have shown significant hemodynamic changes in the dorsal lateral prefrontal cortex (DLPFC) during the active-choice mode and a different activation pattern between genders; these findings correlate well with published literature in functional magnetic resonance imaging (fMRI) and fNIRS studies.

Point defect weakened thermal contraction in monolayer graphene.

We investigate the thermal expansion behaviors of monolayer graphene and three configurations of graphene with point defects, namely the replacement of one carbon atom with a boron or nitrogen atom, or of two neighboring carbon atoms by boron-nitrogen atoms, based on calculations using first-principles density functional theory. It is found that the thermal contraction of monolayer graphene is significantly decreased by point defects. Moreover, the corresponding temperature for negative linear thermal expansion coefficient with the maximum absolute value is reduced. The cause is determined to be point defects that enhance the mechanical strength of graphene and then reduce the amplitude and phonon frequency of the out-of-plane acoustic vibration mode. Such defect weakening of graphene thermal contraction will be useful in nanotechnology to diminish the mismatching or strain between the graphene and its substrate.

Quantum Mechanics-Based Fast and Reliable Prediction of Binding Pose Structures.

Predicting the binding poses of docking with an accurate estimation of binding energies is highly important but very challenging in computational drug design. A quantum mechanics (QM) calculation-based docking approach considering multiple conformations and orientations of the ligand is introduced here to tackle the problem. This QM docking consists of three steps: generating an ensemble of binding poses with a conventional docking simulation, computing the binding energies with self-consistent charge density functional theory tightly binding with dispersion correction (DFTB-D) to selecting the 10 top binding modes, and optimizing the selected binding mode structures using the ONIOM(DFTB:PM7) technique to determine the binding poses. The ONIOM(DFTB-D:PM6) docking approach is tested on 121 ligand-receptor biocomplexes with the crystal structures obtained from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB). The result shows that the new method is highly satisfactory for the accurate prediction of the binding poses. The new docking method should be beneficial to structure-based drug design.