Assembling Structure of Single-Walled Carbon Nanotube Thin Bundles

Atomic force microscopy (AFM), high resolution transmission electron microscopy, and Raman spectroscopy were used to study the assembling structure of thin bundles containing only a few single-walled carbon nanotubes (SWCNTs). The normal close-packed bundles as well as two novel kinds of bundles including spiral bundles and the ribbon-like bundles were observed for both free-standing SWCNTs and SWCNTs on substrates. Molecular mechanics calculation was employed to study the energetic competition between these three types of bundles. It was found that the free-standing spiral bundles and ribbon-like bundles are metastable compared with the close-packed bundles. However, ribbon-like bundles are more likely to be formed on substrates. This indicates that it is not reliable to assess whether the tested nanotube is individual through the height profile of the AFM image

Dissociative Adsorption of O₂ on Al(111): The Role of Orientational Degrees of Freedom

The interaction between O₂ molecules and Al surfaces has long been poorly understood despite its importance in diverse chemical phenomena. Early experimental investigations of adsorption dynamics indicated that abstraction of a single O atom by the surface, instead of dissociative chemisorption, dominates at low O₂ incident kinetic energies. Abstraction of the closer O atom suggests low barrier heights at perpendicular incidence. However, recent measurements suggest that parallel O₂ orientations dominate sticking at low energies. We resolve this apparent contradiction by a systematic ab initio embedded correlated wavefunction study of the stereochemistry of O₂ reacting with Al(111). We identify two important new details: (i) initially, roughly parallel oxygen molecules tend to tilt upright while approaching the surface, suggesting that the abstraction channel does dominate at low energies and (ii) the reaction channel with the lowest barrier indeed corresponds to a parallel orientation, which ultimately evolves either into dissociative chemisorption or toward abstraction

Trajectories of posttraumatic stress disorders among children after the Wenchuan earthquake: a four-year longitudinal study

Background: Previous research has demonstrated heterogeneous patterns of posttraumatic stress disorder (PTSD) among children following disasters. However, no clear consensus has been reached regarding the postdisaster trajectories of PTSD among children. Objective: The current study examined the trajectories of PTSD among children after exposure to the Wenchuan earthquake and explored potential predictors of distinct PTSD trajectories. Methods: A four-year longitudinal study was conducted to follow 301 children who were evaluated for PTSD symptoms following the Wenchuan earthquake. Trauma exposure and some pre-existing characteristics were measured at four months after the disaster, and PTSD symptoms were measured at 4, 16, 29, 40 and 52 months after the disaster. The trajectories were identified with Latent Growth Mixture Modelling, and the predictors were explored with multinomial logistic regression. Results: The following three latent PTSD trajectories were found among children: resilient (74.9%), relapsing (17.7%) and recovery (7.5%). Trauma exposure was more likely to be related to a more severe trajectory of PTSD, having experienced prequake trauma was more likely to be related to the recovery trajectory and school 2 was more likely to be related to the relapsing trajectory. Conclusion: These findings provide novel insights into children’s postdisaster response patterns. Individual heterogeneity existed in posttraumatic reactions. This longer-term longitudinal study captured more detailed and accurate information about the development of these trajectories. Trauma exposure and previous traumatic experience were linked to malignant development of PTSD.</p

Posttraumatic stress and depressive symptoms in children after the Wenchuan earthquake

Background: Many studies have reported the comorbidity of posttraumatic stress disorder (PTSD) and depression in children. However, the underlying relationship between PTSD and depression remains unclear. Objective: This study examines the relationship between PTSD and depressive symptoms in children who survived the Wenchuan earthquake in China. Methods: In total, 301 children were assessed at four months and then followed up at 29, 40 and 52 months after the disaster. The ages of the children ranged from 9.6–14.6 years old, and the sample included 157 males and 144 females. The children were assessed by using the University of California at Los Angeles PTSD reaction index for DSM-IV for PTSD symptoms and the Children’s Depression Inventory for depressive symptoms. Results: Comorbid PTSD and depressive symptoms were prevalent in 4.0, 3.3, 3.7 and 5.1% of the participants at times 1, 2, 3 and 4, respectively. The cross-lagged analysis indicated that PTSD symptoms at time 1 predicted depressive symptoms at time 2; depressive symptoms at time 1 predicted PTSD symptoms at time 2; depressive symptoms at time 2 predicted PTSD symptoms at time 3; and depressive symptoms at time 3 predicted PTSD symptoms at time 4. The findings also showed that being female, poor parental relationships and trauma exposure were risk factors for PTSD or depressive symptoms. Conclusions: The results suggest that the causal relationship between PTSD and depressive symptoms changes over time; the effects of PTSD symptoms tend to decrease, while those of depressive symptoms tend to increase. Two stages of the relationship between PTSD and depressive symptoms were observed, namely, that PTSD and depressive symptoms first influenced each other and then that depressive symptoms predicted PTSD. The results of our study also suggest that females with poor parental relationships and a high degree of trauma exposure are more likely to require intervention.</p

Potential Functional Embedding Theory at the Correlated Wave Function Level. 2. Error Sources and Performance Tests

Quantum mechanical embedding theories partition a complex system into multiple spatial regions that can use different electronic structure methods within each, to optimize trade-offs between accuracy and cost. The present work incorporates accurate but expensive correlated wave function (CW) methods for a subsystem containing the phenomenon or feature of greatest interest, while self-consistently capturing quantum effects of the surroundings using fast but less accurate density functional theory (DFT) approximations. We recently proposed two embedding methods [for a review, see: Acc. Chem. Res. 2014, 47, 2768]: density functional embedding theory (DFET) and potential functional embedding theory (PFET). DFET provides a fast but non-self-consistent density-based embedding scheme, whereas PFET offers a more rigorous theoretical framework to perform fully self-consistent, variational CW/DFT calculations [as defined in part 1, CW/DFT means subsystem 1(2) is treated with CW­(DFT) methods]. When originally presented, PFET was only tested at the DFT/DFT level of theory as a proof of principle within a planewave (PW) basis. Part 1 of this two-part series demonstrated that PFET can be made to work well with mixed Gaussian type orbital (GTO)/PW bases, as long as optimized GTO bases and consistent electron–ion potentials are employed throughout. Here in part 2 we conduct the first PFET calculations at the CW/DFT level and compare them to DFET and full CW benchmarks. We test the performance of PFET at the CW/DFT level for a variety of types of interactions (hydrogen bonding, metallic, and ionic). By introducing an intermediate CW/DFT embedding scheme denoted DFET/PFET, we show how PFET remedies different types of errors in DFET, serving as a more robust type of embedding theory

Physicochemical Analysis of DPPC and Photopolymerizable Liposomal Binary Mixture for Spatiotemporal Drug Release

The development of a spatiotemporal drug delivery system with a long release profile, high loading efficiency, and robust therapeutic effects is still a challenge. Liposomal nanocarriers have secured a fortified position in the biomedical field over decades. Herein, liposomal binary mixtures of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and photopolymerizable 1,2-bis­(10,12-tricosadiynoyl)-sn-glycero-3-phosphocholine (DC8,9PC) phospholipids were prepared for drug delivery applications. The diacetylenic groups of DC8,9PC produce intermolecular cross-linking following UV irradiation. Exposure of the liposomal mixture to 254 nm radiation induces a pore within the lipid bilayer, expediting the release of its entrapped 5,6-carboxyfluorescein dye. The dosage and rate of the released content are highly dependent on the number and size of the induced pore. Photochemical cross-linking studies at different exposure times were reported through the analysis of UV–visible spectrophotometry, nano differential scanning calorimetry, Fourier transform infrared spectroscopy, and Raman spectroscopy. The optimal irradiation time was established after 8 min of exposure, inducing lipid cross-linking with minimal oxidative degradation, which plays an essential role in the pathogenesis of numerous diseases due to the formation of primary and secondary oxidation products, accordingly reducing the encapsulated drug therapeutic level

Design optimization of composite wind turbine blades considering tortuous lightning strike and non-proportional multi-axial fatigue damage

This article presents a design optimization framework which integrates realistic lightning strike electrostatic and fatigue analyses for designing reliable and economical composite wind turbine blades. The novel aspects of this work include: a parametric tortuous lightning stepped leader model that reflects one of the true natural characteristics of the lightning phenomenon; and characterization of both the lightning strike dielectric breakdown failure and multi-axial fatigue failure mechanisms for structural design of composite wind turbine blades. A case study of the structural design optimization of a 5 MW composite wind turbine blade is tested using the framework with two optimization solvers: sequential quadratic programming (SQP) and Bayesian optimization (BO). SQP produces a superior optimal design to BO. In the optimum blade design based on the SQP algorithm, the lightning safety ratio increased by 32% and the expected fatigue life increased more than 15 times compared with the initial blade design.</p

Additional file 1 of Systematic analysis of the role of LDHs subtype in pan-cancer demonstrates the importance of LDHD in the prognosis of hepatocellular carcinoma patients

Additional file 1: Fig. S1. Correlation between expression of LDHs family genes and overall survival of patients with different TCGA cancer types. A. Survival curve analysis between LHDA gene expression and overall survival of patients with ACC, CESC, LGG, LIHC, LUAD and PAAD; B. Survival curve analysis between LDHB gene expression and overall survival in patients with GBM, HNSC, LGG, LIHC, LUAD and SKCM; C. Survival curve analysis between LDHC gene expression and overall survival of UCEC and UVM patients; D. Survival curve analysis between LDHD gene expression and overall survival of patients with ACC, CESC, KIRC, KIRP, LUAD and UVM. Fig. S2. Protein expression levels of LDHA family genes in different cancer tissues and normal tissues based on the HPA database. IHC images of LDHA (A), LDHB (B), LDHC (C) and LDHD (D) in lung and lung cancer, thyroid and thyroid cancer, kidney and kidney cancer from the HPA database. Fig. S3. Assessment of the prognostic value of the LDHs family genes in pan-cancer patients. ROC curve analysis of LDHs family genes to assess the utility of LDHs as a prognostic marker in BRCA patients (A), COAD patients (B); HNSC patients (C); KICH patients (D), KIRC patients (E), KIRP patients (F), LUSC patients (G); READ patients (H), STAD patients(I) and THCA patients (J). Fig. S4. Biological functions of LDHs in pan-cancer. A. KEGG signature of LDHA in LGG, LIHC and STAD for GSEA analysis; B. GSEA analysis of KEGG features of LDHB in BRCA, HNSC, LIHC and STAD; C. GSEA analysis of KEGG features of LDHC in BRCA, KICH and STAD; D. GSEA analysis of KEGG features of LDHD in HNSC, KICH and LIHC. Fig. S5. Correlation of LDHs expression in pan-cancer and immune subtypes. Correlation of LDHs expression with immune subtypes in BLCA (A), BRCA (B), KIRC (C), KIRP (D), LGG (E), LIHC (F), LUAD (G), OV (H), PRAD (I), and UCEC (J). Fig. S6. Association between LDHs family gene expression and pan-cancer molecular subtypes. A. Correlation between LDHA expression and BRCA, HNSC, KIRP, LGG, PCPG, PRAD, STAD and UCEC molecular subtypes; B. Correlation between LDHB expression and BRCA, ESCA, HNSC, LGG, OV, PCPG and PRAD molecular subtypes; C. Correlation between LDHC expression and BRCA, HNSC, OV, PCPG, STAD and UCEC molecular subtypes; D. Correlation between LDHD expression and BRCA, COAD, ESCA, HNSC, LGG, LIHC, PRAD, STAD and UCEC molecular subtypes. Fig. S7. Correlation between the expression of genes of the LDHs family in pan-cancer and immune-related molecules based on the analysis of the TISIDB database. Correlation between the expression of LDHA (A), LDHB (B), LDHC (C) and LDHD (D) in pan-cancer and immune inhibitors, immune stimulators and MHC molecules in the TISIDB database. Fig. S8. Association between LDHD gene expression and clinicopathological features as well as immune cell infiltration in HCC. A. LDHD gene expression in HCC tissues and normal tissues; B-C. Relationship between LDHD expression levels and OS, PFS in HCC patients. Association between LDHD gene expression in HCC and age (D), gender (E), T stage (F), Histological grade (G), Pathological stage (H) and AFP (I). (J) Association between LDHD gene expression and immune cell infiltration

DataSheet1_A Theoretical Model for the Charging Dynamics of Associating Ionic Liquids.docx

Association between cations and anions plays an important role in the interfacial structure of room-temperature ionic liquids (ILs) and their electrochemical performance. Whereas great efforts have been devoted to investigating the association effect on the equilibrium properties of ILs, a molecular-level understanding of the charging dynamics is yet to be established. Here, we propose a theoretical procedure combining reaction kinetics and the modified Poisson-Nernst-Planck (MPNP) equations to study the influences of ionic association on the dynamics of electrical double layer (EDL) in response to an applied voltage. The ionic association introduces a new decay length λS and relaxation time scale τRC=λSL/D, where L is the system size and D is ion diffusivity, that are distinctively different those corresponding to non-associative systems. Analytical expressions have been obtained to reveal the quantitative relations between the dynamic timescales and the association strength.</p

Data_Sheet_1_N6-methyladenosine RNA is modified in the rat hippocampus following traumatic brain injury with hypothermia treatment.ZIP

Recent studies have suggested a role for N6-methyladenosine (m6A) modification in neurological diseases. Hypothermia, a commonly used treatment for traumatic brain injury, plays a neuroprotective role by altering m6A modifications. In this study, methylated RNA immunoprecipitation sequencing (MeRIP-Seq) was applied to conduct a genome-wide analysis of RNA m6A methylation in the rat hippocampus of Sham and traumatic brain injury (TBI) groups. In addition, we identified the expression of mRNA in the rat hippocampus after TBI with hypothermia treatment. Compared with the Sham group, the sequencing results of the TBI group showed that 951 different m6A peaks and 1226 differentially expressed mRNAs were found. We performed cross-linking analysis of the data of the two groups. The result showed that 92 hyper-methylated genes were upregulated, 13 hyper-methylated genes were downregulated, 25 hypo-methylated genes were upregulated, and 10 hypo-methylated genes were downregulated. Moreover, a total of 758 differential peaks were identified between TBI and hypothermia treatment groups. Among these differential peaks, 173 peaks were altered by TBI and reversed by hypothermia treatment, including Plat, Pdcd5, Rnd3, Sirt1, Plaur, Runx1, Ccr1, Marveld1, Lmnb2, and Chd7. We found that hypothermia treatment transformed some aspects of the TBI-induced m6A methylation landscape of the rat hippocampus.</p