This paper reviews recent progress in the studies of buried polymer interfaces using sum frequency generation (SFG) vibrational spectroscopy. Both buried solid/liquid and solid/solid interfaces ...involving polymeric materials are discussed. SFG studies of polymer/water interfaces show that different polymers exhibit varied surface restructuring behavior in water, indicating the importance of probing polymer/water interfaces
in situ. SFG has also been applied to the investigation of interfaces between polymers and other liquids. It has been found that molecular interactions at such polymer/liquid interfaces dictate interfacial polymer structures. The molecular structures of silane molecules, which are widely used as adhesion promoters, have been investigated using SFG at buried polymer/silane and polymer/polymer interfaces, providing molecular-level understanding of polymer adhesion promotion. The molecular structures of polymer/solid interfaces have been examined using SFG with several different experimental geometries. These results have provided molecular-level information about polymer friction, adhesion, interfacial chemical reactions, interfacial electronic properties, and the structure of layer-by-layer deposited polymers. Such research has demonstrated that SFG is a powerful tool to probe buried interfaces involving polymeric materials, which are difficult to study by conventional surface sensitive analytical techniques.
This paper summarizes the early research results on studying proteins and peptides at interfaces using sum frequency generation (SFG) vibrational spectroscopy. SFG studies in the C-H stretching ...frequency region to examine the protein side-chain behavior and in the amide I frequency region to investigate the orientation and conformation of interfacial peptides/proteins are presented. The early chiral SFG research and SFG isotope labeling studies on interfacial peptides/proteins are also discussed. These early SFG studies demonstrate the feasibility of using SFG to elucidate interfacial molecular structures of peptides and proteins in situ, which built a foundation for later SFG investigations on peptides and proteins at interfaces.
This study investigates the virtual water profile of the world in 2004 based on a multi-region input–output model. The water footprints of 112 nation-level regions are calculated and the footprint ...compositions of major water consumers are analyzed. Less than 35% of the global virtual water requirement is provided by agricultural products, in spite of the fact that 69% of the total water withdrawal is associated with agricultural sector. At the national scale, India, the United States, and mainland China are the world's largest virtual water consumers. Per capita water footprint varies from 30m3 for Rest of South Central Africa to 3290m3 for Luxembourg. As one of the major determinants of national footprint, international virtual water trade sums up to 30% of the direct water withdrawal of the world. Meanwhile, results show that 57% of the international virtual water flows is embodied in non-food trade, confirming the importance to take not only food product but also non-food product into account when overall water budget is considered. Mainland China is the world's leading exporter and deficit receiver in terms of virtual water trade (204Gm3 and 142Gm3, respectively), in contrast to the United States as the leading importer (178Gm3) and Japan as the leading surplus receiver (77Gm3). Finally, the virtual water trade connections of China and the United States with their major trading partners are revealed via introducing the index of virtual water dependency. Results presented in this study are of essential implications for policy making regarding water using pattern adjustment and water security enhancement.
This paper utilizes SBM-undesirable model and Malmquist index to examine the urban eco-efficiency in China and analyzes the regional heterogeneity. Through the panel data of 273 prefecture-level ...cities during 2007–2017 in China, the spatial Durbin model is used to examine the influencing factors of urban eco-efficiency associated with technological innovations. The results show that the average values of urban eco-efficiency of the East, Central, and West regions are 0.93, 0.88, and 0.90, respectively. The Moran’s I of eco-efficiency is around 0.8, which shows a strong spatial heterogeneity. It is found that higher innovative ability can increase urban eco-efficiency. Education investment and innovation talents have a U-shape relationship with urban eco-efficiency, while capital investment and innovation performance have an inverted U-shape relationship with it. This research outlines the relationship between technological innovations and urban eco-efficiency, offering policy implications for China’s eco-construction and sustainable urban development.
•Exploring the trend of eco-efficiency of different urban types in China.•Significant spatial autocorrelation and heterogeneity of eco-efficiency are found.•Spatial Durbin model is used to analyze how innovations affect urban eco-efficiency.•The drivers of eco-efficiency in terms of technological innovation are obtained.
An accurate and computationally efficient determination of the cross sections for electron collision ionization of molecules has various applications, such as plasma physics and atmospheric science. ...In the case of large molecules, ab initio calculations are often difficult and time‐consuming. Here, we develop a feed forward neural network to predict the electron impact ionization cross sections of complex molecules. The training (predicting) set in the method consists of a series of theoretical ionization cross sections for small (large) molecules obtained from the combined model, which integrates the Binary‐Encounter‐Bethe and Deutsch‐Märk models. Several complex systems or targets involving electron collision ionization are evaluated, including molecules such as CH4$$ {}_4 $$, C3$$ {}_3 $$H8$$ {}_8 $$, C5$$ {}_5 $$H8$$ {}_8 $$, C6$$ {}_6 $$H10$$ {}_{10} $$, C6$$ {}_6 $$, C2$$ {}_2 $$H6$$ {}_6 $$O, and C6$$ {}_6 $$H6$$ {}_6 $$O. The root mean square errors of the trained and predicted cross sections by the 2×3×3×1$$ 2\times 3\times 3\times 1 $$ neural network (compared to the values from the combined model) are found to be approximately .0086 and .0930 (in 10−20$$ {}^{-20} $$ cm2$$ {}^2 $$), respectively, (using the C2$$ {}_2 $$H6$$ {}_6 $$O molecule as an example), indicating our results are very high accuracy. The excellent agreement between the predicted values and the actual values indicates that the neural network is a practical and powerful tool for determining the electron collision ionization cross sections of complex molecules and can provide valuable insights into the dynamics process. Apart from its fundamental importance, this study has far‐reaching implications for gas discharge, low‐temperature plasmas, and fusion edge plasmas and so forth.
This article describes the application of a feed‐forward neural network to estimate the ionization cross sections of electron collisions with complex molecules. The agreement between the predicted results and other theoretical results highlights the utility and effectiveness of the neural network. The present work contributes significantly to our understanding of the dynamical processes involved.
Traditional consumption-based greenhouse gas emissions accounting attributed the gap between consumption-based and production-based emissions to international trade. Yet few attempts have analyzed ...the temporal deviation between current emissions and future consumption, which can be explained through changes in capital stock. Here we develop a dynamic model to incorporate capital stock change in consumption-based accounting. The new model is applied using global data for 1995-2009. Our results show that global emissions embodied in consumption determined by the new model are smaller than those obtained from the traditional model. The emissions embodied in global capital stock increased steadily during the period. However, capital plays very different roles in shaping consumption-based emissions for economies with different development characteristics. As a result, the dynamic model yields similar consumption-based emissions estimation for many developed countries comparing with the traditional model, but it highlights the dynamics of fast-developing countries.
Background and Aims
DNA damage‐induced NF‐κB activation is a major obstacle to effective antitumour chemotherapy. Long noncoding RNAs (lncRNAs) that regulate chemoresistance of cancer cells remain ...largely unknown. This study aimed to characterize the lncRNAs that may affect chemotherapy sensitivity.
Approach and Results
We found that lncRNA PDIA3P1 (protein disulfide isomerase family A member 3 pseudogene 1) was up‐regulated in multiple cancer types and following treatment with DNA‐damaging chemotherapeutic agents, like doxorubicin (Dox). Higher PDIA3P1 level was associated with poorer recurrence‐free survival of human hepatocellular carcinoma (HCC). Both gain‐of‐function and loss‐of‐function studies revealed that PDIA3P1 protected cancer cells from Dox‐induced apoptosis and allowed tumor xenografts to grow faster and to be more resistant to Dox treatment. Mechanistically, miR‐125a/b and miR‐124 suppressed the expression of tumor necrosis factor receptor‐associated factor 6 (TRAF6), but PDIA3P1 bound to miR‐125a/b/miR‐124 and relieved their repression on TRAF6, leading to activation of the nuclear factor kappa B (NF‐κB) pathway. Consistently, the effect of PDIA3P1 inhibition in promoting Dox‐triggered apoptosis was antagonized by silencing the inhibitor of κBα (IκBα) or overexpressing TRAF6. Administration of BAY 11‐7085, an NF‐κB inhibitor attenuated PDIA3P1‐induced resistance to Dox treatment in mouse xenografts. Moreover, up‐regulation of PDIA3P1 was significantly correlated with elevation of TRAF6, phosphorylated p65, or NF‐κB downstream anti‐apoptosis genes in human HCC tissues. These data indicate that enhanced PDIA3P1 expression may confer chemoresistance by acting as a microRNA sponge to increase TRAF6 expression and augment NF‐κB signaling. Subsequent investigations into the mechanisms of PDIA3P1 up‐regulation revealed that human homologue of mRNA transport mutant 4 (hMTR4), which promotes RNA degradation, could bind to PDIA3P1, and this interaction was disrupted by Dox treatment. Overexpression of hMTR4 attenuated Dox‐induced elevation of PDIA3P1, whereas silencing hMTR4 increased PDIA3P1 level, suggesting that Dox may up‐regulate PDIA3P1 by abrogating the hMTR4‐mediated PDIA3P1 degradation.
Conclusion
There exists a hMTR4‐PDIA3P1‐miR‐125/124‐TRAF6 regulatory axis that regulates NF‐κB signaling and chemoresistance, which may be exploited for anticancer therapy.
Although thousands of long noncoding RNAs (lncRNAs) have been annotated, only a limited number of them have been functionally characterized. Here, we identified an oncogenic lncRNA, named lnc‐UCID ...(lncRNA up‐regulating CDK6 by interacting with DHX9). Lnc‐UCID was up‐regulated in hepatocellular carcinoma (HCC), and a higher lnc‐UCID level was correlated with shorter recurrence‐free survival of HCC patients. Both gain‐of‐function and loss‐of function studies revealed that lnc‐UCID enhanced cyclin‐dependent kinase 6 (CDK6) expression and thereby promoted G1/S transition and cell proliferation. Studies from mouse xenograft models revealed that tumors derived from lnc‐UCID‐silenced HCC cells had a much smaller size than those from control cells, and intratumoral injection of lnc‐UCID small interfering RNA suppressed xenograft growth. Mechanistically, the 850‐1030‐nt domain of lnc‐UCID interacted physically with DEAH (Asp‐Glu‐Ala‐His) box helicase 9 (DHX9), an RNA helicase. On the other hand, DHX9 post‐transcriptionally suppressed CDK6 expression by binding to the 3′‐untranslated region (3′UTR) of CDK6 mRNA. Further investigation disclosed that lnc‐UCID enhanced CDK6 expression by competitively binding to DHX9 and sequestering DHX9 from CDK6‐3′UTR. In an attempt to explore the mechanisms responsible for lnc‐UCID up‐regulation in HCC, we found that the lnc‐UCID gene was frequently amplified in HCC. Furthermore, miR‐148a, whose down‐regulation was associated with an increase of lnc‐UCID in HCC, could bind lnc‐UCID and inhibit its expression. Conclusion: Up‐regulation of lnc‐UCID, which may result from amplification of its gene locus and down‐regulation of miR‐148a, can promote HCC growth by preventing the interaction of DHX9 with CDK6 and subsequently enhancing CDK6 expression. These findings provide insights into the biological functions of lncRNAs, the regulatory network of cell cycle control, and the mechanisms of HCC development, which may be exploited for anticancer therapy.
Coronavirus disease 2019 (COVID-19) has now become a worldwide health concern. The severity of COVID-19 has been classified as mild, moderate, severe and critical 1. To date, there have been a few ...studies focused on the clinical course and outcome of critical cases 2–4. However, information regarding outcomes of mild-to-moderate cases is lacking, despite the fact that mild-to-moderate cases have accounted for approximately 80% of laboratory-confirmed patients 1, 5. This study aimed to investigate short-term outcomes of patients rated with different severities on admission, and to identify risk factors for progression, thereby helping the management of COVID-19 in clinical practice.
With a median (IQR
) follow-up time of 24.0 (17.5–30.0) days, progression occurred in 19.6% moderate, 27.8% severe and 66.7% critical COVID-19. Neutrophil-to-lymphocyte ratio ≥2.973, age ≥50 years, male sex and comorbidity were associated with progression.
https://bit.ly/3crsJr0
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