On the density matrix for the kink ground state of higher spin XXZ chain

The exact expression for the density matrix of the kink ground state of higher spin XXZ chain is obtained

Effect of CO2 enrichment on bacterial metabolism in an Arctic fjord

he anthropogenic increase of carbon dioxide (CO2) alters the seawater carbonate chemistry, with a decline of pH and an increase in the partial pressure of CO2 (pCO2). Although bacteria play a major role in carbon cycling, little is known about the impact of rising pCO2 on bacterial carbon metabolism, especially for natural bacterial communities. In this study, we investigated the effect of rising pCO2 on bacterial production (BP), bacterial respiration (BR) and bacterial carbon metabolism during a mesocosm experiment performed in Kongsfjorden (Svalbard) in 2010. Nine mesocosms with pCO2 levels ranging from ca. 180 to 1400 μatm were deployed in the fjord and monitored for 30 days. Generally BP gradually decreased in all mesocosms in an initial phase, showed a large (3.6-fold average) but temporary increase on day 10, and increased slightly after inorganic nutrient addition. Over the wide range of pCO2 investigated, the patterns in BP and growth rate of bulk and free-living communities were generally similar over time. However, BP of the bulk community significantly decreased with increasing pCO2 after nutrient addition (day 14). In addition, increasing pCO2 enhanced the leucine to thymidine (Leu : TdR) ratio at the end of experiment, suggesting that pCO2 may alter the growth balance of bacteria. Stepwise multiple regression analysis suggests that multiple factors, including pCO2, explained the changes of BP, growth rate and Leu : TdR ratio at the end of the experiment. In contrast to BP, no clear trend and effect of changes of pCO2 was observed for BR, bacterial carbon demand and bacterial growth efficiency. Overall, the results suggest that changes in pCO2 potentially influence bacterial production, growth rate and growth balance rather than the conversion of dissolved organic matter into CO2

Response of bacterioplankton community structure to an artificial gradient of pCO2 in the Arctic Ocean

In order to test the influences of ocean acidification on the ocean pelagic ecosystem, so far the largest CO2 manipulation mesocosm study (European Project on Ocean Acidification, EPOCA) was performed in Kings Bay (Kongsfjorden), Spitsbergen. During a 30 day incubation, bacterial diversity was investigated using DNA fingerprinting and clone library analysis of bacterioplankton samples. Terminal restriction fragment length polymorphism (T-RFLP) analysis of the PCR amplicons of the 16S rRNA genes revealed that general bacterial diversity, taxonomic richness and community structure were influenced by the variation of productivity during the time of incubation, but not the degree of ocean acidification. A BIOENV analysis suggested a complex control of bacterial community structure by various biological and chemical environmental parameters. The maximum apparent diversity of bacterioplankton (i.e., the number of T-RFs) in high and low pCO2 treatments differed significantly. A negative relationship between the relative abundance of Bacteroidetes and pCO2 levels was observed for samples at the end of the experiment by the combination of T-RFLP and clone library analysis. Our study suggests that ocean acidification affects the development of bacterial assemblages and potentially impacts the ecological function of the bacterioplankton in the marine ecosystem

Production of individual marine organic aggregates using paramagnetic microspheres : a new tool for examining microbial associations with aggregates

We describe a new method to produce marine aggregates from natural organic material based on the sticking properties of transparent exopolymeric particles. Seawater samples were prescreened and ultrafiltered to concentrate the 30 kDa to 10 mu m size fraction. First, we produced small magnetizable aggregates by combining glass microfibers and paramagnetic 1-mu m beads with the organic matter present in the concentrated solution. The second step involved clustering the small aggregates into a single macro-aggregate, using a small ring-shaped magnet as an aggregation nucleus. Viral and bacterial densities, determined after dissolution of the newly formed aggregates with methanol, averaged 13.8 x 10(6) +/- 3.6 x 10(6) vir. agg.(-1) and 4.1 x 10(6) +/- 1.1 x10(6) bact. agg.(-1). Bacterial respiration and production measurements of single aggregates averaged 8.47 +/- 1.72 nmol O-2 agg.(-1) h(-1) and 1.54 +/- 0.45 ng C agg.(-1) h(-1), respectively. Particulate organic carbon and nitrogen content of the newly formed macro-aggregates averaged 31.92 +/- 2.67 mu g C agg.(-1) and 3.44 +/- 0.43 mu g N agg.(-1), respectively. This approach allows the concentration and isolation of the organic matter precursors that compose natural aggregates and provides a simple protocol for recombining those precursors into single newly formed macro-aggregates, which can then be easily manipulated for further investigation. This method is a new tool for investigations into the interactions between microorganisms and marine aggregates and their implications at the ecosystem level, but also into the interactions between aggregates and dissolved organic or inorganic substances

A unified framework for efficient estimation of general treatment models

Funder: National Natural Science Foundation of China; Id: http://dx.doi.org/10.13039/501100001809Funder: JSPS; Id: http://dx.doi.org/10.13039/501100001691Funder: KAKENHI; Id: http://dx.doi.org/10.13039/501100001691Funder: Natural Science Foundation of ChinaFunder: Renmin University of China; Id: http://dx.doi.org/10.13039/501100004260This paper presents a weighted optimization framework that unifies the binary, multivalued, and continuous treatment—as well as mixture of discrete and continuous treatment—under a unconfounded treatment assignment. With a general loss function, the framework includes the average, quantile, and asymmetric least squares causal effect of treatment as special cases. For this general framework, we first derive the semiparametric efficiency bound for the causal effect of treatment, extending the existing bound results to a wider class of models. We then propose a generalized optimization estimator for the causal effect with weights estimated by solving an expanding set of equations. Under some sufficient conditions, we establish the consistency and asymptotic normality of the proposed estimator of the causal effect and show that the estimator attains the semiparametric efficiency bound, thereby extending the existing literature on efficient estimation of causal effect to a wider class of applications. Finally, we discuss estimation of some causal effect functionals such as the treatment effect curve and the average outcome. To evaluate the finite sample performance of the proposed procedure, we conduct a small‐scale simulation study and find that the proposed estimation has practical value. In an empirical application, we detect a significant causal effect of political advertisements on campaign contributions in the binary treatment model, but not in the continuous treatment model.</jats:p

A Unified Framework for Efficient Estimation of General Treatment Models

This paper presents a weighted optimization framework that unifies the binary, multivalued, continuous, as well as mixture of discrete and continuous treatment, under the unconfounded treatment assignment. With a general loss function, the framework includes the average, quantile and asymmetric least squares causal effect of treatment as special cases. For this general framework, we first derive the semiparametric efficiency bound for the causal effect of treatment, extending the existing bound results to a wider class of models. We then propose a generalized optimization estimation for the causal effect with weights estimated by solving an expanding set of equations. Under some sufficient conditions, we establish consistency and asymptotic normality of the proposed estimator of the causal effect and show that the estimator attains our semiparametric efficiency bound, thereby extending the existing literature on efficient estimation of causal effect to a wider class of applications. Finally, we discuss estimation of some causal effect functionals such as the treatment effect curve and the average outcome. To evaluate the finite sample performance of the proposed procedure, we conduct a small scale simulation study and find that the proposed estimation has practical value. To illustrate the applicability of the procedure, we revisit the literature on campaign advertise and campaign contributions. Unlike the existing procedures which produce mixed results, we find no evidence of campaign advertise on campaign contribution

MFG-E8 Regulates Angiogenesis in Cutaneous Wound Healing

Our research group recently demonstrated that pericytes are major sources of the secreted glycoprotein and integrin ligand lactadherin (MFG-E8) in B16 melanoma tumors, and that MFG-E8 promotes angiogenesis via enhanced PDGF–PDGFRβ signaling mediated by integrin–growth factor receptor crosstalk. However, sources of MFG-E8 and its possible roles in skin physiology are not well characterized. The objective of this study was to characterize the involvement of MFG-E8 in skin wound healing. In the dermis of normal murine and human skin, accumulations of MFG-E8 were found around CD31+ blood vessels, and MFG-E8 colocalized with PDGFRβ+, αSMA+, and NG2+ pericytes. MFG-E8 protein and mRNA levels were elevated in the dermis during full-thickness wound healing in mice. MFG-E8 was diffusely present in granulation tissue and was localized around blood vessels. Wound healing was delayed in MFG-E8 knockout mice, compared with the wild type, and myofibroblast and vessel numbers in wound areas were significantly reduced in knockout mice. Inhibition of MFG-E8 production with siRNA attenuated the formation of capillary-like structures in vitro. Expression of MFG-E8 in fibrous human granulation tissue with scant blood vessels was less than that in granulation tissue with many blood vessels. These findings suggest that MFG-E8 promotes cutaneous wound healing by enhancing angiogenesis

On the problem of calculation of correlation functions in the six-vertex model with domain wall boundary conditions

The problem of calculation of correlation functions in the six-vertex model with domain wall boundary conditions is addressed by considering a particular nonlocal correlation function, called row configuration probability. This correlation function can be used as building block for computing various (both local and nonlocal) correlation functions in the model. The row configuration probability is calculated using the quantum inverse scattering method; the final result is given in terms of a multiple integral. The connection with the emptiness formation probability, another nonlocal correlation function which was computed elsewhere using similar methods, is also discussed.Comment: 15 pages, 2 figure

Loss of DLX3 tumor suppressive function promotes progression of SCC through EGFR-ERBB2 pathway

Cutaneous squamous cell carcinoma (cSCC) ranks second in the frequency of all skin cancers. The balance between keratinocyte proliferation and differentiation is disrupted in the pathological development of cSCC. DLX3 is a homeobox transcription factor which plays pivotal roles in embryonic development and epidermal homeostasis. To investigate the impact of DLX3 expression on cSCC prognosis, we carried out clinicopathologic analysis of DLX3 expression which showed statistical correlation between tumors of higher pathologic grade and levels of DLX3 protein expression. Further, Kaplan-Meier survival curve analysis demonstrated that low DLX3 expression correlated with poor patient survival. To model the function of Dlx3 in skin tumorigenesis, a two-stage dimethylbenzanthracene (DMBA)/12-O-tetradecanoylphorbol 13-acetate (TPA) study was performed on mice genetically depleted of Dlx3 in skin epithelium (Dlx3cKO). Dlx3cKO mice developed significantly more tumors, with more rapid tumorigenesis compared to control mice. In Dlx3cKO mice treated only with DMBA, tumors developed after similar to 16 weeks suggesting that loss of Dlx3 has a tumor promoting effect. Whole transcriptome analysis of tumor and skin tissue from our mouse model revealed spontaneous activation of the EGFR-ERBB2 pathway in the absence of Dlx3. Together, our findings from human and mouse model system support a tumor suppressive function for DLX3 in skin and underscore the efficacy of therapeutic approaches that target EGFR-ERBB2 pathway