Probing the topcolor-assisted technicolor model via the single t-quark production at Hadron colliders

In this paper, we systematically study the contribution of the TC2 model to the single t-quark production at the Hadron colliders, specially at the LHC. The TC2 model can contribute to the cross section of the single t-quark production in two different ways. First, the existence of the top-pions and top-higgs can modify the $Wtb$ coupling via their loop contributions, and such modification can cause the correction to the cross sections of all three production modes. Our study shows that this kind of correction is negative and very small in all cases. Thus it is difficult to observe such correction even at the LHC. On the other hand, there exist the tree-level FC couplings in the TC2 model which can also contribute to the cross sections of the $tq$ and $t\bar{b}$ production processes. The resonant effect can greatly enhance the cross sections of the $tq$ and $t\bar{b}$ productions. The first evidence of the single t-quark production has been reported by the $D0$ collaboration and the measured cross section for the single t-quark production of $\sigma(p\bar{p}\to tb+X,tqb+X)$ is compatible at the 10% level with the standard model prediction. Because the light top-pion can make great contribution to the $t\bar{b}$ production, the top-pion mass should be very large in order to make the predicted cross section in the TC2 model be consistent with the Tevatron experiments. More detailed information about the top-pion mass and the FC couplings in the TC2 model should be obtained with the running of the LHC.Comment: 30 pages, 3 tables, 10 figure

The Impact of Positive Online Review Tags on Snacks Sales: A Case of Bestore in Tmall

Customers’ reviews in e-commerce sites play a significant role in influencing potential customers’ purchasing decisions which ultimately affects products sales. Chinese e-commerce sites like Tmall, Taobao and JD.com contain a collection of aspect tags that group reviews with similar comments tags to help customers browse reviews and evaluate products more conveniently. To validate whether these tags are useful and actually playing a role in promoting future sales, we collected data including product information and review tags on a regular basis for consecutive 8 weeks from Bestore, a snack seller on Tmall. We classified the collected review tags into 9 types based on their semantic meanings. Finally, we analyzed and performed generalized estimating equations (GEE) modeling on the data set consisting of 234 products with a total of 734 tags. The results show that most of the aspect tags are related to immediate period sales volume and certain tags are more capable of nowcasting next immediate sales

Mural granulosa cell gene expression associated with oocyte developmental competence

<p>Abstract</p> <p>Background</p> <p>Ovarian follicle development is a complex process. Paracrine interactions between somatic and germ cells are critical for normal follicular development and oocyte maturation. Studies have suggested that the health and function of the granulosa and cumulus cells may be reflective of the health status of the enclosed oocyte. The objective of the present study is to assess, using an <it>in vivo </it>immature rat model, gene expression profile in granulosa cells, which may be linked to the developmental competence of the oocyte. We hypothesized that expression of specific genes in granulosa cells may be correlated with the developmental competence of the oocyte.</p> <p>Methods</p> <p>Immature rats were injected with eCG and 24 h thereafter with anti-eCG antibody to induce follicular atresia or with pre-immune serum to stimulate follicle development. A high percentage (30-50%, normal developmental competence, NDC) of oocytes from eCG/pre-immune serum group developed to term after embryo transfer compared to those from eCG/anti-eCG (0%, poor developmental competence, PDC). Gene expression profiles of mural granulosa cells from the above oocyte-collected follicles were assessed by Affymetrix rat whole genome array.</p> <p>Results</p> <p>The result showed that twelve genes were up-regulated, while one gene was down-regulated more than 1.5 folds in the NDC group compared with those in the PDC group. Gene ontology classification showed that the up-regulated genes included lysyl oxidase (<it>Lox</it>) and nerve growth factor receptor associated protein 1 (<it>Ngfrap1</it>), which are important in the regulation of protein-lysine 6-oxidase activity, and in apoptosis induction, respectively. The down-regulated genes included glycoprotein-4-beta galactosyltransferase 2 (<it>Ggbt2</it>), which is involved in the regulation of extracellular matrix organization and biogenesis.</p> <p>Conclusions</p> <p>The data in the present study demonstrate a close association between specific gene expression in mural granulosa cells and the developmental competence of oocytes. This finding suggests that the most differentially expressed gene, lysyl oxidase, may be a candidate biomarker of oocyte health and useful for the selection of good quality oocytes for assisted reproduction.</p

Short-chain fatty acids directly exert anti-inflammatory responses in podocytes and tubular epithelial cells exposed to high glucose

Aims: Gut-microbiome derived short-chain fatty acids exert anti-inflammatory effects and delay progression of kidney disease in diabetic nephropathy. The aim of this study was to examine the impact in vivo and in vitro of short-chain fatty acid treatment on cellular pathways involved in the development of experimental diabetic nephropathy.Methods: To determine the effect of short-chain fatty acids in diabetic nephropathy, we compared wildtype, GPR43−/− and GPR109A−/− mice diabetic mice treated with acetate or butyrate and assessed variables of kidney damage. We also examined the impact of short-chain fatty acid treatment on gene expression in renal tubular cells and podocytes under high glucose conditions.Results: Short-chain fatty acid treatment with acetate or butyrate protected wild-type mice against development of diabetic nephropathy, exhibiting less glomerular hypertrophy, hypercellularity and interstitial fibrosis compared to diabetic controls. Acetate and butyrate treatment did not provide the same degree of protection in diabetic GPR43−/− and GPR109A−/− diabetic mice respectively. Consistent with our in vivo results, expression of pro-inflammatory genes in tubular epithelial cells exposed to high glucose were attenuated by acetate and butyrate treatment. Acetate did not reduce inflammatory or fibrotic responses in glucose stimulated GPR43−/− TECs. Butyrate mediated inhibition of pro-fibrotic gene expression in TECs through GPR109A, and in podocytes via GPR43.Conclusion: SCFAs protect against progression of diabetic nephropathy and diminish podocyte and tubular epithelial injury and interstitial fibrosis via direct, GPR-pathway dependent effects on intrinsic kidney cells. GPR43 and GPR109A are critical to short-chain fatty acid mediated reno-protection and have potential to be harnessed as a therapeutic target in diabetic nephropathy

SurrealDriver: Designing Generative Driver Agent Simulation Framework in Urban Contexts based on Large Language Model

Simulation plays a critical role in the research and development of autonomous driving and intelligent transportation systems. However, the current simulation platforms exhibit limitations in the realism and diversity of agent behaviors, which impede the transfer of simulation outcomes to the real world. In this paper, we propose a generative driver agent simulation framework based on large language models (LLMs), capable of perceiving complex traffic scenarios and providing realistic driving maneuvers. Notably, we conducted interviews with 24 drivers and used their detailed descriptions of driving behavior as chain-of-thought prompts to develop a `coach agent' module, which can evaluate and assist driver agents in accumulating driving experience and developing human-like driving styles. Through practical simulation experiments and user experiments, we validate the feasibility of this framework in generating reliable driver agents and analyze the roles of each module. The results show that the framework with full architect decreased the collision rate by 81.04% and increased the human-likeness by 50%. Our research proposes the first urban context driver agent simulation framework based on LLMs and provides valuable insights into the future of agent simulation for complex tasks.Comment: 12 pages, 8 figure

The role of ERK1/2 in colitis through regulation of NADPH oxidase and mitochondrial fission

Objective To investigate the role of extracellular signal regulated kinase 1/2 （ERK1/2） in colitis through the regulation of NADPH oxidase and mitochondrial fission. Methods Mice models of acute colitis were induced by 3% dextran sulfate sodium （DSS）. Thirty C57BL/6J mice were randomly divided into six groups by random number table method： control group， 3%DSS group，1% dimethyl sulfoxide （DMSO） group， ERK1/2 inhibitor（PD98059） group， 3%DSS+1%DMSO group and 3%DSS+PD98059 group， with five mice in each group. The changes of body weight， colonic length， disease activity index and colonic histopathological changes of mice in the control and 3%DSS groups were evaluated， and the expression levels of ERK1/2， p-ERK1/2， Nicotinamide adenine dinucleotide phosphate oxidase 1 （Nox1） and Nox2 in colonic mucosa of mice were detected. Mice in 1%DMSO and 3%DSS+1%DMSO groups were intraperitoneally injected with 1%DMSO. Mice in the PD98059 and 3%DSS+PD98059 groups were intraperitoneally injected with PD98059. The colonic histopathological changes were evaluated among four groups， and the expression levels of Nox1， Nox2， Dynamin related protein 1 （DRP1）， p-DRP1-S616 and p-DRP1-S637 mitochondrial fission related proteins were detected. Mitochondrial fission of colonic epithelial cells in the control and 3%DSS groups was observed by transmission electron microscopy. The co-localization of Nox2 and mitochondrial outer membrane translocator enzyme TOM complex （TOMM20） in colonic mucosa of mice in two groups was analyzed by double-immunofluorescence staining. The correlation between relative expression levels of DRP1 and Nox2 mRNA in mouse colonic mucosa was analyzed in two groups. Results Compared with the control group， mice in the 3%DSS group exhibited body weight loss， shortened colonic length， increased disease activity index and increased colonic histopathological score. The expression levels of p-ERK1/2， Nox1， Nox2 in colonic mucosa of mice were significantly up-regulated in the 3%DSS group （all P &lt; 0.05）. In mice with colitis， mitochondrial fission in colonic epithelial cells was increased， and the colonic mucosa co-localization of DRP1 and Nox2 was elevated， and the relative mRNA expression levels of both target genes were positively correlated （r = 0.678， P &lt; 0.05）. ERK1/2 inhibitor PD98059 improved colonic histopathological changes in mice with colitis， and down-regulated the expression levels of Nox1， Nox2， DRP1， p-DRP1-S616 in colonic mucosa. Conclusion Inhibition of ERK1/2 may ameliorate colitis by down-regulating NADPH oxidase expression and alleviating mitochondrial fission

Inhibition of EP4 Signaling Attenuates Aortic Aneurysm Formation

BACKGROUND: Aortic aneurysm is a common but life-threatening disease among the elderly, for which no effective medical therapy is currently available. Activation of prostaglandin E(2) (PGE(2)) is known to increase the expression of matrix metalloproteinase (MMP) and the release of inflammatory cytokines, and may thus exacerbate abdominal aortic aneurysm (AAA) formation. We hypothesized that selective blocking of PGE(2), in particular, EP4 prostanoid receptor signaling, would attenuate the development of AAA. METHODS AND FINDINGS: Immunohistochemical analysis of human AAA tissues demonstrated that EP4 expression was greater in AAA areas than that in non-diseased areas. Interestingly, EP4 expression was proportional to the degree of elastic fiber degradation. In cultured human aortic smooth muscle cells (ASMCs), PGE(2) stimulation increased EP4 protein expression (1.4 ± 0.08-fold), and EP4 stimulation with ONO-AE1-329 increased MMP-2 activity and interleukin-6 (IL-6) production (1.4 ± 0.03- and 1.7 ± 0.14-fold, respectively, P<0.05). Accordingly, we examined the effect of EP4 inhibition in an ApoE(-/-) mouse model of AAA infused with angiotensin II. Oral administration of ONO-AE3-208 (0.01-0.5 mg/kg/day), an EP4 antagonist, for 4 weeks significantly decreased the formation of AAA (45-87% reduction, P<0.05). Similarly, EP4(+/-)/ApoE(-/-) mice exhibited significantly less AAA formation than EP4(+/+)/ApoE(-/-) mice (76% reduction, P<0.01). AAA formation induced by periaortic CaCl(2) application was also reduced in EP4(+/-) mice compared with wild-type mice (73% reduction, P<0.001). Furthermore, in human AAA tissue organ cultures containing SMCs and macrophages, doses of the EP4 antagonist at 10-100 nM decreased MMP-2 activation and IL-6 production (0.6 ± 0.06- and 0.7 ± 0.06-fold, respectively, P<0.05) without increasing MMP-9 activity or MCP-1 secretion. Thus, either pharmacological or genetic EP4 inhibition attenuated AAA formation in multiple mouse and human models by lowering MMP activity and cytokine release. CONCLUSION: An EP4 antagonist that prevents the activation of MMP and thereby inhibits the degradation of aortic elastic fiber may serve as a new strategy for medical treatment of AAA

Amygdala connectivity related to subsequent stress responses during the COVID-19 outbreak

Introduction: The amygdala plays an important role in stress responses and stress-related psychiatric disorders. It is possible that amygdala connectivity may be a neurobiological vulnerability marker for stress responses or stress-related psychiatric disorders and will be useful to precisely identify the vulnerable individuals before stress happens. However, little is known about the relationship between amygdala connectivity and subsequent stress responses. The current study investigated whether amygdala connectivity measured before experiencing stress is a predisposing neural feature of subsequent stress responses while individuals face an emergent and unexpected event like the COVID-19 outbreak. Methods: Data collected before the COVID-19 pandemic from an established fMRI cohort who lived in the pandemic center in China (Hubei) during the COVID-19 outbreak were used to investigate the relationship between amygdala connectivity and stress responses during and after the pandemic in 2020. The amygdala connectivity was measured with resting-state functional connectivity (rsFC) and effective connectivity. Results: We found the rsFC of the right amygdala with the dorsomedial prefrontal cortex (dmPFC) was negatively correlated with the stress responses at the first survey during the COVID-19 outbreak, and the rsFC between the right amygdala and bilateral superior frontal gyri (partially overlapped with the dmPFC) was correlated with SBSC at the second survey. Dynamic causal modeling suggested that the self-connection of the right amygdala was negatively correlated with stress responses during the pandemic. Discussion: Our findings expand our understanding about the role of amygdala in stress responses and stress-related psychiatric disorders and suggest that amygdala connectivity is a predisposing neural feature of subsequent stress responses

A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing

Conventionally, the resource allocation is formulated as an optimization problem and solved online with instantaneous scenario information. Since most resource allocation problems are not convex, the optimal solutions are very difficult to be obtained in real time. Lagrangian relaxation or greedy methods are then often employed, which results in performance loss. Therefore, the conventional methods of resource allocation are facing great challenges to meet the ever-increasing QoS requirements of users with scarce radio resource. Assisted by cloud computing, a huge amount of historical data on scenarios can be collected for extracting similarities among scenarios using machine learning. Moreover, optimal or near-optimal solutions of historical scenarios can be searched offline and stored in advance. When the measured data of current scenario arrives, the current scenario is compared with historical scenarios to find the most similar one. Then, the optimal or near-optimal solution in the most similar historical scenario is adopted to allocate the radio resources for the current scenario. To facilitate the application of new design philosophy, a machine learning framework is proposed for resource allocation assisted by cloud computing. An example of beam allocation in multi-user massive multiple-input-multiple-output (MIMO) systems shows that the proposed machine-learning based resource allocation outperforms conventional methods