Finite temperature Dicke phase transition of a Bose-Einstein condensate in an optical cavity

Dicke model predicts a quantum phase transition from normal to superradiant phases for a two-level atomic ensemble coupled with an optical cavity at zero temperature. In a recent pioneer experiment [Nature 464, 1301 (2010)], such a phase transition has been observed using a Bose-Einstein condensate (BEC) in an optical cavity. Compared with the original Dicke model, the experimental system features finite temperature and strong atom-photon nonlinear interaction in BEC. In this Letter, we develop a finite temperature theory for the Dicke phase transition of a BEC in an optical cavity, taking into account the atom-photon nonlinear interaction. In addition to explaining the experimentally observed transition from normal to superradiant phases at finite-temperature, we point it out that a new phase, the coexistence of normal and superradient phases, was also observed in the experiment. We show rich finite temperature phase diagrams existing in the experimental system by tuning various experimental parameters. We find that the specific heat of the BEC can serve as a powerful tool for probing various phases.Comment: 5 pages, 5 figure

Incorporating basic calibrations in existing machine-learned turbulence modeling

This work aims to incorporate basic calibrations of Reynolds-averaged Navier-Stokes (RANS) models as part of machine learning (ML) frameworks. The ML frameworks considered are tensor-basis neural network (TBNN), physics-informed machine learning (PIML), and field inversion & machine learning (FIML) in J. Fluid Mech., 2016, 807, 155-166, Phys. Rev. Fluids, 2017, 2(3), 034603 and J. Comp. Phys., 2016, 305, 758-774, and the baseline RANS models are the one-equation Spalart-Allmaras model, the two-equation $k$-$\omega$ model, and the seven-equation Reynolds stress transport models. ML frameworks are trained against plane channel flow and shear-layer flow data. We compare the ML frameworks and study whether the machine-learned augmentations are detrimental outside the training set. The findings are summarized as follows. The augmentations due to TBNN are detrimental. PIML leads to augmentations that are beneficial inside the training dataset but detrimental outside it. These results are not affected by the baseline RANS model. FIML's augmentations to the two eddy viscosity models, where an inner-layer treatment already exists, are largely neutral. Its augmentation to the seven-equation model, where an inner-layer treatment does not exist, improves the mean flow prediction in a channel. Furthermore, these FIML augmentations are mostly non-detrimental outside the training dataset. In addition to reporting these results, the paper offers physical explanations of the results. Last, we note that the conclusions drawn here are confined to the ML frameworks and the flows considered in this study. More detailed comparative studies and validation & verification studies are needed to account for developments in recent years

Differential Effects of Thiopeptide and Orthosomycin Antibiotics on Translational GTPases

SummaryThe ribosome is a major target in the bacterial cell for antibiotics. Here, we dissect the effects that the thiopeptide antibiotics thiostrepton (ThS) and micrococcin (MiC) as well as the orthosomycin antibiotic evernimicin (Evn) have on translational GTPases. We demonstrate that, like ThS, MiC is a translocation inhibitor, and that the activation by MiC of the ribosome-dependent GTPase activity of EF-G is dependent on the presence of the ribosomal proteins L7/L12 as well as the G′ subdomain of EF-G. In contrast, Evn does not inhibit translocation but is a potent inhibitor of back-translocation as well as IF2-dependent 70S-initiation complex formation. Collectively, these results shed insight not only into fundamental aspects of translation but also into the unappreciated specificities of these classes of translational inhibitors

A Salmonella nanoparticle mimic overcomes multidrug resistance in tumours

Salmonella enterica serotype Typhimurium is a food-borne pathogen that also selectively grows in tumours and functionally decreases P-glycoprotein (P-gp), a multidrug resistance transporter. Here we report that the Salmonella type III secretion effector, SipA, is responsible for P-gp modulation through a pathway involving caspase-3. Mimicking the ability of Salmonella to reverse multidrug resistance, we constructed a gold nanoparticle system packaged with a SipA corona, and found this bacterial mimic not only accumulates in tumours but also reduces P-gp at a SipA dose significantly lower than free SipA. Moreover, the Salmonella nanoparticle mimic suppresses tumour growth with a concomitant reduction in P-gp when used with an existing chemotherapeutic drug (that is, doxorubicin). On the basis of our finding that the SipA Salmonella effector is fundamental for functionally decreasing P-gp, we engineered a nanoparticle mimic that both overcomes multidrug resistance in cancer cells and increases tumour sensitivity to conventional chemotherapeutics

Two-stage motion correction for super-resolution ultrasound imaging in human lower limb

The structure of microvasculature cannot be resolved using conventional ultrasound imaging due to the fundamental diffraction limit at clinical ultrasound frequencies. It is possible to overcome this resolution limitation by localizing individual microbubbles through multiple frames and forming a super-resolved image, which usually requires seconds to minutes of acquisition. Over this time interval, motion is inevitable and tissue movement is typically a combination of large and small scale tissue translation and deformation. Therefore, super-resolution imaging is prone to motion artefacts as other imaging modalities based on multiple acquisitions are. This study investigates the feasibility of a two-stage motion estimation method, which is a combination of affine and non-rigid estimation, for super-resolution ultrasound imaging. Firstly, the motion correction accuracy of the proposed method is evaluated using simulations with increasing complexity of motion. A mean absolute error of 12.2 μm was achieved in simulations for the worst case scenario. The motion correction algorithm was then applied to a clinical dataset to demonstrate its potential to enable in vivo super-resolution ultrasound imaging in the presence of patient motion. The size of the identified microvessels from the clinical super-resolution images were measured to assess the feasibility of the two-stage motion correction method, which reduced the width of the motion blurred microvessels approximately 1.5-fold

Regulation of Asymmetrical Cytokinesis by cAMP during Meiosis I in Mouse Oocytes

Mammalian oocytes undergo an asymmetrical first meiotic division, extruding half of their chromosomes in a small polar body to preserve maternal resources for embryonic development. To divide asymmetrically, mammalian oocytes relocate chromosomes from the center of the cell to the cortex, but little is known about the underlying mechanisms. Here, we show that upon the elevation of intracellular cAMP level, mouse oocytes produced two daughter cells with similar sizes. This symmetrical cell division could be rescued by the inhibition of PKA, a cAMP-dependent protein kinase. Live cell imaging revealed that a symmetrically localized cleavage furrow resulted in symmetrical cell division. Detailed analyses demonstrated that symmetrically localized cleavage furrows were caused by the inappropriate central positioning of chromosome clusters at anaphase onset, indicating that chromosome cluster migration was impaired. Notably, high intracellular cAMP reduced myosin II activity, and the microinjection of phospho-myosin II antibody into the oocytes impeded chromosome migration and promoted symmetrical cell division. Our results support the hypothesis that cAMP plays a role in regulating asymmetrical cell division by modulating myosin II activity during mouse oocyte meiosis I, providing a novel insight into the regulation of female gamete formation in mammals

Proliferating Cell Nuclear Antigen (PCNA) Regulates Primordial Follicle Assembly by Promoting Apoptosis of Oocytes in Fetal and Neonatal Mouse Ovaries

Primordial follicles, providing all the oocytes available to a female throughout her reproductive life, assemble in perinatal ovaries with individual oocytes surrounded by granulosa cells. In mammals including the mouse, most oocytes die by apoptosis during primordial follicle assembly, but factors that regulate oocyte death remain largely unknown. Proliferating cell nuclear antigen (PCNA), a key regulator in many essential cellular processes, was shown to be differentially expressed during these processes in mouse ovaries using 2D-PAGE and MALDI-TOF/TOF methodology. A V-shaped expression pattern of PCNA in both oocytes and somatic cells was observed during the development of fetal and neonatal mouse ovaries, decreasing from 13.5 to 18.5 dpc and increasing from 18.5 dpc to 5 dpp. This was closely correlated with the meiotic prophase I progression from pre-leptotene to pachytene and from pachytene to diplotene when primordial follicles started to assemble. Inhibition of the increase of PCNA expression by RNA interference in cultured 18.5 dpc mouse ovaries strikingly reduced the apoptosis of oocytes, accompanied by down-regulation of known pro-apoptotic genes, e.g. Bax, caspase-3, and TNFα and TNFR2, and up-regulation of Bcl-2, a known anti-apoptotic gene. Moreover, reduced expression of PCNA was observed to significantly increase primordial follicle assembly, but these primordial follicles contained fewer guanulosa cells. Similar results were obtained after down-regulation by RNA interference of Ing1b, a PCNA-binding protein in the UV-induced apoptosis regulation. Thus, our results demonstrate that PCNA regulates primordial follicle assembly by promoting apoptosis of oocytes in fetal and neonatal mouse ovaries

Is (poly-) substance use associated with impaired inhibitory control? A mega-analysis controlling for confounders.

Many studies have reported that heavy substance use is associated with impaired response inhibition. Studies typically focused on associations with a single substance, while polysubstance use is common. Further, most studies compared heavy users with light/non-users, though substance use occurs along a continuum. The current mega-analysis accounted for these issues by aggregating individual data from 43 studies (3610 adult participants) that used the Go/No-Go (GNG) or Stop-signal task (SST) to assess inhibition among mostly "recreational" substance users (i.e., the rate of substance use disorders was low). Main and interaction effects of substance use, demographics, and task-characteristics were entered in a linear mixed model. Contrary to many studies and reviews in the field, we found that only lifetime cannabis use was associated with impaired response inhibition in the SST. An interaction effect was also observed: the relationship between tobacco use and response inhibition (in the SST) differed between cannabis users and non-users, with a negative association between tobacco use and inhibition in the cannabis non-users. In addition, participants' age, education level, and some task characteristics influenced inhibition outcomes. Overall, we found limited support for impaired inhibition among substance users when controlling for demographics and task-characteristics

Two-stage motion correction for super-resolution ultrasound imaging in human lower limb

The structure of microvasculature cannot be resolved using conventional ultrasound imaging due to the fundamental diffraction limit at clinical ultrasound frequencies. It is possible to overcome this resolution limitation by localizing individual microbubbles through multiple frames and forming a super-resolved image, which usually requires seconds to minutes of acquisition. Over this time interval, motion is inevitable and tissue movement is typically a combination of large and small scale tissue translation and deformation. Therefore, super-resolution imaging is prone to motion artefacts as other imaging modalities based on multiple acquisitions are. This study investigates the feasibility of a two-stage motion estimation method, which is a combination of affine and non-rigid estimation, for super-resolution ultrasound imaging. Firstly, the motion correction accuracy of the proposed method is evaluated using simulations with increasing complexity of motion. A mean absolute error of 12.2 μm was achieved in simulations for the worst case scenario. The motion correction algorithm was then applied to a clinical dataset to demonstrate its potential to enable in vivo super-resolution ultrasound imaging in the presence of patient motion. The size of the identified microvessels from the clinical super-resolution images were measured to assess the feasibility of the two-stage motion correction method, which reduced the width of the motion blurred microvessels approximately 1.5-fold