Temperature-driven reorganization of electronic order in CsV3_3Sb5_5

We report a temperature dependent x-ray diffraction study of the electronic ordering instabilities in the kagome material CsV$_3$Sb$_5$. Our measurements between 10 K and 120 K reveal an unexpected reorganization of the three-dimensional electronic order in the bulk of CsV$_3$Sb$_5$: At 10 K, a 2x2x2 superstructure modulation due to electronic order is observed, which upon warming changes to a 2x2x4 superstructure at 60 K. The electronic order-order transition discovered here involves a change in the stacking of electronically ordered V$_3$Sb$_5$-layers and agrees perfectly with anomalies previously observed in magneto-transport measurements. This implies that the temperature dependent three-dimensional electronic order plays a decisive role for transport properties, which are related to the Berry-curvature of the V-bands. Our data also show that the bulk electronic order in CsV$_3$Sb$_5$ breaks the 6-fold rotational symmetry of the underlying $P6/mmm$ lattice structure.Comment: 5 pages, 3 figure

Precision medicine for suicidality: from universality to subtypes and personalization

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a ‘liquid biopsy’ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator

In vitro characterization of sonothrombolysis and echocontrast agents to treat ischemic stroke

The development of adjuvant techniques to improve thrombolytic efficacy is important for advancing ischemic stroke therapy. We characterized octafluoropropane and recombinant tissue plasminogen activator (rt-PA)-loaded echogenic liposomes (OFP t-ELIP) using differential interference and fluorescence microscopy, attenuation spectroscopy, and electrozone sensing. The loading of rt-PA in OFP t-ELIP was assessed using spectrophotometry. Further, it was tested whether the agent shields rt-PA against degradation by plasminogen activator inhibitor-1 (PAI-1). An in vitro system was used to assess whether ultrasound (US) combined with either Definity or OFP t-ELIP enhances rt-PA thrombolysis. Human whole blood clots were mounted in a flow system and visualized using an inverted microscope. The perfusate consisted of either (1) plasma alone, (2) rt-PA, (3) OFP t-ELIP, (4) rt-PA and US, (5) OFP t-ELIP and US, (6) Definity and US, or (7) rt-PA, Definity, and US (n = 16 clots per group). An intermittent US insonation scheme was employed (220 kHz frequency, and 0.44 MPa peak-to-peak pressures) for 30 min. Microscopic imaging revealed that OFP t-ELIP included a variety of structures such as liposomes (with and without gas) and lipid-shelled microbubbles. OFP t-ELIP preserved up to 76% of rt-PA activity in the presence of PAI-1, whereas only 24% activity was preserved for unencapsulated rt-PA. The use of US with rt-PA and Definity enhanced lytic efficacy (p \u3c 0.05) relative to rt-PA alone. US combined with OFP t-ELIP enhanced lysis over OFP t-ELIP alone (p \u3c 0.01). These results demonstrate that ultrasound combined with Definity or OFP t-ELIP can enhance the lytic activity relative to rt-PA or OFP t-ELIP alone, respectively

Transductive Learning for Spatial Data Classification

Learning classifiers of spatial data presents several issues, such as the heterogeneity of spatial objects, the implicit definition of spatial relationships among objects, the spatial autocorrelation and the abundance of unlabelled data which potentially convey a large amount of information. The first three issues are due to the inherent structure of spatial units of analysis, which can be easily accommodated if a (multi-)relational data mining approach is considered. The fourth issue demands for the adoption of a transductive setting, which aims to make predictions for a given set of unlabelled data. Transduction is also motivated by the contiguity of the concept of positive autocorrelation, which typically affect spatial phenomena, with the smoothness assumption which characterize the transductive setting. In this work, we investigate a relational approach to spatial classification in a transductive setting. Computational solutions to the main difficulties met in this approach are presented. In particular, a relational upgrade of the nave Bayes classifier is proposed as discriminative model, an iterative algorithm is designed for the transductive classification of unlabelled data, and a distance measure between relational descriptions of spatial objects is defined in order to determine the k-nearest neighbors of each example in the dataset. Computational solutions have been tested on two real-world spatial datasets. The transformation of spatial data into a multi-relational representation and experimental results are reported and commented

Alterations of EGFR, p53 and PTEN that mimic changes found in basal-like breast cancer promote transformation of human mammary epithelial cells

Breast cancer can be classified into different molecular subtypes with varying clinical and pathological characteristics. The basal-like breast cancer subtype represents one of the most aggressive and lethal types of breast cancer, and due to poor mechanistic understanding, it lacks targeted therapy. Many basal-like breast cancer patient samples display alterations of established drivers of cancer development, including elevated expression of EGFR, p53 inactivating mutations and loss of expression of the tumor suppressor PTEN; however, their contribution to human basal-like breast cancer pathogenesis remains ill-defined. Using non-transformed human mammary epithelial cells, we set out to determine whether altering EGFR, p53 and PTEN in different combinations could contribute to basal-like breast cancer progression through transformation of cells. Altering PTEN in combination with either p53 or EGFR in contrast to any of the single alterations caused increased growth of transformed colonies in soft agar. Concomitantly modifying all three genes led to the highest rate of cellular proliferation and the greatest degree of anchorage-independent colony formation. Results from our effort to engineer a model of BBC expressing alterations of EGFR, p53 and PTEN suggest that these changes are cooperative and likely play a causal role in basal-like breast cancer pathogenesis. Consideration should be given to targeting EGFR and restoring p53 and PTEN signaling simultaneously as a strategy for treatment of this subtype of breast cancer

Review of the mathematical foundations of data fusion techniques in surface metrology

The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed

Prospects for Improving the Intrinsic and Extrinsic Properties of Magnesium Diboride Superconducting Strands

The magnetic and transport properties of magnesium diboride films represent performance goals yet to be attained by powder-processed bulk samples and conductors. Such performance limits are still out of the reach of even the best magnesium diboride magnet wire. In discussing the present status and prospects for improving the performance of powder-based wire we focus attention on (1) the intrinsic (intragrain) superconducting properties of magnesium diboride, Hc2 and flux pinning, (2) factors that control the efficiency with which current is transported from grain-to-grain in the conductor, an extrinsic (intergrain) property. With regard to Item-(1), the role of dopants in Hc2 enhancement is discussed and examples presented. On the other hand their roles in increasing Jc, both via Hc2 enhancement as well as direct fluxoid/pining-center interaction, are discussed and a comprehensive survey of Hc2 dopants and flux-pinning additives is presented. Current transport through the powder-processed wire (an extrinsic property) is partially blocked by the inherent granularity of the material itself and the chemical or other properties of the intergrain surfaces. These and other such results indicate that in many cases less than 15% of the conductor's cross sectional area is able to carry transport current. It is pointed out that densification in association with the elimination of grain-boundary blocking phases would yield five-to ten-fold increases in Jc in relevant regimes, enabling the performance of magnesium diboride in selected applications to compete with that of Nb-Sn

Orexin Depolarizes Central Amygdala Neurons via Orexin Receptor 1, Phospholipase C and Sodium-Calcium Exchanger and Modulates Conditioned Fear

Orexins (OX), also known as hypocretins, are excitatory neuropeptides with well-described roles in regulation of wakefulness, arousal, energy homeostasis, and anxiety. An additional and recently recognized role of OX is modulation of fear responses. We studied the OX neurons of the perifornical hypothalamus (PeF) which send projections to the amygdala, a region critical in fear learning and fear expression. Within the amygdala, the highest density of OX-positive fibers was detected in the central nucleus (CeA). The specific mechanisms underlying OX neurotransmission within the CeA were explored utilizing rat brain slice electrophysiology, pharmacology, and chemogenetic stimulation. We show that OX induces postsynaptic depolarization of medial CeA neurons that is mediated by OX receptor 1 (OXR1) but not OX receptor 2 (OXR2). We further characterized the mechanism of CeA depolarization by OX as phospholipase C (PLC)- and sodium-calcium exchanger (NCX)- dependent. Selective chemogenetic stimulation of OX PeF fibers recapitulated OXR1 dependent depolarization of CeA neurons. We also observed that OXR1 activity modified presynaptic release of glutamate within the CeA. Finally, either systemic or intra-CeA perfusion of OXR1 antagonist reduced the expression of conditioned fear. Together, these data suggest the PeF-CeA orexinergic pathway can modulate conditioned fear through a signal transduction mechanism involving PLC and NCX activity and that selective OXR1 antagonism may be a putative treatment for fear-related disorders

Dual action antifungal small molecule modulates multidrug efflux and TOR signaling.

There is an urgent need for new strategies to treat invasive fungal infections, which are a leading cause of human mortality. Here, we establish two activities of the natural product beauvericin, which potentiates the activity of the most widely deployed class of antifungal against the leading human fungal pathogens, blocks the emergence of drug resistance, and renders antifungal-resistant pathogens responsive to treatment in mammalian infection models. Harnessing genome sequencing of beauvericin-resistant mutants, affinity purification of a biotinylated beauvericin analog, and biochemical and genetic assays reveals that beauvericin blocks multidrug efflux and inhibits the global regulator TORC1 kinase, thereby activating the protein kinase CK2 and inhibiting the molecular chaperone Hsp90. Substitutions in the multidrug transporter Pdr5 that enable beauvericin efflux impair antifungal efflux, thereby impeding resistance to the drug combination. Thus, dual targeting of multidrug efflux and TOR signaling provides a powerful, broadly effective therapeutic strategy for treating fungal infectious disease that evades resistance

Endothelial cells stimulate growth of normal and cancerous breast epithelial cells in 3D culture

<p>Abstract</p> <p>Background</p> <p>Epithelial-stromal interaction provides regulatory signals that maintain correct histoarchitecture and homeostasis in the normal breast and facilitates tumor progression in breast cancer. However, research on the regulatory role of the endothelial component in the normal and malignant breast gland has largely been neglected. The aim of the study was to investigate the effects of endothelial cells on growth and differentiation of human breast epithelial cells in a three-dimensional (3D) co-culture assay.</p> <p>Methods</p> <p>Breast luminal and myoepithelial cells and endothelial cells were isolated from reduction mammoplasties. Primary cells and established normal and malignant breast cell lines were embedded in reconstituted basement membrane in direct co-culture with endothelial cells and by separation of Transwell filters. Morphogenic and phenotypic profiles of co-cultures was evaluated by phase contrast microscopy, immunostaining and confocal microscopy.</p> <p>Results</p> <p>In co-culture, endothelial cells stimulate proliferation of both luminal- and myoepithelial cells. Furthermore, endothelial cells induce a subpopulation of luminal epithelial cells to form large acini/ducts with a large and clear lumen. Endothelial cells also stimulate growth and cloning efficiency of normal and malignant breast epithelial cell lines. Transwell and gradient co-culture studies show that endothelial derived effects are mediated - at least partially - by soluble factors.</p> <p>Conclusion</p> <p>Breast endothelial cells - beside their role in transporting nutrients and oxygen to tissues - are vital component of the epithelial microenvironment in the breast and provide proliferative signals to the normal and malignant breast epithelium. These growth promoting effects of endothelial cells should be taken into consideration in breast cancer biology.</p