Macroscopic transport by synthetic molecular machines

Nature uses molecular motors and machines in virtually every significant biological process, but demonstrating that simpler artificial structures operating through the same gross mechanisms can be interfaced with—and perform physical tasks in—the macroscopic world represents a significant hurdle for molecular nanotechnology. Here we describe a wholly synthetic molecular system that converts an external energy source (light) into biased brownian motion to transport a macroscopic cargo and do measurable work. The millimetre-scale directional transport of a liquid on a surface is achieved by using the biased brownian motion of stimuli-responsive rotaxanes (‘molecular shuttles’) to expose or conceal fluoroalkane residues and thereby modify surface tension. The collective operation of a monolayer of the molecular shuttles is sufficient to power the movement of a microlitre droplet of diiodomethane up a twelve-degree incline.

Acute dosing of latrepirdine (Dimebon), a possible Alzheimer therapeutic, elevates extracellular amyloid-beta levels in vitro and in vivo.

BACKGROUND: Recent reports suggest that latrepirdine (Dimebon, dimebolin), a retired Russian antihistamine, improves cognitive function in aged rodents and in patients with mild to moderate Alzheimer's disease (AD). However, the mechanism(s) underlying this benefit remain elusive. AD is characterized by extracellular accumulation of the amyloid-beta (Abeta) peptide in the brain, and Abeta-lowering drugs are currently among the most popular anti-amyloid agents under development for the treatment of AD. In the current study, we assessed the effect of acute dosing of latrepirdine on levels of extracellular Abeta using in vitro and in vivo experimental systems. RESULTS: We evaluated extracellular levels of Abeta in three experimental systems, under basal conditions and after treatment with latrepirdine. Mouse N2a neuroblastoma cells overexpressing Swedish APP were incubated for 6 hr in the presence of either vehicle or vehicle + latrepirdine (500pM-5 muM). Synaptoneurosomes were isolated from TgCRND8 mutant APP-overexpressing transgenic mice and incubated for 0 to 10 min in the absence or presence of latrepirdine (1 muM or 10 muM). Drug-naïve Tg2576 Swedish mutant APP overexpressing transgenic mice received a single intraperitoneal injection of either vehicle or vehicle + latrepirdine (3.5 mg/kg). Picomolar to nanomolar concentrations of acutely administered latrepirdine increased the extracellular concentration of Abeta in the conditioned media from Swedish mutant APP-overexpressing N2a cells by up to 64% (p = 0.01), while a clinically relevant acute dose of latrepirdine administered i.p. led to an increase in the interstitial fluid of freely moving APP transgenic mice by up to 40% (p = 0.01). Reconstitution of membrane protein trafficking and processing is frequently inefficient, and, consistent with this interpretation, latrepirdine treatment of isolated TgCRND8 synaptoneurosomes involved higher concentrations of drug (1-10 muM) and led to more modest increases in extracellular Abeta(x-42 )levels (+10%; p = 0.001); of note, however, was the observation that extracellular Abeta(x-40 )levels did not change. CONCLUSIONS: Here, we report the surprising association of acute latrepirdine dosing with elevated levels of extracellular Abeta as measured in three independent neuron-related or neuron-derived systems, including the hippocampus of freely moving Tg2576 mice. Given the reported association of chronic latrepirdine treatment with improvement in cognitive function, the effects of chronic latrepirdine treatment on extracellular Abeta levels must now be determined.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

DNA methylation subgroups and the CpG island methylator phenotype in gastric cancer: A comprehensive profiling approach

10.1186/1471-230X-14-55BMC Gastroenterology141-BGMA

Daratumumab plus lenalidomide and dexamethasone versus lenalidomide and dexamethasone in relapsed or refractory multiple myeloma: updated analysis of POLLUX.

In the POLLUX study, daratumumab plus lenalidomide/dexamethasone significantly reduced risk of progression/death versus lenalidomide/dexamethasone alone in relapsed/refractory multiple myeloma. We provide one additional year of follow up and include the effect on minimal residual disease and in clinically relevant subgroups. After 25.4 months of follow up, daratumumab plus lenalidomide/dexamethasone prolonged progression-free survival versus lenalidomide/dexamethasone alone (median not reached vs 17.5 months; hazard ratio, 0.41; 95% confidence interval, 0.31-0.53; P<0.0001). The overall response rate was 92.9% versus 76.4%, and 51.2% versus 21.0% achieved a complete response or better, respectively (both P<0.0001). At the 10-5 sensitivity threshold, 26.2% versus 6.4% were minimal residual disease-negative, respectively (P<0.0001). Post hoc analyses of clinically relevant patient subgroups demonstrated that progression-free survival was significantly prolonged for daratumumab plus lenalidomide/dexamethasone versus lenalidomide/dexamethasone regardless of number of prior lines of therapy. Patients previously treated with lenalidomide or thalidomide and those refractory to bortezomib received similar benefits (all P<0.01). Treatment benefit with daratumumab plus lenalidomide/dexamethasone was maintained in high-risk patients (median progression-free survival 22.6 vs 10.2 months; hazard ratio, 0.53; 95% confidence interval, 0.25-1.13; P=0.0921) and patients with treatment-free intervals of >12 and ≤12 months and >6 and ≤6 months. No new safety signals were observed. In relapsed/refractory multiple myeloma patients, daratumumab plus lenalidomide/dexamethasone continued to improve progression-free survival and deepen responses versus lenalidomide/dexamethasone. Trial Registration: clinicaltrials.gov identifier: 02076009

Single-molecule experiments in biological physics: methods and applications

I review single-molecule experiments (SME) in biological physics. Recent technological developments have provided the tools to design and build scientific instruments of high enough sensitivity and precision to manipulate and visualize individual molecules and measure microscopic forces. Using SME it is possible to: manipulate molecules one at a time and measure distributions describing molecular properties; characterize the kinetics of biomolecular reactions and; detect molecular intermediates. SME provide the additional information about thermodynamics and kinetics of biomolecular processes. This complements information obtained in traditional bulk assays. In SME it is also possible to measure small energies and detect large Brownian deviations in biomolecular reactions, thereby offering new methods and systems to scrutinize the basic foundations of statistical mechanics. This review is written at a very introductory level emphasizing the importance of SME to scientists interested in knowing the common playground of ideas and the interdisciplinary topics accessible by these techniques. The review discusses SME from an experimental perspective, first exposing the most common experimental methodologies and later presenting various molecular systems where such techniques have been applied. I briefly discuss experimental techniques such as atomic-force microscopy (AFM), laser optical tweezers (LOT), magnetic tweezers (MT), biomembrane force probe (BFP) and single-molecule fluorescence (SMF). I then present several applications of SME to the study of nucleic acids (DNA, RNA and DNA condensation), proteins (protein-protein interactions, protein folding and molecular motors). Finally, I discuss applications of SME to the study of the nonequilibrium thermodynamics of small systems and the experimental verification of fluctuation theorems. I conclude with a discussion of open questions and future perspectives.Comment: Latex, 60 pages, 12 figures, Topical Review for J. Phys. C (Cond. Matt

Short interfering RNA against STAT1 attenuates cisplatin-induced ototoxicity in the rat by suppressing inflammation

Cisplatin is widely used for treating various solid tumors. However, this drug produces dose-limiting ototoxicity and nephrotoxicity, which significantly reduce the quality of life of cancer patients. While nephrotoxicity could be alleviated by diuresis, there is currently no approved treatment for hearing loss. Previous studies show that the ROS and inflammation are major contributors to cisplatin-induced hearing loss. In this study, we show that ROS trigger the inflammatory process in the cochlea by activating signal transducer and activator of transcription-1 (STAT1). Activation of STAT1 activation was dependent on ROS generation through NOX3 NADPH oxidase, knockdown of which by siRNA reduced STAT1 activation. Moreover, STAT1 siRNA protected against activation of p53, reduced apoptosis, reduced damage to OHCs and preserved hearing in rats. STAT1 siRNA attenuated the increase in inflammatory mediators, such as TNF-α, inhibition of which protected cells from cisplatin-mediated apoptosis. Finally, we showed that trans-tympanic administration of etanercept, a TNF-α antagonist, protected against OHC damage and cisplatin-induced hearing loss. These studies suggest that controlling inflammation by inhibition of STAT1-dependent pathways in the cochlea could serve as an effective approach to treat cisplatin ototoxicity and improve the overall quality of life for cancer patients

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Critical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions underlie many important biological processes. Computational prediction methods can nicely complement experimental approaches for identifying protein-protein interactions. Recently, a unique category of sequence-based prediction methods has been put forward - unique in the sense that it does not require homologous protein sequences. This enables it to be universally applicable to all protein sequences unlike many of previous sequence-based prediction methods. If effective as claimed, these new sequence-based, universally applicable prediction methods would have far-reaching utilities in many areas of biology research.</p> <p>Results</p> <p>Upon close survey, I realized that many of these new methods were ill-tested. In addition, newer methods were often published without performance comparison with previous ones. Thus, it is not clear how good they are and whether there are significant performance differences among them. In this study, I have implemented and thoroughly tested 4 different methods on large-scale, non-redundant data sets. It reveals several important points. First, significant performance differences are noted among different methods. Second, data sets typically used for training prediction methods appear significantly biased, limiting the general applicability of prediction methods trained with them. Third, there is still ample room for further developments. In addition, my analysis illustrates the importance of complementary performance measures coupled with right-sized data sets for meaningful benchmark tests.</p> <p>Conclusions</p> <p>The current study reveals the potentials and limits of the new category of sequence-based protein-protein interaction prediction methods, which in turn provides a firm ground for future endeavours in this important area of contemporary bioinformatics.</p