A MicroRNA Linking Human Positive Selection and Metabolic Disorders

Postponed access: the file will be accessible after 2021-10-14Positive selection in Europeans at the 2q21.3 locus harboring the lactase gene has been attributed to selection for the ability of adults to digest milk to survive famine in ancient times. However, the 2q21.3 locus is also associated with obesity and type 2 diabetes in humans, raising the possibility that additional genetic elements in the locus may have contributed to evolutionary adaptation to famine by promoting energy storage, but which now confer susceptibility to metabolic diseases. We show here that the miR-128-1 microRNA, located at the center of the positively selected locus, represents a crucial metabolic regulator in mammals. Antisense targeting and genetic ablation of miR-128-1 in mouse metabolic disease models result in increased energy expenditure and amelioration of high-fat-diet-induced obesity and markedly improved glucose tolerance. A thrifty phenotype connected to miR-128-1-dependent energy storage may link ancient adaptation to famine and modern metabolic maladaptation associated with nutritional overabundance.acceptedVersio

Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis

New therapeutic strategies are needed to combat the tuberculosis pandemic and the spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) forms of the disease, which remain a serious public health challenge worldwide1, 2. The most urgent clinical need is to discover potent agents capable of reducing the duration of MDR and XDR tuberculosis therapy with a success rate comparable to that of current therapies for drug-susceptible tuberculosis. The last decade has seen the discovery of new agent classes for the management of tuberculosis3, 4, 5, several of which are currently in clinical trials6, 7, 8. However, given the high attrition rate of drug candidates during clinical development and the emergence of drug resistance, the discovery of additional clinical candidates is clearly needed. Here, we report on a promising class of imidazopyridine amide (IPA) compounds that block Mycobacterium tuberculosis growth by targeting the respiratory cytochrome bc1 complex. The optimized IPA compound Q203 inhibited the growth of MDR and XDR M. tuberculosis clinical isolates in culture broth medium in the low nanomolar range and was efficacious in a mouse model of tuberculosis at a dose less than 1 mg per kg body weight, which highlights the potency of this compound. In addition, Q203 displays pharmacokinetic and safety profiles compatible with once-daily dosing. Together, our data indicate that Q203 is a promising new clinical candidate for the treatment of tuberculosis

Multiple b-values improve discrimination of cortical gray matter regions using diffusion MRI: an experimental validation with a data-driven approach

Objective To investigate whether varied or repeated b-values provide better diffusion MRI data for discriminating cortical areas with a data-driven approach. Methods Data were acquired from three volunteers at 1.5T with b-values of 800, 1400, 2000 s/mm$^{2}$ along 64 diffusion-encoding directions. The diffusion signal was sampled from gray matter in seven regions of interest (ROIs). Rotational invariants of the local diffusion profile were extracted as features that characterize local tissue properties. Random forest classification experiments assessed whether classification accuracy improved when data with multiple b-values were used over repeated acquisition of the same (1400 s/mm$^{2}$) b-value to compare all possible pairs of the seven ROIs. Three data sets from the Human Connectome Project were subjected to similar processing and analysis pipelines in eight ROIs. Results Three different b-values showed an average improvement in correct classification rates of 5.6% and 4.6%, respectively, in the local and HCP data over repeated measurements of the same b-value. The improvement in correct classification rate reached as high as 16% for individual binary classification experiments between two ROIs. Often using only two of the available three b-values were adequate to make such an improvement in classification rates. Conclusion Acquisitions with varying b-values are more suitable for discriminating cortical areas

Recombinant as a biofactory for various single- and multi-element nanomaterials

Nanomaterials (NMs) are mostly synthesized by chemical and physical methods, but biological synthesis is also receiving great attention. However, the mechanisms for biological producibility of NMs, crystalline versus amorphous, are not yet understood. Here we report biosynthesis of 60 different NMs by employing a recombinant Escherichia coli strain coexpressing metallothionein, a metal-binding protein, and phytochelatin synthase that synthesizes a metal-binding peptide phytochelatin. Both an in vivo method employing live cells and an in vitro method employing the cell extract are used to synthesize NMs. The periodic table is scanned to select 35 suitable elements, followed by biosynthesis of their NMs. Nine crystalline single-elements of Mn3O4, Fe3O4, Cu2O, Mo, Ag, In(OH)3, SnO2, Te, and Au are synthesized, while the other 16 elements result in biosynthesis of amorphous NMs or no NM synthesis. Producibility and crystallinity of the NMs are analyzed using a Pourbaix diagram that predicts the stable chemical species of each element for NM biosynthesis by varying reduction potential and pH. Based on the analyses, the initial pH of reactions is changed from 6.5 to 7.5, resulting in biosynthesis of various crystalline NMs of those previously amorphous or not-synthesized ones. This strategy is extended to biosynthesize multi-element NMs including CoFe2O4, NiFe2O4, ZnMn2O4, ZnFe2O4, Ag2S, Ag2TeO3, Ag2WO4, Hg3TeO6, PbMoO4, PbWO4, and Pb5(VO4)3OH NMs. The strategy described here allows biosynthesis of NMs with various properties, providing a platform for manufacturing various NMs in an environmentally friendly manner

Contribution of the Degeneration of the Neuro-Axonal Unit to the Pathogenesis of Multiple Sclerosis

Multiple sclerosis (MS) is a demyelinating, autoimmune disease of the central nervous system. In recent years, it has become more evident that neurodegeneration, including neuronal damage and axonal injury, underlies permanent disability in MS. This manuscript reviews some of the mechanisms that could be responsible for neurodegeneration and axonal damage in MS and highlights the potential role that dysfunctional heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) and antibodies to hnRNP A1 may play in MS pathogenesis

Multiple b-values improve discrimination of cortical gray matter regions using diffusion MRI: an experimental validation with a data-driven approach

Objective To investigate whether varied or repeated b-values provide better diffusion MRI data for discriminating cortical areas with a data-driven approach. Methods Data were acquired from three volunteers at 1.5T with b-values of 800, 1400, 2000 s/mm2 along 64 diffusion-encoding directions. The diffusion signal was sampled from gray matter in seven regions of interest (ROIs). Rotational invariants of the local diffusion profile were extracted as features that characterize local tissue properties. Random forest classification experiments assessed whether classification accuracy improved when data with multiple b-values were used over repeated acquisition of the same (1400 s/mm2) b-value to compare all possible pairs of the seven ROIs. Three data sets from the Human Connectome Project were subjected to similar processing and analysis pipelines in eight ROIs. Results Three different b-values showed an average improvement in correct classification rates of 5.6% and 4.6%, respectively, in the local and HCP data over repeated measurements of the same b-value. The improvement in correct classification rate reached as high as 16% for individual binary classification experiments between two ROIs. Often using only two of the available three b-values were adequate to make such an improvement in classification rates. Conclusion Acquisitions with varying b-values are more suitable for discriminating cortical areas.ISSN:0968-5243ISSN:1352-866

First-dollar cost-sharing for skilled nursing facility care in medicare advantage plans.

BackgroundThe initial days of a Medicare-covered skilled nursing facility (SNF) stay may have no cost-sharing or daily copayments depending on beneficiaries' enrollment in traditional Medicare or Medicare Advantage. Some policymakers have advocated imposing first-dollar cost-sharing to reduce post-acute expenditures. We examined the relationship between first-dollar cost-sharing for a SNF stay and use of inpatient and SNF services.MethodsWe identified seven Medicare Advantage plans that introduced daily SNF copayments of $25-$150 in 2009 or 2010. Copays began on the first day of a SNF admission. We matched these plans to seven matched control plans that did not introduce first-dollar cost-sharing. In a difference-in-differences analysis, we compared changes in SNF and inpatient utilization for the 172,958 members of intervention and control plans.ResultsIn intervention plans the mean annual number of SNF days per 100 continuously enrolled inpatients decreased from 768.3 to 750.6 days when cost-sharing changes took effect. Control plans experienced a concurrent increase: 721.7 to 808.1 SNF days per 100 inpatients (adjusted difference-in-differences: -87.0 days [95% CI (-112.1,-61.9)]). In intervention plans, we observed no significant changes in the probability of any SNF service use or the number of inpatient days per hospitalized member relative to concurrent trends among control plans.ConclusionsAmong several strategies Medicare Advantage plans can employ to moderate SNF use, first-dollar SNF cost-sharing may be one influential factor.Trial registrationNot applicable

First-dollar cost-sharing for skilled nursing facility care in medicare advantage plans

Abstract Background The initial days of a Medicare-covered skilled nursing facility (SNF) stay may have no cost-sharing or daily copayments depending on beneficiaries’ enrollment in traditional Medicare or Medicare Advantage. Some policymakers have advocated imposing first-dollar cost-sharing to reduce post-acute expenditures. We examined the relationship between first-dollar cost-sharing for a SNF stay and use of inpatient and SNF services. Methods We identified seven Medicare Advantage plans that introduced daily SNF copayments of $25-$150 in 2009 or 2010. Copays began on the first day of a SNF admission. We matched these plans to seven matched control plans that did not introduce first-dollar cost-sharing. In a difference-in-differences analysis, we compared changes in SNF and inpatient utilization for the 172,958 members of intervention and control plans. Results In intervention plans the mean annual number of SNF days per 100 continuously enrolled inpatients decreased from 768.3 to 750.6 days when cost-sharing changes took effect. Control plans experienced a concurrent increase: 721.7 to 808.1 SNF days per 100 inpatients (adjusted difference-in-differences: −87.0 days [95% CI (−112.1,-61.9)]). In intervention plans, we observed no significant changes in the probability of any SNF service use or the number of inpatient days per hospitalized member relative to concurrent trends among control plans. Conclusions Among several strategies Medicare Advantage plans can employ to moderate SNF use, first-dollar SNF cost-sharing may be one influential factor. Trial registration Not applicable