Experimental test of the Jarzynski equality in a single spin-1 system using high-fidelity single-shot readouts

The Jarzynski equality (JE), which connects the equilibrium free energy with non-equilibrium work statistics, plays a crucial role in quantum thermodynamics. Although practical quantum systems are usually multi-level systems, most tests of the JE were executed in two-level systems. A rigorous test of the JE by directly measuring the work distribution of a physical process in a high-dimensional quantum system remains elusive. Here, we report an experimental test of the JE in a single spin-1 system. We realized nondemolition projective measurement of this three-level system via cascading high-fidelity single-shot readouts and directly measured the work distribution utilizing the two-point measurement protocol. The validity of the JE was verified from the non-adiabatic to adiabatic zone and under different effective temperatures. Our work puts the JE on a solid experimental foundation and makes the NV center system a mature toolbox to perform advanced experiments of stochastic quantum thermodynamics

Novel plasmid-mediated colistin resistance gene mcr-3 in Escherichia coli

The mobile colistin resistance gene mcr-1 has attracted global attention, as it heralds the breach of polymyxins, one of the last-resort antibiotics for the treatment of severe clinical infections caused by multidrug-resistant Gramnegative bacteria. To date, six slightly different variants of mcr-1, and a second mobile colistin resistance gene, mcr-2, have been reported or annotated in the GenBank database. Here, we characterized a third mobile colistin resistance gene, mcr-3. The gene coexisted with 18 additional resistance determinants in the 261-kb IncHI2-type plasmid pWJ1 from porcine Escherichia coli. mcr-3 showed 45.0% and 47.0% nucleotide sequence identity to mcr-1 and mcr-2, respectively, while the deduced amino acid sequence of MCR-3 showed 99.8 to 100% and 75.6 to 94.8% identity to phosphoethanolamine transferases found in other Enterobacteriaceae species and in 10 Aeromonas species, respectively. pWJ1 was mobilized to an E. coli recipient by conjugation and contained a plasmid backbone similar to those of other mcr- 1-carrying plasmids, such as pHNSHP45-2 from the original mcr-1-harboring E. coli strain. Moreover, a truncated transposon element, TnAs2, which was characterized only in Aeromonas salmonicida, was located upstream of mcr-3 in pWJ1. This ΔTnAs2-mcr-3 element was also identified in a shotgun genome sequence of a porcine E. coli isolate from Malaysia, a human Klebsiella pneumoniae isolate from Thailand, and a human Salmonella enterica serovar Typhimurium isolate from the United States. These results suggest the likelihood of a wide dissemination of the novel mobile colistin resistance gene mcr-3 among Enterobacteriaceae and aeromonads; the latter may act as a potential reservoir for mcr-3. IMPORTANCE The emergence of the plasmid-mediated colistin resistance gene mcr-1 has attracted substantial attention worldwide. Here, we examined a colistin-resistant Escherichia coli isolate that was negative for both mcr-1 and mcr-2 and discovered a novel mobile colistin resistance gene, mcr-3. The amino acid sequence of MCR-3 aligned closely with phosphoethanolamine transferases from Enterobacteriaceae and Aeromonas species originating from both clinical infections and environmental samples collected in 12 countries on four continents. Due to the ubiquitous profile of aeromonads in the environment and the potential transfer of mcr-3 between Enterobacteriaceae and Aeromonas species, the wide spread of mcr-3 may be largely underestimated. As colistin has been and still is widely used in veterinary medicine and used at increasing frequencies in human medicine, the continuous monitoring of mobile colistin resistance determinants in colistin-resistant Gram-negative bacteria is imperative for understanding and tackling the dissemination of mcr genes in both the agricultural and health care sectors

Plasmid-mediated novel blaNDM-17 gene encoding a Carbapenemase with enhanced activity in a sequence type 48 Escherichia coli strain

Carbapenem-resistant Enterobacteriaceae (CRE) have spread worldwide, leaving very few treatment options available. New Delhi metallo-beta-lactamase (NDM) is the main carbapenemase mediating CRE resistance and is of increasing concern. NDM-positive Enterobacteriaceae of human origin are frequently identified; however, the emergence of NDM, and particularly novel variants, in bacteria of food animal origin has never been reported. Here, we characterize a novel NDM variant (assigned NDM-17) identified in a β-lactam-resistant sequence type 48 (ST48) Escherichia coli strain that was isolated from a chicken in China. Compared to NDM-1, NDM-17 had three amino acid substitutions (V88L, M154L, and E170K) that confer significantly enhanced carbapenemase activity. Compared to NDM-5, NDM-17 had only one amino acid substitution (E170K) and slightly increased isolate resistance to carbapenem, as indicated by increased MIC values. The gene encoding NDM-17 (blaNDM-17) was located on an IncX3 plasmid, which was readily transferrable to recipient E. coli strain J53 by conjugation, suggesting the possibility of the rapid dissemination of blaNDM-17. Enzyme kinetics showed that NDM-17 could hydrolyze all β-lactams tested, except for aztreonam, and had a significantly higher affinity for all β-lactams tested than did NDM-5. The emergence of this novel NDM variant could pose a threat to public health because of its transferability and enhanced carbapenemase activity

The impact of local government investment on the carbon emissions reduction effect: An empirical analysis of panel data from 30 provinces and municipalities in China.

Among studies of the factors that influence carbon emissions and related regulations, economic aggregates, industrial structures, energy structures, population levels, and energy prices have been extensively explored, whereas studies from the perspective of fiscal leverage, particularly of local government investment (LGI), are rare. Of the limited number of studies on the effect of LGI on carbon emissions, most focus on its direct effect. Few studies consider regulatory effects, and there is a lack of emphasis on local areas. Using a cointegration test, a panel data model and clustering analysis based on Chinese data between 2000 and 2013, this study measures the direct role of LGI in carbon dioxide (CO2) emissions reduction. First, overall, within the sample time period, a 1% increase in LGI inhibits carbon emissions by 0.8906% and 0.5851% through its influence on the industrial structure and energy efficiency, respectively, with the industrial structure path playing a greater role than the efficiency path. Second, carbon emissions to some extent exhibit inertia. The previous year's carbon emissions impact the following year's carbon emissions by 0.5375%. Thus, if a reduction in carbon emissions in the previous year has a positive effect, then the carbon emissions reduction effect generated by LGI in the following year will be magnified. Third, LGI can effectively reduce carbon emissions, but there are significant regional differences in its impact. For example, in some provinces, such as Sichuan and Anhui, economic growth has not been decoupled from carbon emissions. Fourth, the carbon emissions reduction effect in the 30 provinces and municipalities sampled in this study can be classified into five categories-strong, relatively strong, medium, relatively weak and weak-based on the degree of local governments' regulation of carbon emissions. The carbon emissions reduction effect of LGI is significant in the western and central regions of China but not in the eastern and northeast regions. This study helps overcome the limitations of previous studies on the regulatory effects of LGI on carbon emissions, and the constructed model may more closely reflect actual economic conditions. Moreover, the current study can benefit countries similar to China that aim to objectively identify the impacts of their LGI on carbon emissions, and such countries can use it as a reference in the formulation of investment policies based on their economic and industrial characteristics

Leg Stiffness and Vertical Stiffness of Habitual Forefoot and Rearfoot Strikers during Running

Foot strike patterns influence the running efficiency and may be an injury risk. However, differences in the leg stiffness between runners with habitual forefoot (hFFS) and habitual rearfoot (hRFS) strike patterns remain unclear. This study aimed at determining the differences in the stiffness, associated loading rate, and kinematic performance between runners with hFFS and hRFS during running. Kinematic and kinetic data were collected amongst 39 runners with hFFS and 39 runners with hRFS running at speed of 3.3 m/s, leg stiffness (Kleg), and vertical stiffness (Kvert), and impact loads were calculated. Results found that runners with hFFS had greater Kleg (P=0.010, Cohen’s d=0.60), greater peak vertical ground reaction force (vGRF) (P=0.040, Cohen’s d=0.47), shorter contact time(tc) (P<0.001, Cohen’s d=0.85), and smaller maximum leg compression (ΔL) (P=0.002, Cohen’s d=0.72) compared with their hRFS counterparts. Runners with hFFS had lower impact peak (IP) (P<0.001, Cohen’s d=1.65), vertical average loading rate (VALR) (P<0.001, Cohen’s d=1.20), and vertical instantaneous loading rate (VILR) (P<0.001, Cohen’s d=1.14) compared with runners with hRFS. Runners with hFFS landed with a plantar flexed ankle, whereas runners with hRFS landed with a dorsiflexed ankle (P<0.001, Cohen’s d=3.35). Runners with hFFS also exhibited more flexed hip (P=0.020, Cohen’s d=0.61) and knee (P<0.001, Cohen’s d=1.15) than runners with hRFS at initial contact. These results might indicate that runners with hFFS were associated with better running economy through the transmission of elastic energy

Results of Johansen cointegration tests.

<p>Results of Johansen cointegration tests.</p

Regional categorization of carbon emissions inhibition by <i>LGI</i>.

<p>Regional categorization of carbon emissions inhibition by <i>LGI</i>.</p

GMM estimation results for the dynamic regulating model.

<p>GMM estimation results for the dynamic regulating model.</p