Iron–platinum–arsenide superconductors Ca₁₀(Pt_nAs₈)(Fe_2−xPt_xAs₂)₅

An overview of the crystal structures and physical properties of the recently discovered iron-platinum-arsenide superconductors, Ca-10(PtnAs8)(Fe2-xPtxAs2)(5) (n = 3 and 4), which have a superconducting transition temperature up to 38K, is provided. The crystal structure consists of superconducting Fe2As2 layers alternating with platinum-arsenic layers, PtnAs8. The upper critical field H-c2, hydrostatic pressure dependence of superconducting transition temperature T-c, and normal-state magnetic susceptibility are reported

Alkyl hydroperoxide reductase enhances the growth of Leuconostoc mesenteroides lactic acid bacteria at low temperatures

Lactic acid bacteria (LAB) can cause deterioration of food quality even at low temperatures. In this study, we investigated the cold-adaptation mechanism of a novel food spoilage LAB, Leuconostoc mesenteroides NH04 (NH04). L. mesenteroides was isolated from several spoiled cooked meat products at a high frequency in our factories. NH04 grew rapidly at low temperatures within the shelf-life period and resulted in heavy financial losses. NH04 grew more rapidly than related strains such as Leuconostoc mesenteroides NBRC3832 (NBRC3832) at 10°C. Proteome analysis of NH04 demonstrated that this strain produces a homolog of alkyl hydroperoxide reductase––AhpC––the expression of which can be induced at low temperatures. The expression level of AhpC in NH04 was approximately 6-fold higher than that in NBRC3832, which was grown under the same conditions. Although AhpC is known to have an anti-oxidative role in various bacteria by catalyzing the reduction of alkyl hydroperoxide and hydrogen peroxide, the involvement of AhpC in cold adaptation of food spoilage bacteria was unclear. We introduced an expression plasmid containing ahpC into NBRC3832, which grows slower than NH04 at 10°C, and found that expression of AhpC enhanced growth. These results demonstrated that AhpC, which likely increases anti-oxidative capacity of LAB, plays an important role in their rapid growth at low temperatures

Predictive factors for tooth loss during supportive periodontal therapy in patients with severe periodontitis: a Japanese multicenter study

Abstract Background Supportive periodontal therapy (SPT) must take individual patient risk factors into account. We conducted a multicenter joint retrospective cohort study to investigate the value of modified periodontal risk assessment (MPRA) and therapy-resistant periodontitis (TRP) assessment as predictive factors for tooth loss due to periodontal disease in patients with severe periodontitis during SPT. Methods The subjects were 82 patients from 11 dental institutions who were diagnosed with severe periodontitis and continued SPT for at least 1 year (mean follow-up = 4.9 years) between 1981 and 2008. The outcome was tooth loss due to periodontal disease during SPT. The Cox proportional hazards model was used to analyze sex, age, diabetes status, smoking history, number of periodontal pockets measuring ≥6 mm, rate of bleeding on probing, bone loss/age ratio, number of teeth lost, MPRA, and TRP assessment as explanatory variables. Results Univariate analysis showed that loss of ≥8 teeth by the start of SPT [hazard ratio (HR) 2.86], MPRA score indicating moderate risk (HR 8.73) or high risk (HR 11.04), and TRP assessment as poor responsiveness to treatment (HR 2.79) were significantly associated with tooth loss (p < 0.05). In a model in which the explanatory variables of an association that was statistically significant were added simultaneously, the HR for poor responsiveness to treatment and ≥8 teeth lost was significant at 20.17 compared with patients whose TRP assessment indicated that they responded favorably to treatment and who had lost <8 teeth by the start of SPT. Conclusion MPRA and TRP assessment may be useful predictive factors for tooth loss due to periodontal disease during SPT in Japanese patients with severe periodontitis. Additionally, considering the number of teeth lost by the start of SPT in TRP assessment may improve its predictive accuracy