Objective. To observe the effects of traditional Chinese moxibustion, compared with sham moxibustion, on the quality of life (QOL) in patients with chronic knee osteoarthritis (KOA). Methods. This is a randomized double-blinded, placebo-controlled trial. 150 patients with KOA were randomly allocated to either a true moxibustion treatment (n = 77) or a sham moxibustion treatment (n = 73) three times a week for six weeks. The QOL of patients was evaluated with SF-36 at baseline and 3, 6, and 12 weeks after baseline. Results. 136 patients were available for analysis. Participants in the true moxibustion group experienced statistically significantly greater improvement in GH (general health) scores than the sham group at week 6 (P = 0.015) and week 12 (P = 0.029). Participants in the true moxibustion group experienced statistically significantly greater improvement in VT (vitality) scores than the sham group at week 12 (P = 0.042). No significant adverse effects were found during the trial. Conclusion. A 6-week moxibustion treatment seems to improve general health and vitality, which are associated with physical and mental quality of life, in patients with KOA up to 12 weeks, relative to credible sham moxibustion. This trial is registered with Clinicaltrials.gov ISRCTN68475405.

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In the so-called lightbulb process, on days r = 1, . . . , n, out of n lightbulbs, all initially off, exactly r bulbs, selected uniformly and independent of the past, have their status changed from off to on, or vice versa. With X the number of bulbs on at the terminal time n, an even integer, and µ = n/2, σ 2 = var(X), we have sup z∈R |P(where Z is a standard normal random variable and 0 = 1/2 √ n + 1/2n + e −n/2 /3 for n ≥ 6, yielding a bound of order O(n −1/2 ) as n → ∞. A similar, though slightly larger bound, holds for odd n. The results are shown using a version of Stein's method for bounded, monotone size bias couplings. The argument for even n depends on the construction of a variable X s on the same space as X that has the X-size bias distribution, that is, which satisfies E[Xg(X)] = µ E[g(X s )] for all bounded continuous g, and for which there exists a B ≥ 0, in this case B = 2, such that X ≤ X s ≤ X + B almost surely. The argument for odd n is similar to that for even n, but one first couples X closely to V , a symmetrized version of X, for which a size bias coupling of V to V s can proceed as in the even case. In both the even and odd cases, the crucial calculation of the variance of a conditional expectation requires detailed information on the spectral decomposition of the lightbulb chain.

Community structure is heterogeneous at a variety of spatial and temporal scales, and this variation has been shown to influence the risk of zoonotic diseases such as West Nile Virus and Lyme disease. Theoretical models and most empirical evidence suggest that the greatest influence of host diversity occurs when transmission is frequency-dependent (i.e., the rate of contact is constant). These theoretical models are generally based on ordinary differential equations and become intractable when considering more than a few species. This makes it particularly difficult to predict how we might expect the transmission of infectious diseases to change as community structure changes in space or in time. Here we develop a model in which we construct a network of interactions between hosts and vectors to quantify the change in risk under different scenarios of community disassembly. Decreased vector biodiversity always reduced mean risk, while a change in host community structure led to increased or decreased mean risk depending on the manner in which community disassembly altered mean competence of the "new" community. These trends in mean risk can be generalized across a multitude of natural systems because they do not depend on the distribution of host quality, though simulation suggests that variation around the mean can be very high. The primary value of model is that it can be used to establish upper and lower bounds on the expected change in disease risk with decreasing biodiversity.

Based on two separate randomized controlled trials (RCTs) on traditional Chinese medicine (TCM) moxibustion and 10.6-μm infrared laser moxibustion in treating knee osteoarthritis (OA), we did an indirect and preliminary comparison of the effects of the 10.6-μm laser moxibustion with the traditional moxibustion for knee osteoarthritis. The objective was to see whether the laser moxibustion is non-inferior to the traditional moxibustion in alleviating symptoms of knee osteoarthritis such as pain, stiffness, and joint dysfunction as well as improving quality of life for the patients with knee osteoarthritis, and whether a further RCT directly comparing the laser and traditional moxibustion is necessary. Pooled data from two RCTs in patients with knee osteoarthritis, trial ISRCTN68475405 and trial ISRCTN26065334, were used. In the two RCTs, the eligibility criteria were almost identical, the treatment procedure (i.e., sessions, duration, and points) were similar, and the outcome measurements (i.e., WOMAC for symptoms and SF-36 for quality of life) were the same. The double robustness method was used for the WOMAC scale and the SF-36 endpoints to detect the difference between traditional and laser moxibustion. The analysis comprised 55 patients from ISRCTN68475405 in real moxibustion arm (moxibustion group) and 88 patients from ISRCTN26065334 in real laser moxibustion arm (laser group). Demographic characteristics and course of disease were similar between the two groups. Causal inference, using the doubly robust estimating approach to correct for bias due to baseline differences, showed that there was no statistically significant difference in the WOMAC pain, stiffness, and physical function between the two treatments at midterm, end of treatment, and 4 weeks after the end of treatment (P > 0.05). The exception was that there was statistically significantly more benefit associated with laser moxibustion compared with traditional moxibustion in physical function at the follow-up of 4 weeks after the end of treatment (P=0.006). There was no statistically significant Lin Lin and Ke Cheng contributed equally to this study, and should be considered as co-first authors.