Ferritin level prospectively predicts hepatocarcinogenesis in patients with chronic hepatitis B virus infection

Previous studies have detected a higher level of ferritin in patients with hepatocellular carcinoma (HCC), but a potential causal association between serum ferritin level and hepatocarcinogenesis remains to be clarified. Using a well-established prospective cohort and longitudinally collected serial blood samples, the association between baseline ferritin levels and HCC risk were evaluated in 1,152 patients infected with hepatitis B virus (HBV), a major risk factor for HCC. The association was assessed by Cox proportional hazards regression model using univariate and multivariate analyses and longitudinal analysis. It was demonstrated that HBV patients who developed HCC had a significantly higher baseline ferritin level than those who remained cancer-free (188.00 vs. 108.00 ng/ml, P\u3c0.0001). The patients with a high ferritin level (≥200 ng/ml) had 2.43-fold increased risk of HCC compared to those with lower ferritin levels [hazard ratio (HR), 2.43; 95% confidence interval, 1.63-3.63]. A significant trend of increasing HRs along with elevated ferritin levels was observed (P for trend \u3c0.0001). The association was still significant after multivariate adjustment. Incorporating ferritin into the α-fetoprotein (AFP) model significantly improved the performance of HCC prediction (the area under the curve from 0.74 to 0.77, P=0.003). Longitudinal analysis showed that the average ferritin level in HBV patients who developed HCC was persistently higher than in those who were cancer-free during follow-up. HCC risk reached a peak at approximately the fifth year after baseline ferritin detection. Moreover, stratified analyses showed that the association was noted in both males and females, and was prominent in patients with a low AFP value. In short, serum ferritin level could independently predict the risk of HBV-related HCC and may have a complementary role in AFP-based HCC diagnosis. Future studies are warranted to validate these findings and test its clinical applicability in HCC prevention and management. © 2018, Spandidos Publication

Statistical calibration and exact one-sided simultaneous tolerance intervals for polynomial regression

Statistical calibration using linear regression is a useful statistical tool having many applications. Calibration for infinitely many future y-values requires the construction of simultaneous tolerance intervals (STI’s). As calibration often involves only two variables x and y and polynomial regression is probably the most frequently used model for relating y with x, construction of STI’s for polynomial regression plays a key role in statistical calibration for infinitely many future y-values. The only exact STI’s published in the statistical literature are provided by Mee et al. (1991) and Odeh and Mee (1990). But they are for a multiple linear regression model, in which the covariates are assumed to have no functional relationships. When applied to polynomial regression, the resultant STI’s are conservative. In this paper, one-sided exact STI’s have been constructed for a polynomial regression model over any given interval. The available computer program allows the exact methods developed in this paper to be implemented easily. Real examples are given for illustration

Counting by weighing:know your numbers with confidence

Counting by weighing is often more efficient than counting manually, which is time consuming and prone to human errors, especially when the number of items (e.g. plant seeds, printed labels or coins) is large. Papers in the statistical literature have focused on how to count, by weighing, a random number of items that is close to a prespecified number in some sense. The paper considers the new problem, arising from a consultation with a company, of making inference about the number of 1p coins in a bag with known weight for infinitely many bags, by using the estimated distribution of coin weight from one calibration data set only. Specifically, a lower confidence bound has been constructed on the number of 1p coins for each of infinitely many future bags of 1p coins, as required by the company. As the same calibration data set is used repeatedly in the construction of all these lower confidence bounds, the interpretation of coverage frequency of the lower confidence bounds that is proposed is different from that of a usual confidence set

Confidence sets for optimal factor levels of a response surface

Construction of confidence sets for the optimal factor levels is an important topic in response surfaces methodology. In Wan et al. (2015), an exact inline image confidence set has been provided for a maximum or minimum point (i.e., an optimal factor level) of a univariate polynomial function in a given interval. In this article, the method has been extended to construct an exact inline image confidence set for the optimal factor levels of response surfaces. The construction method is readily applied to many parametric and semiparametric regression models involving a quadratic function. A conservative confidence set has been provided as an intermediate step in the construction of the exact confidence set. Two examples are given to illustrate the application of the confidence sets. The comparison between confidence sets indicates that our exact confidence set is better than the only other confidence set available in the statistical literature that guarantees the inline image confidence level

The Parasitoid Eretmocerus hayati Is Compatible with Barrier Cropping to Decrease Whitefly (Bemisia tabaci MED) Densities on Cotton in China

The whitefly, Bemisia tabaci (Gennadius) cryptic species Mediterranean (MED), is a destructive insect pest worldwide. In order to contribute to controlling B. tabaci by non-chemical methods, we examined the possibility of using a combination of trap/barrier crops and a parasitoid natural enemy in cotton. We performed field experiments using cantaloupe (Cucumis melo) and sunflower (Helianthus annuus) as trap crops and maize (Zea mays) as a barrier crop combined with periodic releases of the parasitoid Eretmocerus hayati in Hebei Province, Northern China. All treatments significantly reduced immature whitefly densities. Parasitism rate was significantly higher in cotton plots intercropped with sunflower and with perimeter-planted cantaloupe. Adult whitefly density was negatively related to parasitoid abundance and was significantly lower in cotton plots intercropped with maize than in the control plots. Intercropping was more effective than perimeter-planting at reducing B. tabaci densities and increasing yield. Parasitoid dispersal was not hampered by barrier crops, indicating that the two methods of control are compatible. These results contribute to the development of integrated pest management methods against this important pest.National Natural Science Foundation of China (NSFC) (31760541) (31672087); National Key R&D Project of China (2016YFC1201200, 2017YFC1200600); International Science and Technology Cooperation of China (2015DFG32300)info:eu-repo/semantics/publishedVersio

Confidence sets for optimal factor levels of a response surface

Construction of confidence sets for the optimal factor levels is an important topic in response surfaces methodology. In Wan et al. (2015), an exact (1 - a) confidence set has been provided for a maximum or minimum point (i.e., an optimal factor level) of a univariate polynomial function in a given interval. In this article, the method has been extended to construct an exact (1 - a) confidence set for the optimal factor levels of response surfaces. The construction method is readily applied to many parametric and semiparametric regression models involving a quadratic function. A conservative confidence set has been provided as an intermediate step in the construction of the exact confidence set. Two examples are given to illustrate the application of the confidence sets. The comparison between confidence sets indicates that our exact confidence set is better than the only other confidence set available in the statistical literature that guarantees the (1 - a) confidence level

A finite rotation, small strain 2D elastic head model, with applications in mild traumatic brain injury

Rotational head motions have been shown to play a key role in traumatic brain injury. There is great interest in developing methods to rapidly predict brain tissue strains and strain rates resulting from rotational head motions to estimate brain injury risk and to guide the design of protective equipment. Idealized continuum mechanics based head models provide an attractive approach for rapidly estimating brain strains and strain rates. These models are capable of capturing the wave dynamics and transient response of the brain while being significantly easier and faster to apply compared to more sophisticated and detailed finite element head models. In this work, we present a new idealized continuum mechanics based head model that accounts for the head's finite rotation, which is an improvement upon prior models that have been based on a small rotation assumption. Despite the simplicity of the model, we show that the proposed 2D elastic finite rotation head model predicts comparable strains to a more detailed finite element head model, demonstrating the potential usefulness of the model in rapidly estimating brain injury risk. This newly proposed model can serve as a basis for introducing finite rotations into more sophisticated head models in the future.Comment: 33pages, 11figure

Cold Storage Effects on Fitness of the Whitefly Parasitoids Encarsia sophia and Eretmocerus hayati

Successful biological control of the whitefly Bemisia tabaci involves the mass rearing of biocontrol agents in large numbers for field release. Cold storage of the biocontrol agents is often necessary to provide a sufficient number of biocontrol agents during an eventual pest outbreak. In this study, the fitness of two whitefly parasitoids Encarsia sophia Girault and Dodd (Hymenoptera: Aphelinidae) and Eretmocerus hayati Zolnerowich and Rose (Hymenoptera: Aphelinidae) was evaluated under fluctuating cold storage temperatures. The emergence rate of old pupae of either species was not affected when stored at 12, 10, 8 and 6 °C for 1 week. Cold storage had no effect on the longevity of the emerging adult En. sophia except young pupae stored at 4 °C, while Er. hayati was negatively affected after 2 weeks of storage time at all temperatures. Parasitism by adults emerging from older pupae stored at 12 °C for 1 week was equivalent to the control. Combined with the results for the emergence time, we suggest that the old pupal stage of En. sophia and Er. hayati could be stored at 12 and 10 °C, respectively (transferred every 22 h to 26 ± 1 °C for 2 h), for 1 week, with no or little adverse effect.National Natural Science Foundation of China (NSFC) (31672087); National Key Research and Development Project of China (2017YFC1200600, 2016YFC1201200); International Science & Technology Cooperation Program of China (2015DFG32300); Shenzhen Science and Technology Program (KQTD20180411143628272)info:eu-repo/semantics/publishedVersio

Scalable Tactile Sensing for an Omni-adaptive Soft Robot Finger

Robotic fingers made of soft material and compliant structures usually lead to superior adaptation when interacting with the unstructured physical environment. In this paper, we present an embedded sensing solution using optical fibers for an omni-adaptive soft robotic finger with exceptional adaptation in all directions. In particular, we managed to insert a pair of optical fibers inside the finger's structural cavity without interfering with its adaptive performance. The resultant integration is scalable as a versatile, low-cost, and moisture-proof solution for physically safe human-robot interaction. In addition, we experimented with our finger design for an object sorting task and identified sectional diameters of 94\% objects within the $\pm$6mm error and measured 80\% of the structural strains within $\pm$0.1mm/mm error. The proposed sensor design opens many doors in future applications of soft robotics for scalable and adaptive physical interactions in the unstructured environment.Comment: 8 pages, 6 figures, full-length version of a submission to IEEE RoboSoft 202