BackgroundChanged temperature not only threaten agricultural production, but they also affect individual biological behavior, population and community of many insects, and consequently reduce the stability of our ecosystem. Insect’s ability to respond to temperature stress evolved through a complex adaptive process, thus resulting in varied temperature tolerance among different insects. Both high and low extreme temperatures are detrimental to insect development since they constitute an important abiotic stress capable of inducing abnormal biological responses. Many studies on heat or cold tolerance of ladybirds have focused on measurements of physiological and biochemical indexes such as supercooling point, higher/lower lethal temperatures, survival rate, dry body weight, water content, and developmental duration. And studies of the molecular mechanisms of ladybird responses to heat or cold stress have focused on single genes, such as those encoding heat shock proteins, but has not been analyzed by transcriptome profiling.ResultsIn this study, we report the use of Digital Gene Expression (DGE) tag profiling to gain insight into transcriptional events associated with heat- and cold-stress in C. montrouzieri. About 6 million tags (49 bp in length) were sequenced in a heat stress group, a cold stress group and a negative control group. We obtained 687 and 573 genes that showed significantly altered expression levels following heat and cold shock treatments, respectively. Analysis of the global gene expression pattern suggested that 42 enzyme-encoding genes mapped to many Gene Ontology terms are associated with insect’s response to heat- and cold-stress.ConclusionsThese results provide a global assessment of genes and molecular mechanisms involved in heat and cold tolerance.
Seasonal influenza epidemics cause serious public health problems in China. Search queries-based surveillance was recently proposed to complement traditional monitoring approaches of influenza epidemics. However, developing robust techniques of search query selection and enhancing predictability for influenza epidemics remains a challenge. This study aimed to develop a novel ensemble framework to improve penalized regression models for detecting influenza epidemics by using Baidu search engine query data from China. The ensemble framework applied a combination of bootstrap aggregating (bagging) and rank aggregation method to optimize penalized regression models. Different algorithms including lasso, ridge, elastic net and the algorithms in the proposed ensemble framework were compared by using Baidu search engine queries. Most of the selected search terms captured the peaks and troughs of the time series curves of influenza cases. The predictability of the conventional penalized regression models were improved by the proposed ensemble framework. The elastic net regression model outperformed the compared models, with the minimum prediction errors. We established a Baidu search engine queries-based surveillance model for monitoring influenza epidemics, and the proposed model provides a useful tool to support the public health response to influenza and other infectious diseases.
We study the global strong solutions to a 3-dimensional parabolic-hyperbolic Keller-Segel model with initial data close to a stable equilibrium with perturbations belonging to L 2 (R 3 ) × H 1 (R 3 ). We obtain global well-posedness and decay property. Furthermore, if the mean value of initial cell density is smaller than a suitabale constant, then the chemical concentration decays exponentially to zero as t goes to infinity. Proofs of the main results are based on an application of Fourier analysis method to uniform estimates for a linearized parabolic-hyperbolic system and also based on the smoothing effect of the cell density as well as the damping effect of the chemical concentration.
Objective:Myoclonus, a common complication during intravenous induction with etomidate, is bothersome to both anesthesiologists and patients. This study explored the preventive effect of pretreatment with propofol on etomidate-related myoclonus.Methods:This was a prospective, double-blind, clinical, randomized controlled study. Totally, 363 patients who were scheduled for a short-duration, painless gastrointestinal endoscopy were divided into 5 groups. Four groups received 0 mg/kg (E group), 0.25 mg/kg (LPE group), 0.50 mg/kg (MPE group), or 0.75 mg/kg (HPE group) propofol pretreatment before etomidate anesthesia. Another group only received 1 to 2 mg/kg of propofol (P group) as anesthesia. The incidence and severity of myoclonus, patient circulation and respiratory status, and intraoperative and postoperative complications were recorded.Results:The incidence of myoclonus in the LPE group (26.8%), MPE group (16.4%), HPE group (14.9%), and P group (0) was lower than the E group (48.6%, P < .05). The incidence of grade 1, 2, and 3 of myoclonus in the LPE group, MPE group, HPE group, and P group was significantly lower than the E group, and that in the P group was lower than the LPE group (P < .05). The incidence of hypoxemia in the P group was higher than the E group, and the incidence of adverse events in the HPE group and P group was lower than the E group (P < .05).Discussion:Pretreatment with propofol was feasible for preventing etomidate-related myoclonus. Furthermore, as propofol dosage increased, its effect on reducing the incidence and severity of myoclonic movements induced by etomidate increased.
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