Efficacy of 1% fipronil dust of activated carbon against subterranean termite Coptotermes formosanus Shiraki in laboratory conditions

Toxicity and horizontal transmission of 1% fipronil dust of activated carbon were measured using the subterranean termite Coptotermes formosanus Shiraki in laboratory conditions. 1% fipronil dust of activated carbon has delayed toxicity towards C. formosanus compared with 0.5% fipronil dust of French chalk; knockdown times KT50 and KT90 were delayed by >9 and >15 h respectively. Furthermore, 1% fipronil dust of activated carbon showed excellent primary and secondary horizontal transfer levels. In primary horizontal transfer, recipient mortalities reached 100% by 24, 48 and 72 h at donor-recipient ratios of 1:1, 1:5 and 1:10, respectively. High transfer efficacies were also found if donor-recipient ratios were greatly increased: mortality reached 100% at 9 d at ratio 1:25 and >90% at 12 d at 1:50. In secondary horizontal transfer, the toxicant transmitting ability of C. formosanus was greater when the primary horizontal transfer ratio was lower, and the highest transfer efficacy was found with a donor-recipient ratio of 1:1 - recipient mortalities reached 100% at 5 d and 11 d, respectively. Application of 1% fipronil dust of activated carbon overcomes the problem that that too high a concentration kills termites before they can contaminate their nestmates, while a lower concentration may not supply a sufficient dose for effective transfer from treated to untreated termites; this preparation has delayed toxicity, dose-dependent toxicity in horizontal transfer and high efficacy to control C. formosanus

HMGB1: a double-edged sword and therapeutic target in the female reproductive system

HMGB1 that belongs to the High Mobility Group-box superfamily, is a nonhistone chromatin associated transcription factor. It is present in the nucleus of eukaryotes and can be actively secreted or passively released by kinds of cells. HMGB1 is important for maintaining DNA structure by binding to DNA and histones, protecting it from damage. It also regulates the interaction between histones and DNA, affecting chromatin packaging, and can influence gene expression by promoting nucleosome sliding. And as a DAMP, HMGB1 binding to RAGE and TLRs activates NF-κB, which triggers the expression of downstream genes like IL-18, IL-1β, and TNF-α. HMGB1 is known to be involved in numerous physiological and pathological processes. Recent studies have demonstrated the significance of HMGB1 as DAMPs in the female reproductive system. These findings have shed light on the potential role of HMGB1 in the pathogenesis of diseases in female reproductive system and the possibilities of HMGB1-targeted therapies for treating them. Such therapies can help reduce inflammation and metabolic dysfunction and alleviate the symptoms of reproductive system diseases. Overall, the identification of HMGB1 as a key player in disease of the female reproductive system represents a significant breakthrough in our understanding of these conditions and presents exciting opportunities for the development of novel therapies

Estimation in Generalized Estimating Equation measurement error models using instrumental variables/ Estimating the cardinality of latent defective edges in hypergraphs

This dissertation consists of two studies. The first develops theory for a new method for estimating regression parameters using generalized estimating equations (GEE) with panel data prone to covariate measurement error. The focus is on logistic regression, though the method is applicable to other models. The method requires availability ofinstrumental variables (IV) to identify model parameters. Simulations are performed to assess the performance of the proposed estimator. The method, abbreviated GEEIV, is able to accurately estimate logistic regression parameters masked by measurement error in a variety of population configurations. In the second study, an algorithm is proposed to estimate the number of latent defective edges in large hypergraphs. The new statistical method combines the strength of sampling strategies and an existing algorithmic method known for efficient latent edge identification for small graphs. Our statistical approach strikes a balance between computational time consumption and estimation power, with the flexibility to adapt to several assumption violations. Simulations are performed on both synthetic data and a simulator loaded with US western grid structures. The new algorithm was able give unbiased estimates using relatively little computational time for the synthetic data for a wide range of combinations of graph sizes, defective graph edges and defective edge distributions. Simulation results from US western grid data agreed with a previous study on relatively small latent edge sets. On a large edge set, previous studies were not able to provide a reasonable estimate. The new algorithm was able to give estimates and confidence intervals for the larger problem