The infinite dilution molar conductivity
(λB
∞) that represents the interactions
between ions and solvent molecules is an important transfer property
for the utilization of ionic liquids (ILs) in electrochemical applications.
However, employing the quantitative structure–property relationship
(QSPR) model to predict the λB
∞ of unconventional ions remains to be
explored. In this work, new λB
∞-QSPR models were developed to predict
the λB
∞ of ions in aqueous solutions by using multiple linear regression
(MLR) and stepwise linear regression (SLR) methods based on the molecular
descriptors obtained by COSMO-SAC. A total of 132 cations and 158
anions data points at different temperatures were collected and tested.
The results showed that the determination coefficients (R
2) of the QSPR model using MLR for cations and anions
were 0.9515 and 0.9411, and the average absolute relative deviations
(AARD) were 6.79% and 10.42%, respectively, indicating that the proposed
λB
∞-QSPR model was excellent at predicting λB
∞. Moreover, R
2 of the QSPR model using SLR for cations and anions were
0.9450 and 0.9406, and AARD were 7.10% and 10.19%, respectively, implying
that the λB
∞-QSPR model with fewer descriptors could also predict λB
∞ satisfactorily.
We envisage the established λB
∞-QSPR models provide an available method
for obtaining λB
∞ of ions in aqueous solutions.
Thermal conductivity (λ) is an extremely crucial
indicator
of the heat transfer capability of ionic liquids (ILs) and plays a
critical function in their industrial applications. In this study,
there are two descriptors for model construction, namely, the charge
density distribution area of ions at a specific interval (S
σi) obtained using the conductor-like
screening model for the segment activity coefficient (COSMO-SAC) and
the cavity volume of ILs (V
cosmo). Using
the multiple linear regression (MLR) approach, a quantitative structure–property
relationship (QSPR) model was proposed to describe the thermal conductivity
of ILs. Furthermore, 606 experiment data points for 44 ILs at different
temperatures and pressures were collected from the literature, which
were randomly divided into a training set and a testing set for feasibility
analysis. For the model built by the total data, its determination
coefficients (R
2), root mean square error
(RMSE), and average absolute relative deviation (AARD) are 0.9713,
0.004304, and 2.18%, respectively; thus, the developed λ-QSPR
model offers a relatively good prediction of λ for ILs. Meanwhile,
the percentage of extraterritorial points in the model’s application
domain (AD) analysis is only 3.80% and the double extraterritorial
region is blank. Overall, the proposed model reproduces the change
of λ with temperature (T) and pressure (p) well and outperforms other models of similar type. Moreover,
it provides an effective approach to predicting the thermal conductivity
of ILs.
Background. Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders among women of reproductive age. As a widely used complementary and alternative therapy, acupuncture is increasingly used to treat PCOS. However, the effect of acupuncture in treating PCOS is uncertain, and the mechanisms are unclear. This systematic review aims to determine the efficacy of acupuncture on PCOS in animal preclinical models. Methods. Experimental animal studies of acupuncture in PCOS animal models were searched in PubMed, Web of Science, China National Knowledge Infrastructure, and the Chinese Science and Technology Periodical Database from inception to December 2020. The risk of bias was assessed using the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) risk of bias tool. Results. A total of 358 studies were screened based on the title and abstract, and 31 studies were included. A total of 722 animals were involved, and all studies used either Wistar rats or SD rats. Twenty-six studies used electroacupuncture, 9 studies used manual acupuncture, and 5 of them employed both electroacupuncture and manual acupuncture. A total of 22 acupoints were involved; 7 studies followed the modern acupuncture pattern, and the rest followed classic acupuncture theory. Conclusions. The present review summarizes the current evidence of the effects of acupuncture on PCOS in animal models. Unfortunately, we could not draw a definite conclusion due to the methodological weakness of the included studies and the high heterogeneity. Well-designed studies are needed in the future to fill this gap.
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