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The present study aimed to compare the sedative and analgesic effects of caudal epidural administration of lidocaine alone or in combination with four different α 2 -adrenergic agonists in Mediterranean miniature donkeys. A total of ten clinically healthy (five males and five females) Mediterranean miniature donkeys with an age of 5 ± 1 years, a weight of 100 ± 2 kg and a height at the withers of 0.8 ± 0.06 m (mean ± standard deviation) were used in experimental, crossover (Latin square), randomized, and blinded study. Animals were assigned to five treatment groups including lidocaine alone (0.22 mg kg -1 ), or associated with one among xylazine (0.17 mg kg -1 ), detomidine (30 μg kg -1 ), medetomidine (15 μg kg -1 ), dexmedetomidine (5 μg kg -1 ) with a minimum washout period of 8 days between treatments. The degree of sedation was investigated using a simple descriptive scale of 0-3. Sedation scores were compared at each time using nonparametric (Kruskal-Wallis and Mann-Whitney U) tests. Analgesia was assessed by pinprick test. Sedation was greater in lidocaine and/or α 2 -adrenergic agonist groups than in lidocaine group at 45-75 minutes after drug administration (P < .05). There were no significant differences among groups in time to onset of analgesia and ataxia and also in number of animals with complete perineal analgesia and ataxia. Duration of analgesia and ataxia were longer in lidocaine and/or α 2 -adrenergic agonist groups than in lidocaine (P < .05). There were no significant differences among lidocaine and/or α 2 -adrenergic agonist groups in sedation score and duration of analgesia and ataxia. No significant differences were observed in heart and respiratory rate and also rectal temperature at any time points between groups and within groups. Caudal epidural administration of α 2 - adrenergic agonists associated with lidocaine resulted in sedative effects on Mediterranean miniature donkeys, while lidocaine alone did not induce sedation. These drugs associations should be considered when superior analgesia is advocated., (Copyright © 2022. Published by Elsevier Inc.)

Regarding the great potential of dual binding site inhibitors of acetylcholinesterase as the future potent drugs of Alzheimer's disease, this study was devoted to extraction of the most effective structural features of these inhibitors from among a large number of quantitative descriptors. To do this, we adopted a unique approach in quantitative structure-activity relationships. An efficient feature selection method was emphasized in such an approach, using the confirmative results of different routine and novel feature selection methods. The proposed methods generated quite consistent results ensuring the effectiveness of the selected structural features.

Regarding the fact that the protein structure is principally encoded in its sequence, investigating the bonding state of cysteine has gained a great deal of attention due to its significance in the formation of protein structure. Due to lack of evident influence of free cysteines on the protein structure, it may be expected that only half-cystines convey encoded information. The results obtained from the analysis of amino acid distribution in proximity of both states of cysteines explicitly indicated that perquisite information for inducing cysteine bonding state is present even in the flanking amino acid sequences of free cysteines.

In this study, membrane proteins were classified using the information hidden in their sequences. It was achieved by applying the wavelet analysis to the sequences and consequently extracting several features, each of them revealing a proportion of the information content present in the sequence. The resultant features were made normalized and subsequently fed into a cascaded model developed in order to reduce the effect of the existing bias in the dataset, rising from the difference in size of the membrane protein classes. The results indicate an improvement in prediction accuracy of the model in comparison with similar works. The application of the presented model can be extended to other fields of structural biology due to its efficiency, simplicity and flexibility.