Clinical Note: Use of Clonidine to Detoxify Opiate-Addicted Patients

This study investigated the utility of systematically administering clonidine to detoxify opiate-dependent inpatients. Fifteen patients received a 0.1 mg dose of clonidine orally at 8:00 am, 12:00 noon, 4:00 pm, and at bedtime. A 0.1 mg dose was also administered as needed if any withdrawal signs were evidenced, but this additional dose was rarely needed after the second day of treatment. Night sweats were the only significant complaint reported. All 15 patients were successfully detoxified after ten days of treatment

Combination of scoring schemes for protein docking

<p>Abstract</p> <p>Background</p> <p>Docking algorithms are developed to predict in which orientation two proteins are likely to bind under natural conditions. The currently used methods usually consist of a sampling step followed by a scoring step. We developed a weighted geometric correlation based on optimised atom specific weighting factors and combined them with our previously published amino acid specific scoring and with a comprehensive SVM-based scoring function.</p> <p>Results</p> <p>The scoring with the atom specific weighting factors yields better results than the amino acid specific scoring. In combination with SVM-based scoring functions the percentage of complexes for which a near native structure can be predicted within the top 100 ranks increased from 14% with the geometric scoring to 54% with the combination of all scoring functions. Especially for the enzyme-inhibitor complexes the results of the ranking are excellent. For half of these complexes a near-native structure can be predicted within the first 10 proposed structures and for more than 86% of all enzyme-inhibitor complexes within the first 50 predicted structures.</p> <p>Conclusion</p> <p>We were able to develop a combination of different scoring schemes which considers a series of previously described and some new scoring criteria yielding a remarkable improvement of prediction quality.</p

Standardized protocols for clinical and histopathological characterization of hidradenitis suppurativa tissue specimens

Methods for describing and reporting the clinical and histologic characteristics of cutaneous tissue samples from patients with hidradenitis suppurativa (HS) are not currently standardized, limiting clinicians’ and scientists’ ability to uniformly record, report, and communicate about the characteristics of tissue used in translational experiments. A recently published consensus statement outlined morphological definitions of typical HS lesions, but no consensus has been reached regarding clinical characterization and examination of HS tissue samples. In this study, we aimed to establish a protocol for reporting histopathologic and clinical characteristics of HS tissue specimens. This study was conducted from May 2023 to August 2023. Experts in clinical care, dermatopathology, and translational research were recruited, and a modified Delphi technique was used to develop a protocol for histologic reporting and clinical characterization of submitted tissue specimens from patients with HS. A total of 27 experts participated (14 dermatologists, 3 fellowship-trained dermatopathologists, 3 plastic surgeons, 3 general surgeons, and 4 research scientists) in creating and reviewing protocols for the clinical and histopathological examination of HS tissue specimens. The protocols were formatted as a synoptic report and will help to consistently classify specimens in biobanks on the basis of histologic features and more accurately report and select samples used in translational research projects

Optimised amino acid specific weighting factors for unbound protein docking

<p>Abstract</p> <p>Background</p> <p>One of the most challenging aspects of protein-protein docking is the inclusion of flexibility into the docking procedure. We developed a postfilter where the grid-representation of proteins for docking is extended by an optimised weighting factor for each amino acid.</p> <p>Results</p> <p>For up to 86% of the evaluated complexes a near-native structure was within the top 5% of the ranked prediction output. The weighting factors obtained by the optimisation procedure correlate to a certain extent with the flexibility of the amino acids, their hydrophobicity and with their propensity to be in the interface.</p> <p>Conclusion</p> <p>Use of the optimised amino acid specific parameters yields a strong increase of near-native structures on the first ranks of the prediction.</p