Learning Bayesian Networks in the Space of Structures by a Hybrid Optimization Algorithm

Bayesian networks (BNs) are one of the most widely used class for machine learning and decision making tasks especially in uncertain domains. However, learning BN structure from data is a typical NP-hard problem. In this paper, we present a novel hybrid algorithm for BN structure learning, called MMABC. It’s based on a recently introduced meta-heuristic, which has been successfully applied to solve a variety of optimization problems: Artificial Bee Colony (ABC). MMABC algorithm consists of three phases: (i) obtain an initial undirected graph by the subroutine MMPC. (ii) Generate the initial population of solutions based on the undirected graph and (iii) perform the ABC algorithm to orient the edges. We describe all the elements necessary to tackle our learning problem, and experimentally compare the performance of our algorithm with two state-of-the-art algorithms reported in the literature. Computational results demonstrate that our algorithm achieves better performance than other two related algorithms

Part 1: Design and Synthesis of BRDT Selective Inhibitors as Male Contraceptive Agents Part 2: Focused Library Synthesis for TGR5 (Takeda G Protein-Coupled Receptor 5) Antagonist

University of Minnesota Ph.D. dissertation. September 2020. Major: Medicinal Chemistry. Advisor: Gunda Georg. 1 computer file (PDF); xxiii, 235 pages.Unintended pregnancies can have significant adverse socioeconomic effects and health risks for women. One approach to reducing unintended pregnancies is the use of effective contraceptive methods. While women have multiple reversible contraceptive options, there is an unmet need for men to pursue safe and reversible infertility. Chapter 1 provides a brief overview of two pharmacological approaches to male contraception: disrupting the hormonal milieu (hormonal) and targeting key cellular components in sperm maturation and function (non-hormonal). Because of adverse effects resulting from hormonal disruption, we aim to develop safe novel non-hormonal male contraceptive agents. To this end, we have targeted the testis-specific bromodomain (BRDT), an epigenetic reader protein essential for spermatogenesis. Chapter 2 describes the validation of a tricyclic dihydropyridine hit from a virtual screening campaign. Based on the sequence alignment, we hypothesized that engaging the unique Arg54 in the first bromodomain of BRDT (BRDT-1), would achieve BRDT-1 selectivity over other bromodomain isoforms. Guided by this hypothesis, we explored three structural modifications on the scaffold: conversion its lactone functionality to a lactam, lactone ring-opening, and conformational restriction by macrocyclization. Cellularly active analogs with a greater than 10-fold increase in affinity were obtained. However, the desired BRDT-1 selectivity was not achieved for any of the three subsets. Additionally, novel mechanisms of action for targeting BRDT were pursued, including proteolysis-targeted chimeras (PROTACs) for selective protein degradation and bivalent molecules for simultaneous occupancies of two bromodomains. Chapter 3 focuses on an inherited genetic disorder, polycystic liver disease (PLD). The G protein-coupled receptor TGR5 activation was identified as strongly associated with PLD. To develop a TGR5 antagonist, we hypothesized that known TGR5 agonists could be converted to antagonists via systematic structural modifications. After selecting the nicotinamide core as our starting point, we used combinatorial chemistry to generate a focused library with over 100 analogs. The screenings for agonist and antagonist activity, however, only yielded TGR5 agonists rather than antagonists. Nevertheless, the results provide novel structure-activity relationship insight for TGR5 agonists based on the nicotinamide core. This experiment highlights the need to obtain additional information including the co-crystal structures for future TGR5 antagonist discovery efforts

1,4-Dihydropyridinebutyrolactone-derived ring-opened ester and amide analogs targeting BET bromodomains.

Based on a previously reported 1,4-dihydropyridinebutyrolactone virtual screening hit, nine lactone ring-opened ester and seven amide analogs were prepared. The analogs were designed to provide interactions with residues at the entrance of the ZA loop of the testis-specific bromodomain (ZA) channel to enhance the affinity and selectivity for the bromodomain and extra-terminal (BET) subfamily of bromodomains. Compound testing by AlphaScreen showed that neither the affinity nor the selectivity of the ester and lactam analogs was improved for BRD4-1 and the first bromodomain of the testis-specific bromodomain (BRDT-1). The esters retained affinity comparable to the parent compound, whereas the affinity for the amide analogs was reduced 10-fold. A representative benzyl ester analog was found to retain high selectivity for BET bromodomains as shown by a BROMOscan. X-ray analysis of the allyl ester analog in complex with BRD4-1 and BRDT-1 revealed that the ester side chain is located next to the ZA loop and solvent exposed

Prediction of postoperative complications of pediatric cataract patients using data mining

Abstract Background The common treatment for pediatric cataracts is to replace the cloudy lens with an artificial one. However, patients may suffer complications (severe lens proliferation into the visual axis and abnormal high intraocular pressure; SLPVA and AHIP) within 1 year after surgery and factors causing these complications are unknown. Methods Apriori algorithm is employed to find association rules related to complications. We use random forest (RF) and Naïve Bayesian (NB) to predict the complications with datasets preprocessed by SMOTE (synthetic minority oversampling technique). Genetic feature selection is exploited to find real features related to complications. Results Average classification accuracies in three binary classification problems are over 75%. Second, the relationship between the classification performance and the number of random forest tree is studied. Results show except for gender and age at surgery (AS); other attributes are related to complications. Except for the secondary IOL placement, operation mode, AS and area of cataracts; other attributes are related to SLPVA. Except for the gender, operation mode, and laterality; other attributes are related to the AHIP. Next, the association rules related to the complications are mined out. Then additional 50 data were used to test the performance of RF and NB, both of then obtained the accuracies of over 65% for three classification problems. Finally, we developed a webserver to assist doctors. Conclusions The postoperative complications of pediatric cataracts patients can be predicted. Then the factors related to the complications are found. Finally, the association rules that is about the complications can provide reference to doctors

Chemical and thermal reduction of graphene oxide and its electrically conductive polylactic acid nanocomposites

Graphene oxide (GO) was reduced with biocompatible glucose and polyvinylpyrrolidone (PVP) and incorporated in polylactic acid (PLA). The thermal reduction of GO during the compression molding of PLA was also studied to delineate the reduction efficiencies from thermal and chemical processes. Results indicate that glucose is more effective in the reduction of GO (rGO-g) with a much higher electrical conductivity than PVP and thermally treated GO. Even rGO-g was also highly efficient in improving the electrical conductivity of PLA. The composite with ∼1.25 vol.% of rGO-g exhibited a high conductivity of ∼2.2 S/m due to the chemical reduction of GO with glucose and the thermal reduction of rGO-g during the compression molding process

Dihydropyridine Lactam Analogs Targeting BET Bromodomains.

Inhibitors of Bromodomain and Extra Terminal (BET) proteins are investigated for various therapeutic indications, but selectivity for BRD2, BRD3, BRD4, BRDT and their respective tandem bromodomains BD1 and BD2 remains suboptimal. Here we report selectivity-focused structural modifications of previously reported dihydropyridine lactam 6 by changing linker length and linker type of the lactam side chain in efforts to engage the unique arginine 54 (R54) residue in BRDT-BD1 to achieve BRDT-selective affinity. We found that the analogs were highly selective for BET bromodomains, and generally more selective for the first (BD1) and second (BD2) bromodomains of BRD4 rather than for those of BRDT. Based on AlphaScreen and BromoScan results and on crystallographic data for analog 10 j, we concluded that the lack of selectivity for BRDT is most likely due to the high flexibility of the protein and the unfavorable trajectory of the lactam side chain that do not allow interaction with R54. A 15-fold preference for BD2 over BD1 in BRDT was observed for analogs 10 h and 10 m, which was supported by protein-based 19 F NMR experiments with a BRDT tandem bromodomain protein construct

Preventing corneal blindness caused by keratitis using artificial intelligence

Keratitis is the main cause of corneal blindness worldwide, but most vision loss caused by keratitis can be avoidable via early detection and treatment, which are challenging in resource-limited settings. Here, the authors develop a deep learning system for the automated classification of keratitis and other cornea abnormalities