Accelerating Antimicrobial Peptide Discovery for WHO Priority Pathogens through Predictive and Interpretable Machine Learning Models.

The escalating menace of multidrug-resistant (MDR) pathogens necessitates a paradigm shift from conventional antibiotics to innovative alternatives. Antimicrobial peptides (AMPs) emerge as a compelling contender in this arena. Employing in silico methodologies, we can usher in a new era of AMP discovery, streamlining the identification process from vast candidate sequences, thereby optimizing laboratory screening expenditures. Here, we unveil cutting-edge machine learning (ML) models that are both predictive and interpretable, tailored for the identification of potent AMPs targeting World Health Organization's (WHO) high-priority pathogens. Furthermore, we have developed ML models that consider the hemolysis of human erythrocytes, emphasizing their therapeutic potential. Anchored in the nuanced physical-chemical attributes gleaned from the three-dimensional (3D) helical conformations of AMPs, our optimized models have demonstrated commendable performance-boasting an accuracy exceeding 75% when evaluated against both low-sequence-identified peptides and recently unveiled AMPs. As a testament to their efficacy, we deployed these models to prioritize peptide sequences stemming from PEM-2 and subsequently probed the bioactivity of our algorithm-predicted peptides vis-à-vis WHO's priority pathogens. Intriguingly, several of these new AMPs outperformed the native PEM-2 in their antimicrobial prowess, thereby underscoring the robustness of our modeling approach. To elucidate ML model outcomes, we probe via Shapley Additive exPlanations (SHAP) values, uncovering intricate mechanisms guiding diverse actions against bacteria. Our state-of-the-art predictive models expedite the design of new AMPs, offering a robust countermeasure to antibiotic resistance. Our prediction tool is available to the public at https://ai-meta.chem.ncu.edu.tw/amp-meta.

27-GAUGE NEEDLE-ASSISTED TECHNIQUE FOR REPOSITIONING A DISLOCATED INTRAOCULAR LENS.

BACKGROUND: Several techniques for the reposition of a posterior chamber intraocular lens (IOL) posterior dislocating into the vitreous cavity have been developed. However, most of these methods are complicated or include externalizing part of the IOL from a corneal or scleral wound. We here describe a 27-gauge needle-assisted technique for management of a dislocated posterior chamber IOL. METHODS: This is a retrospective, noncomparative, interventional case series that discusses the results of 27-gauge needle-assisted reposition of the posterior chamber IOL with transscleral sulcus fixation in 5 consecutive cases with an IOL dislocated into vitreous cavity. These patients underwent IOL reposition with the above-mentioned technique between April 2013 and October 2014 and were followed up for at least two months thereafter. RESULTS: The IOLs of the five cases were stable with proper centrations. The postoperative best-corrected visual acuity ranged from 20/30 to 20/20. CONCLUSION: The technique of 27-gauge needle-assisted reposition of the posterior chamber IOL with transscleral fixation is effective for reposition of a dislocated IOL. This technique provides good IOL fixation without creating a large corneal wound or scleral flap.