Approaching Artificial Intelligence in Orthopaedics: Predictive Analytics and Machine Learning to Prognosticate Arthroscopic Rotator Cuff Surgical Outcomes.

Machine learning (ML) has not yet been used to identify factors predictive for post-operative functional outcomes following arthroscopic rotator cuff repair (ARCR). We propose a novel algorithm to predict ARCR outcomes using machine learning. This is a retrospective cohort study from a prospectively collected database.

Streamlining the KOOS Activities of Daily Living Subscale Using Machine Learning.

Background: Functional outcome scores provide valuable data, yet they can be burdensome to patients and require significant resources to administer. The Knee injury and Osteoarthritis Outcome Score (KOOS) is a knee-specific patient-reported outcome measure (PROM) and is validated for anterior cruciate ligament (ACL) reconstruction outcomes. The KOOS requires 42 questions in 5 subscales.

The effect of antiapoptosis genes on clarification performance.

Optimal bioreactor harvest time is typically determined based on maximizing product titer without compromising product quality. We suggest that ease of downstream purification should also be considered during harvest. In this view, we studied the effect of antiapoptosis genes on downstream performance.

Mapping discontinuous protein-binding sites via structure-based peptide libraries: combining in silico and in vitro approaches.

To perform their various functions, protein surfaces often have to interact with each other in a specific way. Usually, only parts of a protein are accessible and can act as binding sites. Because proteins consist of polypeptide chains that fold into complex three-dimensional shapes, binding sites can be divided into two different types: linear sites that follow the primary amino acid sequence and discontinuous binding sites, which are made up of short peptide fragments that are adjacent in spatial proximity.

Biophysical characterization of DNA and RNA aptamer interactions with hen egg lysozyme.

This work characterized the binding of an RNA aptamer recognizing hen egg white lysozyme, as well as a literature-reported single-stranded DNA analog of sequence identical to the original RNA aptamer, using fluorescence anisotropy, isothermal titration calorimetry (ITC) and analytical ultracentrifugation. The polyanionic DNA aptamer analog is selective for lysozyme even over cationic cytochrome c and has been reported to be successfully used in biosensing applications. The association however, is predominantly of electrostatic character, strongly salt-sensitive and entropically-driven, in contrast to previously described enthalpically-driven antibody-lysozyme and DNA aptamer-VEGF interactions.

Engineered 5S ribosomal RNAs displaying aptamers recognizing vascular endothelial growth factor and malachite green.

In previous work, Vibrio proteolyticus 5S rRNA was shown to stabilize 13-50 nucleotide "guest" RNA sequences for expression in Escherichia coli. The expressed chimeric RNAs accumulated to high levels in E. coli without being incorporated into ribosomes and without obvious effects on the host cells.

Biophysical characterization of DNA aptamer interactions with vascular endothelial growth factor.

The binding of a DNA aptamer (5'-CCGTCTTCCAGACAAGAGTGCAGGG-3') to recombinant human vascular endothelial growth factor (VEGF(165)) was characterized using surface plasmon resonance (SPR), fluorescence anisotropy and isothermal titration calorimetry (ITC). Results from both fluorescence anisotropy and ITC indicated that a single aptamer molecule binds to each VEGF homodimer, unlike other VEGF inhibitors that exhibit 2(ligand):1(VEGF homodimer) stoichiometry. In addition, ITC revealed that the association of the aptamer to VEGF at 20 degrees C is enthalpically driven, with an unfavorable entropy contribution.

Enhanced protein affinity and selectivity of clustered-charge anion-exchange adsorbents.

In this work, we examined the possibility of improving ion-exchange adsorbent performance by nanoscale structuring of ligands into clusters of fixed size rather than a random distribution of individual charges. The calcium-depleted form of the protein alpha-lactalbumin, which displays a cluster of acidic amino acid residues, showed enhanced adsorption affinity and capacity on clustered-charge pentalysinamide and pentaargininamide adsorbents as compared to single-charge lysinamide and argininamide adsorbents of matched total charge. Two differently charge-clustered mutants of rat microsomal cytochrome b(5), E11Q and E44Q, with the same total charge also were well differentiated by clustered-charge adsorbents.

Water-elutability of nucleic acids from metal-chelate affinity adsorbents: enhancement by control of surface charge density.

Immobilized metal affinity chromatography (IMAC) is widely used for purification of proteins, especially "hexahistidine-tagged" recombinant proteins. We previously demonstrated the application of IMAC to selective capture of nucleic acids, including RNA, selectively-denatured genomic DNA, and PCR primers through interactions with purine bases exposed in single-stranded regions. We also found that the binding affinity of nucleic acids for IMAC adsorbents can be increased several-fold by addition of 20 volume% of neutral additives such as ethanol or DMSO.

Neutral additives enhance the metal-chelate affinity adsorption of nucleic acids: role of water activity.

Immobilized metal-chelate affinity chromatography has been widely used in the purification of proteins, and we have recently found that it can also be applied to purification of nucleic acids through interactions involving exposed bases, especially purines. Here we report that the inclusion of moderate quantities of neutral solutes in the buffer substantially enhances the binding affinity of nucleic acids for immobilized metal-chelate affinity adsorbents. Addition of 20% (v/v) of solutes such as ethanol, methanol, isopropanol, n-propanol, and dimethyl sulfoxide enhances the initial affinity of binding of total yeast RNA by 4.