RSS 1.0Clinical Medicine
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This collection contains clinical research and documentation from a variety of Irish health organisations.
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Stent Optimization Using Optical Coherence Tomography and Its Prognostic Implications After Percutaneous Coronary Intervention.Background Stent underexpansion has been known to be associated with worse outcomes. We sought to define optical coherence tomography assessed optimal stent expansion index (SEI), which associates with lower incidence of follow-up major adverse cardiac events (MACEs). Methods and Results A total of 315 patients (involving 370 lesions) who underwent optical coherence tomography-aided coronary stenting were retrospectively included. SEI was calculated separately for equal halves of each stented segment using minimum stent area/mean reference lumen area ([proximal reference area+distal reference area]/2). The smaller of the 2 was considered to be the SEI of that case. Follow-up MACE was defined as a composite of all-cause death, myocardial infarction, stent thrombosis, and target lesion revascularization. Average minimum stent area was 6.02 (interquartile range, 4.65-7.92) mm2, while SEI was 0.79 (interquartile range, 0.71-0.86). Forty-seven (12.7%) incidences of MACE were recorded for 370 included lesions during a median follow-up duration of 557 (interquartile range, 323-1103) days. Receiver operating characteristic curve analysis identified 0.85 as the best SEI cutoff (<0.85) to predict follow-up MACE (area under the curve, 0.60; sensitivity, 0.85; specificity, 0.34). MACE was observed in 40 of 260 (15.4%) lesions with SEI <0.85 and in 7 of 110 (6.4%) lesions with SEI ≥0.85 (P=0.02). Least absolute shrinkage and selection operator regression identified SEI <0.85 (odds ratio, 3.55; 95% CI, 1.40-9.05; P<0.01) and coronary calcification (odds ratio, 2.47; 95% CI, 1.00-6.10; P=0.05) as independent predictors of follow-up MACE. Conclusions The present study identified SEI <0.85, associated with increased incidence of MACE, as the optimal cutoff in daily practice. Along with suboptimal SEI (<0.85), coronary calcification was also found to be a significant predictor of follow-up MACE.
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Allantodapsone is a Pan-Inhibitor of Staphylococcus aureus Adhesion to Fibrinogen, Loricrin, and Cytokeratin 10.Staphylococcus aureus infections have become a major challenge in health care due to increasing antibiotic resistance. We aimed to design small molecule inhibitors of S. aureus surface proteins to be developed as colonization inhibitors. We identified allantodapsone in an initial screen searching for inhibitors of clumping factors A and B (ClfA and ClfB). We used microbial adhesion assays to investigate the effect of allantodapsone on extracellular matrix protein interactions. Allantodapsone inhibited S. aureus Newman adhesion to fibrinogen with an IC50 of 21.3 μM (95% CI 4.5-102 μM), minimum adhesion inhibitory concentration (MAIC) of 100 μM (40.2 μg/mL). Additionally, allantodapsone inhibited adhesion of Lactococcus lactis strains exogenously expressing the clumping factors to fibrinogen (L. lactis ClfA, IC50 of 3.8 μM [95% CI 1.0-14.3 μM], MAIC 10 μM, 4.0 μg/mL; and L. lactis ClfB, IC50 of 11.0 μM [95% CI 0.9-13.6 μM], MAIC 33 μM, 13.3 μg/mL), indicating specific inhibition. Furthermore, the dapsone and alloxan fragments of allantodapsone did not have any inhibitory effect. Adhesion of S. aureus Newman to L2v loricrin is dependent on the expression of ClfB. Allantodapsone caused a dose dependent inhibition of S. aureus adhesion to the L2v loricrin fragment, with full inhibition at 40 μM (OD600 0.11 ± 0.01). Furthermore, recombinant ClfB protein binding to L2v loricrin was inhibited by allantodapsone (P < 0.0001). Allantodapsone also demonstrated dose dependent inhibition of S. aureus Newman adhesion to cytokeratin 10 (CK10). Allantodapsone is the first small molecule inhibitor of the S. aureus clumping factors with potential for development as a colonization inhibitor. IMPORTANCE S. aureus colonization of the nares and the skin provide a reservoir of bacteria that can be transferred to wounds that can ultimately result in systemic infections. Antibiotic resistance can make these infections difficult to treat with significant associated morbidity and mortality. We have identified and characterized a first-in-class small molecule inhibitor of the S. aureus clumping factors A and B, which has the potential to be developed further as a colonization inhibitor.
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Arthroscopic Correction of Sports-Related Femoroacetabular Impingement in Competitive Athletes: 2-Year Clinical Outcome and Predictors for Achieving Minimal Clinically Important Difference.At 2-year follow-up, statistically significant improvements were observed for all PROMs (P < .001 for all), and 84% of athletes continued to play sport. Higher preoperative PROM scores reduced the likelihood of achieving MCID; however, returning to play was the strongest predictor of reaching MCID in this athletic cohort. Using absolute score change (mean change or distribution method) to calculate MCID was less accurate owing to ceiling effects and dependence on preoperative PROM scores.
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Characterising the efficacy and bioavailability of bioactive peptides identified for attenuating muscle atrophy within a -derived functional ingredient.Characterising key components within functional ingredients as well as assessing efficacy and bioavailability is an important step in validating nutritional interventions. Machine learning can assess large and complex data sets, such as proteomic data from plants sources, and so offers a prime opportunity to predict key bioactive components within a larger matrix. Using machine learning, we identified two potentially bioactive peptides within a Vicia faba derived hydrolysate, NPN_1, an ingredient which was previously identified for preventing muscle loss in a murine disuse model. We investigated the predicted efficacy of these peptides in vitro and observed that HLPSYSPSPQ and TIKIPAGT were capable of increasing protein synthesis and reducing TNF-α secretion, respectively. Following confirmation of efficacy, we assessed bioavailability and stability of these predicted peptides and found that as part of NPN_1, both HLPSYSPSPQ and TIKIPAGT survived upper gut digestion, were transported across the intestinal barrier and exhibited notable stability in human plasma. This work is a first step in utilising machine learning to untangle the complex nature of functional ingredients to predict active components, followed by subsequent assessment of their efficacy, bioavailability and human plasma stability in an effort to assist in the characterisation of nutritional interventions.
