Can cartilage loss be detected in knee osteoarthritis (OA) patients with 3–6 months' observation using advanced image analysis of 3T MRI?

SummaryPurposePrior investigations of magnetic resonance imaging (MRI) biomarkers of cartilage loss in knee osteoarthritis (OA) suggest that trials of interventions which affect this biomarker with adequate statistical power would require large clinical studies of 1–2 years duration. We hypothesized that smaller, shorter duration, “Proof of Concept” (PoC) studies might be achievable by: (1) selecting a population at high risk of rapid medial tibio-femoral (TF) progression, in conjunction with; (2) high-field MRI (3T), and; (3) using advanced image analysis. The primary outcome was the cartilage thickness in the central medial femur.MethodsMulti-centre, non-randomized, observational cohort study at four sites in the US. Eligible participants were females with knee pain, a body mass index (BMI)≥25kg/m2, symptomatic radiographic evidence of medial TF OA, and varus mal-alignment. The 29 participants had a mean age of 62 years, mean BMI of 36kg/m2, with eight index knees graded as Kellgren–Lawrence (K&L)=2 and 21 as K&L=3. Eligible participants had four MRI scans of one knee: two MRIs (1 week apart) were acquired as a baseline with follow-up MRI at 3 and 6 months. A trained operator, blind to time-point but not subject, manually segmented the cartilage from the Dual Echo Steady State water excitation MR images. Anatomically corresponding regions of interest were identified on each image by using a three-dimensional statistical shape model of the endosteal bone surface, and the cartilage thickness (with areas denuded of cartilage included as having zero thickness – ThCtAB) within each region was calculated. The percentage change from baseline at 3 and 6 months was assessed using a log-scale analysis of variance (ANOVA) model including baseline as a covariate. The primary outcome was the change in cartilage thickness within the aspect of central medial femoral condyle exposed within the meniscal window (w) during articulation, neglecting cartilage edges [nuclear (n)] (nwcMF·ThCtAB), with changes in other regions considered as secondary endpoints.ResultsAnatomical mal-alignment ranged from −1.9° to 6.3°, with mean 0.9°. With one exception, no changes in ThCtAB were detected at the 5% level for any of the regions of interest on the TF joint at 3 or 6 months of follow-up. The change in the primary variable (nwcMF·ThCtAB) from (mean) baseline at 3 months from the log-scale ANOVA model was −2.1% [95% confidence interval (CI) (−4.4%, +0.2%)]. The change over 6 months was 0.0% [95% CI (−2.7%, +2.8%)]. The 95% CI for the change from baseline did not include zero for the cartilage thickness within the meniscal window of the lateral tibia (wLT·ThCtAB) at 6 month follow-up (−1.5%, 95% CI [−2.9, −0.2]), but was not significant at the 5% level after correction for multiple comparisons.ConclusionsThe small inconsistent compartment changes, and the relatively high variabilities in cartilage thickness changes seen over time in this study, provide no additional confidence for a 3- or 6-month PoC study using a patient population selected on the basis of risk for rapid progression with the MRI acquisition and analyses employed

Beta Atomic Contacts: Identifying Critical Specific Contacts in Protein Binding Interfaces

Specific binding between proteins plays a crucial role in molecular functions and biological processes. Protein binding interfaces and their atomic contacts are typically defined by simple criteria, such as distance-based definitions that only use some threshold of spatial distance in previous studies. These definitions neglect the nearby atomic organization of contact atoms, and thus detect predominant contacts which are interrupted by other atoms. It is questionable whether such kinds of interrupted contacts are as important as other contacts in protein binding. To tackle this challenge, we propose a new definition called beta (β) atomic contacts. Our definition, founded on the β-skeletons in computational geometry, requires that there is no other atom in the contact spheres defined by two contact atoms; this sphere is similar to the van der Waals spheres of atoms. The statistical analysis on a large dataset shows that β contacts are only a small fraction of conventional distance-based contacts. To empirically quantify the importance of β contacts, we design βACV, an SVM classifier with β contacts as input, to classify homodimers from crystal packing. We found that our βACV is able to achieve the state-of-the-art classification performance superior to SVM classifiers with distance-based contacts as input. Our βACV also outperforms several existing methods when being evaluated on several datasets in previous works. The promising empirical performance suggests that β contacts can truly identify critical specific contacts in protein binding interfaces. β contacts thus provide a new model for more precise description of atomic organization in protein quaternary structures than distance-based contacts

Tibial coverage, meniscus position, size and damage in knees discordant for joint space narrowing - data from the Osteoarthritis Initiative.

INTRODUCTION: Meniscal extrusion is thought to be associated with less meniscus coverage of the tibial surface, but the association of radiographic disease stage with quantitative measures of tibial plateau coverage is unknown. We therefore compared quantitative and semi-quantitative measures of meniscus position and morphology in individuals with bilateral painful knees discordant on medial joint space narrowing (mJSN). METHODS: A sample of 60 participants from the first half (2,678 cases) of the Osteoarthritis Initiative cohort fulfilled the inclusion criteria: bilateral frequent pain, Osteoarthritis Research Society International (OARSI) mJSN grades 1-3 in one, no-JSN in the contra-lateral (CL), and no lateral JSN in either knee (43 unilateral mJSN1; 17 mJSN2/3; 22 men, 38 women, body mass index (BMI) 31.3 + 3.9 kg/m(2)). Segmentation and three-dimensional quantitative analysis of the tibial plateau and meniscus, and semi-quantitative evaluation of meniscus damage (magnetic resonance imaging (MRI) osteoarthritis knee score = MOAKS) was performed using coronal 3T MR images (MPR DESSwe and intermediate-weighted turbo spin echo (IW-TSE) images). CL knees were compared using paired t-tests (between-knee, within-person design). RESULTS: Medial tibial plateau coverage was 36 + 9% in mJSN1 vs 45 + 8% in CL no-JSN knees, and was 31 + 9% in mJSN2/3 vs 46 + 6% in no-JSN knees (both P < 0.001). mJSN knees showed greater meniscus extrusion and damage (MOAKS), but no significant difference in meniscus volume. No significant differences in lateral tibial coverage, lateral meniscus morphology or position were observed. CONCLUSIONS: Knees with medial JSN showed substantially less medial tibial plateau coverage by the meniscus. We suggest that the less meniscal coverage, i.e., less mechanical protection may be a reason for greater rates of cartilage loss observed in JSN knees. Copyright 2012 Osteoarthritis Research Society International. All rights reserved

Real-world scenario improvements in serum phosphorus levels and pill burden in peritoneal dialysis patients treated with sucroferric oxyhydroxide

BackgroundA database analysis was conducted to assess the effectiveness of sucroferric oxyhydroxide (SO) on lowering serum phosphorus and phosphate binder (PB) pill burden among adult peritoneal dialysis (PD) patients prescribed SO as part of routine care.MethodsAdult PD patients (n = 258) prescribed SO through a renal pharmacy service were analyzed. Baseline was 3 months before SO prescription. SO-treated follow-up was for 6 months or until either a new PB was prescribed, SO was not refilled, PD modality changed, or patient was discharged. In-range serum phosphorus was defined as ≤5.5 mg/dL.ResultsAt baseline, mean serum phosphorus was 6.59 mg/dL with 10 prescribed PB pills/day. The proportion of patients achieving in-range serum phosphorus increased by 72% from baseline to month 6. Prescribed PB pills/day decreased by 57% (10 at baseline to 4.3 at SO follow-up, p &lt; 0.0001). The mean length of SO follow-up was 5.1 months; SO follow-up ended for 38, 27, and 50 patients at months 4, 5, and 6, respectively, due to no further PB fills, and for 10, 11, and 4 patients at months 4, 5, and 6, respectively, due to another PB prescribed. In patients with baseline serum phosphorus &gt;5.5 mg/dL who achieved in-range serum phosphorus during SO follow-up for ≥1 quarter, a notable improvement in serum phosphorus (6.54 to 5.10 mg/dL, p &lt; 0.0001) was observed, and there was a 53% reduction in PB pill burden (9.9 to 4.7, p &lt; 0.0001).ConclusionAmong PD patients prescribed SO as part of routine care, improvements in serum phosphorus control and &gt;50% reduction in PB pills/day were observed

Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions

IMPORTANCE Current approaches to identifying individuals at high risk for opioid overdose target many patients who are not truly at high risk. OBJECTIVE To develop and validate a machine-learning algorithm to predict opioid overdose risk among Medicare beneficiaries with at least 1 opioid prescription. DESIGN, SETTING, AND PARTICIPANTS A prognostic study was conducted between September 1, 2017, and December 31, 2018. Participants (n = 560 057) included fee-for-service Medicare beneficiaries without cancer who filled 1 or more opioid prescriptions from January 1, 2011, to December 31, 2015. Beneficiaries were randomly and equally divided into training, testing, and validation samples. EXPOSURES Potential predictors (n = 268), including sociodemographics, health status, patterns of opioid use, and practitioner-level and regional-level factors, were measured in 3-month windows, starting 3 months before initiating opioids until loss of follow-up or the end of observation. MAIN OUTCOMES AND MEASURES Opioid overdose episodes from inpatient and emergency department claims were identified. Multivariate logistic regression (MLR), least absolute shrinkage and selection operator-type regression (LASSO), random forest (RF), gradient boosting machine (GBM), and deep neural network (DNN) were applied to predict overdose risk in the subsequent 3 months after initiation of treatment with prescription opioids. Prediction performance was assessed using the C statistic and other metrics (eg, sensitivity, specificity, and number needed to evaluate [NNE] to identify one overdose). The Youden index was used to identify the optimized threshold of predicted score that balanced sensitivity and specificity. RESULTS Beneficiaries in the training (n = 186 686), testing (n = 186 685), and validation (n = 186 686) samples had similar characteristics (mean [SD] age of 68.0 [14.5] years, and approximately 63% were female, 82% were white, 35% had disabilities, 41% were dual eligible, and 0.60% had at least 1 overdose episode). In the validation sample, the DNN (C statistic = 0.91; 95% CI, 0.88-0.93) and GBM (C statistic = 0.90; 95% CI, 0.87-0.94) algorithms outperformed the LASSO (C statistic = 0.84; 95% CI, 0.80-0.89), RF (C statistic = 0.80; 95% CI, 0.75-0.84), and MLR (C statistic = 0.75; 95% CI, 0.69-0.80) methods for predicting opioid overdose. At the optimized sensitivity and specificity, DNN had a sensitivity of 92.3%, specificity of 75.7%, NNE of 542, positive predictive value of 0.18%, and negative predictive value of 99.9%. The DNN classified patients into low-risk (76.2%[142 180] of the cohort), medium-risk (18.6%[34 579] of the cohort), and high-risk (5.2%[9747] of the cohort) subgroups, with only 1 in 10 000 in the low-risk subgroup having an overdose episode. More than 90% of overdose episodes occurred in the high-risk and medium-risk subgroups, although positive predictive values were low, given the rare overdose outcome. CONCLUSIONS AND RELEVANCE Machine-learning algorithms appear to perform well for risk prediction and stratification of opioid overdose, especially in identifying low-risk subgroups that have minimal risk of overdose.NIH/National Institute on Drug Abuse [R01DA044985]; Pharmaceutical Research and Manufacturers of America Foundation Research Starter AwardOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Albumin-associated free fatty acids induce macropinocytosis in podocytes

Podocytes are specialized epithelial cells in the kidney glomerulus that play important structural and functional roles in maintaining the filtration barrier. Nephrotic syndrome results from a breakdown of the kidney filtration barrier and is associated with proteinuria, hyperlipidemia, and edema. Additionally, podocytes undergo changes in morphology and internalize plasma proteins in response to this disorder. Here, we used fluid-phase tracers in murine models and determined that podocytes actively internalize fluid from the plasma and that the rate of internalization is increased when the filtration barrier is disrupted. In cultured podocytes, the presence of free fatty acids (FFAs) associated with serum albumin stimulated macropinocytosis through a pathway that involves FFA receptors, the Gβ/Gγ complex, and RAC1. Moreover, mice with elevated levels of plasma FFAs as the result of a high-fat diet were more susceptible to Adriamycin-induced proteinuria than were animals on standard chow. Together, these results support a model in which podocytes sense the disruption of the filtration barrier via FFAs bound to albumin and respond by enhancing fluid-phase uptake. The response to FFAs may function in the development of nephrotic syndrome by amplifying the effects of proteinuria

Structural analysis on mutation residues and interfacial water molecules for human TIM disease understanding

10.1186/1471-2105-14-S16-S11BMC Bioinformatics14SUPPL16-BBMI

Evaluating Temporal Factors in Combined Interventions of Workforce Shift and School Closure for Mitigating the Spread of Influenza

10.1371/journal.pone.0032203PLoS ONE7