Test-retest precision and longitudinal cartilage thickness loss in the IMI-APPROACH cohort.

OBJECTIVE: To investigate the test-retest precision and to report the longitudinal change in cartilage thickness, the percentage of knees with progression and the predictive value of the machine-learning-estimated structural progression score (s-score) for cartilage thickness loss in the IMI-APPROACH cohort - an exploratory, 5-center, 2-year prospective follow-up cohort. DESIGN: Quantitative cartilage morphology at baseline and at least one follow-up visit was available for 270 of the 297 IMI-APPROACH participants (78% females, age: 66.4 ± 7.1 years, body mass index (BMI): 28.1 ± 5.3 kg/m2, 55% with radiographic knee osteoarthritis (OA)) from 1.5T or 3T MRI. Test-retest precision (root mean square coefficient of variation) was assessed from 34 participants. To define progressor knees, smallest detectable change (SDC) thresholds were computed from 11 participants with longitudinal test-retest scans. Binary logistic regression was used to evaluate the odds of progression in femorotibial cartilage thickness (threshold: -211 µm) for the quartile with the highest vs the quartile with the lowest s-scores. RESULTS: The test-retest precision was 69 µm for the entire femorotibial joint. Over 24 months, mean cartilage thickness loss in the entire femorotibial joint reached -174 µm (95% CI: [-207, -141] µm, 32.7% with progression). The s-score was not associated with 24-month progression rates by MRI (OR: 1.30, 95% CI: [0.52, 3.28]). CONCLUSION: IMI-APPROACH successfully enrolled participants with substantial cartilage thickness loss, although the machine-learning-estimated s-score was not observed to be predictive of cartilage thickness loss. IMI-APPROACH data will be used in subsequent analyses to evaluate the impact of clinical, imaging, biomechanical and biochemical biomarkers on cartilage thickness loss and to refine the machine-learning-based s-score. GOV IDENTIFICATION: NCT03883568.

A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women.

OBJECTIVE: Knee osteoarthritis (OA) is among the higher contributors to global disability. Despite its high prevalence, currently, there is no cure for this disease. Furthermore, the available diagnostic approaches have large precision errors and low sensitivity. Therefore, there is a need for new biomarkers to correctly identify early knee OA. METHOD: We have created an analytics pipeline based on machine learning to identify small models (having few variables) that predict the 30-months incidence of knee OA (using multiple clinical and structural OA outcome measures) in overweight middle-aged women without knee OA at baseline. The data included clinical variables, food and pain questionnaires, biochemical markers (BM) and imaging-based information. RESULTS: All the models showed high performance (AUC > 0.7) while using only a few variables. We identified both the importance of each variable within the models as well its direction. Finally, we compared the performance of two models with the state-of-the-art approaches available in the literature. CONCLUSIONS: We showed the potential of applying machine learning to generate predictive models for the knee OA incidence. Imaging-based information were found particularly important in the proposed models. Furthermore, our analysis confirmed the relevance of known BM for knee OA. Overall, we propose five highly predictive small models that can be possibly adopted for an early prediction of knee OA.

Coupled photochemical-biological system to treat biorecalcitrant wastewater.

The aim of the present work is to study a coupled system to treat biorecalcitrant wastewaters. The combination consists of an advanced oxidation process (AOP) named photo-Fenton (Ph-F), which is a photochemical treatment and a sequencing batch biofilter reactor (SBBR). The synthetic wastewater used to optimise this process is a solution of 200 ppm of 4-chlorophenol (4-CP). The first part of the work is the study of the biodegradability enhancement achieved by the photochemical process, measured as the ratio between the biochemical oxygen demand (BOD5) and the chemical oxygen demand (COD). The second step is the start-up and optimisation of the biological process. The results showed that it is necessary to severely treat the toxic solution (with 500 ppm of [H2O2]0) in order to achieve more than 90% of TOC removal in the whole process. The photochemical and biological treatments lasted 50 minutes and 24 hours, respectively.

[Laparoscopic treatment of perforated duodenal ulcer]. / Tratamiento laparoscópico de la úlcera duodenal perforada.

OBJECTIVE: To analyze the results obtained in patients undergoing laparoscopic surgery for perforated duodenal ulcer. PATIENTS AND METHOD: From January 2000 to August 2006, 15 consecutive patients with perforated duodenal ulcer underwent laparoscopic surgery after preoperative selection (ASA scores, time since onset of the perforation). RESULTS: The mean age was 44.6 +/- 15.5 years (range, 18-75). There were 10 men and five women. Fourteen patients were ASA I-II. Time since onset of perforation was more than 12 hours in only one patient. Operative time was 70.5 +/- 9.6 minutes. There were two conversions (13.3%) to the open approach and two postoperative complications (prolonged ileus in one patient and self-limiting leakage in another). There were no intra-abdominal collections or mortality in the entire series. The mean length of hospital stay was 6.5 +/- 2.1 days. CONCLUSIONS: In selected patients, laparoscopic treatment of perforated duodenal ulcer is safe and feasible. Technical standardization and appropriate patient selection are essential to define the real role of the laparoscopic approach in perforated duodenal ulcer.

Two short peptides including segments of subunit A of Escherichia coli DNA gyrase as potential probes to evaluate the antibacterial activity of quinolones.

Quinolones constitute a family of compounds with a potent antibiotic activity. The enzyme DNA gyrase, responsible for the replication and transcription processes in DNA of bacteria, is involved in the mechanism of action of these drugs. In this sense, it is believed that quinolones stabilize the so-called 'cleavable complex' formed by DNA and gyrase, but the whole process is still far from being understood at the molecular level. This information is crucial in order to design new biological active products. As an approach to the problem, we have designed and synthesized low molecular weight peptide mimics of DNA gyrase. These peptides correspond to sequences of the subunit A of the enzyme from Escherichia coli, that include the quinolone resistance-determining region (positions 75-92) and a segment containing the catalytic Tyr-122 (positions 116-130). The peptide mimic of the non-mutated enzyme binds to ciprofloxin (CFX) only when DNA and Mg2+ were present (Kd = 1.6 x 10(-6) M), a result previously found with DNA gyrase. On the other hand, binding was reduced when mutations of Ser-83 to Leu-83 and Asp-87 to Asn-87 were introduced, a double change previously found in the subunit A of DNA gyrase from several CFX-resistant clinical isolates of E. coli. These results suggest that synthetic peptides designed in a similar way to that described here can be used as mimics of gyrases (topoisomerases) in order to study the binding of the quinolone to the enzyme-DNA complex as well as the mechanism of action of these antibiotics.