Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets.

ISPTM: an iterative search algorithm for systematic identification of post-translational modifications from complex proteome mixtures.

Identifying protein post-translational modifications (PTMs) from tandem mass spectrometry data of complex proteome mixtures is a highly challenging task. Here we present a new strategy, named iterative search for identifying PTMs (ISPTM), for tackling this challenge. The ISPTM approach consists of a basic search with no variable modification, followed by iterative searches of many PTMs using a small number of them (usually two) in each search. The performance of the ISPTM approach was evaluated on mixtures of 70 synthetic peptides with known modifications, on an 18-protein standard mixture with unknown modifications and on real, complex biological samples of mouse nuclear matrix proteins with unknown modifications. ISPTM revealed that many chemical PTMs were introduced by urea and iodoacetamide during sample preparation and many biological PTMs, including dimethylation of arginine and lysine, were significantly activated by Adriamycin treatment in nuclear matrix associated proteins. ISPTM increased the MS/MS spectral identification rate substantially, displayed significantly better sensitivity for systematic PTM identification compared with that of the conventional all-in-one search approach, and offered PTM identification results that were complementary to InsPecT and MODa, both of which are established PTM identification algorithms. In summary, ISPTM is a new and powerful tool for unbiased identification of many different PTMs with high confidence from complex proteome mixtures.

The Relationship between Bacterial Load and Initial Run Time of a Surgical Helmet.

Background: Periprosthetic joint infection (PJI) is a complication of arthroplasty surgery with significant morbidity and mortality. Surgical helmets are a possible source of infection. Pre-existing dust and microorganisms on its surface may be blown into the surgical field by the helmet ventilation system. Methods: Twenty surgical helmets at our institution were assessed through microscopy and polymerase chain reaction testing. Helmets were arranged with agar plates under the front and rear outflow vents. Helmets ran while plates were exchanged at different time points. Bacterial growth was assessed via colony counts and correlated with fan operating time. Gram staining and 16S sequencing were performed to identify bacterial species. Results: The primary microbiological contaminate identified was Burkholderia. There was an inverse relationship between colony formation and fan operating time. The highest number of colonies was found within the first minute of fan operating time. There was a significant decrease in the number of colonies formed from the zero-minute to the three (27 vs 5; P = <.01), four (27 vs 3; P = <.01), and five-minute (27 vs 4; P = <.01) time points for the front outflow plates. A significant difference was also observed between the one-minute and four-minute time points (P = .046). Conclusion: We observed an inverse relationship between bacterial spread helmet fan operation time, which may correlate with dispersion of pre-existing contaminates. To decrease contamination risk, we recommend that helmets are run for at least 3 min prior to entering the operating room.

Biomechanical Comparison of Krackow Repair and Percutaneous Achilles Repair System for Achilles Tendon Rupture Fixation: A Cadaveric and Finite Element Analysis Study.

Background: Open and percutaneous repair surgeries are widely used for the Achilles tendon rupture. However, prior biomechanic studies of these 2 approaches have mixed conclusions; therefore, we designed a cadaver and finite element (FE) model biomechanical study to compare the mechanical differences between the percutaneous Achilles repair system (PARS) and Krackow open repair under tensile load and rotation. Methods: Sixteen Achilles tendons were extracted from fresh-frozen cadaver ankles and the calcaneums were fixed in mortar. A force control dynamic tensile mechanical test was performed at 1 Hz with 30- and 100-N cyclic loads. Initial intact baseline testing was followed by an incision on all Achilles tendons, 4 cm from the calcaneus insertion, which were then repaired using the PARS (n = 8) or Krackow (n = 8) method. Recorded force-displacement values were used to calculate mechanical parameters, and statistical significance of differences was determined by unpaired (between repair techniques) and paired (intact vs repaired) t tests. Material properties of the Achilles tendon in the FE model were modified and a 10-Nm flexion was simulated for intact and surgical groups. Results: No differences were found between intact tendons assigned to PARS or Krackow repairs in Young's modulus (P = .582) and stiffness (P = .323). Pre- and postoperative Young's modulus was significantly decreased for both groups (Intact 230.60±100.76 MPa vs PARS 142.44±37.37 MPa, P < .012; Intact 207.46±81.12 MPa vs Krackow109.43±27.63 MPa, P < .002). Stiffness decreased significantly after surgery for both groups (Intact 25.33±10.89 N/mm vs PARS 6.51±1.68 N/mm, P < .003; Intact 20.30±8.65 N/mm vs Krackow 5.97±1.30 N/mm, P < .003). PARS ultimate tensile strength was significantly higher than the Krackow (PARS 280.29±47.32 N vs Krackow 196.97±54.28 N, P < .003) but not significantly different in the ultimate tensile strain. PARS had a significantly lower postoperative gap compared to Krackow (PARS 9.75±5.87 mm vs Krackow 25.19±7.72 mm, P < .001). FE analysis predicted an increased talocalcaneal contact pressure, maximum principal stress, and rotation in the Krackow vs PARS models, respectively. Conclusion: Biomechanical parameters observed in this study through mechanical testing and FE analysis favor the selection of PARS over the Krackow repair based on better strength, higher failure force, and lower gap generation.Clinical Relevance: The study has analyzed two Achilles tendon repair methods using cadaver and numerical estimation and may help clinicians gain insight into selection of tendon repair approaches to generate better clinical outcomes.

The Rothman Index as a predictor of postdischarge adverse events after elective spine surgery.

BACKGROUND CONTEXT: The Rothman Index (RI) is a comprehensive rating of overall patient condition in the hospital setting. It is used at many medical centers and calculated based on vital signs, laboratory values, and nursing assessments in the electronic medical record. Previous research has demonstrated an association with adverse events, readmission, and mortality in other fields, but it has not been investigated in spine surgery. PURPOSE: The present study aims to determine the potential utility of the RI as a predictor of adverse events after discharge following elective spine surgery. STUDY DESIGN/SETTING: This retrospective cohort study was carried out at a large academic medical center. PATIENT SAMPLE: A total of 2,687 patients who underwent elective spine surgery between 2013 and 2016 were included in the present study. OUTCOME MEASURES: The occurrence of adverse events and readmission after discharge from the hospital, within postoperative day 30, was determined in the present study. METHODS: Patient characteristics and 30-day perioperative outcomes were characterized, with events being classified as "major adverse events" or "minor adverse events" using standardized criteria. Rothman Index scores from the hospitalization were analyzed and compared for those who did or did not experience adverse events after discharge. The association of lowest and latest scores on adverse events was determined with multivariate regression, controlling for demographics, comorbidities, surgical procedure, and length of stay. RESULTS: Postdischarge adverse events were experienced by 7.1% of patients. The latest and lowest RI values were significantly inversely correlated with any adverse events, major adverse events, minor adverse events and readmissions after controlling for age, gender, body mass index, American Society of Anesthesiologists (ASA) class, surgical site, and hospital length of stay. Rates of readmission and any adverse event consistently had an inverse correlation with lowest and latest RI scores, with patients at increased risk with lowest score below 65 or latest score below 85. CONCLUSIONS: The RI is a tool that can be used to predict postdischarge adverse events after elective spine surgery that adds value to commonly used indices such as patient demographics and ASA. It is found that this can help physicians identify high-risk patients before discharge and should be able to better inform clinical decisions.