Ancient gene duplications have shaped developmental stage-specific expression in Pristionchus pacificus

BACKGROUND: The development of multicellular organisms is accompanied by gene expression changes in differentiating cells. Profiling stage-specific expression during development may reveal important insights into gene sets that contributed to the morphological diversity across the animal kingdom. RESULTS: We sequenced RNA-seq libraries throughout a developmental timecourse of the nematode Pristionchus pacificus. The transcriptomes reflect early larval stages, adult worms including late larvae, and growth-arrested dauer larvae and allowed the identification of developmentally regulated gene clusters. Our data reveals similar trends as previous transcriptome profiling of dauer worms and represents the first expression data for early larvae in P. pacificus. Gene expression clusters characterizing early larval stages show most significant enrichments of chaperones, while collagens are most significantly enriched in transcriptomes of late larvae and adult worms. By combining expression data with phylogenetic analysis, we found that developmentally regulated genes are found in paralogous clusters that have arisen through lineage-specific duplications after the split from the Caenorhabditis elegans branch. CONCLUSIONS: We propose that gene duplications of developmentally regulated genes represent a plausible evolutionary mechanism to increase the dosage of stage-specific expression. Consequently, this may contribute to the substantial divergence in expression profiles that has been observed across larger evolutionary time scales

Classification of various sources of error in range assessment using proton radiography and neural networks in head and neck cancer patients

This study evaluates the suitability of convolutional neural networks (CNN) to automatically process proton radiography (PR) based images. CNNs are used to classify PR images impaired by several sources of error affecting the proton range, more precisely setup and calibration curve errors. PR simulations were performed in 40 head and neck cancer patients, at three different anatomical locations (fields A, B and C, centered for head and neck, neck and base of skull coverage). Field sizes were 26x26cm2 for field A and 4.5x4.5cm2 for fields B and C. Range shift maps were obtained by comparing an unperturbed reference PR against a PR where one or more sources of error affected the proton range. CT calibration curve errors in soft, bone and fat tissues and setup errors in the anterior-posterior and inferior-superior directions were simulated individually and in combination. A CNN was trained for each type of PR field, leading to 3 CNNs trained with a mixture of range shift maps arising from one or more sources of range error. To test the full/partial/wrong agreement between predicted and actual sources of range error in the range shift maps, exact, partial and wrong match percentages were computed for an independent test dataset containing range shift maps arising from isolated or combined errors, retrospectively. The CNN corresponding to field A showed superior capability to detect isolated and combined errors, with exact matches of 92% and 71% respectively. Field B showed exact matches of 80% and 54%, and field C resulted in exact matches of 77% and 41%. The suitability of CNNs to classify PR based images containing different sources of error affecting the proton range was demonstrated. This procedure enables the detection of setup and calibration curve errors when they appear individually or in combination, providing valuable information for the interpretation of PR images

Optimizing calibration settings for accurate water equivalent path length assessment using flat panel proton radiography

Proton range uncertainties can compromise the effectiveness of proton therapy treatments. Water equivalent path length (WEPL) assessment by flat panel detector proton radiography (FP-PR) can provide means of range uncertainty detection. Since WEPL accuracy intrinsically relies on the FP-PR calibration parameters, the purpose of this study is to establish an optimal calibration procedure that ensures high accuracy of WEPL measurements. To that end, several calibration settings were investigated. FP-PR calibration datasets were obtained simulating PR fields with different proton energies, directed towards water-equivalent material slabs of increasing thickness. The parameters investigated were the spacing between energy layers (ΔE) and the increment in thickness of the water-equivalent material slabs (ΔX) used for calibration. 30 calibrations were simulated, as a result of combining ΔE=9, 7, 5, 3, 1 MeV and ΔX=10, 8, 5, 3, 2, 1 mm. FP-PRs through a CIRS electron density phantom were simulated, and WEPL images corresponding to each calibration were obtained. Ground truth WEPL values were provided by range probing multi-layer ionization chamber simulations on each insert of the phantom. Relative WEPL errors between FP-PR simulations and ground truth were calculated for each insert. Mean relative WEPL errors and standard deviations across all inserts were computed for WEPL images obtained with each calibration. Large mean and standard deviations were found in WEPL images obtained with large ΔE values (ΔE= 9 or 7MeV), for any ΔX. WEPL images obtained with ΔE≤ 5MeV and ΔX≤ 5mm resulted in a WEPL accuracy with mean values within ±0.5% and standard deviations around 1%. An optimal FP calibration in the framework of this study was established, characterized by 3MeV≤ ΔE ≤ 5MeV and 2mm ≤ ΔX ≤ 5mm. Within these boundaries, highly accurate WEPL acquisitions using FP-PR are feasible and practical, holding the potential to assist future online range verification quality control procedures

Feasibility of patient specific quality assurance for proton therapy based on independent dose calculation and predicted outcomes

PURPOSE: Patient specific quality assurance (PSQA) is required to verify the treatment delivery and the dose calculation by the treatment planning system (TPS). The objective of this work is to demonstrate the feasibility to substitute resource consuming measurement based PSQA (PSQAM) by independent dose recalculations (PSQAIDC), and that PSQAIDC results may be interpreted in a clinically relevant manner using normal tissue complication probability (NTCP) and tumor control probability (TCP) models. METHODS AND MATERIALS: A platform for the automatic execution of the two following PSQAIDC workflows was implemented: (i) using the TPS generated plan and (ii) using treatment delivery log files (log-plan). 30 head and neck cancer (HNC) patients were retrospectively investigated. PSQAM results were compared with those from the two PSQAIDC workflows. TCP / NTCP variations between PSQAIDC and the initial TPS dose distributions were investigated. Additionally, for two example patients that showed low passing PSQAM results, eight error scenarios were simulated and verified via measurements and log-plan based calculations. For all error scenarios ΔTCP / NTCP values between the nominal and the log-plan dose were assessed. RESULTS: Results of PSQAM and PSQAIDC from both implemented workflows agree within 2.7% in terms of gamma pass ratios. The verification of simulated error scenarios shows comparable trends between PSQAM and PSQAIDC. Based on the 30 investigated HNC patients, PSQAIDC observed dose deviations translate into a minor variation in NTCP values. As expected, TCP is critically related to observed dose deviations. CONCLUSIONS: We demonstrated a feasibility to substitute PSQAM with PSQAIDC. In addition, we showed that PSQAIDC results can be interpreted in clinically more relevant manner, for instance using TCP / NTCP

Technical note:Flat panel proton radiography with a patient specific imaging field for accurate WEPL assessment

Background: Proton radiography (PR) uses highly energetic proton beams to create images where energy loss is the main contrast mechanism. Water-equivalent path length (WEPL) measurements using flat panel PR (FP-PR) have potential for in vivo range verification. However, an accurate WEPL measurement via FP-PR requires irradiation with multiple energy layers, imposing high imaging doses. Purpose: A FP-PR method is proposed for accurate WEPL determination based on a patient-specific imaging field with a reduced number of energies (n) to minimize imaging dose. Methods: Patient-specific FP-PRs were simulated and measured for a head and neck (HN) phantom. An energy selection algorithm estimated spot-wise the lowest energy required to cross the anatomy (Emin) using a water-equivalent thickness map. Starting from Emin, n was restricted to certain values (n = 26, 24, 22, …, 2 for simulations, n = 10 for measurements), resulting in patient-specific FP-PRs. A reference FP-PR with a complete set of energies was compared against patient-specific FP-PRs covering the whole anatomy via mean absolute WEPL differences (MAD), to evaluate the impact of the developed algorithm. WEPL accuracy of patient-specific FP-PRs was assessed using mean relative WEPL errors (MRE) with respect to measured multi-layer ionization chamber PRs (MLIC-PR) in the base of skull, brain, and neck regions. Results: MADs ranged from 2.1 mm (n = 26) to 21.0 mm (n = 2) for simulated FP-PRs, and 7.2 mm for measured FP-PRs (n = 10). WEPL differences below 1 mm were observed across the whole anatomy, except at the phantom surfaces. Measured patient-specific FP-PRs showed good agreement against MLIC-PRs, with MREs of 1.3 ± 2.0%, −0.1 ± 1.0%, and −0.1 ± 0.4% in the three regions of the phantom. Conclusion: A method to obtain accurate WEPL measurements using FP-PR with a reduced number of energies selected for the individual patient anatomy was established in silico and validated experimentally. Patient-specific FP-PRs could provide means of in vivo range verification.</p

Tropomyosin concentration but not formin nucleators mDia1 and mDia3 determines the level of tropomyosin incorporation into actin filaments

The majority of actin filaments in human cells exist as a co-polymer with tropomyosin, which determines the functionality of actin filaments in an isoform dependent manner. Tropomyosin isoforms are sorted to different actin filament populations and in yeast this process is determined by formins, however it remains unclear what process determines tropomyosin isoform sorting in mammalian cells. We have tested the roles of two major formin nucleators, mDia1 and mDia3, in the recruitment of specific tropomyosin isoforms in mammals. Despite observing poorer cell-cell attachments in mDia1 and mDia3 KD cells and an actin bundle organisation defect with mDia1 knock down;depletion of mDia1 and mDia3 individually and concurrently did not result in any significant impact on tropomyosin recruitment to actin filaments, as observed via immunofluorescence and measured via biochemical assays. Conversely, in the presence of excess Tpm3.1, the absolute amount of Tpm3.1-containing actin filaments is not fixed by actin filament nucleators but rather depends on the cell concentration of Tpm3.1. We conclude that mDia1 and mDia3 are not essential for tropomyosin recruitment and that tropomyosin incorporation into actin filaments is concentration dependent

Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy

In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation decisions. Image quality deficiencies though, hamper dose calculation accuracy and make corrections of CBCTs a necessity. This study compared three methods to correct CBCTs and create synthetic CTs that are suitable for proton dose calculations. CBCTs, planning CTs and repeated CTs (rCT) from 33 H&N cancer patients were used to compare a deep convolutional neural network (DCNN), deformable image registration (DIR) and an analytical image-based correction method (AIC) for synthetic CT (sCT) generation. Image quality of sCTs was evaluated by comparison with a same-day rCT, using mean absolute error (MAE), mean error (ME), Dice similarity coefficient (DSC), structural non-uniformity (SNU) and signal/contrast-to-noise ratios (SNR/CNR) as metrics. Dosimetric accuracy was investigated in an intracranial setting by performing gamma analysis and calculating range shifts. Neural network-based sCTs resulted in the lowest MAE and ME (37/2 HU) and the highest DSC (0.96). While DIR and AIC generated images with a MAE of 44/77 HU, a ME of -8/1 HU and a DSC of 0.94/0.90. Gamma and range shift analysis showed almost no dosimetric difference between DCNN and DIR based sCTs. The lower image quality of AIC based sCTs affected dosimetric accuracy and resulted in lower pass ratios and higher range shifts. Patient-specific differences highlighted the advantages and disadvantages of each method. For the set of patients, the DCNN created synthetic CTs with the highest image quality. Accurate proton dose calculations were achieved by both DCNN and DIR based sCTs. The AIC method resulted in lower image quality and dose calculation accuracy was reduced compared to the other methods

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Septic Shock: A Genomewide Association Study and Polygenic Risk Score Analysis.

Previous genetic association studies have failed to identify loci robustly associated with sepsis, and there have been no published genetic association studies or polygenic risk score analyses of patients with septic shock, despite evidence suggesting genetic factors may be involved. We systematically collected genotype and clinical outcome data in the context of a randomized controlled trial from patients with septic shock to enrich the presence of disease-associated genetic variants. We performed genomewide association studies of susceptibility and mortality in septic shock using 493 patients with septic shock and 2442 population controls, and polygenic risk score analysis to assess genetic overlap between septic shock risk/mortality with clinically relevant traits. One variant, rs9489328, located in AL589740.1 noncoding RNA, was significantly associated with septic shock (p = 1.05 × 10-10); however, it is likely a false-positive. We were unable to replicate variants previously reported to be associated (p < 1.00 × 10-6 in previous scans) with susceptibility to and mortality from sepsis. Polygenic risk scores for hematocrit and granulocyte count were negatively associated with 28-day mortality (p = 3.04 × 10-3; p = 2.29 × 10-3), and scores for C-reactive protein levels were positively associated with susceptibility to septic shock (p = 1.44 × 10-3). Results suggest that common variants of large effect do not influence septic shock susceptibility, mortality and resolution; however, genetic predispositions to clinically relevant traits are significantly associated with increased susceptibility and mortality in septic individuals