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Axicabtagene ciloleucel (axi-cel) received marketing authorisation in Canada for the treatment of relapsed or refractory large B-cell lymphoma after two or more lines of systemic therapy, and the clinical and economic value of axi-cel to patients and the healthcare system should be examined. The objective of this analysis is to determine, from societal and public healthcare payer perspectives, the cost effectiveness of axi-cel versus best supportive care for patients with relapsed or refractory large B-cell lymphoma in Canada.A pharmacoeconomic model was developed and populated with clinical data derived from the ZUMA-1 and SCHOLAR-1 studies using a propensity score-matched comparison. A partitioned survival mixture-cure modelling approach was taken to characterise the potential curative effect of axi-cel therapy in large B-cell lymphoma. Healthcare resource utilisation and adverse event data were based on results from ZUMA-1, and utility values were derived from ZUMA-1 data supplemented with published literature. Costs (in 2021 Canadian dollars) were taken from publicly available Canadian cost databases and published literature. Benefits and costs were discounted at 1.5% per year, and sensitivity analyses were conducted to assess the robustness of the results.In the base case, axi-cel generated an incremental 6.2 life-years compared to best supportive care, corresponding to 4.6 additional quality-adjusted life-years, and was associated with $606,010 in additional costs. The incremental cost-utility ratio was $132,747 per quality-adjusted life-year gained compared with best supportive care from a societal perspective ($106,392 per quality-adjusted life-year gained from a public healthcare payer perspective). Key drivers of the analysis included progression-free survival and overall survival values for axi-cel.The results of this analysis suggest that axi-cel may be considered a cost-effective allocation of resources compared with best supportive care for the treatment of adult patients with relapsed or refractory large B-cell lymphoma in Canada.

Bacteria can form dense communities called biofilms, where cells are embedded in a self-produced extracellular matrix. Exploiting competitive interactions between strains within the biofilm context can have potential applications in biological, medical, and industrial systems. By combining mathematical modelling with experimental assays, we reveal that spatial structure and competitive dynamics within biofilms are significantly affected by the location and density of the founder cells used to inoculate the biofilm. Using a species-independent theoretical framework describing colony biofilm formation, we show that the observed spatial structure and relative strain biomass in a mature biofilm comprising two isogenic strains can be mapped directly to the geographical distributions of founder cells. Moreover, we define a predictor of competitive outcome that accurately forecasts relative abundance of strains based solely on the founder cells’ potential for radial expansion. Consequently, we reveal that variability of competitive outcome in biofilms inoculated at low founder density is a natural consequence of the random positioning of founding cells in the inoculum. Extension of our study to non-isogenic strains that interact through local antagonisms, shows that even for strains with different competition strengths, a race for space remains the dominant mode of competition in low founder density biofilms. Our results, verified by experimental assays using Bacillus subtilis, highlight the importance of spatial dynamics on competitive interactions within biofilms and hence to related applications.

Acute Promyelocytic Leukemia is caused by expression of the oncogenic Promyelocytic Leukemia (PML)–Retinoic Acid Receptor Alpha (RARA) fusion protein. Therapy with arsenic trioxide results in degradation of PML-RARA and PML and cures the disease. Modification of PML and PML-RARA with SUMO and ubiquitin precedes ubiquitin-mediated proteolysis. To identify additional components of this pathway, we performed proteomics on PML bodies. This revealed that association of p97/VCP segregase with PML bodies is increased after arsenic treatment. Pharmacological inhibition of p97 altered the number, morphology, and size of PML bodies, accumulated SUMO and ubiquitin modified PML and blocked arsenic-induced degradation of PML-RARA and PML. p97 localized to PML bodies in response to arsenic, and siRNA-mediated depletion showed that p97 cofactors UFD1 and NPLOC4 were critical for PML degradation. Thus, the UFD1-NPLOC4-p97 segregase complex is required to extract poly-ubiquitinated, poly-SUMOylated PML from PML bodies, prior to degradation by the proteasome.

Arsenic is an effective treatment for Acute Promyelocytic Leukaemia as it induces degradation of the Promyelocytic Leukaemia (PML) – retinoic acid receptor alpha (RARA) oncogenic fusion protein. Some patients relapse with arsenic resistant disease because of missense mutations in PML. To determine the mechanistic basis for arsenic resistance we reconstituted PML-/- cells with YFP fusions of wild type (WT) and two mutant forms of PMLV found in patients refractory to arsenic, A216T and L217F. Both mutants formed PML bodies that were larger, but less numerous than WT and neither responded to arsenic by degradation. Analysis of immunoprecipitated PML bodies indicated that while WT PML experiences increased SUMO1, SUMO2/3 and ubiquitin conjugation, A216T PML is almost completely unresponsive and therefore does not recruit the SUMO targeted ubiquitin E3 ligase RNF4. Compared to WT PML, L217F PML was modified to a similar extent by SUMO2 but not SUMO1 and although it recruited RNF4, it failed to develop the appropriate poly-ubiquitin conjugates required to recruit the segregase p97, which is essential for PML degradation.

Introduction The type of methods used in economic evaluations of health technology can lead to results that may influence decisions. Despite the potential impact on decision making, there is very little documentation of methods used in economic evaluation in oncology pertaining to key assumptions and extrapolation methods of survival benefits, especially in terms of survival analysis techniques and methods for extrapolation. Objectives The primary objectives of this study were to identify, examine, and describe the methods used in economic evaluations in oncology over a 10-year period, while secondary objectives included examining the use of identified methods across different geographic regions. Methods A systematic search of the published oncology literature was conducted to identify economic evaluations of advanced or metastatic cancers published between 2010 and 2019 using the PUBMED, Ovid MEDLINE, and EMBASE databases. A random sample was taken, and information on type of study, data source, modeling techniques, and survival analysis methods were abstracted and descriptively summarized. Results A total of 8481 abstracts were identified and 76 economic evaluations were abstracted and assessed. Most identified studies were from North America (38%), East Asia (21%), continental Europe (18%), or the UK (16%), and most commonly focused on lung cancer (18%), colorectal cancer (16%), or breast cancer (13%). A large majority of studies were based on data from randomized controlled trials (82%), utilized a cost-utility approach (82%), and took a public healthcare system perspective (83%). Common model structures included Markov (49%) and partitioned survival (17%). Fitted parametric curves were the most commonly used extrapolation method (89%) for overall survival and most often utilized the Weibull distribution (64%). Secondary assessments showed modest regional variation in the use of identified methods, including the use of fitted parametric curves, testing of the proportional hazards assumption, and validation of results. Conclusion A majority of papers in the study sample reported basic characteristics of study type, data source used, modeling techniques, and utilization of survival analysis methods. However, greater detail in reporting extrapolation methods, statistical analyses, and validation of results could be potential improvements, especially across regions, in order to support greater consistency in decision making. Future research could document the diffusion of novel modeling techniques into economic evaluation. Supplementary Information The online version contains supplementary material available at 10.1007/s41669-021-00263-w.

Parkinson’s disease (PD) is a major and progressive neurodegenerative disorder, yet the biological mechanisms involved in its aetiology are poorly understood. Evidence links this disorder with mitochondrial dysfunction and/or impaired lysosomal degradation – key features of the autophagy of mitochondria, known as mitophagy. Here, we investigated the role of LRRK2, a protein kinase frequently mutated in PD, in this process in vivo. Using mitophagy and autophagy reporter mice, bearing either knockout of LRRK2 or expressing the pathogenic kinase-activating G2019S LRRK2 mutation, we found that basal mitophagy was specifically altered in clinically relevant cells and tissues. Our data show that basal mitophagy inversely correlates with LRRK2 kinase activity in vivo. In support of this, use of distinct LRRK2 kinase inhibitors in cells increased basal mitophagy, and a CNS penetrant LRRK2 kinase inhibitor, GSK3357679A, rescued the mitophagy defects observed in LRRK2 G2019S mice. This study provides the first in vivo evidence that pathogenic LRRK2 directly impairs basal mitophagy, a process with strong links to idiopathic Parkinson’s disease, and demonstrates that pharmacological inhibition of LRRK2 is a rational mitophagy-rescue approach and potential PD therapy.

Bacteria can form dense communities called biofilms, where cells are embedded in a self-produced extracellular matrix. Exploiting competitive interactions between strains within the biofilm context can have potential applications in biological, medical, and industrial systems. By combining mathematical modelling with experimental assays, we reveal that spatial structure and competitive dynamics within biofilms are significantly affected by the location and density of the founder cells used to inoculate the biofilm. Using a species-independent theoretical framework describing colony biofilm formation, we show that the observed spatial structure and relative strain biomass in a mature biofilm comprising two isogenic strains can be mapped directly to the geographical distributions of founder cells. Moreover, we define a predictor of competitive outcome that accurately forecasts relative abundance of strains based solely on the founder cells' potential for radial expansion. Consequently, we reveal that variability of competitive outcome in biofilms inoculated at low founder density is a natural consequence of the random positioning of founding cells in the inoculum. Extension of our study to non-isogenic strains that interact through local antagonisms, shows that even for strains with different competition strengths, a race for space remains the dominant mode of competition in low founder density biofilms. Our results, verified by experimental assays using Bacillus subtilis, highlight the importance of spatial dynamics on competitive interactions within biofilms and hence to related applications.

Highlights • The first demonstration of phenobarbital-induced hepatocyte proliferation in 3D liver microtissue models. • Integration of quantitative histopathology data with genomics (transcriptomics/proteomics). • In vitro cross-species risk assessment. • CAR-mediated mode of action. • Quantitative histopathology of 3D microtissues., Characterisation of the mode of action (MOA) of constitutive androstane receptor (CAR)-mediated rodent liver tumours involves measurement 5 key events including activation of the CAR receptor, altered gene expression, hepatocellular proliferation, clonal expansion and increased hepatocellular adenomas/carcinomas. To test whether or not liver 3D microtissues (LiMTs) recapitulate CAR- mediated procarcinogenic key events in response to the prototypical CAR activator phenobarbital (PB) we performed hepatocyte proliferation (LI%) analysis in rat and human LiMTs using a microTMA technology in conjunction with integrated transcriptomics (microarray) and proteomics analysis. The rationale for this approach was that LiMTs containing parenchymal and non-parenchymal cells (NPCs) are more physiologically representative of liver and thus would generate data more relevant to the in vivo situation. Rat and human LiMTs were treated with PB over a range of concentrations (500 uM - 2000 uM) and times (24 h - 96 h) in a dose-response/time-course analysis. There was a dose-dependent induction of LI% in rat LiMTs, however there was little or no effect of PB on LI% in human LiMTs. ATP levels in the rat and human LiMTs were similar to control in all of the PB treatments. There was also a dose- and time-dependent PB-mediated RNA induction of CAR regulated genes CYP2B6/Cyp2b2, CYP3A7/Cyp3a9 and UGT1A6/Ugt1a6 in human and rat LiMTs, respectively. These CAR regulated genes were also upregulated at the protein level. Ingenuity pathways analysis (IPA) indicated that there was a significant (Z score >2.0;-log p value >) activation of CAR by PB in both human and rat LiMTs. These results indicate that human and rat LiMTs showed the expected responses at the level of PB-induced hepatocyte proliferation and enzyme induction with rat LiMTs showing significant dose-dependent effects while human LiMTs showed no proliferation response but did show dose-dependent enzyme induction at the RNA and protein levels. In conclusion LiMTs serve as a model to provide mechanistic data for 3 of the 5 key events considered necessary to establish a CAR-mediated MOA for liver tumourigenesis and thus can potentially reduce the use of animals when compiling mechanistic data packages.

Parkinson’s disease (PD) is a major and progressive neurodegenerative disorder, yet the biological mechanisms involved in its aetiology are poorly understood. Evidence links this disorder with mitochondrial dysfunction and/or impaired lysosomal degradation – key features of the autophagy of mitochondria, known as mitophagy. Here we investigated the role of LRRK2, a protein kinase frequently mutated in PD, on this process in vivo. Using mitophagy and autophagy reporter mice, bearing either knockout of LRRK2 or expressing the pathogenic kinase-activating G2019S LRRK2 mutation, we found that basal mitophagy was specifically altered in clinically relevant cells and tissues. Our data show that basal mitophagy inversely correlates with LRRK2 kinase activity in vivo. In support of this, use of distinct LRRK2 kinase inhibitors in cells increased basal mitophagy, and a CNS penetrant LRRK2 kinase inhibitor, GSK3357679A, rescued the mitophagy defects observed in LRRK2 G2019S mice. This study provides the first in vivo evidence that pathogenic LRRK2 directly impairs basal mitophagy, a process with strong links to idiopathic Parkinson’s disease, and demonstrates that pharmacological inhibition of LRRK2 is a rational mitophagy-rescue approach and potential PD therapy.

General macroautophagy is a naturally occurring phenomenon. Based on our auto-QC reporter, which consists of a tandem mCherry-GFP tag associated with the N terminus of MAP1LC3B/LC3B, we developed the auto-QC counter macro for FIJI. This macro enables the semi-automated detection and quantitation of autophagosomes and autolysosomes with the auto-QC reporter. Here we describe how this macro works, and provide a step-by-step guide on how to use it. The “auto-QC counter” for Fiji/ImageJ (Schindelin et al., 2012; Schneider, Rasband, & Eliceiri, 2012) macro allows semi-automated batch analysis of autophagy in a set of images. Autophagy is identified using differences in fluorescence intensity between the red mCherry and green GFP proteins of an auto-QC reporter delivered to autophagosomes. Similar to the mito-QC reporter (Allen, Toth, James, & Ganley, 2013; McWilliams et al., 2016; Montava-Garriga, Singh, Ball, & Ganley, 2020), the auto-QC reporter displays similar red and green channel intensities outside the lysosome using typical imaging parameters giving a red/green intensity ratio close to 1. In autophagosomes, quenching of the GFP leads to a relatively higher red/green intensity ratio. In contrast to our previously published “mito-QC counter” macro, which first identifies punctae in a red/green ratio channel and then filters according to red intensity, the autophagy counter macro we describe here first identifies punctae in the red channel and then interrogates the red/green ratio. The advantage of this approach is that “yellow” (red+green) punctae are identified for quantification as well as the red-only punctae (the caveat is that the red channel must be relatively “clean” and free from background fluorescence, which is less of a limitation when using the mito-QC counter approach of identifying punctae in the red/green ratio image first). In terms of usage, the autophagy counter macro takes as input a folder of images in which an outline for each cell of interest has been created and added to the image overlay in Fiji/ImageJ before saving as tiff. Upon running the macro the user is first asked to select a folder containing images to analyse. A Dialog then prompts the user to check/adjust the following parameters: 1) and 2) green and red channel index, 3) spot size (in microns), 4) a peak finding threshold to identify punctae, 5) a minimum red intensity for punctae of interest, and 6) a red/green intensity ratio threshold to classify punctae as “red” rather than “yellow”. These parameters are discussed in more detail in the next paragraph. Batch analysis of the images in the input folder then begins, and a new output folder is created with a date and timestamp in the name. A new Results table is created for each run, with one row of results per cell region-of-interest, and this is saved to the output folder with a “spots” image corresponding to each input image that shows the location and classification of the punctae identified. To help use the macro effectively we describe here in words the procedure it follows, as well as taking a more detailed look at the input parameters and results. After choosing the input images and updating parameters the macro first applies a median filter to all channels to reduce the impact of noise on the results. The scale of the median filter is determined by the third macro parameter “spotSize” (in calibrated units, typically microns) – this should be around the same size as the smallest autophagosomes, since making it larger will degrade the resolution to a point where individual autophagosomes are not detected. Next, the macro uses ImageJ’s built-in “Find Maxima” function to identify peaks in a filtered version of the red channel image: the macro implements a “Difference of Gaussian” (DoG) filter to enhance spots at the scale of interest and suppress local background. In layman’s terms this is achieved by subtracting a very blurred version of the original image from a less blurred version of it. The scale of the less blurred version is set according to the spotSize parameter, and the more blurred version is several times this scale (the non-user-adjustable parameter DoGmultiplier = 5 by default). The Find Maxima function used for peak detection then takes an input parameter called Prominence, which determines how much above local background an intensity peak must be to be detected. The Prominence value used for peak detection is determined by the fourth macro parameter “peakNstd”: we apply an autothresholding strategy where we calculate standard deviation (std) of the DoG-filtered red channel intensities and use a threshold Prominence = std x peakNstd. The peakNstd value should be more than zero and less than 5, and we suggest a default value of 2. Having detected candidate intensity peaks in the DoG-filtered red channel, the macro then looks at the original (median-filtered) red channel intensity of each peak. Again, an auto-thresholding strategy is used: peak red intensity values must be greater than or equal to the average (mean) red channel intensity plus a number of standard deviations to be counted as a red spot. The number of standard deviations used to calculate this threshold is set according to the fifth macro parameter, “redMinimumSD” (default = 1). Spots that fail to meet this criterion are classified as “black” to signify insufficient red intensity. Finally, spots are classified as “red” only or “yellow” (i.e. red+green) by looking at the ratio of red channel intensity to green channel intensity: the minimum red/green intensity ratio to be counted as “red” only is determined by the sixth macro parameter “rThresh”. The appropriate value for rThresh will obviously depend on the imaging parameters used for the red and green channels (i.e. exposure time, laser power, dwell time etc.) but should not vary between images if these parameters are kept fixed. The Results table produced by the macro displays: nBlack, the number of spots below the red minimum intensity; nRed, the number of red spots with a high red/green ratio; nYellow, the number of red spots that also coincide with significant green intensity; and then the four main input parameters spotSize, peakNstd, rThresh and redMinimumSD are recorded for future reference (redMinimum is the actual threshold red intensity value calculated using the redMinimumSD parameter).

General macroautophagy is a naturally occurring phenomenon. Based on our auto-QC reporter, which consists of a tandem mCherry-GFP tag associated with the N terminus of MAP1LC3B/LC3B, we developed the auto-QC counter macro for FIJI. This macro enables the semi-automated detection and quantitation of autophagosomes and autolysosomes with the auto-QC reporter. Here we describe how this macro works, and provide a step-by-step guide on how to use it. The “auto-QC counter” for Fiji/ImageJ (Schindelin et al., 2012; Schneider, Rasband, & Eliceiri, 2012) macro allows semi-automated batch analysis of autophagy in a set of images. Autophagy is identified using differences in fluorescence intensity between the red mCherry and green GFP proteins of an auto-QC reporter delivered to autophagosomes. Similar to the mito-QC reporter (Allen, Toth, James, & Ganley, 2013; McWilliams et al., 2016; Montava-Garriga, Singh, Ball, & Ganley, 2020), the auto-QC reporter displays similar red and green channel intensities outside the lysosome using typical imaging parameters giving a red/green intensity ratio close to 1. In autophagosomes, quenching of the GFP leads to a relatively higher red/green intensity ratio. In contrast to our previously published “mito-QC counter” macro, which first identifies punctae in a red/green ratio channel and then filters according to red intensity, the autophagy counter macro we describe here first identifies punctae in the red channel and then interrogates the red/green ratio. The advantage of this approach is that “yellow” (red+green) punctae are identified for quantification as well as the red-only punctae (the caveat is that the red channel must be relatively “clean” and free from background fluorescence, which is less of a limitation when using the mito-QC counter approach of identifying punctae in the red/green ratio image first). In terms of usage, the autophagy counter macro takes as input a folder of images in which an outline for each cell of interest has been created and added to the image overlay in Fiji/ImageJ before saving as tiff. Upon running the macro the user is first asked to select a folder containing images to analyse. A Dialog then prompts the user to check/adjust the following parameters: 1) and 2) green and red channel index, 3) spot size (in microns), 4) a peak finding threshold to identify punctae, 5) a minimum red intensity for punctae of interest, and 6) a red/green intensity ratio threshold to classify punctae as “red” rather than “yellow”. These parameters are discussed in more detail in the next paragraph. Batch analysis of the images in the input folder then begins, and a new output folder is created with a date and timestamp in the name. A new Results table is created for each run, with one row of results per cell region-of-interest, and this is saved to the output folder with a “spots” image corresponding to each input image that shows the location and classification of the punctae identified. To help use the macro effectively we describe here in words the procedure it follows, as well as taking a more detailed look at the input parameters and results. After choosing the input images and updating parameters the macro first applies a median filter to all channels to reduce the impact of noise on the results. The scale of the median filter is determined by the third macro parameter “spotSize” (in calibrated units, typically microns) – this should be around the same size as the smallest autophagosomes, since making it larger will degrade the resolution to a point where individual autophagosomes are not detected. Next, the macro uses ImageJ’s built-in “Find Maxima” function to identify peaks in a filtered version of the red channel image: the macro implements a “Difference of Gaussian” (DoG) filter to enhance spots at the scale of interest and suppress local background. In layman’s terms this is achieved by subtracting a very blurred version of the original image from a less blurred version of it. The scale of the less blurred version is set according to the spotSize parameter, and the more blurred version is several times this scale (the non-user-adjustable parameter DoGmultiplier = 5 by default). The Find Maxima function used for peak detection then takes an input parameter called Prominence, which determines how much above local background an intensity peak must be to be detected. The Prominence value used for peak detection is determined by the fourth macro parameter “peakNstd”: we apply an autothresholding strategy where we calculate standard deviation (std) of the DoG-filtered red channel intensities and use a threshold Prominence = std x peakNstd. The peakNstd value should be more than zero and less than 5, and we suggest a default value of 2. Having detected candidate intensity peaks in the DoG-filtered red channel, the macro then looks at the original (median-filtered) red channel intensity of each peak. Again, an auto-thresholding strategy is used: peak red intensity values must be greater than or equal to the average (mean) red channel intensity plus a number of standard deviations to be counted as a red spot. The number of standard deviations used to calculate this threshold is set according to the fifth macro parameter, “redMinimumSD” (default = 1). Spots that fail to meet this criterion are classified as “black” to signify insufficient red intensity. Finally, spots are classified as “red” only or “yellow” (i.e. red+green) by looking at the ratio of red channel intensity to green channel intensity: the minimum red/green intensity ratio to be counted as “red” only is determined by the sixth macro parameter “rThresh”. The appropriate value for rThresh will obviously depend on the imaging parameters used for the red and green channels (i.e. exposure time, laser power, dwell time etc.) but should not vary between images if these parameters are kept fixed. The Results table produced by the macro displays: nBlack, the number of spots below the red minimum intensity; nRed, the number of red spots with a high red/green ratio; nYellow, the number of red spots that also coincide with significant green intensity; and then the four main input parameters spotSize, peakNstd, rThresh and redMinimumSD are recorded for future reference (redMinimum is the actual threshold red intensity value calculated using the redMinimumSD parameter).

Objectives To validate novel non-contacting Confocal-Laser-Scanning-Microscopy (CLSM) methodology with conventional Contacting Profilometry (CP) measures investigating brushing or dab-on of stannous-fluoride dentifrice on early aggressive dentine erosion. Methods 75 polished human dentine samples were prepared and eroded in agitated 6% citric acid then randomly allocated into 5 intervention groups; artificial saliva control (1); controlled use of a pressure sensitive counter-rotating oscillatory powered toothbrush with sodium-fluoride NaF (2) or stannous-fluoride SnF2 (3), and dab-on application of NaF (4) or SnF2 (5). Samples underwent three cycles of intervention and 2-min agitated 6 % citric acid challenges. CLSM images were taken and 3D reconstructions produced of step height using a developed software algorithm. In addition, 20 % samples were randomised and profiled using CP to measure step height and surface roughness. Vickers's diamond micro-hardness testing was carried out on all samples. Results Comparing CLSM and CP; Pearson correlation was 0.77 and Intra-class correlation 0.81 (p = 0.01). There were no significant statistical differences in step height between groups using both CLSM and CP. From baseline, SnF2 brushing (3) increased micro-hardness more than control (1) (p = 0.03), NaF (4) and SnF2 dab-on (5) (p ≤ 0.001), and increased surface roughness more than control (p = 0.02), NaF brushing (2) and NaF dab-on (4) (p ≤ 0.017). Dab-on of SnF2 (5) produced rougher surfaces than control (1) (p = 0.014) and reduced hardness compared with NaF brushing (p = 0.04). Conclusions Good agreement and correlation exists between CLSM and CP measures in dentine. There were no significant differences in surface loss after interventions between groups. Compared with control, SnF2 application increased dentine surface roughness and SnF2 controlled powered brushing application increased dentine hardness, likely caused by exposure of uneroded dentine. Clinical significance Isosurfaces produced using CLSM can be used to represent dentine step height loss. They show good correlation and agreement with conventional CP measures, following early aggressive erosion-abrasion cycles of dentine. The CLSM and computer algorithm therefore provides an accurate, standalone and non-contacting three-dimensional measurement of early dentine wear. Stannous-fluoride brushing, and dab-on application offer no benefits following early aggressive erosion in dentine. To reduce dentine wear, limiting erosive challenges and avoiding brushing post-erosion is advised., Applied Computing in Medical Science; Software Engineering; Biophysics; Mathematical Biosciences; Biocomputational Method; Dentistry; Dental Materials; Prosthetic Dentistry; Medical Imaging; Dentistry; Measurement; Abrasion; Dab-on; Dentine-wear; Dentifrice; Erosion

Background Ovarian cancer is a leading cause of cancer-related mortality. Although the disease is relatively rare, it carries a disproportionately large morbidity burden. Objective We conducted a cost-utility analysis from a Canadian public payer perspective to determine the cost effectiveness of bevacizumab, a newly available treatment option for recurrent ovarian cancer. Methods Using a 7-year time horizon, a three health-state cohort-based partitioned survival model was developed to assess the cost utility of bevacizumab plus chemotherapy (BEV) versus chemotherapy alone. We reconstructed individual patient data from published Kaplan–Meier curves. Clinical parameters, including progression-free survival and overall survival, were derived from the AURELIA phase III randomized controlled trial. Costs, resource utilization and utility values from recent Canadian sources were used to populate the model. Results were presented using incremental cost-utility ratios (ICURs). Uncertainty was examined through univariate and probabilistic sensitivity analyses. Results The reconstructed individual patient data matched the AURELIA trial results. Total costs for the BEV and chemotherapy treatment arms were $Can79,086 and $Can54,982, respectively. Total estimated quality-adjusted life-years (QALYs) were 1.1055 and 0.9926 for the BEV and chemotherapy arms, respectively. The ICUR was estimated to be $Can213,424 per QALY gained. At a willingness-to-pay threshold of $Can100,000 per QALY gained, the probability of BEV being cost effective was 0. Conclusions The results of our analysis suggest that the addition of bevacizumab to single-agent chemotherapy treatment, while improving patient outcomes, is unlikely to be cost effective in this Canadian patient population. The results also provide some preliminary validation for use of individual patient data-reconstruction techniques in pharmacoeconomic evaluation. Electronic supplementary material The online version of this article (doi:10.1007/s41669-017-0030-7) contains supplementary material, which is available to authorized users.

Highlights • The mito-QC reporter is a powerful model to monitor mitophagy in vitro and in vivo. • The mito-QC Counter is a new semi-automated tool to quantify mitophagy. • Mitophagy is induced in ARPE19 cells and varies in distinct skeletal muscle regions., Mitophagy is a natural phenomenon and entails the lysosomal degradation of mitochondria by the autophagy pathway. In recent years, the development of fluorescent pH-sensitive mitochondrial reporters has greatly facilitated the monitoring of mitophagy by distinguishing between cytosolic mitochondria or those delivered to acidic lysosomes. We recently published the mito-QC reporter, which consists of a mitochondrial outer membrane-localised tandem mCherry-GFP tag. This allows the quantification of mitophagy via the increase in red-only mCherry signal that arises when the GFP signal is quenched upon mitochondrial delivery to lysosomes. Here we develop a macro for FIJI, the mito-QC Counter, and describe its use to allow reliable and consistent semi-automated quantification of mitophagy. In this methods article we describe step-by-step how to detect and quantify mitophagy and show that mitophagy levels can be reliably calculated in different cell lines and under distinct stimuli. Finally, we show that the mito-QC Counter can be used to quantify mitophagy in tissues of mito-QC transgenic mice. We demonstrate that mitophagy levels in skeletal muscle correlates with glycolytic activity. Our present data show that the mito-QC Counter macro for FIJI enables the robust quantification of mitophagy both in vitro and in vivo.

Automated image analysis has become key to extract quantitative information from scientific microscopy bioimages, but the methods involved are now often so refined that they can no longer be unambiguously described using written protocols. We introduce BIAFLOWS, a software tool with web services and a user interface specifically designed to document, interface, reproducibly deploy, and benchmark image analysis workflows. BIAFLOWS allows image analysis workflows to be compared fairly and shared in a reproducible manner, safeguarding research results and promoting the highest quality standards in bioimage analysis. A curated instance of BIAFLOWS is available online; it is currently populated with 34 workflows that can be triggered to process image datasets illustrating 15 common bioimage analysis problems organized in 9 major classes. As a complete case study, the open benchmarking of 7 nuclei segmentation workflows, including classical and deep learning techniques, was performed on this online instance. All the results presented can be reproduced online.

Photoreception is pivotal to our experience and perception of the natural world; hence the eye is of prime importance for most vertebrate animals to sense light. Central to visual health is mitochondrial homeostasis, and the selective autophagic turnover of mitochondria (mitophagy) is predicted to play a key role here. Despite studies that link aberrant mitophagy to ocular dysfunction, little is known about the prevalence of basal mitophagy, or its relationship to general autophagy, in the visual system. In this study, we utilize the mito-QC mouse and a closely related general macroautophagy reporter model to profile basal mitophagy and macroautophagy in the adult and developing eye. We report that ocular macroautophagy is widespread, but surprisingly mitophagy does not always follow the same pattern of occurrence. We observe low levels of mitophagy in the lens and ciliary body, in stark contrast to the high levels of general MAP1LC3-dependent macroautophagy in these regions. We uncover a striking reversal of this process in the adult retina, where mitophagy accounts for a larger degree of the macroautophagy taking place, specifically in the photoreceptor neurons of the outer nuclear layer. We also show the developmental regulation of autophagy in a variety of ocular tissues. In particular, mitophagy in the adult mouse retina is reversed in localization during the latter stages of development. Our work thus defines the landscape of mitochondrial homeostasis in the mammalian eye, and in doing so highlights the selective nature of autophagy in vivo and the specificity of the reporters used. Abbreviations: ATG: autophagy related; GFP: green fluorescent protein; LC3: microtubule associated protein 1 light chain 3; ONH: optic nerve head; ONL: outer nuclear layer; RPE: retinal pigment epithelium.

A high throughput histology (microTMA) platform was applied for testing drugs against tumors in a novel 3D heterotypic glioblastoma brain sphere (gBS) model consisting of glioblastoma tumor cells, iPSC-derived neurons, glial cells and astrocytes grown in a spheroid. The differential responses of gBS tumors and normal neuronal cells to sustained treatments with anti-cancer drugs temozolomide (TMZ) and doxorubicin (DOX) were investigated. gBS were exposed to TMZ or DOX over a 7-day period. Untreated gBS tumors increased in size over a 4-week culture period, however, there was no increase in the number of normal neuronal cells. TMZ (100 uM) and DOX (0.3 uM) treatments caused ~30% (P~0.07) and ~80% (P

Summary Image analysis is key to extracting quantitative information from scientific microscopy images, but the methods involved are now often so refined that they can no longer be unambiguously described by written protocols. We introduce BIAFLOWS, an open-source web tool enabling to reproducibly deploy and benchmark bioimage analysis workflows coming from any software ecosystem. A curated instance of BIAFLOWS populated with 34 image analysis workflows and 15 microscopy image datasets recapitulating common bioimage analysis problems is available online. The workflows can be launched and assessed remotely by comparing their performance visually and according to standard benchmark metrics. We illustrated these features by comparing seven nuclei segmentation workflows, including deep-learning methods. BIAFLOWS enables to benchmark and share bioimage analysis workflows, hence safeguarding research results and promoting high-quality standards in image analysis. The platform is thoroughly documented and ready to gather annotated microscopy datasets and workflows contributed by the bioimaging community., Highlights • Image analysis is inescapable in extracting quantitative data from scientific images • It can be difficult to deploy and apply state-of-the-art image analysis methods • Comparing heterogeneous image analysis methods is tedious and error prone • We introduce a platform to deploy and fairly compare image analysis workflows, The Bigger Picture Image analysis is currently one of the major hurdles in the bioimaging chain, especially for large datasets. BIAFLOWS seeds the ground for virtual access to image analysis workflows running in high-performance computing environments. Providing a broader access to state-of-the-art image analysis is expected to have a strong impact on research in biology, and in other fields where image analysis is a critical step in extracting scientific results from images. BIAFLOWS could also be adopted as a federated platform to publish microscopy images together with the workflows that were used to extract scientific data from these images. This is a milestone of open science that will help to accelerate scientific progress by fostering collaborative practices., While image analysis is becoming inescapable in the extraction of quantitative information from scientific images, it is currently challenging for life scientists to find, test, and compare state-of-the-art image analysis methods compatible with their own microscopy images. It is also difficult and time consuming for algorithm developers to validate and reproducibly share their methods. BIAFLOWS is a web platform addressing these needs. It can be used as a local solution or through an immediately accessible and curated online instance.

SummaryThe concerted action of many protein kinases helps orchestrate the error-free progression through mitosis of mammalian cells. The roles and regulation of some prominent mitotic kinases, such as cyclin-dependent kinases, are well-established. However, these and other known mitotic kinases alone cannot account for the extent of protein phosphorylation that has been reported during mammalian mitosis. Here we demonstrate that CK1α, of the casein kinase 1 family of protein kinases, localises to the spindle and is required for proper spindle-positioning and timely cell division. CK1α is recruited to the spindle by FAM83D, and cells devoid ofFAM83D, or those harbouring CK1α-binding-deficientFAM83DF283A/F283Aknockin mutation, display pronounced spindle-positioning defects, and a prolonged mitosis. RestoringFAM83Dat the endogenous locus inFAM83D-/-cells, or artificially delivering CK1α to the spindle inFAM83DF283A/F283Acells, rescues these defects. These findings implicate CK1α as new mitotic kinase that orchestrates the kinetics and orientation of cell division.

Mutations in PINK1 and Parkin result in autosomal recessive Parkinson's disease (PD). Cell culture and in vitro studies have elaborated the PINK1-dependent regulation of Parkin and defined how this dyad orchestrates the elimination of damaged mitochondria via mitophagy. PINK1 phosphorylates ubiquitin at serine 65 (Ser65) and Parkin at an equivalent Ser65 residue located within its N-terminal ubiquitin-like domain, resulting in activation; however, the physiological significance of Parkin Ser65 phosphorylation in vivo in mammals remains unknown. To address this, we generated a Parkin Ser65Ala (S65A) knock-in mouse model. We observe endogenous Parkin Ser65 phosphorylation and activation in mature primary neurons following mitochondrial depolarization and reveal this is disrupted in Parkin S65A/S65A neurons. Phenotypically, Parkin S65A/S65A mice exhibit selective motor dysfunction in the absence of any overt neurodegeneration or alterations in nigrostriatal mitophagy. The clinical relevance of our findings is substantiated by the discovery of homozygous PARKIN ( PARK2 ) p.S65N mutations in two unrelated patients with PD. Moreover, biochemical and structural analysis demonstrates that the Parkin S65N/S65N mutant is pathogenic and cannot be activated by PINK1. Our findings highlight the central role of Parkin Ser65 phosphorylation in health and disease.

Linear 2D- or 3D-structured illumination microscopy (SIM or 3D-SIM, respectively) enables multicolor volumetric imaging of fixed and live specimens with subdiffraction resolution in all spatial dimensions. However, the reliance of SIM on algorithmic post-processing renders it particularly sensitive to artifacts that may reduce resolution, compromise data and its interpretations, and drain resources in terms of money and time spent. Here we present a protocol that allows users to generate high-quality SIM data while accounting and correcting for common artifacts. The protocol details preparation of calibration bead slides designed for SIM-based experiments, the acquisition of calibration data, the documentation of typically encountered SIM artifacts and corrective measures that should be taken to reduce them. It also includes a conceptual overview and checklist for experimental design and calibration decisions, and is applicable to any commercially available or custom platform. This protocol, plus accompanying guidelines, allows researchers from students to imaging professionals to create an optimal SIM imaging environment regardless of specimen type or structure of interest. The calibration sample preparation and system calibration protocol can be executed within 1-2 d.

Fluorescence microscopy is particularly well suited to the study of cell biology, due to its noninvasive nature, high sensitivity detection of specific molecules, and high spatial and temporal resolution. In recent years, there has been an important transition from imaging the static distributions of molecules as a snapshot in time in fixed material to live-cell imaging of the dynamics of molecules in cells: in essence visualizing biochemical processes in living cells. Furthermore, in the last 5 years, there have been important advances in so-called "super-resolution" imaging methods that have overcome the resolution limits imposed by the diffraction of light in optical systems. Live-cell imaging is now beginning to deliver in unprecedented detail, bridging the resolution gap between electron microscopy and light microscopy. We discuss the various factors that limit the spatial and temporal resolution of microscopy and how to overcome them, how to best prepare specimens for high resolution imaging, and the choice of fluorochromes. We also summarize the pros and cons of the different super-resolution techniques and introduce some of the key data analysis tasks that a cell biologist employing high resolution microscopy is typically interested in.

Three-dimensional structured illumination microscopy (3D-SIM) is a versatile and accessible method for super-resolution fluorescence imaging, but generating high-quality data is challenging, particularly for non-specialist users. We present SIMcheck, a suite of ImageJ plugins enabling users to identify and avoid common problems with 3D-SIM data, and assess resolution and data quality through objective control parameters. Additionally, SIMcheck provides advanced calibration tools and utilities for common image processing tasks. This open-source software is applicable to all commercial and custom platforms, and will promote routine application of super-resolution SIM imaging in cell biology.

This study investigates the validity of assumptions used to justify large aid disbursements to power sector projects in developing countries. Using neoclassical growth theory and panel data analysis this study illustrates the basis for and limitations of the assumption of a causal electricity–economic growth relationship. The relationship between electricity consumption and economic growth is statistically tested on a sample of 77 countries over a 25 year period from 1980 to 2005 using extensions of the Solow growth model and the model employed by Mankiw et al. (1992) to include electricity as an explicit factor of production. We also explore whether there is any concrete evidence supporting the claim that regions previously without electricity experience positive development outcomes in the shape of economic growth and poverty alleviation upon its introduction. The study focuses on Norway's experience with power sector aid, looking into the results and the data amassed from its half century involvement in clean energy electrification projects in developing countries. Our resulting analysis suggests that there are reasonable grounds to pursue electricity as a development enabler; however, there is insufficient information to justify increased power aid disbursements without a significant change in evaluation and scrutiny of existing and future electrification projects.

A PAR-1–mediated bias in microtubule organization in the Drosophila oocyte underlies posterior-directed mRNA transport., Cytoskeletal organization is central to establishing cell polarity in various cellular contexts, including during messenger ribonucleic acid sorting in Drosophila melanogaster oocytes by microtubule (MT)-dependent molecular motors. However, MT organization and dynamics remain controversial in the oocyte. In this paper, we use rapid multichannel live-cell imaging with novel image analysis, tracking, and visualization tools to characterize MT polarity and dynamics while imaging posterior cargo transport. We found that all MTs in the oocyte were highly dynamic and were organized with a biased random polarity that increased toward the posterior. This organization originated through MT nucleation at the oocyte nucleus and cortex, except at the posterior end of the oocyte, where PAR-1 suppressed nucleation. Our findings explain the biased random posterior cargo movements in the oocyte that establish the germline and posterior.

Fluorescence imaging of dynamical processes in live cells often results in a low signal-to-noise ratio. We present a novel feature-preserving non-local means approach to denoise such images to improve feature recovery and particle detection. The commonly used non-local means filter is not optimal for noisy biological images containing small features of interest because image noise prevents accurate determination of the correct coefficients for averaging, leading to over-smoothing and other artifacts. Our adaptive method addresses this problem by constructing a particle feature probability image, which is based on Haar-like feature extraction. The particle probability image is then used to improve the estimation of the correct coefficients for averaging. We show that this filter achieves higher peak signal-to-noise ratio in denoised images and has a greater capability in identifying weak particles when applied to synthetic data. We have applied this approach to live-cell images resulting in enhanced detection of end-binding-protein 1 foci on dynamically extending microtubules in photo-sensitive Drosophila tissues. We show that our feature-preserving non-local means filter can reduce the threshold of imaging conditions required to obtain meaningful data.

A global ocean observing system for the physical climate system, comprising both in situ and satellite components, was conceived largely at the Ocean Observations conference in St. Raphael. France, in October 1999. It was recognized that adequate information was not available on the state of the world ocean or its regional variations to address a range of important societal needs. Subsequent work by the marine carbon community and others in the ocean science and operational communities led to an agreed international plan described in the Global Climate Observing System (GCOS) Implementation Plan (GCOS-92, 2004). This foundation observing system was designed to meet climate requirements, but also supports weather prediction, global and coastal ocean prediction, marine hazard warning systems, transportation, marine environment and ecosystem monitoring, and naval applications. Here, we describe efforts made to reach the goals set out in the international plan. Thanks to these efforts, most of the ice-free ocean above 2000-miles is now being observed systematically for the first time, and a global repeat hydrographic survey and selected transport measurements supplement these networks. The system is both integrated and composite. It depends upon in situ and satellite networks that measure the same variable using different sensors. In this way, optimum use is made of all available platforms and sensors to maximize coverage and attain maximum accuracy. The biggest challenge for the greater oceanographic community -- including both research and operational components -- will be demonstrating impacts and benefits sufficient to justify the funds needed to complete the observing system, as well as to sustain its funding for the long term.

We have developed new 2D and 3D experiments for the measurement of Cα–Hα residual dipolar coupling constants in 13C and 15N labelled proteins. Two experiments, 2D (HNCO)-(J-CA)NH and 3D (HN)CO-(J-CA)NH, sample the Cα–Hα splitting by means of Cα magnetization, while 2D (J-HACACO)NH and 3D J-HA(CACO)NH use Hα magnetization to achieve a similar result. In the 2D experiments the coupling evolution is superimposed on the evolution of the 15N chemical shifts and the IPAP principle is used to obtain 1H–15N HSQC-like spectra from which the splitting is determined. The use of a third dimension in 3D experiments reduces spectral overlap to the point where use of an IPAP scheme may not be necessary. The length of the sampling interval in the J-dimension of these experiments is dictated solely by the relaxation properties of Cα or Hα nuclei. This was made possible by the use of Cα selective pulses in combination with either a DPFGSE or modified BIRD pulses. Inclusion of these pulse sequence elements in the J-evolution periods removes unwanted spin–spin interactions. This allows prolonged sampling periods (∼25 ms) yielding higher precision Cα–Hα splitting determination than is achievable with existing frequency based methods.

Purpose The objective of the study was to evaluate the cost-effectiveness of gadoxetic acid–enhanced magnetic resonance imaging (EOB-MRI) in the diagnosis and treatment of hepatocellular carcinoma (HCC) in Japan compared with extracellular contrast media–enhanced MRI (ECCM-MRI) and contrast media–enhanced computed tomography (CE-CT) scanning. Methods A 6-stage Markov model was developed to estimate lifetime direct costs and clinical outcomes associated with EOB-MRI. Diagnostic sensitivity and specificity, along with clinical data on HCC survival, recurrence, treatment patterns, costs, and health state utility values, were derived from predominantly Japanese publications. Parameters unavailable from publications were estimated in a Delphi panel of Japanese clinical experts who also confirmed the structure and overall approach of the model. Sensitivity analyses, including one-way, probabilistic, and scenario analyses, were conducted to account for uncertainty in the results. Findings Over a lifetime horizon, EOB-MRI was associated with lower direct costs (¥2,174,869) and generated a greater number of quality-adjusted life years (QALYs) (9.502) than either ECCM-MRI (¥2,365,421, 9.303 QALYs) or CE-CT (¥2,482,608, 9.215 QALYs). EOB-MRI was superior to the other diagnostic strategies considered, and this finding was robust over sensitivity and scenario analyses. A majority of the direct costs associated with HCC in Japan were found to be costs of treatment. The model results revealed the superior cost-effectiveness of the EOB-MRI diagnostic strategy compared with ECCM-MRI and CE-CT. Implications EOB-MRI could be the first-choice imaging modality for medical care of HCC among patients with hepatitis or liver cirrhosis in Japan. Widespread implementation of EOB-MRI could reduce health care expenditures, particularly downstream treatment costs, associated with HCC.

DNA double-strand break (DSB) repair by homologous recombination has evolved to maintain genetic integrity in all organisms. Although many reactions that occur during homologous recombination are known, it is unclear where, when and how they occur in cells. Here, by using conventional and super-resolution microscopy, we describe the progression of DSB repair in live Escherichia coli. Specifically, we investigate whether homologous recombination can occur efficiently between distant sister loci that have segregated to opposite halves of an E. coli cell. We show that a site-specific DSB in one sister can be repaired efficiently using distant sister homology. After RecBCD processing of the DSB, RecA is recruited to the cut locus, where it nucleates into a bundle that contains many more RecA molecules than can associate with the two single-stranded DNA regions that form at the DSB. Mature bundles extend along the long axis of the cell, in the space between the bulk nucleoid and the inner membrane. Bundle formation is followed by pairing, in which the two ends of the cut locus relocate at the periphery of the nucleoid and together move rapidly towards the homology of the uncut sister. After sister locus pairing, RecA bundles disassemble and proteins that act late in homologous recombination are recruited to give viable recombinants 1-2-generation-time equivalents after formation of the initial DSB. Mutated RecA proteins that do not form bundles are defective in sister pairing and in DSB-induced repair. This work reveals an unanticipated role of RecA bundles in channelling the movement of the DNA DSB ends, thereby facilitating the long-range homology search that occurs before the strand invasion and transfer reactions.