Market Segmentation Trees

We seek to provide an interpretable framework for segmenting users in a population for personalized decision-making. The standard approach is to perform market segmentation by clustering users according to similarities in their contextual features, after which a "response model" is fit to each segment to model how users respond to personalized decisions. However, this methodology is not ideal for personalization, since two users could in theory have similar features but different response behaviors. We propose a general methodology, Market Segmentation Trees (MSTs), for learning interpretable market segmentations explicitly driven by identifying differences in user response patterns. To demonstrate the versatility of our methodology, we design two new, specialized MST algorithms: (i) Choice Model Trees (CMTs) which can be used to predict a user's choice amongst multiple options, and (ii) Isotonic Regression Trees (IRTs) which can be used to solve the bid landscape forecasting problem. We provide a customizable, open-source code base for training MSTs in Python which employs several strategies for scalability, including parallel processing and warm starts. We provide a theoretical analysis of the asymptotic running time of our training method validating its computational tractability on large datasets. We assess the practical performance of MSTs on several synthetic and real world datasets, showing our method reliably finds market segmentations which accurately model response behavior. Further, when applying MSTs to historical bidding data from a leading demand-side platform (DSP), we show that MSTs consistently achieve a 5-29% improvement in bid landscape forecasting accuracy over the DSP's current model. Our findings indicate that integrating market segmentation with response modeling consistently leads to improvements in response prediction accuracy, thereby aiding personalization

Modified Gravity and Dark Energy models Beyond w(z)w(z)CDM Testable by LSST

One of the main science goals of the Large Synoptic Survey Telescope (LSST) is to uncover the nature of cosmic acceleration. In the base analysis, possible deviations from the Lambda-Cold-Dark-Matter ($\Lambda$CDM) background evolution will be probed by fitting a $w(z)$CDM model, which allows for a redshift-dependent dark energy equation of state with $w(z)$, within general relativity (GR). A rich array of other phenomena can arise due to deviations from the standard $\Lambda$CDM+GR model though, including modifications to the growth rate of structure and lensing, and novel screening effects on non-linear scales. Concrete physical models are needed to provide consistent predictions for these (potentially small) effects, to give us the best chance of detecting them and separating them from astrophysical systematics. A complex plethora of possible models has been constructed over the past few decades, with none emerging as a particular favorite. This document prioritizes a subset of these models along with rationales for further study and inclusion into the LSST Dark Energy Science Collaboration (DESC) data analysis pipelines, based on their observational viability, theoretical plausibility, and level of theoretical development. We provide references and theoretical expressions to aid the integration of these models into DESC software and simulations, and give justifications for why other models were not prioritized. While DESC efforts are free to pursue other models, we provide here guidelines on which theories appear to have higher priority for collaboration efforts due to their perceived promise and greater instructional value.Comment: 61 pages. Some acknowledgments and references added. This is version-1.1 of an internal collaboration document of LSST-DESC that is being made public and is not planned for submission to a journa

Improving total saccharification yield of Arabidopsis plants by vessel-specific complementation of caffeoyl shikimate esterase (cse) mutants

Background: Caffeoyl shikimate esterase (CSE) was recently characterized as an enzyme central to the lignin biosynthetic pathway in Arabidopsis thaliana. The cse-2 loss-of-function mutant shows a typical phenotype of lignin-deficient mutants, including collapsed vessels, reduced lignin content, and lignin compositional shift, in addition to a fourfold increase in cellulose-to-glucose conversion when compared to the wild type. However, this mutant exhibits a substantial developmental arrest, which might outweigh the gains in fermentable sugar yield. To restore its normal growth and further improve its saccharification yield, we investigated a possible cause for the yield penalty of the cse-2 mutant. Furthermore, we evaluated whether CSE expression is under the same multi-leveled transcriptional regulatory network as other lignin biosynthetic genes and analyzed the transcriptional responses of the phenylpropanoid pathway upon disruption of CSE. Results: Transactivation analysis demonstrated that only second-level MYB master switches (MYB46 and MYB83) and lignin-specific activators (MYB63 and MYB85), but not top-level NAC master switches or other downstream transcription factors, effectively activate the CSE promoter in our protoplast-based system. The cse-2 mutant exhibited transcriptional repression of genes upstream of CSE, while downstream genes were mainly unaffected, indicating transcriptional feedback of CSE loss-of-function on monolignol biosynthetic genes. In addition, we found that the expression of CSE under the control of the vessel-specific VND7 promoter in the cse-2 background restored the vasculature integrity resulting in improved growth parameters, while the overall lignin content remained relatively low. Thus, by restoring the vascular integrity and biomass parameters of cse-2, we further improved glucose release per plant without pretreatment, with an increase of up to 36 % compared to the cse-2 mutant and up to 154 % compared to the wild type. Conclusions: Our results contribute to a better understanding of how the expression of CSE is regulated by secondary wall-associated transcription factors and how the expression of lignin genes is affected upon CSE loss-of-function in Arabidopsis. Moreover, we found evidence that vasculature collapse is underlying the yield penalty found in the cse-2 mutant. Through a vessel-specific complementation approach, vasculature morphology and final stem weight were restored, leading to an even higher total glucose release per plant

Hybrid kernelised expectation maximisation for Bremsstrahlung SPECT reconstruction in SIRT with 90Y micro-spheres

BACKGROUND: Selective internal radiation therapy with Yttrium-90 microspheres is an effective therapy for liver cancer and liver metastases. Yttrium-90 is mainly a high-energy beta particle emitter. These beta particles emit Bremsstrahlung radiation during their interaction with tissue making post-therapy imaging of the radioactivity distribution feasible. Nevertheless, image quality and quantification is difficult due to the continuous energy spectrum which makes resolution modelling, attenuation and scatter estimation challenging and therefore the dosimetry quantification is inaccurate. As a consequence a reconstruction algorithm able to improve resolution could be beneficial. METHODS: In this study, the hybrid kernelised expectation maximisation (HKEM) is used to improve resolution and contrast and reduce noise, in addition a modified HKEM called frozen HKEM (FHKEM) is investigated to further reduce noise. The iterative part of the FHKEM kernel was frozen at the 72nd sub-iteration. When using ordered subsets algorithms the data is divided in smaller subsets and the smallest algorithm iterative step is called sub-iteration. A NEMA phantom with spherical inserts was used for the optimisation and validation of the algorithm, and data from 5 patients treated with Selective internal radiation therapy were used as proof of clinical relevance of the method. RESULTS: The results suggest a maximum improvement of 56% for region of interest mean recovery coefficient at fixed coefficient of variation and better identification of the hot volumes in the NEMA phantom. Similar improvements were achieved with patient data, showing 47% mean value improvement over the gold standard used in hospitals. CONCLUSIONS: Such quantitative improvements could facilitate improved dosimetry calculations with SPECT when treating patients with Selective internal radiation therapy, as well as provide a more visible position of the cancerous lesions in the liver

Triple modality image reconstruction of PET data using SPECT, PET, CT information increases lesion uptake in images of patients treated with radioembolization with [Formula: see text] micro-spheres.

PURPOSE: Nuclear medicine imaging modalities like computed tomography (CT), single photon emission CT (SPECT) and positron emission tomography (PET) are employed in the field of theranostics to estimate and plan the dose delivered to tumors and the surrounding tissues and to monitor the effect of the therapy. However, therapeutic radionuclides often provide poor images, which translate to inaccurate treatment planning and inadequate monitoring images. Multimodality information can be exploited in the reconstruction to enhance image quality. Triple modality PET/SPECT/CT scanners are particularly useful in this context due to the easier registration process between images. In this study, we propose to include PET, SPECT and CT information in the reconstruction of PET data. The method is applied to Yttrium-90 ([Formula: see text]Y) data. METHODS: Data from a NEMA phantom filled with [Formula: see text]Y were used for validation. PET, SPECT and CT data from 10 patients treated with Selective Internal Radiation Therapy (SIRT) were used. Different combinations of prior images using the Hybrid kernelized expectation maximization were investigated in terms of VOI activity and noise suppression. RESULTS: Our results show that triple modality PET reconstruction provides significantly higher uptake when compared to the method used as standard in the hospital and OSEM. In particular, using CT-guided SPECT images, as guiding information in the PET reconstruction significantly increases uptake quantification on tumoral lesions. CONCLUSION: This work proposes the first triple modality reconstruction method and demonstrates up to 69% lesion uptake increase over standard methods with SIRT [Formula: see text]Y patient data. Promising results are expected for other radionuclide combination used in theranostic applications using PET and SPECT

Cystic fibrosis carriership and tuberculosis: hints toward an evolutionary selective advantage based on data from the Brazilian territory.

BACKGROUND: The reason why Cystic Fibrosis (CF) is the most common fatal genetic disease among Caucasians has been incompletely studied. We aimed at deepening the hypothesis that CF carriers have a relative protection against Mycobacterium tuberculosis (Mtb) infection. METHODS: Applying spatial epidemiology, we studied the link between CF carriership rate and tuberculosis (TB) incidence in Brazil. We corrected for 5 potential environmental and 2 immunological confounders in this relation: monthly income, sanitary provisions, literacy rates, racial composition and population density along with AIDS incidence rates and diabetes mellitus type 2. Smoking data were incomplete and not available for analysis. RESULTS: A significant, negative correlation between CF carriership rate and TB incidence, independent of any of the seven confounders was found. CONCLUSION: We provide exploratory support for the hypothesis that carrying a single CFTR mutation arms against Mtb infections

Preliminary study of the antioxidant properties of flowers and roots of Pyrostegia venusta (Ker Gawl) Miers

<p>Abstract</p> <p>Background</p> <p>Free radical stress leads to tissue injury and can eventually to arthritis, atherosclerosis, diabetes mellitus, neurodegenerative diseases and carcinogenesis. Several studies are ongoing worldwide to find natural antioxidants of plant origin. We assessed the <it>in-vitro </it>antioxidant activities and screened the phytochemical constituents of methanolic extracts of <it>Pyrostegia venusta </it>(Ker Gawl) <it>Miers</it>.</p> <p>Methods</p> <p>We evaluated the antioxidant potential and phytochemical constituents of <it>P. venusta </it>using 1,1-Diphenyl-2-picrylhydrazyl (DPPH), 2, 2'-azinobis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and ferric reducing antioxidant power (FRAP) assays. Gas chromatography-mass spectroscopy (GC-MS) studies were also undertaken to assess the phytochemical composition of the flower extracts.</p> <p>Results</p> <p>Phytochemical analyses revealed the presence of terpenoids, alkaloids, tannins, steroids, and saponins. The reducing ability of both extracts was in the range (in μm Fe(II)/g) of 112.49-3046.98 compared with butylated hydroxytoluene (BHT; 63.56 ± 2.62), catechin (972.02 ± 0.72 μm) and quercetin 3208.27 ± 31.29. A significant inhibitory effect of extracts of flowers (IC₅₀= 0.018 ± 0.69 mg/ml) and roots (IC₅₀= 0.026 ± 0.94 mg/ml) on ABTS free radicals was detected. The antioxidant activity of the extracts of flowers (95%) and roots (94%) on DPPH radicals was comparable with that of ascorbic acid (98.9%) and BHT (97.6%). GC-MS study revealed the presence of myoinositol, hexadecanoic acid, linoleic acid, palmitic acid and oleic acid in the flower extracts.</p> <p>Conclusion</p> <p>These data suggest that <it>P. venusta </it>is a natural source of antioxidants. The extracts of flowers and roots of <it>P. venusta </it>contain significant amounts of phytochemicals with antioxidative properties and could serve as inhibitors or scavengers of free radicals. <it>P. venusta </it>could be exploited as a potential source for plant-based pharmaceutical products. These results could form a sound basis for further investigation in the potential discovery of new natural bioactive compounds.</p

Prevalence of bat viruses associated with land-use change in the Atlantic Forest, Brazil

Introduction: Bats are critical to maintaining healthy ecosystems and many species are threatened primarily due to global habitat loss. Bats are also important hosts of a range of viruses, several of which have had significant impacts on global public health. The emergence of these viruses has been associated with land-use change and decreased host species richness. Yet, few studies have assessed how bat communities and the viruses they host alter with land-use change, particularly in highly biodiverse sites. Methods: In this study, we investigate the effects of deforestation on bat host species richness and diversity, and viral prevalence and richness across five forested sites and three nearby deforested sites in the interior Atlantic Forest of southern Brazil. Nested-PCR and qPCR were used to amplify and detect viral genetic sequence from six viral families (corona-, adeno-, herpes-, hanta-, paramyxo-, and astro-viridae) in 944 blood, saliva and rectal samples collected from 335 bats. Results: We found that deforested sites had a less diverse bat community than forested sites, but higher viral prevalence and richness after controlling for confounding factors. Viral detection was more likely in juvenile males located in deforested sites. Interestingly, we also found a significant effect of host bat species on viral prevalence indicating that viral taxa were detected more frequently in some species than others. In particular, viruses from the Coronaviridae family were detected more frequently in generalist species compared to specialist species. Discussion: Our findings suggest that deforestation may drive changes in the ecosystem which reduce bat host diversity while increasing the abundance of generalist species which host a wider range of viruses