3D Reconstruction of Sculptures from Single Images via Unsupervised Domain Adaptation on Implicit Models

Acquiring the virtual equivalent of exhibits, such as sculptures, in virtual reality (VR) museums, can be labour-intensive and sometimes infeasible. Deep learning based 3D reconstruction approaches allow us to recover 3D shapes from 2D observations, among which single-view-based approaches can reduce the need for human intervention and specialised equipment in acquiring 3D sculptures for VR museums. However, there exist two challenges when attempting to use the well-researched human reconstruction methods: limited data availability and domain shift. Considering sculptures are usually related to humans, we propose our unsupervised 3D domain adaptation method for adapting a single-view 3D implicit reconstruction model from the source (real-world humans) to the target (sculptures) domain. We have compared the generated shapes with other methods and conducted ablation studies as well as a user study to demonstrate the effectiveness of our adaptation method. We also deploy our results in a VR application

On the Design Fundamentals of Diffusion Models: A Survey

Diffusion models are generative models, which gradually add and remove noise to learn the underlying distribution of training data for data generation. The components of diffusion models have gained significant attention with many design choices proposed. Existing reviews have primarily focused on higher-level solutions, thereby covering less on the design fundamentals of components. This study seeks to address this gap by providing a comprehensive and coherent review on component-wise design choices in diffusion models. Specifically, we organize this review according to their three key components, namely the forward process, the reverse process, and the sampling procedure. This allows us to provide a fine-grained perspective of diffusion models, benefiting future studies in the analysis of individual components, the applicability of design choices, and the implementation of diffusion models

A Simpler Machine Learning Model for Acute Kidney Injury Risk Stratification in Hospitalized Patients

Background: Hospitalization-associated acute kidney injury (AKI), affecting one-in-five inpatients, is associated with increased mortality and major adverse cardiac/kidney endpoints. Early AKI risk stratification may enable closer monitoring and prevention. Given the complexity and resource utilization of existing machine learning models, we aimed to develop a simpler prediction model. Methods: Models were trained and validated to predict risk of AKI using electronic health record (EHR) data available at 24 h of inpatient admission. Input variables included demographics, laboratory values, medications, and comorbidities. Missing values were imputed using multiple imputation by chained equations. Results: 26,410 of 209,300 (12.6%) inpatients developed AKI during admission between 13 July 2012 and 11 July 2018. The area under the receiver operating characteristic curve (AUROC) was 0.86 for Random Forest and 0.85 for LASSO. Based on Youden’s Index, a probability cutoff of \u3e0.15 provided sensitivity and specificity of 0.80 and 0.79, respectively. AKI risk could be successfully predicted in 91% patients who required dialysis. The model predicted AKI an average of 2.3 days before it developed. Conclusions: The proposed simpler machine learning model utilizing data available at 24 h of admission is promising for early AKI risk stratification. It requires external validation and evaluation of effects of risk prediction on clinician behavior and patient outcomes

Demethylating agents in combination with CD7-targeted CAR-T for the successful treatment of a case with mixed-phenotype acute leukemia relapsed after allogeneic hematopoietic stem cell transplantation: A Case Report

BackgroundAllogeneic hematopoietic stem cell transplantation (allo-HSCT) has cured many patients with malignant hematologic diseases such as mixed phenotype acute leukemia (MPAL), while those relapsing after allo-HSCT still exhibit high mortality, poor prognosis, and no standard treatment modalities. It is necessary to explore more therapeutic modalities for patients with post-transplant relapse to obtain a better prognosis.Case presentationIn this case report, a young male with MPAL received allo-HSCT after reaching complete remission (CR) by induction chemotherapy. Unfortunately, relapse of both myeloid and T lineages occurred nine months later. After receiving demethylating chemotherapy, myeloid lineage measurable residual disease (MRD) turned negative. T-lineage MRD turned negative after CD7-targeted chimeric antigen receptor (CAR)-T cell therapy. The bone marrow remained MRD-negative for 4 months. This case preliminarily demonstrated a long-lasting CR with CD7-targeted CAR-T cell therapy, allowing a better prognosis.ConclusionDemethylating drugs combined with CD7-targeted CAR-T cell therapy is feasible in treating MPAL patients with relapse after transplantation, with good efficacy and safety, which will be a promising treatment option for MPAL

The role of spin in the kinetic control of recombination in organic photovoltaics.

In biological complexes, cascade structures promote the spatial separation of photogenerated electrons and holes, preventing their recombination. In contrast, the photogenerated excitons in organic photovoltaic cells are dissociated at a single donor-acceptor heterojunction formed within a de-mixed blend of the donor and acceptor semiconductors. The nanoscale morphology and high charge densities give a high rate of electron-hole encounters, which should in principle result in the formation of spin-triplet excitons, as in organic light-emitting diodes. Although organic photovoltaic cells would have poor quantum efficiencies if every encounter led to recombination, state-of-the-art examples nevertheless demonstrate near-unity quantum efficiency. Here we show that this suppression of recombination arises through the interplay between spin, energetics and delocalization of electronic excitations in organic semiconductors. We use time-resolved spectroscopy to study a series of model high-efficiency polymer-fullerene systems in which the lowest-energy molecular triplet exciton (T1) for the polymer is lower in energy than the intermolecular charge transfer state. We observe the formation of T1 states following bimolecular recombination, indicating that encounters of spin-uncorrelated electrons and holes generate charge transfer states with both spin-singlet ((1)CT) and spin-triplet ((3)CT) characters. We show that the formation of triplet excitons can be the main loss mechanism in organic photovoltaic cells. But we also find that, even when energetically favoured, the relaxation of (3)CT states to T1 states can be strongly suppressed by wavefunction delocalization, allowing for the dissociation of (3)CT states back to free charges, thereby reducing recombination and enhancing device performance. Our results point towards new design rules both for photoconversion systems, enabling the suppression of electron-hole recombination, and for organic light-emitting diodes, avoiding the formation of triplet excitons and enhancing fluorescence efficiency.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC)This is the accepted version of the original publication available at: http://www.nature.com/nature/journal/v500/n7463/full/nature12339.html

Genome-wide association studies for diabetic macular edema and proliferative diabetic retinopathy

Background: Diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR) are sight threatening complications of diabetes mellitus and leading causes of adult onset blindness worldwide. Genetic risk factors for diabetic retinopathy (DR) have been described previously, but have been difficult to replicate between studies, which have often used composite phenotypes and been conducted in different populations. This study aims to identify genetic risk factors for DME and PDR as separate complications in Australians of European descent with type 2 diabetes. Methods: Caucasian Australians with type 2 diabetes were evaluated in a genome wide association study (GWAS) to compare 270 DME cases and 176 PDR cases with 435 non retinopathy controls. All participants were genotyped by SNP array and after data cleaning, cases were compared to controls using logistic regression adjusting for relevant covariates. Results: The top ranked SNP for DME was rs1990145 (p = 4.10 x 10(-6), OR = 2.02 95%CI [1.50, 2.72]) on chromosome 2. The top-ranked SNP for PDR was rs918519 (p = 3.87 x 10(-6), OR = 0.35 95%CI [0.22, 0.54]) on chromosome 5. A trend towards association was also detected at two SNPs reported in the only other reported GWAS of DR in Caucasians; rs12267418 near MALRD1 (p = 0.008) in the DME cohort and rs16999051 in the diabetes gene PCSK.2 (p = 0.007) in the PDR cohort. Conclusion: This study has identified loci of interest for DME and PDR, two common ocular complications of diabetes. These findings require replication in other Caucasian cohorts with type 2 diabetes and larger cohorts will be required to identify genetic loci with statistical confidence. There is considerable overlap in the patient cohorts with each retinopathy subtype, complicating the search for genes that contribute to PDR and DME biology

RNA-Seq analysis of resistant and susceptible potato varieties during the early stages of potato virus Y infection

Background: Potato virus Y (PVY) is one of the most important plant viruses affecting potato production. The interactions between potato and PVY are complex and the outcome of the interactions depends on the potato genotype, the PVY strain, and the environmental conditions. A potato cultivar can induce resistance to a specific PVY strain, yet be susceptible to another. How a single potato cultivar responds to PVY in both compatible and incompatible interactions is not clear. Results: In this study, we used RNA-sequencing (RNA-Seq) to investigate and compare the transcriptional changes in leaves of potato upon inoculation with PVY. We used two potato varieties: Premier Russet, which is resistant to the PVY strain O (PVYᴼ) but susceptible to the strain NTN (PVYᴺᵀᴺ), and Russet Burbank, which is susceptible to all PVY strains that have been tested. Leaves were inoculated with PVYᴼ or PVYᴺᵀᴺ, and samples were collected 4 and 10 h post inoculation (hpi). A larger number of differentially expressed (DE) genes were found in the compatible reactions compared to the incompatible reaction. For all treatments, the majority of DE genes were down-regulated at 4 hpi and up-regulated at 10 hpi. Gene Ontology enrichment analysis showed enrichment of the biological process GO term “Photosynthesis, light harvesting” specifically in PVYᴼ-inoculated Premier Russet leaves, while the GO term “nucleosome assembly” was largely overrepresented in PVYᴺᵀᴺ-inoculated Premier Russet leaves and PVYᴼ-inoculated Russet Burbank leaves but not in PVYᴼ-inoculated Premier Russet leaves. Fewer genes were DE over 4-fold in the incompatible reaction compared to the compatible reactions. Amongst these, five genes were DE only in PVYᴼ-inoculated Premier Russet leaves, and all five were down-regulated. These genes are predicted to encode for a putative ABC transporter, a MYC2 transcription factor, a VQ-motif containing protein, a non-specific lipid-transfer protein, and a xyloglucan endotransglucosylase-hydroxylase. Conclusions: Our results show that the incompatible and compatible reactions in Premier Russet shared more similarities, in particular during the initial response, than the compatible reactions in the two different hosts. Our results identify potential key processes and genes that determine the fate of the reaction, compatible or incompatible, between PVY and its host

The GALEX Ultraviolet Atlas of Nearby Galaxies

We present images, integrated photometry, and surface-brightness and color profiles for a total of 1034 nearby galaxies recently observed by the Galaxy Evolution Explorer (GALEX) satellite in its far-ultraviolet (FUV; λ_(eff) = 1516 Å) and near-ultraviolet (NUV; λ_(eff) = 2267 Å) bands. Our catalog of objects is derived primarily from the GALEX Nearby Galaxies Survey (NGS) supplemented by galaxies larger than 1' in diameter serendipitously found in these fields and in other GALEX exposures of similar of greater depth. The sample analyzed here adequately describes the distribution and full range of properties (luminosity, color, star formation rate [SFR]) of galaxies in the local universe. From the surface brightness profiles obtained we have computed asymptotic magnitudes, colors, and luminosities, along with the concentration indices C31 and C42. We have also morphologically classified the UV surface brightness profiles according to their shape. This data set has been complemented with archival optical, near-infrared, and far-infrared fluxes and colors. We find that the integrated (FUV − K) color provides robust discrimination between elliptical and spiral/irregular galaxies and also among spiral galaxies of different subtypes. Elliptical galaxies with brighter K-band luminosities (i.e., more massive) are redder in (NUV − K) color but bluer in (FUV − NUV) (a color sensitive to the presence of a strong UV upturn) than less massive ellipticals. In the case of the spiral/irregular galaxies our analysis shows the presence of a relatively tight correlation between the (FUV − NUV) color (or, equivalently, the slope of the UV spectrum, β) and the total infrared-to-UV ratio. The correlation found between (FUV − NUV) color and K-band luminosity (with lower luminosity objects being bluer than more luminous ones) can be explained as due to an increase in the dust content with galaxy luminosity. The images in this Atlas along with the profiles and integrated properties are publicly available through a dedicated Web page

Genetic study of Diabetic Retinopathy: recruitment methodology and analysis of baseline characteristics

ARC and NHMRC funded authors may self-archive the author accepted version of their paper (authors manuscript) after a 12-month embargo period from publication in an open access institutional repository.BACKGROUND: Diabetic retinopathy (DR) is a blinding disease of increasing prevalence, caused by a complex interplay of genetic and environmental factors. Here we describe the patient recruitment methodology, case and control definitions, and clinical characteristics of a study sample to be used for genome-wide association (GWAS) analysis to detect genetic risk variants of DR. METHODS: 1669 participants with either type 1 (T1) or type 2 (T2) diabetes mellitus (DM) aged 18 to 95 years were recruited in Australian hospital clinics. Individuals with T2DM had disease duration of at least 5 years, and were taking oral hypoglycemic medication, and/or insulin therapy. Participants underwent ophthalmic examination. Medical history and biochemistry results were collected. Venous blood was obtained for genetic analysis. RESULTS: 683 diabetic cases (178 T1DM and 505 T2DM participants) with sight-threatening DR, defined as severe non-proliferative DR (NPDR), proliferative DR (PDR) or diabetic macular edema (DME) were included in this analysis. 812 individuals with DM but no DR or minimal NPDR were recruited as controls (191 with T1DM and 621 with T2DM). The presence of sight-threatening DR was significantly correlated with DM duration, hypertension, nephropathy, neuropathy, HbA1C and BMI. DME was associated with T2DM (p<0.001), whereas PDR was associated with T1DM (p<0.001). CONCLUSIONS: Adoption of a case-control study design involving extremes of the DR phenotype makes this a suitable cohort, for a well-powered GWAS to detect genetic risk variants for DR.This work was funded by a grant from the Ophthalmic Research Institute of Australia, and Project Grant #595918 from the National Health and Medical Research Council (NHMRC) of Australia. JEC is supported in part by a NHMRC Practitioner Fellowship and KPB by a Career Development Fellowship. Research conducted at Moorfields Eye Hospital was funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology