PERGAMO: Personalized 3D Garments from Monocular Video

Clothing plays a fundamental role in digital humans. Current approaches to animate 3D garments are mostly based on realistic physics simulation, however, they typically suffer from two main issues: high computational run-time cost, which hinders their development; and simulation-to-real gap, which impedes the synthesis of specific real-world cloth samples. To circumvent both issues we propose PERGAMO, a data-driven approach to learn a deformable model for 3D garments from monocular images. To this end, we first introduce a novel method to reconstruct the 3D geometry of garments from a single image, and use it to build a dataset of clothing from monocular videos. We use these 3D reconstructions to train a regression model that accurately predicts how the garment deforms as a function of the underlying body pose. We show that our method is capable of producing garment animations that match the real-world behaviour, and generalizes to unseen body motions extracted from motion capture dataset.Comment: Published at Computer Graphics Forum (Proc. of ACM/SIGGRAPH SCA), 2022. Project website http://mslab.es/projects/PERGAMO

Comprehensive analysis and insights gained from long-term experience of the Spanish DILI Registry

Altres ajuts: Fondo Europeo de Desarrollo Regional (FEDER); Agencia Española del Medicamento; Consejería de Salud de Andalucía.Background & Aims: Prospective drug-induced liver injury (DILI) registries are important sources of information on idiosyncratic DILI. We aimed to present a comprehensive analysis of 843 patients with DILI enrolled into the Spanish DILI Registry over a 20-year time period. Methods: Cases were identified, diagnosed and followed prospectively. Clinical features, drug information and outcome data were collected. Results: A total of 843 patients, with a mean age of 54 years (48% females), were enrolled up to 2018. Hepatocellular injury was associated with younger age (adjusted odds ratio [aOR] per year 0.983; 95% CI 0.974-0.991) and lower platelet count (aOR per unit 0.996; 95% CI 0.994-0.998). Anti-infectives were the most common causative drug class (40%). Liver-related mortality was more frequent in patients with hepatocellular damage aged ≥65 years (p = 0.0083) and in patients with underlying liver disease (p = 0.0221). Independent predictors of liver-related death/transplantation included nR-based hepatocellular injury, female sex, higher onset aspartate aminotransferase (AST) and bilirubin values. nR-based hepatocellular injury was not associated with 6-month overall mortality, for which comorbidity burden played a more important role. The prognostic capacity of Hy's law varied between causative agents. Empirical therapy (corticosteroids, ursodeoxycholic acid and MARS) was prescribed to 20% of patients. Drug-induced autoimmune hepatitis patients (26 cases) were mainly females (62%) with hepatocellular damage (92%), who more frequently received immunosuppressive therapy (58%). Conclusions: AST elevation at onset is a strong predictor of poor outcome and should be routinely assessed in DILI evaluation. Mortality is higher in older patients with hepatocellular damage and patients with underlying hepatic conditions. The Spanish DILI Registry is a valuable tool in the identification of causative drugs, clinical signatures and prognostic risk factors in DILI and can aid physicians in DILI characterisation and management. Lay summary: Clinical information on drug-induced liver injury (DILI) collected from enrolled patients in the Spanish DILI Registry can guide physicians in the decision-making process. We have found that older patients with hepatocellular type liver injury and patients with additional liver conditions are at a higher risk of mortality. The type of liver injury, patient sex and analytical values of aspartate aminotransferase and total bilirubin can also help predict clinical outcomes

Optimization of adsorptive removal of α-toluic acid by CaO2 nanoparticles using response surface methodology

The present work addresses the optimization of process parameters for adsorptive removal of α-toluic acid by calcium peroxide (CaO2) nanoparticles using response surface methodology (RSM). CaO2 nanoparticles were synthesized by chemical precipitation method and confirmed by Transmission electron microscopy (TEM) and high-resolution TEM (HRTEM) analysis which shows the CaO2 nanoparticles size range of 5–15 nm. A series of batch adsorption experiments were performed using CaO2 nanoparticles to remove α-toluic acid from the aqueous solution. Further, an experimental based central composite design (CCD) was developed to study the interactive effect of CaO2 adsorbent dosage, initial concentration of α-toluic acid, and contact time on α-toluic acid removal efficiency (response) and optimization of the process. Analysis of variance (ANOVA) was performed to determine the significance of the individual and the interactive effects of variables on the response. The model predicted response showed a good agreement with the experimental response, and the coefficient of determination, (R2) was 0.92. Among the variables, the interactive effect of adsorbent dosage and the initial α-toluic acid concentration was found to have more influence on the response than the contact time. Numerical optimization of process by RSM showed the optimal adsorbent dosage, initial concentration of α-toluic acid, and contact time as 0.03 g, 7.06 g/L, and 34 min respectively. The predicted removal efficiency was 99.50%. The experiments performed under these conditions showed α-toluic acid removal efficiency up to 98.05%, which confirmed the adequacy of the model prediction

Clinical and genetic characteristics of late-onset Huntington's disease

Background: The frequency of late-onset Huntington's disease (>59 years) is assumed to be low and the clinical course milder. However, previous literature on late-onset disease is scarce and inconclusive. Objective: Our aim is to study clinical characteristics of late-onset compared to common-onset HD patients in a large cohort of HD patients from the Registry database. Methods: Participants with late- and common-onset (30–50 years)were compared for first clinical symptoms, disease progression, CAG repeat size and family history. Participants with a missing CAG repeat size, a repeat size of ≤35 or a UHDRS motor score of ≤5 were excluded. Results: Of 6007 eligible participants, 687 had late-onset (11.4%) and 3216 (53.5%) common-onset HD. Late-onset (n = 577) had significantly more gait and balance problems as first symptom compared to common-onset (n = 2408) (P <.001). Overall motor and cognitive performance (P <.001) were worse, however only disease motor progression was slower (coefficient, −0.58; SE 0.16; P <.001) compared to the common-onset group. Repeat size was significantly lower in the late-onset (n = 40.8; SD 1.6) compared to common-onset (n = 44.4; SD 2.8) (P <.001). Fewer late-onset patients (n = 451) had a positive family history compared to common-onset (n = 2940) (P <.001). Conclusions: Late-onset patients present more frequently with gait and balance problems as first symptom, and disease progression is not milder compared to common-onset HD patients apart from motor progression. The family history is likely to be negative, which might make diagnosing HD more difficult in this population. However, the balance and gait problems might be helpful in diagnosing HD in elderly patients