Detecting Bias in Monte Carlo Renderers using Welch’s t-test

When checking the implementation of a new renderer, one usually compares the output to that of a reference implementation. However, such tests require a large number of samples to be reliable, and sometimes they are unable to reveal very subtle differences that are caused by bias, but overshadowed by random noise. We propose using Welch’s t-test, a statistical test that reliably finds small bias even at low sample counts. Welch’s t-test is an established method in statistics to determine if two sample sets have the same underlying mean, based on sample statistics. We adapt it to test whether two renderers converge to the same image, i.e., the same mean per pixel or pixel region. We also present two strategies for visualizing and analyzing the test’s results, assisting us in localizing especially problematic image regions and detecting biased implementations with high confidence at low sample counts both for the reference and tested implementation

Path Guiding with Vertex Triplet Distributions

Good importance sampling strategies are decisive for the quality and robustness of photorealistic image synthesis with Monte Carlo integration. Path guiding approaches use transport paths sampled by an existing base sampler to build and refine a guiding distribution. This distribution then guides subsequent paths in regions that are otherwise hard to sample. We observe that all terms in the measurement contribution function sampled during path construction depend on at most three consecutive path vertices. We thus propose to build a 9D guiding distribution over vertex triplets that adapts to the full measurement contribution with a 9D Gaussian mixture model (GMM). For incremental path sampling, we query the model for the last two vertices of a path prefix, resulting in a 3D conditional distribution with which we sample the next vertex along the path. To make this approach scalable, we partition the scene with an octree and learn a local GMM for each leaf separately. In a learning phase, we sample paths using the current guiding distribution and collect triplets of path vertices. We resample these triplets online and keep only a fixed-size subset in reservoirs. After each progression, we obtain new GMMs from triplet samples by an initial hard clustering followed by expectation maximization. Since we model 3D vertex positions, our guiding distribution naturally extends to participating media. In addition, the symmetry in the GMM allows us to query it for paths constructed by a light tracer. Therefore our method can guide both a path tracer and light tracer from a jointly learned guiding distribution

Dual disassembly and biological evaluation of enzyme/oxidation-responsive polyester-based nanoparticulates for tumor-targeting delivery

Polyester-based nanoparticulates (NPs) are ideal nanocarriers for intracellular delivery of anticancer drugs because of their biocompatibility. However, an on-going challenge is the controlled and enhanced release of encapsulated therapeutics in response to unique changes that occur within cancer cells. Herein, we report the versatility of dual responses to enzymatic and oxidative reactions found in cancer cells toward the development of polyester-NPs as effective tumor-targeting intracellular nanocarriers. A facile nanoprecipitation method allows for the preparation of hydrophobic cores composed of novel polyester designed with esterase-responsive ester groups and oxidation-responsive sulfide linkages on their backbones, physically stabilized with poly(ethylene glycol)-based polymeric shells. The formed core/shell-type NPs with a diameter of 120 nm exhibit excellent colloidal stability in physiological conditions and in the presence of serum proteins. When exposed to esterase and hydrogen peroxide, NP integrity is disrupted, leading to the enhanced release of encapsulated doxorubicin, confirmed by dynamic light scattering and spectroscopic analysis. Combined results from epifluorescence microscopy, confocal laser scanning microscopy, flow cytometry, and cell viability demonstrate that doxorubicin-loaded NPs reveal rapid penetration and enhanced intracellular release of doxorubicin, thus inhibiting tumor progression. Importantly, the cellular uptake of doxorubicin-loaded core/shell NPs primarily via caveolae-dependent mechanism promotes their use in targeting a broad spectrum of cancers

Leaky ryanodine receptors contribute to diaphragmatic weakness during mechanical ventilation

Ventilator-induced diaphragmatic dysfunction (VIDD) refers to the diaphragm muscle weakness that occurs following prolonged controlled mechanical ventilation (MV). The presence of VIDD impedes recovery from respiratory failure. However, the pathophysiological mechanisms accounting for VIDD are still not fully understood. Here, we show in human subjects and a mouse model of VIDD that MV is associated with rapid remodeling of the sarcoplasmic reticulum (SR) Ca2+ release channel/ryanodine receptor (RyR1) in the diaphragm. The RyR1 macromolecular complex was oxidized, S-nitrosylated, Ser-2844 phosphorylated, and depleted of the stabilizing subunit calstabin1, following MV. These posttranslational modifications of RyR1 were mediated by both oxidative stress mediated by MV and stimulation of adrenergic signaling resulting from the anesthesia. We demonstrate in the murine model that such abnormal resting SR Ca2+ leak resulted in reduced contractile function and muscle fiber atrophy for longer duration of MV. Treatment with β-adrenergic antagonists or with S107, a small molecule drug that stabilizes the RyR1–calstabin1 interaction, prevented VIDD. Diaphragmatic dysfunction is common in MV patients and is a major cause of failure to wean patients from ventilator support. This study provides the first evidence to our knowledge of RyR1 alterations as a proximal mechanism underlying VIDD (i.e., loss of function, muscle atrophy) and identifies RyR1 as a potential target for therapeutic intervention

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Emotional experiences and psychological well-being in 51 countries during the covid-19 pandemic

The COVID-19 pandemic presents challenges to psychological well-being, but how can we predict when people suffer or cope during sustained stress? Here, we test the prediction that specific types of momentary emotional experiences are differently linked to psychological well-being during the pandemic. Study 1 used survey data collected from 24,221 participants in 51 countries during the COVID-19 outbreak. We show that, across countries, well-being is linked to individuals’ recent emotional experiences, including calm, hope, anxiety, loneliness, and sadness. Consistent results are found in two age, sex, and ethnicity-representative samples in the United Kingdom (n = 971) and the United States (n = 961) with preregistered analyses (Study 2). A prospective 30-day daily diary study conducted in the United Kingdom (n = 110) confirms the key role of these five emotions and demonstrates that emotional experiences precede changes in well-being (Study 3). Our findings highlight differential relationships between specific types of momentary emotional experiences and well-being and point to the cultivation of calm and hope as candidate routes for well-being interventions during periods of sustained stress

Abstracts from the 8th International Conference on cGMP Generators, Effectors and Therapeutic Implications

This work was supported by a restricted research grant of Bayer AG

Dataset to "Identifiability Analysis and Parameter Estimation of Microgel Synthesis: A Set-Membership Approach"

Functional microgels with tailored structure and specific properties are required for medical and technical applications, thus motivating model-based optimization of their fabrication processes. An important step in the creation of accurate models is parameter estimation. We present a methodology for a parameter identifiability analysis, which approximates the feasible parameter set as a box by solving a series of constrained dynamic optimization problems. The method is applied to the synthesis of microgels based on two monomers, N-vinylcaprolactam and N-isopropylacrylamide, and the cross-linker N,N-methylenebis(acrylamide). The results show that kinetic parameters corresponding to the reaction of the monomers are identifiable as are a subset of the kinetic parameters involving the cross-linker. The reaction kinetics of the cross-linking are faster in comparison to the main polymerization reaction for N-vinylcaprolactam; this allows for an improved understanding of the occurring reaction phenomena. The reaction kinetics of the cross-linking are not identifiable for N-isopropylacrylamide for the given experimental setup; model-based experimental design for parameter precision might enable their identification. The results also indicate potential for model simplification and allow us to make suggestions toward the enhancement of Raman spectroscopy measurements