Predictive models that accurately emulate complex scientific processes can achieve speed-ups over numerical simulators or experiments and at the same time provide surrogates for improving the subsequent analysis. Consequently, there is a recent surge in utilizing modern machine learning methods to build data-driven emulators. In this work, we study an often overlooked, yet important, problem of choosing loss functions while designing such emulators. Popular choices such as the mean squared error or the mean absolute error are based on a symmetric noise assumption and can be unsuitable for heterogeneous data or asymmetric noise distributions. We propose Learn-by-Calibrating, a novel deep learning approach based on interval calibration for designing emulators that can effectively recover the inherent noise structure without any explicit priors. Using a large suite of use-cases, we demonstrate the efficacy of our approach in providing high-quality emulators, when compared to widely-adopted loss function choices, even in small-data regimes.The human metabolome provides a window into the mechanisms and biomarkers of various diseases. However, because of limited availability, many sample types are still difficult to study by metabolomic analyses. Here, we present a mass spectrometry (MS)-based metabolomics strategy that only consumes sub-nanoliter sample volumes. The approach consists of combining a customized metabolomics workflow with a pulsed MS ion generation method, known as triboelectric nanogenerator inductive nanoelectrospray ionization (TENGi nanoESI) MS. Samples tested with this approach include exhaled breath condensate collected from cystic fibrosis patients as well as in vitro-cultured human mesenchymal stromal cells. Both test samples are only available in minimum amounts.  https://www.selleckchem.com/products/npd4928.html  Experiments show that picoliter-volume spray pulses suffice to generate high-quality spectral fingerprints, which increase the information density produced per unit sample volume. This TENGi nanoESI strategy has the potential to fill in the gap in metabolomics where liquid chromatography-MS-based analyses cannot be applied. Our method opens up avenues for future investigations into understanding metabolic changes caused by diseases or external stimuli.Defects from grain interiors and boundaries of perovskite films cause significant nonradiative recombination energy loss, and thus perovskite films with controlled crystallinity and large grains is critical for improvement of both photovoltaic performance and stability for perovskite-based solar cells. Here, a methylamine (MA0) gas-assisted crystallization method is developed for fabrication of methylammonium lead iodide (MAPbI3) perovskite films. In the process, the perovskite film is formed via controlled release of MA0 gas molecules from a liquid intermediate phase MAPbI3·xMA0. The resulting perovskite film comprises millimeter-sized grains with (110)-uniaxial crystallographic orientation, exhibiting much low trap density, long carrier lifetime, and excellent environmental stability. The corresponding perovskite solar cell exhibits a power conversion efficiency (PCE) of ~ 21.36%, which is among the highest reported for MAPbI3-based devices. This method provides important progress towards the fabrication of high-quality perovskite thin films for low-cost, highly efficient and stable perovskite solar cells.The human Immunodeficiency Centromeric Instability Facial Anomalies (ICF) 4 syndrome is a severe disease with increased mortality caused by mutation in the LSH gene. Although LSH belongs to a family of chromatin remodeling proteins, it remains unknown how LSH mediates its function on chromatin in vivo. Here, we use chemical-induced proximity to rapidly recruit LSH to an engineered locus and find that LSH specifically induces macroH2A1.2 and macroH2A2 deposition in an ATP-dependent manner. Tethering of LSH induces transcriptional repression and silencing is dependent on macroH2A deposition. Loss of LSH decreases macroH2A enrichment at repeat sequences and results in transcriptional reactivation. Likewise, reduction of macroH2A by siRNA interference mimicks transcriptional reactivation. ChIP-seq analysis confirmed that LSH is a major regulator of genome-wide macroH2A distribution. Tethering of ICF4 mutations fails to induce macroH2A deposition and ICF4 patient cells display reduced macroH2A deposition and transcriptional reactivation supporting a pathogenic role for altered marcoH2A deposition. We propose that LSH is a major chromatin modulator of the histone variant macroH2A and that its ability to insert marcoH2A into chromatin and transcriptionally silence is disturbed in the ICF4 syndrome.Diverse toxicological mechanisms may mediate the impact of environmental toxicants (phthalates, phenols, polycyclic aromatic hydrocarbons, and metals) on pregnancy outcomes. In this study, we introduce an analytical framework for multivariate mediation analysis to identify mediation pathways (q = 61 mediators) in the relationship between environmental toxicants (p = 38 analytes) and gestational age at delivery. Our analytical framework includes (1) conducting pairwise mediation for unique exposure-mediator combinations, (2) exposure dimension reduction by estimating environmental risk scores, and (3) multivariate mediator analysis using either Bayesian shrinkage mediation analysis, population value decomposition, or mediation pathway penalization. Dimension reduction demonstrates that a one-unit increase in phthalate risk score is associated with a total effect of 1.07 lower gestational age (in weeks) at delivery (95% confidence interval 0.48-1.67) and eicosanoids from the cytochrome p450 pathway mediated 26% of this effect (95% confidence interval 4-63%). Eicosanoid products derived from the cytochrome p450 pathway may be important mediators of phthalate toxicity.Triplet excitons have been identified as the major obstacle to the realisation of organic laser diodes, as accumulation of triplet excitons leads to significant losses under continuous wave (CW) operation and/or electrical excitation. Here, we report the design and synthesis of a solid-state organic triplet quencher, as well as in-depth studies of its dispersion into a solution processable bis-stilbene-based laser dye. By blending the laser dye with 20 wt% of the quencher, negligible effects on the ASE thresholds, but a complete suppression of singlet-triplet annihilation (STA) and a 20-fold increase in excited-state photostability of the laser dye under CW excitation, were achieved. We used small-area OLEDs (0.2 mm2) to demonstrate efficient STA suppression by the quencher in the nanosecond range, supported by simulations to provide insights into the observed STA quenching under electrical excitation. The results demonstrate excellent triplet quenching ability under both optical and electrical excitations in the nanosecond range, coupled with excellent solution processability.