Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian Processes

Deep Gaussian Process (DGP) models offer a powerful nonparametric approach for Bayesian inference, but exact inference is typically intractable, motivating the use of various approximations. However, existing approaches, such as mean-field Gaussian assumptions, limit the expressiveness and efficacy of DGP models, while stochastic approximation can be computationally expensive. To tackle these challenges, we introduce Neural Operator Variational Inference (NOVI) for Deep Gaussian Processes. NOVI uses a neural generator to obtain a sampler and minimizes the Regularized Stein Discrepancy in L2 space between the generated distribution and true posterior. We solve the minimax problem using Monte Carlo estimation and subsampling stochastic optimization techniques. We demonstrate that the bias introduced by our method can be controlled by multiplying the Fisher divergence with a constant, which leads to robust error control and ensures the stability and precision of the algorithm. Our experiments on datasets ranging from hundreds to tens of thousands demonstrate the effectiveness and the faster convergence rate of the proposed method. We achieve a classification accuracy of 93.56 on the CIFAR10 dataset, outperforming SOTA Gaussian process methods. Furthermore, our method guarantees theoretically controlled prediction error for DGP models and demonstrates remarkable performance on various datasets. We are optimistic that NOVI has the potential to enhance the performance of deep Bayesian nonparametric models and could have significant implications for various practical application

Determination of 13 Diuretics in Animal-Derived Foods by Ultra-high Performance Liquid Chromatography-Tandem Mass Spectrometry

A novel efficient and accurate ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the detection of 13 diuretics in animal-derived foods was developed. The samples were extracted with acetonitrile or 90% acetonitrile solution and cleaned up on a PRiME HLB pass-through solid phase extraction (SPE) column. Then, an ACQUITY HSS T3 column (100 mm × 2.1 mm, 1.8 μm) was used for chromatographic separation by gradient elution using a mobile phase consisting of 5 mmol/L aqueous ammonium acetate and acetonitrile, and an electrospray ionization source (ESI) operated in both positive and negative ion scanning modes with multiple reaction monitoring (MRM) was used to detect the diuretics qualitatively and quantitatively. The results showed that the calibration curves for all the analytes exhibited good linearity with correlation coefficients above 0.997 0. The limits of quantification ranged from 2.0 to 5.0 μg/kg. The recoveries of the proposed method ranged between 68.3% and 118.0%, with relative standard deviations (RSDs) between 0.47% and 9.5% (n = 6). This method is a fast, simple, accurate, and practical one for the detection of diuretics

Detection of Pine Nut Allergen in Three Kinds of Food by Ultra-high Performance Liquid Chromatography-Tandem Mass Spectrometry

An ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was established for the detection of pine nut allergen Pin k 2 in food matrices. Pine nuts were ground, degreased, and enzymatically extracted and the hydrolysate was separated and analyzed by using an Easy-nLC 1000-QExecutive high-resolution mass spectrometer, and the mass spectral data obtained were processed using Protein Pilot TM software and the Uniprot protein database. The specificity was verified by Basic Local Alignment Search Tool (BLAST), and three pine nut-specific peptides were selected finally. The developed method exhibited a good linear relationship in the concentration range of 0.001–50 mg/mL, and the limit of quantification was 1 mg/kg. The average recoveries for blank biscuit, chocolate and beverage were 88.50%–107.57%, with a relative standard deviation (RSD) not exceeding 6.08%, and the matrix effect was 89.77%–96.13%. This method has the advantages of high sensitivity and good specificity, and can be applied to the detection of pine nut allergens in food samples such as biscuits, chocolate, and beverages, which provides technical support for the authentication of food labels and the detection of latent allergens in foods

Enzymatic Degradation of Alginate and in Vitro Immunological Activity of Its Degraded Products

In this study, changes in the molecular mass of alginate were investigated during its enzymatic degradation and the processing parameters for the enzymatic preparation of alginate oligosaccharides were explored. Furthermore, the in vitro immunological activity of degraded products with different molecular mass was evaluated. The results showed that the molecular mass of alginate decreased significantly after degradation by alginate lyase, and three degradation products with different molecular mass were obtained through gradient ethanol fractionation. Their weight-average molecular masses were 13.4, 5.73 and 3.85 kDa, respectively. Using single factor experiments, the optimal processing parameters were determined as pH 7.0, alginate lyase dosage 15 U/g substrate, and hydrolysis time 24 h, giving a yield of 28.05%. All alginate and its degraded products had immunoenhancing activity in mouse macrophages, and among them, the effect of the product with a weight-average molecular mass of 5.73 kDa was most pronounced and more pronounced than that of alginate oligosaccharides. By adding TAK-242, a blocker of macrophage Toll-like receptor 4 (TLR4), it was verified that the degraded products of alginate regulated macrophage immune activity by inducing the secretion of TLR4 and consequently causing cascade reactions to increase the secretion of NO, TNF-α and IL-6. These results can provide a theoretical basis for the high-value utilization of alginate

Rapid determination of 103 common veterinary drug residues in milk and dairy products by ultra performance liquid chromatography tandem mass spectrometry

A multi-residue method has been developed for the identification and quantification of 103 common veterinary drug residues in milk and dairy Products. This method was based on QuEChERS with dispersive solid-phase where C18 sorbent and anhydrous sodium sulfate were used to sample purification. After evaporation and reconstitution, the samples were analyzed by ultra-performance liquid chromatography-tandem mass spectrometry. The mean recovery results were all higher than 60% except ampicillin, pipemidic acid, enoxacin, and estriol, and the relative standard deviation was <20.0%. The limit of quantification ranged between 0.1 and 5 μg/kg for milk and between 0.5 and 25 μg/kg for milk powder. It was successfully used to detect residues of veterinary drug in real samples. This study proposes a simple and fast analytical method for monitoring multi-class veterinary drug residues to ensure food safety

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase chain reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics

Gene Expression Profiling Identifies Two Chordoma Subtypes Associated with Distinct Molecular Mechanisms and Clinical Outcomes.

PURPOSE: Chordoma is a rare bone tumor with a high recurrence rate and limited treatment options. The aim of this study was to identify molecular subtypes of chordoma that may improve clinical management. EXPERIMENTAL DESIGN: We conducted RNA sequencing in 48 tumors from patients with Chinese skull-base chordoma and identified two major molecular subtypes. We then replicated the classification using a NanoString panel in 48 patients with chordoma from North America. RESULTS: Tumors in one subtype were more likely to have somatic mutations and reduced expression in chromatin remodeling genes, such as PBRM1 and SETD2, whereas the other subtype was characterized by the upregulation of genes in epithelial-mesenchymal transition and Sonic Hedgehog pathways. IHC staining of top differentially expressed genes between the two subtypes in 312 patients with Chinese chordoma with long-term follow-up data showed that the expression of some markers such as PTCH1 was significantly associated with survival outcomes. CONCLUSIONS: Our findings may improve the understanding of subtype-specific tumorigenesis of chordoma and inform clinical prognostication and targeted options

Analysis of Common and Specific Mechanisms of Liver Function Affected by Nitrotoluene Compounds

BACKGROUND: Nitrotoluenes are widely used chemical manufacturing and munitions applications. This group of chemicals has been shown to cause a range of effects from anemia and hypercholesterolemia to testicular atrophy. We have examined the molecular and functional effects of five different, but structurally related, nitrotoluenes on using an integrative systems biology approach to gain insight into common and disparate mechanisms underlying effects caused by these chemicals. METHODOLOGY/PRINCIPAL FINDINGS: Sprague-Dawley female rats were exposed via gavage to one of five concentrations of one of five nitrotoluenes [2,4,6-trinitrotoluene (TNT), 2-amino-4,6-dinitrotoluene (2ADNT) 4-amino-2,6-dinitrotoulene (4ADNT), 2,4-dinitrotoluene (2,4DNT) and 2,6-dinitrotoluene (2,6DNT)] with necropsy and tissue collection at 24 or 48 h. Gene expression profile results correlated well with clinical data and liver histopathology that lead to the concept that hematotoxicity was followed by hepatotoxicity. Overall, 2,4DNT, 2,6DNT and TNT had stronger effects than 2ADNT and 4ADNT. Common functional terms, gene expression patterns, pathways and networks were regulated across all nitrotoluenes. These pathways included NRF2-mediated oxidative stress response, aryl hydrocarbon receptor signaling, LPS/IL-1 mediated inhibition of RXR function, xenobiotic metabolism signaling and metabolism of xenobiotics by cytochrome P450. One biological process common to all compounds, lipid metabolism, was found to be impacted both at the transcriptional and lipid production level. CONCLUSIONS/SIGNIFICANCE: A systems biology strategy was used to identify biochemical pathways affected by five nitroaromatic compounds and to integrate data that tie biochemical alterations to pathological changes. An integrative graphical network model was constructed by combining genomic, gene pathway, lipidomic, and physiological endpoint results to better understand mechanisms of liver toxicity and physiological endpoints affected by these compounds

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe