Probing Liver Injuries Induced by Thioacetamide in Human In Vitro Pooled Hepatocyte Experiments.

Animal studies are typically utilized to understand the complex mechanisms associated with toxicant-induced hepatotoxicity. Among the alternative approaches to animal studies, in vitro pooled human hepatocytes have the potential to capture population variability. Here, we examined the effect of the hepatotoxicant thioacetamide on pooled human hepatocytes, divided into five lots, obtained from forty diverse donors. For 24 h, pooled human hepatocytes were exposed to vehicle, 1.33 mM (low dose), and 12 mM (high dose) thioacetamide, followed by RNA-seq analysis. We assessed gene expression variability using heat maps, correlation plots, and statistical variance. We used KEGG pathways and co-expression modules to identify underlying physiological processes/pathways. The co-expression module analysis showed that the majority of the lots exhibited activation for the bile duct proliferation module. Despite lot-to-lot variability, we identified a set of common differentially expressed genes across the lots with similarities in their response to amino acid, lipid, and carbohydrate metabolism. We also examined efflux transporters and found larger lot-to-lot variability in their expression patterns, indicating a potential for alteration in toxicant bioavailability within the cells, which could in turn affect the gene expression patterns between the lots. Overall, our analysis highlights the challenges in using pooled hepatocytes to understand mechanisms of toxicity.

Final Measurement of the

This Letter reports one of the most precise measurements to date of the antineutrino spectrum from a purely ^{235}U-fueled reactor, made with the final dataset from the PROSPECT-I detector at the High Flux Isotope Reactor. By extracting information from previously unused detector segments, this analysis effectively doubles the statistics of the previous PROSPECT measurement. The reconstructed energy spectrum is unfolded into antineutrino energy and compared with both the Huber-Mueller model and a spectrum from a commercial reactor burning multiple fuel isotopes. A local excess over the model is observed in the 5-7 MeV energy region. Comparison of the PROSPECT results with those from commercial reactors provides new constraints on the origin of this excess, disfavoring at 2.0 and 3.7 standard deviations the hypotheses that antineutrinos from ^{235}U are solely responsible and noncontributors to the excess observed at commercial reactors, respectively.

Improved Measurement of the Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay.

Reactor neutrino experiments play a crucial role in advancing our knowledge of neutrinos. In this Letter, the evolution of the flux and spectrum as a function of the reactor isotopic content is reported in terms of the inverse-beta-decay yield at Daya Bay with 1958 days of data and improved systematic uncertainties. These measurements are compared with two signature model predictions: the Huber-Mueller model based on the conversion method and the SM2018 model based on the summation method. The measured average flux and spectrum, as well as the flux evolution with the ^{239}Pu isotopic fraction, are inconsistent with the predictions of the Huber-Mueller model. In contrast, the SM2018 model is shown to agree with the average flux and its evolution but fails to describe the energy spectrum. Altering the predicted inverse-beta-decay spectrum from ^{239}Pu fission does not improve the agreement with the measurement for either model. The models can be brought into better agreement with the measurements if either the predicted spectrum due to ^{235}U fission is changed or the predicted ^{235}U, ^{238}U, ^{239}Pu, and ^{241}Pu spectra are changed in equal measure.

Using a Graph Convolutional Neural Network Model to Identify Bile Salt Export Pump Inhibitors.

The bile salt export pump (BSEP) is a key transporter involved in the efflux of bile salts from hepatocytes to bile canaliculi. Inhibition of BSEP leads to the accumulation of bile salts within the hepatocytes, leading to possible cholestasis and drug-induced liver injury. Screening for and identification of chemicals that inhibit this transporter aid in understanding the safety liabilities of these chemicals. Moreover, computational approaches to identify BSEP inhibitors provide an alternative to the more resource-intensive, gold standard experimental approaches. Here, we used publicly available data to develop predictive machine learning models for the identification of potential BSEP inhibitors. Specifically, we analyzed the utility of a graph convolutional neural network (GCNN)-based approach in combination with multitask learning to identify BSEP inhibitors. Our analyses showed that the developed GCNN model performed better than the variable-nearest neighbor and Bayesian machine learning approaches, with a cross-validation receiver operating characteristic area under the curve of 0.86. In addition, we compared GCNN-based single-task and multitask models and evaluated their utility in addressing data limitation challenges commonly observed in bioactivity modeling. We found that multitask models performed better than single-task models and can be utilized to identify active molecules for targets with limited data availability. Overall, our developed multitask GCNN-based BSEP model provides a useful tool for prioritizing hits during early drug discovery and in risk assessment of chemicals.

Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay.

We present a new determination of the smallest neutrino mixing angle θ_{13} and the mass-squared difference Δm_{32}^{2} using a final sample of 5.55×10^{6} inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample is selected from the complete dataset obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are sin^{2}2θ_{13}=0.0851±0.0024, Δm_{32}^{2}=(2.466±0.060)×10^{-3} eV^{2} for the normal mass ordering or Δm_{32}^{2}=-(2.571±0.060)×10^{-3} eV^{2} for the inverted mass ordering.

Assessing Kidney Injury Induced by Mercuric Chloride in Guinea Pigs with In Vivo and In Vitro Experiments.

Acute kidney injury, which is associated with high levels of morbidity and mortality, affects a significant number of individuals, and can be triggered by multiple factors, such as medications, exposure to toxic chemicals or other substances, disease, and trauma. Because the kidney is a critical organ, understanding and identifying early cellular or gene-level changes can provide a foundation for designing medical interventions. In our earlier work, we identified gene modules anchored to histopathology phenotypes associated with toxicant-induced liver and kidney injuries. Here, using in vivo and in vitro experiments, we assessed and validated these kidney injury-associated modules by analyzing gene expression data from the kidneys of male Hartley guinea pigs exposed to mercuric chloride. Using plasma creatinine levels and cell-viability assays as measures of the extent of renal dysfunction under in vivo and in vitro conditions, we performed an initial range-finding study to identify the appropriate doses and exposure times associated with mild and severe kidney injuries. We then monitored changes in kidney gene expression at the selected doses and time points post-toxicant exposure to characterize the mechanisms of kidney injury. Our injury module-based analysis revealed a dose-dependent activation of several phenotypic cellular processes associated with dilatation, necrosis, and fibrogenesis that were common across the experimental platforms and indicative of processes that initiate kidney damage. Furthermore, a comparison of activated injury modules between guinea pigs and rats indicated a strong correlation between the modules, highlighting their potential for cross-species translational studies.

First Measurement of High-Energy Reactor Antineutrinos at Daya Bay.

This Letter reports the first measurement of high-energy reactor antineutrinos at Daya Bay, with nearly 9000 inverse beta decay candidates in the prompt energy region of 8-12 MeV observed over 1958 days of data collection. A multivariate analysis is used to separate 2500 signal events from background statistically. The hypothesis of no reactor antineutrinos with neutrino energy above 10 MeV is rejected with a significance of 6.2 standard deviations. A 29% antineutrino flux deficit in the prompt energy region of 8-11 MeV is observed compared to a recent model prediction. We provide the unfolded antineutrino spectrum above 7 MeV as a data-based reference for other experiments. This result provides the first direct observation of the production of antineutrinos from several high-Q_{ß} isotopes in commercial reactors.

Joint Determination of Reactor Antineutrino Spectra from

A joint determination of the reactor antineutrino spectra resulting from the fission of ^{235}U and ^{239}Pu has been carried out by the Daya Bay and PROSPECT Collaborations. This Letter reports the level of consistency of ^{235}U spectrum measurements from the two experiments and presents new results from a joint analysis of both data sets. The measurements are found to be consistent. The combined analysis reduces the degeneracy between the dominant ^{235}U and ^{239}Pu isotopes and improves the uncertainty of the ^{235}U spectral shape to about 3%. The ^{235}U and ^{239}Pu antineutrino energy spectra are unfolded from the jointly deconvolved reactor spectra using the Wiener-SVD unfolding method, providing a data-based reference for other reactor antineutrino experiments and other applications. This is the first measurement of the ^{235}U and ^{239}Pu spectra based on the combination of experiments at low- and highly enriched uranium reactors.

Joint Measurement of the

The PROSPECT and STEREO collaborations present a combined measurement of the pure ^{235}U antineutrino spectrum, without site specific corrections or detector-dependent effects. The spectral measurements of the two highest precision experiments at research reactors are found to be compatible with χ^{2}/ndf=24.1/21, allowing a joint unfolding of the prompt energy measurements into antineutrino energy. This ν[over ¯]_{e} energy spectrum is provided to the community, and an excess of events relative to the Huber model is found in the 5-6 MeV region. When a Gaussian bump is fitted to the excess, the data-model χ^{2} value is improved, corresponding to a 2.4σ significance.

Observational study of clinico-radiological follow-up of COVID-19 pneumonia: a district general hospital experience in the UK.

BACKGROUND: The British Thoracic Society (BTS) recommends that all patients admitted with COVID-19 pneumonia should have a chest X-ray (CXR) and clinical follow-up at 6 or 12 weeks, depending on the disease severity. Little data is available on long-term CXR follow-up for moderate and severe COVID-19 pneumonia. This study aims to evaluate compliance with clinico-radiological follow-up of patients recovering from COVID-19 pneumonia at a local hospital in the UK, as per the BTS guidance, and to analyse radiological changes at clinical follow-up at 12 weeks, in order to risk-stratify and improve patient outcomes. METHODS: This is a single-centre retrospective audit of 255 consecutive COVID-19 positive patients admitted to a local hospital in the UK over 5 months between May and October 2020. All CXRs and clinic follow-up at 12 ± 8 weeks were checked on an electronic database. RESULTS: Over one in two (131/255) patients had CXR evidence of COVID-19 pneumonia during the initial hospital admission. Half of the patients (60/131) died before CXR or clinic follow-up. Fifty-eight percent (41/71) of the surviving patients had a follow-up CXR, and only two developed respiratory complications- one had residual lung fibrosis, another a pulmonary embolism. Eighty-eight percent (36/41) of the patients had either resolution or improved radiological changes at follow-up. Most patients who had abnormal follow-up CXR were symptomatic (6/8), and many asymptomatic patients at follow-up had a normal CXR (10/12). CONCLUSIONS: Although there were concerns about interstitial lung disease (ILD) incidence in patients with COVID-19 pneumonia, most of our patients with COVID-19 pneumonia had no pulmonary complications at follow-up with CXR. This emphasises that CXR, a cost-effective investigation, can be used to risk-stratify patients for long term pulmonary complications following their COVID-19 pneumonia. However, we acknowledge the limitations of a low CXR and clinic follow-up rate in our cohort.

Genomics and metabolomics of early-stage thioacetamide-induced liver injury: An interspecies study between guinea pig and rat.

To study the complex processes involved in liver injuries, researchers rely on animal investigations, using chemically or surgically induced liver injuries, to extrapolate findings and infer human health risks. However, this presents obvious challenges in performing a detailed comparison and validation between the highly controlled animal models and development of liver injuries in humans. Furthermore, it is not clear whether there are species-dependent and -independent molecular initiating events or processes that cause liver injury before they eventually lead to end-stage liver disease. Here, we present a side-by-side study of rats and guinea pigs using thioacetamide to examine the similarities between early molecular initiating events during an acute-phase liver injury. We exposed Sprague Dawley rats and Hartley guinea pigs to a single dose of 25 or 100 mg/kg thioacetamide and collected blood plasma for metabolomic analysis and liver tissue for RNA-sequencing. The subsequent toxicogenomic analysis identified consistent liver injury trends in both genomic and metabolomic data within 24 and 33 h after thioacetamide exposure in rats and guinea pigs, respectively. In particular, we found species similarities in the key injury phenotypes of inflammation and fibrogenesis in our gene module analysis for liver injury phenotypes. We identified expression of several common genes (e.g., SPP1, TNSF18, SERPINE1, CLDN4, TIMP1, CD44, and LGALS3), activation of injury-specific KEGG pathways, and alteration of plasma metabolites involved in amino acid and bile acid metabolism as some of the key molecular processes that changed early upon thioacetamide exposure and could play a major role in the initiation of acute liver injury.

Nonfuel Antineutrino Contributions in the High Flux Isotope Reactor.

Reactor neutrino experiments have seen major improvements in precision in recent years. With the experimental uncertainties becoming lower than those from theory, carefully considering all sources of ν ¯ e is important when making theoretical predictions. One source of ν ¯ e that is often neglected arises from the irradiation of the nonfuel materials in reactors. The ν ¯ e rates and energies from these sources vary widely based on the reactor type, configuration, and sampling stage during the reactor cycle and have to be carefully considered for each experiment independently. In this article, we present a formalism for selecting the possible ν ¯ e sources arising from the neutron captures on reactor and target materials. We apply this formalism to the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory, the ν ¯ e source for the the Precision Reactor Oscillation and Spectrum Measurement (PROSPECT) experiment. Overall, we observe that the nonfuel ν ¯ e contributions from HFIR to PROSPECT amount to 1% above the inverse beta decay threshold with a maximum contribution of 9% in the 1.8-2.0 MeV range. Nonfuel contributions can be particularly high for research reactors like HFIR because of the choice of structural and reflector material in addition to the intentional irradiation of target material for isotope production. We show that typical commercial pressurized water reactors fueled with low-enriched uranium will have significantly smaller nonfuel ν ¯ e contribution.

Improved Constraints on Sterile Neutrino Mixing from Disappearance Searches in the MINOS, MINOS+, Daya Bay, and Bugey-3 Experiments.

Searches for electron antineutrino, muon neutrino, and muon antineutrino disappearance driven by sterile neutrino mixing have been carried out by the Daya Bay and MINOS+ collaborations. This Letter presents the combined results of these searches, along with exclusion results from the Bugey-3 reactor experiment, framed in a minimally extended four-neutrino scenario. Significantly improved constraints on the θ_{µe} mixing angle are derived that constitute the most constraining limits to date over five orders of magnitude in the mass-squared splitting Δm_{41}^{2}, excluding the 90% C.L. sterile-neutrino parameter space allowed by the LSND and MiniBooNE observations at 90% CL_{s} for Δm_{41}^{2}<13 eV^{2}. Furthermore, the LSND and MiniBooNE 99% C.L. allowed regions are excluded at 99% CL_{s} for Δm_{41}^{2}<1.6 eV^{2}.

A toxicogenomic approach to assess kidney injury induced by mercuric chloride in rats.

Kidney injury caused by disease, trauma, environmental exposures, or drugs may result in decreased renal function, chronic kidney disease, or acute kidney failure. Diagnosis of kidney injury using serum creatinine levels, a common clinical test, only identifies renal dysfunction after the kidneys have undergone severe damage. Other indicators sensitive to kidney injury, such as the level of urine kidney injury molecule-1 (KIM-1), lack the ability to differentiate between injury phenotypes. To address early detection as well as detailed categorization of kidney-injury phenotypes in preclinical animal or cellular studies, we previously identified eight sets (modules) of co-expressed genes uniquely associated with kidney histopathology. Here, we used mercuric chloride (HgCl2)-a model nephrotoxicant-to chemically induce kidney injuries as monitored by KIM-1 levels in Sprague Dawley rats at two doses (0.25 or 0.50 mg/kg) and two exposure lengths (10 or 34 h). We collected whole transcriptome RNA-seq data derived from five animals at each dose and time point to perform a toxicogenomics analysis. Consistent with documented injury phenotypes for HgCl2 toxicity, our kidney-injury-module approach identified the onset of necrosis and dilation as early as 10 h after a dose of 0.50 mg/kg that produced only mild injury as judged by urinary KIM-1 excretion. The results of these animal studies highlight the potential of the kidney-injury-module approach to provide a sensitive and histopathology-specific readout of renal toxicity.

Mining Public Toxicogenomic Data Reveals Insights and Challenges in Delineating Liver Steatosis Adverse Outcome Pathways.

Exposure to chemicals contributes to the development and progression of fatty liver, or steatosis, a process characterized by abnormal accumulation of lipids within liver cells. However, lack of knowledge on how chemicals cause steatosis has prevented any large-scale assessment of the 80,000+ chemicals in current use. To address this gap, we mined a large, publicly available toxicogenomic dataset associated with 18 known steatogenic chemicals to assess responses across assays (in vitro and in vivo) and species (i.e., rats and humans). We identified genes that were differentially expressed (DEGs) in rat in vivo, rat in vitro, and human in vitro studies in which rats or in vitro primary cell lines were exposed to the chemicals at different doses and durations. Using these DEGs, we performed pathway enrichment analysis, analyzed the molecular initiating events (MIEs) of the steatosis adverse outcome pathway (AOP), and predicted metabolite changes using metabolic network analysis. Genes indicative of oxidative stress were among the DEGs most frequently observed in the rat in vivo studies. Nox4, a pro-fibrotic gene, was down-regulated across these chemical exposure conditions. We identified eight genes (Cyp1a1, Egr1, Ccnb1, Gdf15, Cdk1, Pdk4, Ccna2, and Ns5atp9) and one pathway (retinol metabolism), associated with steatogenic chemicals and whose response was conserved across the three in vitro and in vivo systems. Similarly, we found the predicted metabolite changes, such as increases of saturated and unsaturated fatty acids, conserved across the three systems. Analysis of the target genes associated with the MIEs of the current steatosis AOP did not provide a clear association between these 18 chemicals and the MIEs, underlining the multi-factorial nature of this disease. Notably, our overall analysis implicated mitochondrial toxicity as an important and overlooked MIE for chemical-induced steatosis. The integrated toxicogenomics approach to identify genes, pathways, and metabolites based on known steatogenic chemicals, provide an important mean to assess development of AOPs and gauging the relevance of new testing strategies.

Teaching an Old Dog New Tricks: Strategies That Improve Early Recognition in Similarity-Based Virtual Screening.

High throughput screening (HTS) is an important component of lead discovery, with virtual screening playing an increasingly important role. Both methods typically suffer from lack of sensitivity and specificity against their true biological targets. With ever-increasing screening libraries and virtual compound collections, it is now feasible to conduct follow-up experimental testing on only a small fraction of hits. In this context, advances in virtual screening that achieve enrichment of true actives among top-ranked compounds ("early recognition") and, hence, reduce the number of hits to test, are highly desirable. The standard ligand-based virtual screening method for large compound libraries uses a molecular similarity search method that ranks the likelihood of a compound to be active against a drug target by its highest Tanimoto similarity to known active compounds. This approach assumes that the distributions of Tanimoto similarity values to all active compounds are identical (i.e., same mean and standard deviation)-an assumption shown to be invalid (Baldi and Nasr, 2010). Here, we introduce two methods that improve early recognition of actives by exploiting similarity information of all molecules. The first method ranks a compound by its highest z-score instead of its highest Tanimoto similarity, and the second by an aggregated score calculated from its Tanimoto similarity values to all known actives and inactives (or a large number of structurally diverse molecules when information on inactives is unavailable). Our evaluations, which use datasets of over 20 HTS campaigns downloaded from PubChem, indicate that compared to the conventional approach, both methods achieve a ~10% higher Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC) score-a metric of early recognition. Given the increasing use of virtual screening in early lead discovery, these methods provide straightforward means to enhance early recognition.

Extraction of the

This Letter reports the first extraction of individual antineutrino spectra from ^{235}U and ^{239}Pu fission and an improved measurement of the prompt energy spectrum of reactor antineutrinos at Daya Bay. The analysis uses 3.5×10^{6} inverse beta-decay candidates in four near antineutrino detectors in 1958 days. The individual antineutrino spectra of the two dominant isotopes, ^{235}U and ^{239}Pu, are extracted using the evolution of the prompt spectrum as a function of the isotope fission fractions. In the energy window of 4-6 MeV, a 7% (9%) excess of events is observed for the ^{235}U (^{239}Pu) spectrum compared with the normalized Huber-Mueller model prediction. The significance of discrepancy is 4.0σ for ^{235}U spectral shape compared with the Huber-Mueller model prediction. The shape of the measured inverse beta-decay prompt energy spectrum disagrees with the prediction of the Huber-Mueller model at 5.3σ. In the energy range of 4-6 MeV, a maximal local discrepancy of 6.3σ is observed.

Measurement of the Antineutrino Spectrum from

This Letter reports the first measurement of the ^{235}U ν[over ¯]_{e} energy spectrum by PROSPECT, the Precision Reactor Oscillation and Spectrum experiment, operating 7.9 m from the 85 MW_{th} highly enriched uranium (HEU) High Flux Isotope Reactor. With a surface-based, segmented detector, PROSPECT has observed 31678±304(stat) ν[over ¯]_{e}-induced inverse beta decays, the largest sample from HEU fission to date, 99% of which are attributed to ^{235}U. Despite broad agreement, comparison of the Huber ^{235}U model to the measured spectrum produces a χ^{2}/ndf=51.4/31, driven primarily by deviations in two localized energy regions. The measured ^{235}U spectrum shape is consistent with a deviation relative to prediction equal in size to that observed at low-enriched uranium power reactors in the ν[over ¯]_{e} energy region of 5-7 MeV.

Search for Sterile Neutrinos in MINOS and MINOS+ Using a Two-Detector Fit.

A search for mixing between active neutrinos and light sterile neutrinos has been performed by looking for muon neutrino disappearance in two detectors at baselines of 1.04 and 735 km, using a combined MINOS and MINOS+ exposure of 16.36×10^{20} protons on target. A simultaneous fit to the charged-current muon neutrino and neutral-current neutrino energy spectra in the two detectors yields no evidence for sterile neutrino mixing using a 3+1 model. The most stringent limit to date is set on the mixing parameter sin^{2}θ_{24} for most values of the sterile neutrino mass splitting Δm_{41}^{2}>10^{-4} eV^{2}.

Comparative Proteomic Analysis of Liver Steatosis and Fibrosis after Oral Hepatotoxicant Administration in Sprague-Dawley Rats.

The past decade has seen an increase in the development and clinical use of biomarkers associated with histological features of liver disease. Here, we conduct a comparative histological and global proteomics analysis to identify coregulated modules of proteins in the progression of hepatic steatosis or fibrosis. We orally administered the reference chemicals bromobenzene (BB) or 4,4'-methylenedianiline (4,4'-MDA) to male Sprague-Dawley rats for either 1 single administration or 5 consecutive daily doses. Livers were preserved for histopathology and global proteomics assessment. Analysis of liver sections confirmed a dose- and time-dependent increase in frequency and severity of histopathological features indicative of lipid accumulation after BB or fibrosis after 4,4'-MDA. BB administration resulted in a dose-dependent increase in the frequency and severity of inflammation and vacuolation. 4,4'-MDA administration resulted in a dose-dependent increase in the frequency and severity of periportal collagen accumulation and inflammation. Pathway analysis identified a time-dependent enrichment of biological processes associated with steatogenic or fibrogenic initiating events, cellular functions, and toxicological states. Differentially expressed protein modules were consistent with the observed histology, placing physiologically linked protein networks into context of the disease process. This study demonstrates the potential for protein modules to provide mechanistic links between initiating events and histopathological outcomes.