Search

Abstract Background Chromodomain helicase DNA-binding protein 8 (Chd8) is a high-confidence risk gene for autism spectrum disorder (ASD). However, how Chd8 haploinsufficiency impairs gene expression in the brain and impacts behavior at different stages of life is unknown. Methods We generated a mutant mouse line with an ASD-linked loss-of-function mutation in Chd8 (V986*; stop codon mutation). We examined the behavior of Chd8 mutant mice along with transcriptional changes in the cerebral cortex as a function of age, with a focus on one embryonic (E14.5) and three postnatal ages (1, 6, and 12 months). Results Chd8 V986*/+ mutant mice displayed macrocephaly, reduced rearing responses and reduced center time in the open field, and enhanced social novelty preference. Behavioral phenotypes were more evident in Chd8 V986*/+ mutant mice at 1 year of age. Pup survival was reduced in wild-type x Chd8 V986*/+ crosses when the mutant parent was female. Transcriptomic analyses indicated that pathways associated with synaptic and neuronal projections and sodium channel activity were reduced in the cortex of embryonic Chd8 V986*/+ mice and then equalized relative to wild-type mice in the postnatal period. At 12 months of age, expression of genes associated with endoplasmic reticulum (ER) stress, chaperone-mediated protein folding, and the unfolded protein response (UPR) were reduced in Chd8 V986*/+ mice, whereas genes associated with the c-MET signaling pathway were increased in expression. Limitations It is unclear whether the transcriptional changes observed with age in Chd8 V986*/+ mice reflect a direct effect of CHD8-regulated gene expression, or if CHD8 indirectly affects the expression of UPR/ER stress genes in adult mice as a consequence of neurodevelopmental abnormalities. Conclusions Collectively, these data suggest that UPR/ER stress pathways are reduced in the cerebral cortex of aged Chd8 V986*/+ mice. Our study uncovers neurodevelopmental and age-related phenotypes in Chd8 V986*/+ mice and highlights the importance of controlling for age when studying Chd8 haploinsufficient mice.

Abstract Background How the brain develops accurate models of the external world and generates appropriate behavioral responses is a vital question of widespread multidisciplinary interest. It is increasingly understood that brain signal variability—posited to enhance perception, facilitate flexible cognitive representations, and improve behavioral outcomes—plays an important role in neural and cognitive development. The ability to perceive, interpret, and respond to complex and dynamic social information is particularly critical for the development of adaptive learning and behavior. Social perception relies on oxytocin-regulated neural networks that emerge early in development. Methods We tested the hypothesis that individual differences in the endogenous oxytocinergic system early in life may influence social behavioral outcomes by regulating variability in brain signaling during social perception. In study 1, 55 infants provided a saliva sample at 5 months of age for analysis of individual differences in the oxytocinergic system and underwent electroencephalography (EEG) while listening to human vocalizations at 8 months of age for the assessment of brain signal variability. Infant behavior was assessed via parental report. In study 2, 60 infants provided a saliva sample and underwent EEG while viewing faces and objects and listening to human speech and water sounds at 4 months of age. Infant behavior was assessed via parental report and eye tracking. Results We show in two independent infant samples that increased brain signal entropy during social perception is in part explained by an epigenetic modification to the oxytocin receptor gene (OXTR) and accounts for significant individual differences in social behavior in the first year of life. These results are measure-, context-, and modality-specific: entropy, not standard deviation, links OXTR methylation and infant behavior; entropy evoked during social perception specifically explains social behavior only; and only entropy evoked during social auditory perception predicts infant vocalization behavior. Conclusions Demonstrating these associations in infancy is critical for elucidating the neurobiological mechanisms accounting for individual differences in cognition and behavior relevant to neurodevelopmental disorders. Our results suggest that an epigenetic modification to the oxytocin receptor gene and brain signal entropy are useful indicators of social development and may hold potential diagnostic, therapeutic, and prognostic value.

Abstract Background Increasing evidence suggests a causal relationship between the gut microbiome and psychiatric illnesses. In particular, autism spectrum disorder is associated with gastrointestinal symptoms and alterations in the gut microbiome. Administration of probiotics is a commonly used strategy by caregivers of people with neurodevelopmental illness. However, evidence for successful improvement in gut microbiome and (behavioral) symptoms has been lacking. Results Here, we use a novel ferret model of maternal immune activation to show that high-dose probiotic administration in a placebo-controlled study design causes changes in the gut microbiome in the form of a transient increase in the administered bacterial species. In contrast, we found no differences in baseline microbiome composition or changes induced by probiotic administration between animals exposed in utero to maternal immune activation and control animals. However, the relative presence of several bacterial species correlated with an increased preference for novelty (object and conspecific). Intriguingly, several of the hits in this screen are species that have previously emerged in the literature as being associated with autism and anxiety. Conclusions Together, our results suggest that high-dose probiotic interventions may be beneficial for the adjunct treatment of psychiatric illnesses. Placebo-controlled clinical trials in humans are urgently needed.

Abstract Background Recent advances in kernel-based Deep Learning models have introduced a new era in medical research. Originally designed for pattern recognition and image processing, Deep Learning models are now applied to survival prognosis of cancer patients. Specifically, Deep Learning versions of the Cox proportional hazards models are trained with transcriptomic data to predict survival outcomes in cancer patients. Methods In this study, a broad analysis was performed on TCGA cancers using a variety of Deep Learning-based models, including Cox-nnet, DeepSurv, and a method proposed by our group named AECOX (AutoEncoder with Cox regression network). Concordance index and p-value of the log-rank test are used to evaluate the model performances. Results All models show competitive results across 12 cancer types. The last hidden layers of the Deep Learning approaches are lower dimensional representations of the input data that can be used for feature reduction and visualization. Furthermore, the prognosis performances reveal a negative correlation between model accuracy, overall survival time statistics, and tumor mutation burden (TMB), suggesting an association among overall survival time, TMB, and prognosis prediction accuracy. Conclusions Deep Learning based algorithms demonstrate superior performances than traditional machine learning based models. The cancer prognosis results measured in concordance index are indistinguishable across models while are highly variable across cancers. These findings shedding some light into the relationships between patient characteristics and survival learnability on a pan-cancer level.

Abstract Background Given the vast range of molecular mechanisms giving rise to breast cancer, it is unlikely universal cures exist. However, by providing a more precise prognosis for breast cancer patients through integrative models, treatments can become more individualized, resulting in more successful outcomes. Specifically, we combine gene expression, pseudogene expression, miRNA expression, clinical factors, and pseudogene-gene functional networks to generate these models for breast cancer prognostics. Establishing a LASSO-generated molecular gene signature revealed that the increased expression of genes STXBP5, GALP and LOC387646 indicate a poor prognosis for a breast cancer patient. We also found that increased CTSLP8 and RPS10P20 and decreased HLA-K pseudogene expression indicate poor prognosis for a patient. Perhaps most importantly we identified a pseudogene-gene interaction, GPS2-GPS2P1 (improved prognosis) that is prognostic where neither the gene nor pseudogene alone is prognostic of survival. Besides, miR-3923 was predicted to target GPS2 using miRanda, PicTar, and TargetScan, which imply modules of gene-pseudogene-miRNAs that are potentially functionally related to patient survival. Results In our LASSO-based model, we take into account features including pseudogenes, genes and candidate pseudogene-gene interactions. Key biomarkers were identified from the features. The identification of key biomarkers in combination with significant clinical factors (such as stage and radiation therapy status) should be considered as well, enabling a specific prognostic prediction and future treatment plan for an individual patient. Here we used our PseudoFuN web application to identify the candidate pseudogene-gene interactions as candidate features in our integrative models. We further identified potential miRNAs targeting those features in our models using PseudoFuN as well. From this study, we present an interpretable survival model based on LASSO and decision trees, we also provide a novel feature set which includes pseudogene-gene interaction terms that have been ignored by previous prognostic models. We find that some interaction terms for pseudogenes and genes are significantly prognostic of survival. These interactions are cross-over interactions, where the impact of the gene expression on survival changes with pseudogene expression and vice versa. These may imply more complicated regulation mechanisms than previously understood. Conclusions We recommend these novel feature sets be considered when training other types of prognostic models as well, which may provide more comprehensive insights into personalized treatment decisions.

Abstract Purpose To compare rates of persistent postoperative pain (PPP) after lumbar spine surgery—commonly known as Failed Back Surgery Syndrome—and healthcare costs for instrumented lumbar spinal fusion versus decompression/discectomy. Methods The UK population-based healthcare data from the Hospital Episode Statistics (HES) database from NHS Digital and the Clinical Practice Research Datalink (CPRD) were queried to identify patients with PPP following lumbar spinal surgery. Rates of PPP were calculated by type of surgery (instrumented and non-instrumented). Total healthcare costs associated with the surgery and covering the 24-month period after index hospital discharge were estimated using standard methods for classifying health care encounters into major categories of health care resource utilization (i.e., inpatient hospital stays, outpatient clinic visits, accident and emergency attendances, primary care encounters, and medications prescribed in primary care) and applying the appropriate unit costs (expressed in 2013 GBP). Results Increasing the complexity of surgery with instrumentation was not associated with an increased rate of PPP. However, 2-year healthcare costs following discharge after surgery are significantly higher among patients who underwent instrumented surgery compared with decompression/discectomy. Conclusions Although there is a not insubstantial risk of ongoing pain following spine surgery, with 1-in-5 patients experiencing PPP within 2 years of surgery, the underlying indications for surgical modality and related choice of surgical procedure do not, by itself, appear to be a driving factor.

Abstract Purpose To develop a method for using an intact posterior cruciate ligament (PCL) as a predictor of anterior cruciate ligament (ACL) graft size and examine possible differences in tunnel length based on all‐epiphyseal drilling method. Methods One hundred one patients 5–18 years of age with magnetic resonance imaging (MRI) of the knee at an outpatient pediatric orthopaedic clinic from 2008 to 2020 were included. ACL and PCL coronal, sagittal, and length measurements were made in all patients. Tunnel length measurements were made in patients with open physes. Statistical analyses were performed to evaluate potential associations in patient bony or ligamentous measurements. Results PCL sagittal width and PCL coronal width were statistically significant predictors of ACL sagittal width and ACL coronal width, respectively (p = 0.002, R = 0.304; p = 0.008, R = 0.264). The following equations were developed to calculate ACL coronal and sagittal width measurements from the corresponding measurement on an intact PCL; ACL Coronal Width (mm) = 6.23 + (0.16 x PCL Coronal Width); ACL Sagittal Width (mm) = 5.85 + (0.53 x PCL Sagittal Width). Mean tibial maximum oblique length (27.8 mm) was longer than mean tibial physeal sparing length (24.9 mm). Mean femoral maximum oblique length (36.9 mm) was comparable to mean femoral physeal sparing length (36.1 mm). Both were longer than mean femoral straight lateral length (32.7 mm). Conclusion An intact PCL is a predictor of native ACL size. Tunnel length differs based on chosen drilling method in all‐epiphyseal technique. Level of evidence Diagnostic Level III.

The bright star λ Ser hosts a hot Neptune with a minimum mass of 13.6 M _⊕ and a 15.5 day orbit. It also appears to be a solar analog, with a mean rotation period of 25.8 days and surface differential rotation very similar to the Sun. We aim to characterize the fundamental properties of this system and constrain the evolutionary pathway that led to its present configuration. We detect solar-like oscillations in time series photometry from the Transiting Exoplanet Survey Satellite, and we derive precise asteroseismic properties from detailed modeling. We obtain new spectropolarimetric data, and we use them to reconstruct the large-scale magnetic field morphology. We reanalyze the complete time series of chromospheric activity measurements from the Mount Wilson Observatory, and we present new X-ray and ultraviolet observations from the Chandra and Hubble space telescopes. Finally, we use the updated observational constraints to assess the rotational history of the star and estimate the wind braking torque. We conclude that the remaining uncertainty on the stellar age currently prevents an unambiguous interpretation of the properties of λ Ser, and that the rate of angular momentum loss appears to be higher than for other stars with a similar Rossby number. Future asteroseismic observations may help to improve the precision of the stellar age.

The carbon-to-oxygen (C/O) ratio in an exoplanet atmosphere has been suggested as a potential diagnostic of planet formation. Now that a number of exoplanets have measured C/O ratios, it is possible to examine this diagnostic at a population level. Here, we present an analysis of currently measured C/O ratios of directly imaged and transit/eclipse planets. First, we derive atmospheric parameters for the substellar companion HD 284149 AB b using data taken with the OSIRIS integral field spectrograph at the W.M. Keck Observatory and report two non-detections from our ongoing imaging spectroscopy survey with Keck/OSIRIS. We find an effective temperature of T _eff = 2502 K, with a range of 2291–2624 K, $\mathrm{log}g\,=\,4.52$ , with a range of 4.38–4.91, and [M/H] = 0.37, with a range of 0.10–0.55. We derive a C/O of ${0.59}_{-0.30}^{+0.15}$ for HD 284149 AB b. We add this measurement to the list of C/O ratios for directly imaged planets and compare them with those from a sample of transit/eclipse planets. We also derive the first dynamical mass estimate for HD 284149 AB b, finding a mass of ∼28 M _Jup . There is a trend in C/O ratio with companion mass ( M _Jup ), with a break seen around 4 M _Jup . We run a Kolmogorov–Smirnov and an Anderson–Darling test on planets above and below this mass boundary, and find that they are two distinct populations. This could be additional evidence of two distinct populations possibly having two different formation pathways, with companion mass as an indicator of most likely formation scenario.

While radial velocity surveys have demonstrated that the population of gas giants peaks around 3 au, the most recent high-contrast imaging surveys have only been sensitive to planets beyond ∼10 au. Sensitivity at small angular separations from stars is currently limited by the variability of the point-spread function. We demonstrate how moderate-resolution integral-field spectrographs can detect planets at smaller separations (≲ 0.3“) by detecting the distinct spectral signature of planets compared to the host star. Using OSIRIS ( R ≈ 4000) at the W.M. Keck Observatory, we present the results of a planet search via this methodology around 20 young targets in the Ophiuchus and Taurus star-forming regions. We show that OSIRIS can outperform high-contrast coronagraphic instruments equipped with extreme adaptive optics and non-redundant masking in the 0.05“–0.3“ regime. As a proof of concept, we present the 34 σ detection of a high-contrast M dwarf companion at ≈0.1“ with flux ratio of ≈ 0.92% around the field F2 star HD 148352. We developed an open-source Python package, breads , for the analysis of moderate-resolution integral-field spectroscopy data in which the planet and the host star signal are jointly modeled. The diffracted starlight continuum is forward-modeled using a spline model, which removes the need for prior high-pass filtering or continuum normalization. The code allows for analytic marginalization of linear hyperparameters, which simplifies the posterior sampling of other parameters (e.g., radial velocity, effective temperature). This technique could prove very powerful when applied to integral-field spectrographs such as NIRSpec on the JWST and other upcoming first-light instruments on the future Extremely Large Telescopes.

The HR 2562 system is a rare case where a brown dwarf companion resides in a cleared inner hole of a debris disk, offering invaluable opportunities to study the dynamical interaction between a substellar companion and a dusty disk. We present the first ALMA observation of the system as well as the continued Gemini Planet Imager monitoring of the companion’s orbit with six new epochs from 2016 to 2018. We update the orbital fit, and in combination with absolute astrometry from GAIA, place a 3 σ upper limit of 18.5 M _J on the companion’s mass. To interpret the ALMA observations, we used radiative transfer modeling to determine the disk properties. We find that the disk is well resolved and nearly edge-on. While the misalignment angle between the disk and the orbit is weakly constrained, due to the short orbital arc available, the data strongly support a (near) coplanar geometry for the system. Furthermore, we find that the models that describe the ALMA data best have inner radii that are close to the companion’s semimajor axis. Including a posteriori knowledge of the system’s SED further narrows the constraints on the disk’s inner radius and places it at a location that is in reasonable agreement with (possibly interior to) predictions from existing dynamical models of disk truncation by an interior substellar companion. HR 2562 has the potential over the next few years to become a new test bed for dynamical interaction between a debris disk and a substellar companion.

Abstract Background RNA sequencing technologies have allowed researchers to gain a better understanding of how the transcriptome affects disease. However, sequencing technologies often unintentionally introduce experimental error into RNA sequencing data. To counteract this, normalization methods are standardly applied with the intent of reducing the non-biologically derived variability inherent in transcriptomic measurements. However, the comparative efficacy of the various normalization techniques has not been tested in a standardized manner. Here we propose tests that evaluate numerous normalization techniques and applied them to a large-scale standard data set. These tests comprise a protocol that allows researchers to measure the amount of non-biological variability which is present in any data set after normalization has been performed, a crucial step to assessing the biological validity of data following normalization. Results In this study we present two tests to assess the validity of normalization methods applied to a large-scale data set collected for systematic evaluation purposes. We tested various RNASeq normalization procedures and concluded that transcripts per million (TPM) was the best performing normalization method based on its preservation of biological signal as compared to the other methods tested. Conclusion Normalization is of vital importance to accurately interpret the results of genomic and transcriptomic experiments. More work, however, needs to be performed to optimize normalization methods for RNASeq data. The present effort helps pave the way for more systematic evaluations of normalization methods across different platforms. With our proposed schema researchers can evaluate their own or future normalization methods to further improve the field of RNASeq normalization.

The repressive states of peroxisome proliferator-activated receptor γ (PPARγ) are ill-defined, despite nuclear receptors being a major drug target. Here authors demonstrate multiple structurally distinct repressive states, providing a structural rationale for ligand bias in a nuclear receptor.

Abstract The Chemistry and Camera (ChemCam) instrument on board the Mars Science Laboratory (MSL) rover Curiosity has collected a very large and unique data set of in‐situ spectra and images of Mars since landing in August 2012. More than 800,000 single shot laser‐induced breakdown spectroscopy (LIBS) spectra measured on more than 2,500 individual targets were returned so far by ChemCam. Such a data set is ideally suited for the application of statistical methods for the recognition of patterns that are difficult to observe by humans. In this work, we develop an approach relying on the feature extraction method Non‐Negative Matrix Factorization (NMF) and the repetition of k‐means clustering to classify ChemCam spectra. A strong consistency of the clustering results among the repetitions were found, which allowed us to identify six clusters representing the dominant compositions measured by ChemCam in Gale crater so far. By tracking clusters across the rover traverse from landing to sol 2756, we are able to provide a chemostratigraphic overview of the Gale crater from the ChemCam perspective. Transitions between major geologic groups (such as the Bradbury and the Mt. Sharp groups) are identifiable demonstrating that they are compositionally distinct, consistent with previous work. Compositional differences between their members also appear in the results. Furthermore, a first approach in which a random forest classifier was trained and validated with the obtained cluster assignments, reveals promising results for predicting cluster memberships of new ChemCam LIBS data acquired after sol 2756.

Utilizing optimal control to simulate a model Hamiltonian is an emerging strategy that leverages the intrinsic physics of a device with digital quantum simulation methods. Here we evaluate optimal control for probing the nonequilibrium properties of symmetry-protected topological (SPT) states simulated with superconducting hardware. Assuming a tunable transmon architecture, we cast the evolution of these SPT states as a series of one- and two-site pulse optimization problems that are solved in the presence of leakage constraints. From the generated pulses, we classically simulate the time-dependent melting of the perturbed SPT string order across a six-site model with an average state infidelity of 10^{−3}. The feasibility of these pulses as well as their efficient application indicate that high-fidelity simulations of string order melting are within reach of current quantum computing systems.

Triple-negative breast cancer (TNBC) is an aggressive and highly lethal disease, which warrants the critical need to identify new therapeutic targets. We show that Zinc Fingers and Homeoboxes 2 (ZHX2) is amplified or overexpressed in TNBC cell lines and patients. Functionally, depletion of ZHX2 inhibited TNBC cell growth and invasion in vitro, orthotopic tumor growth, and spontaneous lung metastasis in vivo. Mechanistically, ZHX2 bound with hypoxia-inducible factor (HIF) family members and positively regulated HIF1α activity in TNBC. Integrated ChIP-seq and gene expression profiling demonstrated that ZHX2 co-occupied with HIF1α on transcriptionally active promoters marked by H3K4me3 and H3K27ac, thereby promoting gene expression. Among the identified ZHX2 and HIF1α coregulated genes, overexpression of AP2B1, COX20, KDM3A, or PTGES3L could partially rescue TNBC cell growth defect by ZHX2 depletion, suggested that these downstream targets contribute to the oncogenic role of ZHX2 in an accumulative fashion. Furthermore, multiple residues (R491, R581, and R674) on ZHX2 are important in regulating its phenotype, which correspond with their roles on controlling ZHX2 transcriptional activity in TNBC cells. These studies establish that ZHX2 activates oncogenic HIF1α signaling, therefore serving as a potential therapeutic target for TNBC.

Decommissioning of offshore oil and gas structures is either occurring, or imminent in most regions of the world. Most jurisdictions require that offshore structures be removed for onshore disposal. However, there is growing interest in understanding the ecological and socio-economic benefits of leaving structures in the water. Descriptions of how fish utilize the vertical structure created by wellhead platform jackets (platforms) will provide insights into possible outcomes of decommissioning alternatives, such as full removal, leave in situ, or translocation to a designated reefing site. We surveyed fish assemblages associated with seven platforms and five reference sites located ∼150 km offshore in the central Gulf of Thailand. The platforms spanned the entire water column (∼75 m) and were a mix of three and four legged structures. We used a Remotely Operated Vehicle (ROV) fitted with an underwater stereo video system to quantify the abundance, size, biomass, and economic value of fish associated with the platforms. We recorded 43 species of fish on the platforms and five reference sites with most fishes on platforms categorized as coral-reef or coral-reef-associated species. We observed a strong vertical zonation in the fish assemblage on the platforms. The Regal demoiselle (Neopomacentrus cyanomos) was numerically dominant (75% of all fish observed). We measured 3,933 kg of fish on the platforms with Caranx sexfasciatus accounting for 76.12% of that. We conservatively estimate each platform had a scaled mean biomass of ∼2,927 kg and the fished species had scaled mean economic value of 175,500 Thai Baht per platform. We estimated that the biomass of fish associated with the seven platforms was at least four times higher per unit area than some of the world’s most productive coral reefs.

Before formulating radiopharmaceuticals for injection, it is necessary to remove various impurities via purification. Conventional synthesis methods involve relatively large quantities of reagents, requiring high-resolution and high-capacity chromatographic methods (e.g., semi-preparative radio-HPLC) to ensure adequate purity of the radiopharmaceutical. Due to the use of organic solvents during purification, additional processing is needed to reformulate the radiopharmaceutical into an injectable buffer. Recent developments in microscale radiosynthesis have made it possible to synthesize radiopharmaceuticals with vastly reduced reagent masses, minimizing impurities. This enables purification with lower-capacity methods, such as analytical HPLC, with a reduction of purification time and volume (that shortens downstream re-formulation). Still, the need for a bulky and expensive HPLC system undermines many of the advantages of microfluidics. This study demonstrates the feasibility of using radio-TLC for the purification of radiopharmaceuticals. This technique combines high-performance (high-resolution, high-speed separation) with the advantages of a compact and low-cost setup. A further advantage is that no downstream re-formulation step is needed. Production and purification of clinical scale batches of [18F]PBR-06 and [18F]Fallypride are demonstrated with high yield, purity, and specific activity. Automating this radio-TLC method could provide an attractive solution for the purification step in microscale radiochemistry systems.

Picoliter-scale droplets have many applications in chemistry and biology, such as biomolecule synthesis, drug discovery, nucleic acid quantification, and single cell analysis. However, due to the complicated processes used to fabricate microfluidic channels, most picoliter (pL) droplet generation methods are limited to research in laboratories with cleanroom facilities and complex instrumentation. The purpose of this work is to investigate a method that uses 3D printing to fabricate microfluidic devices that can generate droplets with sizes

The objective of the current study was to evaluate the effect of differing electrical stimulation (ES) voltage levels on beef longissimus muscle tenderness, postmortem temperature, pH decline, and carcass quality. Beef carcasses from 3 commercial beef processing plants (A, B, C) were exposed to 3 varying voltage levels: (1) control (no ES), (2) ES level 1 (ES1; 60 Hz for 17 s each at 16, 20, 24, and 28 V), and (3) ES level 2 (ES2; 60 Hz for 17 s each at 25, 35, 45, and 55 V) prior to chilling. Ninety beef carcasses were selected from each of the 3 plants, and within a carcass, paired sides were randomly assigned to one of 3 ES treatments (n = 60 sides/treatment/plant). The results indicated that ES affected (P < 0.05) muscle pH at 3 h postmortem in 2 of the 3 plants. However, ES did not affect (P > 0.05) pH at the time of grading (postrigor). Although the slice shear force (SSF) values were lower (P < 0.05) for ES steaks compared with controls, voltage did not affect (P > 0.05) SSF values. Variation in SSF was observed among the plants (P < 0.05), with steaks from Plant C having greater (P < 0.05) SSF values compared with steaks from Plants A and B, which exhibited similar (P > 0.05) SSF values. Overall, although ES steaks had lower SSF values compared with control steaks, the lack of difference in postmortem tenderness between ES1 and ES2 voltage settings indicated that the low ES voltages minimally influenced SSF values.

Objectives: Understanding vaccine intentions and attitudes of health professionals is critical as the Pfizer-BioNTech and the Moderna COVID19 vaccines are being administered throughout the United States. This study estimates the level of vaccine hesitancy at a health sciences center in West Texas prior to the distribution of the vaccines. Methods: An analytical cross-sectional study was performed via anonymous Qualtrics survey administered to approximately 4500 faculty, staff, postdoctoral research associates/medical residents, and employees at a multi-campus health sciences university in the United States. Respondents were asked demographic questions and intention to receive the vaccine. Factors associated with the intention to receive a vaccine were determined using logistic regression analysis. Results: A total sample of 2258 subjects were evaluated (50.0% response rate). Among all respondents, 64.6% reported that they would probably or definitely receive the COVID-19 vaccine. Men had higher levels of intention to receive the vaccine (OR = 2.11, 95% CI 1.64-2.71); respondents who indicated yearly influenza vaccines are necessary were also more likely to receive the vaccine (OR = 6.04, 95% CI 4.70-7.75). Eighty-three percent of faculty and 56% of the staff reported intention to receive the vaccine. Respondents who had previously tested positive for COVID-19 reported more interest in receiving the vaccine (58.5% yes vs 41.5% no). Conclusion: In this study, the intention to receive the COVID-19 vaccination at a United States health sciences center falls below the necessary herd immunity estimates. Public health initiatives must be developed to decrease vaccine hesitancy, especially among health professionals.

Restricted Boltzmann Machine (RBM) is an energy-based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained using contrastive divergence (CD). However, training with CD is slow and does not estimate the exact gradient of the log-likelihood cost function. In this work, the model expectation of gradient learning for RBM has been calculated using a quantum annealer (D-Wave 2000Q), where obtaining samples is faster than Markov chain Monte Carlo (MCMC) used in CD. Training and classification results of RBM trained using quantum annealing are compared with the CD-based method. The performance of the two approaches is compared with respect to the classification accuracies, image reconstruction, and log-likelihood results. The classification accuracy results indicate comparable performances of the two methods. Image reconstruction and log-likelihood results show improved performance of the CD-based method. It is shown that the samples obtained from quantum annealer can be used to train an RBM on a 64-bit “bars and stripes” dataset with classification performance similar to an RBM trained with CD. Though training based on CD showed improved learning performance, training using a quantum annealer could be useful as it eliminates computationally expensive MCMC steps of CD.

Genetics are a known contributor to differences in alcohol sensitivity in humans with fetal alcohol spectrum disorders (FASDs) and in animal models. Our study profiled gene expression in gastrulation-stage embryos from two commonly used, genetically similar mouse substrains, C57BL/6J (6J) and C57BL/6NHsd (6N), that differ in alcohol sensitivity. First, we established normal gene expression patterns at three finely resolved time points during gastrulation and developed a web-based interactive tool. Baseline transcriptional differences across strains were associated with immune signaling. Second, we examined the gene networks impacted by alcohol in each strain. Alcohol caused a more pronounced transcriptional effect in the 6J versus 6N mice, matching the increased susceptibility of the 6J mice. The 6J strain exhibited dysregulation of pathways related to cell death, proliferation, morphogenic signaling and craniofacial defects, while the 6N strain showed enrichment of hypoxia and cellular metabolism pathways. These datasets provide insight into the changing transcriptional landscape across mouse gastrulation, establish a valuable resource that enables the discovery of candidate genes that may modify alcohol susceptibility that can be validated in humans, and identify novel pathogenic mechanisms of alcohol. This article has an associated First Person interview with the first author of the paper.

The hydroxylase EgIN2 contributes to triple negative breast cancers. Here, using an enzyme-substrate trapping strategy, the authors identify ASDL as a bona fide substrate of EgIN2 promoting aggressive properties of TNBC via the activation of cMYC signaling.

Abstract Quantum annealing is a promising heuristic method to solve combinatorial optimization problems, and efforts to quantify performance on real-world problems provide insights into how this approach may be best used in practice. We investigate the empirical performance of quantum annealing to solve the Nurse Scheduling Problem (NSP) with hard constraints using the D-Wave 2000Q quantum annealing device. NSP seeks the optimal assignment for a set of nurses to shifts under an accompanying set of constraints on schedule and personnel. After reducing NSP to a novel Ising-type Hamiltonian, we evaluate the solution quality obtained from the D-Wave 2000Q against the constraint requirements as well as the diversity of solutions. For the test problems explored here, our results indicate that quantum annealing recovers satisfying solutions for NSP and suggests the heuristic method is potentially achievable for practical use. Moreover, we observe that solution quality can be greatly improved through the use of reverse annealing, in which it is possible to refine returned results by using the annealing process a second time. We compare the performance of NSP using both forward and reverse annealing methods and describe how this approach might be used in practice.

Abstract To fully utilize the power of single-cell RNA sequencing (scRNA-seq) technologies for identifying cell lineages and bona fide transcriptional signals, it is necessary to combine data from multiple experiments. We present BERMUDA (Batch Effect ReMoval Using Deep Autoencoders), a novel transfer-learning-based method for batch effect correction in scRNA-seq data. BERMUDA effectively combines different batches of scRNA-seq data with vastly different cell population compositions and amplifies biological signals by transferring information among batches. We demonstrate that BERMUDA outperforms existing methods for removing batch effects and distinguishing cell types in multiple simulated and real scRNA-seq datasets.

Summary: Although embryonic brain development and neurodegeneration have received considerable attention, the events that govern postnatal brain maturation are less understood. Here, we identify the miR-29 family to be strikingly induced during the late stages of brain maturation. Brain maturation is associated with a transient, postnatal period of de novo non-CG (CH) DNA methylation mediated by DNMT3A. We examine whether an important function of miR-29 during brain maturation is to restrict the period of CH methylation via its targeting of Dnmt3a. Deletion of miR-29 in the brain, or knockin mutations preventing miR-29 to specifically target Dnmt3a, result in increased DNMT3A expression, higher CH methylation, and repression of genes associated with neuronal activity and neuropsychiatric disorders. These mouse models also develop neurological deficits and premature lethality. Our results identify an essential role for miR-29 in restricting CH methylation in the brain and illustrate the importance of CH methylation regulation for normal brain maturation.

For many-body methods such as MCSCF and CASSCF, in which the number of one-electron orbitals is optimized and independent of the basis set used, there are no problems with using plane-wave basis sets. However, for methods currently used in quantum computing such as select configuration interaction (CI) and coupled cluster (CC) methods, it is necessary to have a virtual space that is able to capture a significant amount of electron-electron correlation in the system. The virtual orbitals in a pseudopotential plane-wave Hartree–Fock calculation, because of Coulomb repulsion, are often scattering states that interact very weakly with the filled orbitals. As a result, very little correlation energy is captured from them. The use of virtual spaces derived from the one-electron operators has also been tried, and while some correlations are captured, the amount is quite low. To overcome these limitations, we have been developing new classes of algorithms to define virtual spaces by optimizing orbitals from small pairwise CI Hamiltonians, which we term as correlation optimized virtual orbitals with the abbreviation COVOs. With these procedures, we have been able to derive virtual spaces, containing only a few orbitals, which are able to capture a significant amount of correlation. The focus in this manuscript is on using these derived basis sets to target full CI (FCI) quality results for H2 on near-term quantum computers. However, the initial results for this approach were promising. We were able to obtain good agreement with FCI/cc-pVTZ results for this system with just 4 virtual orbitals, using both FCI and quantum simulations. The quality of the results using COVOs suggests that it may be possible to use them in other many-body approaches, including coupled cluster and Møller–Plesset perturbation theories, and open up the door to many-body calculations for pseudopotential plane-wave basis set methods.

Midbrain dopaminergic neurons are responsible for several functions in the reward system, control of emotion, motivation, cognition, and motor behavior. A set of well-characterized transcription factors involved in specification, neurogenesis, and neuronal differentiation determines the fate of these neurons and modulates their survival and maintenance postnatally. Identifying novel molecular connections with these factors might, therefore, lead to a better understanding of physiology as well as dysfunction and degeneration of these neurons in Parkinson's disease. To explore the links between developmental pathways and to identify novel linkages, we examined the correlations of phylogenetic profiles of these factors with those of the entire human proteome. Our analysis revealed two distinct evolutionary pathways comprising the early and late developmental factors and new linkages with these developmental cascades. These results suggest an evolutionary scenario for the development of the midbrain and dopaminergic neurons, with potential novel links to the canonical and non-canonical functions of the transcription factors.

The final assembly of planets involves mutual collisions of large similar-sized protoplanets (“giant impacts”), setting the stage for modern geologic and atmospheric processes. However, thermodynamic consequences of impacts in diverse (exo)planetary systems/models are poorly understood. Impact velocity in “self-stirred” systems is proportional to the mass of the colliding bodies ( v _imp ∝ M ^1/3 ), providing a predictable transition to supersonic collisions in roughly Mars-sized bodies. In contrast, nearby larger planets, or migrating gas giants, stir impact velocities, producing supersonic collisions between smaller protoplanets and shifting outcomes to disruption and nonaccretion. Our particle hydrocode simulations suggest that thermodynamic processing can be enhanced in merging collisions more common to calmer dynamical systems due to post-impact processes that scale with the mass of the accreting remnant. Thus, impact heating can involve some contribution from energy scaling, a departure from pure velocity-scaling in cratering scenarios. Consequently, planetary thermal history depends intimately on the initial mass distribution assumptions and dynamical conditions of formation scenarios. In even the gentlest pairwise accretions, sufficiently large bodies feature debris fields dominated by melt and vapor. This likely plays a critical role in the observed diversity of exoplanet systems and certain debris disks. Furthermore, we suggest solar system formation models that involve self-stirred dynamics or only one to a few giant impacts between larger-than-Mars-sized bodies (e.g., “pebble accretion”) are more congruent with the “missing mantle problem” for the main belt, as we demonstrate debris would be predominantly vapor and thus less efficiently retained due to solar radiation pressure effects.

By design, the variational quantum eigensolver (VQE) strives to recover the lowest-energy eigenvalue of a given Hamiltonian by preparing quantum states guided by the variational principle. In practice, the prepared quantum state is indirectly assessed by the value of the associated energy. Novel adaptive derivative-assembled pseudo-trotter (ADAPT) ansatz approaches and recent formal advances now establish a clear connection between the theory of quantum chemistry and the quantum state ansatz used to solve the electronic structure problem. Here we benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves for a few selected diatomic molecules, namely H2, NaH, and KH. Using numerical simulation, we find both methods provide good estimates of the energy and ground state, but only ADAPT-VQE proves to be robust to particularities in optimization methods. Another relevant finding is that gradient-based optimization is overall more economical and delivers superior performance than analogous simulations carried out with gradient-free optimizers. The results also identify small errors in the prepared state fidelity which show an increasing trend with molecular size.

Background: The Papanicolaou smear (Pap smear, Pap test) is one of the most routine screening tests performed in medicine. The development and widespread use of this test has brought a considerable decrease in the incidence of cervical cancer. Unfortunately, this disease process continues to convey significant morbidity and mortality. These persistent phenomena may be the result of inadequate compliance with routine Pap smear screening, in which limited education is thought to play a role, particularly among ethnic minority groups. Methods: A Google search using the phrase “pap smear” was performed and the first fourteen web addresses were analyzed using four standardized readability indices: the Flesh-Kinkaid Grade Level, the Simple Measure of Gobbledygook, the Gunning Fog Index and the Automated Readability Index. The average grade level readability was then compared to the American Medical Association recommendation that health care information should be written at a 5th or 6th-grade reading level (i.e., ages 10-12 years). Results: The average grade-level readability values of the fourteen analyzed sites using the four aforementioned indices were 8.9, 8.8, 11.9, and 8.4, respectively. The mean readability of all four indices was 9.5. Conclusion: The grade-level readability of commonly accessed internet information regarding Pap smears is above the recommendation of the American Medical Association. Health care providers and website authors should be cognizant of this, as it may impact compliance. This is particularly important given that this routine healthcare test is recommended for nearly fifty percent of the world’s population at various points throughout their lifetime.

Massive, irreparable rotator cuff tears are challenging to manage. Often, these tears are not amenable to primary repair and necessitate additional treatment options. This is especially true in patients with absent glenohumeral arthritis in the setting of a massive, irreparable rotator cuff tear. Superior capsular reconstruction (SCR), originally described by Mihata using a fascia lata autograft, has grown in popularity for the treatment of irreparable rotator cuff tears as a salvage option with good clinical outcomes. More recently, SCR techniques have been described using dermal allograft. Biomechanical studies and reported clinical series show promising results, with favorable postoperative clinical outcomes. The procedure, however, may be technically challenging, especially when performed using an all-arthroscopic technique. This article describes an all-arthroscopic technique using a predetermined graft size, unique medial fixation to ease graft passage, and knotless single-row lateral fixation to optimize suture management and efficiency.

Amidst the COVID-19 pandemic, clinicians have been plagued with dilemmas related to the uncertainty about diagnostic testing for the virus. It has become commonplace for a patient under investigation (PUI) to repeatedly test negative but have imaging findings that are consistent with COVID-19. This raises the question of when the treating team should entertain alternative diagnoses. We present such a case to help provide a framework for how to weigh repeatedly negative test results in clinical decision making when there is ongoing concern for COVID-19.

Mercury (Hg) and selenium (Se) are contaminants of concern for fish in the Upper Colorado River Basin (UCRB). We explored Hg and Se in fish tissues (2,324 individuals) collected over 50 years (1962-2011) from the UCRB. Samples include native and non-native fish collected from lotic waterbodies spanning 7 major tributaries to the Colorado River. There was little variation of total mercury (THg) in fish assemblages basin-wide and only 13% (272/1959) of individual fish samples exceeded the fish health benchmark (0.27 μg THg/g ww). Most THg exceedances were observed in the White-Yampa tributary whereas the San Juan had the lowest mean THg concentration. Risks associated with THg are species specific with exceedances dominated by Colorado Pikeminnow (mean = 0.38 and standard error ± 0.08 μg THg/g ww) and Roundtail Chub (0.24 ± 0.06 μg THg/g ww). For Se, 48% (827/1720) of all individuals exceeded the fish health benchmark (5.1 μg Se/g dw). The Gunnison river had the most individual exceedances of the Se benchmark (74%) whereas the Dirty Devil had the fewest. We identified that species of management concern accumulate THg and Se to levels above risk thresholds and that fishes of the White-Yampa (THg) and Gunnison (Se) rivers are at the greatest risk in the UCRB.

The diagnosis of infectious diseases is ineffective when the diagnostic test does not meet one or more of the necessary standards of affordability, accessibility, and accuracy. The World Health Organization further clarifies these standards with a set of criteria that has the acronym ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free and Deliverable to end-users). The advancement of the digital age has led to a revision of the ASSURED criteria to REASSURED: Real-time connectivity, Ease of specimen collection, Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free or simple, and Deliverable to end-users. Many diagnostic tests have been developed that aim to satisfy the REASSURED criteria; however, most of them only detect a single target. With the progression of syndromic infections, coinfections and the current antimicrobial resistance challenges, the need for multiplexed diagnostics is now more important than ever. This review summarizes current diagnostic technologies for multiplexed detection and forecasts which methods have promise for detecting multiple targets and meeting all REASSURED criteria.