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A feeding trial was conducted in a recirculation aquaculture system (RAS) to test the growth of juvenile Atlantic salmon (Salmo salar). A standard salmon diet (Control) was used as the template for two experimental diets that contained a combination of Black Soldier Fly (Hermetia illucens) larvae (BSFL) defatted meal (EnviroMeal) and fermented soy protein (MEPRO®). The two ingredients were combined to replace fish meal by 50 or 100% (MEP/Meal 50 and MEP/Meal 100) in the experimental diets. At the 12-week trial conclusion, all growth parameters were similar among the three treatments. The diet containing no fish meal, MEP/Meal 100, demonstrated slightly higher numeric growth performance compared to the Control and MEP/Meal 50 treatment. Similarly, a histological analysis of distal intestines and organosomatic indices showed no significant difference among treatments. All intestinal samples were healthy in appearance showing no apparent enteritis. The results of this study show a combination of fermented soy and BSFL meal may be a viable option in sustainable diets for commercial Atlantic salmon production.

Congenital disorders resulting in pathological protein deficiencies are most often treated postnatally with protein or enzyme replacement therapies. However, treatment of these disorders in utero before irreversible disease onset could significantly minimize disease burden, morbidity, and mortality. One possible strategy for the prenatal treatment of congenital disorders is in utero delivery of messenger RNA (mRNA). mRNA is a nucleic acid therapeutic that has previously been investigated as a platform for protein replacement therapies and gene editing technologies. While viral vectors have been explored to induce intracellular expression of mRNA, they are limited in their clinical application due to risks associated with immunogenicity and genomic integration. As an alternative to viral vectors, safe and efficient in utero mRNA delivery can be achieved using ionizable lipid nanoparticles (LNPs). While LNPs have demonstrated potent in vivo mRNA delivery to the liver following intravenous administration, intra-amniotic delivery has the potential to deliver mRNA to cells and tissues beyond those in the liver, such as in the skin, lung, and digestive tract. However, LNP stability in fetal amniotic fluid and how this stability affects mRNA delivery has not been previously investigated. Here, we engineered a library of LNPs using orthogonal design of experiments (DOE) to evaluate how LNP structure affects their stability in amniotic fluid ex utero and whether a lead candidate identified from these stability measurements enables intra-amniotic mRNA delivery in utero. We used a combination of techniques including dynamic light scattering (DLS), transmission electron microscopy (TEM), and chromatography followed by protein content quantification to screen LNP stability in amniotic fluids. These results identified multiple lead LNP formulations that are highly stable in amniotic fluids ranging from small animals to humans, including mouse, sheep, pig, and human amniotic fluid samples. We then demonstrate that stable LNPs from the ex utero screen in mouse amniotic fluid enabled potent mRNA delivery in primary fetal lung fibroblasts and in utero following intra-amniotic injection in a murine model. This exploration of ex utero stability in amniotic fluids demonstrates a means by which to identify novel LNP formulations for prenatal treatment of congenital disorders via in utero mRNA delivery.

Pacemaker malfunction refers to a failure of the pacemaker to perform the desired cardiac pacemaking function. These malfunctions can occur anywhere within the system from the pulse generator and leads to the electrode-myocardium interface. These failures of sensing, capture, and inadequate pacing can have severe hemodynamic consequences, so rapid identification of specific dysfunction is critical to intervention and stabilization. Emergency providers should be aware of pacemaker components, function, basic programming, and types of malfunctions to adequately assess, stabilize, and disposition patients.

Previous work suggests that acoustic waves at frequencies below human hearing (infrasound) are produced during tornadogenesis and continue through the life of a tornado, which have potential to locate and profile tornadic events and provide a range of improvements relative to current radar capabilities, which are the current primary measurement tool. Confirming and identifying the fluid mechanism responsible for infrasonic production has been impeded by limited availability and quality (propagation-related uncertainty) of tornadic infrasound data. This paper describes an effort to increase the number of measurements and reduce the uncertainty in subsequent analysis by equipping storm chasers and first responders in regular proximity to tornadoes with mobile infrasound measurement capabilities. The study focus is the design, calibration, deployment, and analysis of data collected by a Ground-based Local INfrasound Data Acquisition (GLINDA) system that collects and relays data from an infrasound microphone, GPS receiver, and an inertial measurement unit (IMU). GLINDA has been deployed with storm chasers beginning in May 2020 and has provided continuing real-time automated monitoring of spectrum and peak detection. In analysis of sampled severe weather phenomena, the signal measured from an EFU (EF-Unknown, where EF represents the Enhanced Fujita scale) tornado (Lakin, KS, USA) shows an elevated broadband signal between 10 and 15 Hz. A significant hail event produced no significant increase in infrasound signal despite rotation in the storm. The consistency of these observations with existing fixed-array measurements and real-time tools to reduce measurement uncertainty demonstrates the value of acquiring tornado infrasound observations from mobile on-location systems and introduces a capability for real-time processing and display of mobile infrasonic measurements.

Reduction of phosphorus dichloride 6, supported by the diaryloxyphenyl group (OCO) featuring two bulky phenoxy wingtips, by PMe3, generates a reactive intermediate that behaves as a base-stabilized phosphinidene (OCO)P (5). Warming up a solution of this species in toluene to room temperature results in trimerization to give the isolable cyclic triphosphine [(OCO)P]3, whereas in situ trapping with 2,3-dimethylbutadiene-1,3 afforded a 3,4-dimethylphospholene-3. Investigation of the reduction of 6 by the phosphine PMe3 by NMR led to the observation of a persistent species between -10 °C and 10 °C. DFT study of this process suggest that this compound cannot be the proposed phosphinidene 5, and is more likely the disphosphine (OCO)ClP-PCl(OCO) (12). Attempted reduction of 5 by the bulky carbene IPr resulted in unusual electrophilic substitution in the carbene olefin backbone by the chlorophosphinyl group.

In utero base editing has the potential to correct disease-causing mutations before the onset of pathology. Mucopolysaccharidosis type I (MPS-IH, Hurler syndrome) is a lysosomal storage disease (LSD) affecting multiple organs, often leading to early postnatal cardiopulmonary demise. We assessed in utero adeno-associated virus serotype 9 (AAV9) delivery of an adenine base editor (ABE) targeting the Idua G→A (W392X) mutation in the MPS-IH mouse, corresponding to the common IDUA G→A (W402X) mutation in MPS-IH patients. Here we show efficient long-term W392X correction in hepatocytes and cardiomyocytes and low-level editing in the brain. In utero editing was associated with improved survival and amelioration of metabolic, musculoskeletal, and cardiac disease. This proof-of-concept study demonstrates the possibility of efficiently performing therapeutic base editing in multiple organs before birth via a clinically relevant delivery mechanism, highlighting the potential of this approach for MPS-IH and other genetic diseases., Lysosomal storage diseases like mucopolysaccharidosis type I (MPS I) cause pathology before birth and result in early morbidity and mortality. Here, the authors show that in utero base editing mediates multi-organ phenotypic and survival benefits in a mouse model recapitulating a common human MPSI mutation.

Animals with elodont dentition and unfused mandible symphyses are hypothesized to have symmetric incisor morphology. Since these animals maintain their teeth by gnawing, they may provide physiologic feedback on mechanical function when unilateral mandible defects are created that manifest as ipsilateral changes in tooth structure. This defect model would potentially generate important information on the functional/mechanical properties of implants. Rats’ and rabbits’ mandibles and teeth are analyzed with µCT at baseline and post-intervention (n = 8 for each). Baseline incisors were compared. In a unilateral mandible pilot study, defects—ranging from critical size defect to complete ramus osteotomies—were created to assess effect on dentition (rats, n = 7, rabbits, n = 6). Within 90% confidence intervals, animals showed no baseline left/right differences in their incisors. There are apparent dental changes associated with unilateral defect type and location. Thus, at baseline, animals exhibit statistically significant incisor symmetry and there is an apparent relationship between mandible defect and incisor growth. The baseline symmetry proven here sets the stage to study the degree to which hemi-mandible destabilizing procedures result in measurable &amp, reproducible disruption of dental asymmetry. In a validated model, an implant designed to function under load that prevents incisor asymmetry would provide supporting evidence that the implant has clinically useful load-bearing function.

Link prediction in artificial intelligence is used to identify missing links or derive future relationships that can occur in complex networks. A link prediction model was developed using the complex heterogeneous biomedical knowledge graph, SemNet, to predict missing links in biomedical literature for drug discovery. A web application visualized knowledge graph embeddings and link prediction results using TransE, CompleX, and RotatE based methods. The link prediction model achieved up to 0.44 hits@10 on the entity prediction tasks. The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as COVID-19, served as a case study to demonstrate the efficacy of link prediction modeling for drug discovery. The link prediction algorithm guided identification and ranking of repurposed drug candidates for SARS-CoV-2 primarily by text mining biomedical literature from previous coronaviruses, including SARS and middle east respiratory syndrome (MERS). Repurposed drugs included potential primary SARS-CoV-2 treatment, adjunctive therapies, or therapeutics to treat side effects. The link prediction accuracy for nodes ranked highly for SARS coronavirus was 0.875 as calculated by human in the loop validation on existing COVID-19 specific data sets. Drug classes predicted as highly ranked include anti-inflammatory, nucleoside analogs, protease inhibitors, antimalarials, envelope proteins, and glycoproteins. Examples of highly ranked predicted links to SARS-CoV-2: human leukocyte interferon, recombinant interferon-gamma, cyclosporine, antiviral therapy, zidovudine, chloroquine, vaccination, methotrexate, artemisinin, alkaloids, glycyrrhizic acid, quinine, flavonoids, amprenavir, suramin, complement system proteins, fluoroquinolones, bone marrow transplantation, albuterol, ciprofloxacin, quinolone antibacterial agents, and hydroxymethylglutaryl-CoA reductase inhibitors. Approximately 40% of identified drugs were not previously connected to SARS, such as edetic acid or biotin. In summary, link prediction can effectively suggest repurposed drugs for emergent diseases.

Tyrosine kinase inhibitors (TKIs) are the frontline therapy for BCR-ABL (Ph+) chronic myeloid leukemia (CML). A systematic meta-analysis of 43 peer-reviewed studies with 10,769 CML patients compared the incidence of gastrointestinal adverse events (GI AEs) in a large heterogeneous CML population as a function of TKI type. Incidence and severity of nausea, vomiting, and diarrhea were assessed for imatinib, dasatinib, bosutinib, and nilotinib. Examination of combined TKI average GI AE incidence found diarrhea most prevalent (22.5%), followed by nausea (20.6%), and vomiting (12.9%). Other TKI GI AEs included constipation (9.2%), abdominal pain (7.6%), gastrointestinal hemorrhage (3.5%), and pancreatitis (2.2%). Mean GI AE incidence was significantly different between TKIs (p &lt, 0.001): bosutinib (52.9%), imatinib (24.2%), dasatinib (20.4%), and nilotinib (9.1%). Diarrhea was the most prevalent GI AE with bosutinib (79.2%) and dasatinib (28.1%), whereas nausea was most prevalent with imatinib (33.0%) and nilotinib (13.2%). Incidence of grade 3 or 4 severe GI AEs was ≤3% except severe diarrhea with bosutinib (9.5%). Unsupervised clustering revealed treatment efficacy measured by the complete cytogenetic response, major molecular response, and overall survival is driven most by disease severity, not TKI type. For patients with chronic phase CML without resistance, optimal TKI selection should consider TKI AE profile, comorbidities, and lifestyle.

It is often difficult to distinguish morphologically between closely related species of fleas (Siphonaptera). Morphological identification of fleas often requires microscopic examination of internal structures in specimens cleared using caustic solutions. This process degrades DNA and/or inhibits DNA extraction from specimens, which limits molecular-based studies on individual fleas and their microbiomes. Our objective was to distinguish between Oropsylla rupestris (Jordan), Oropsylla tuberculata (Baker), Oropsylla bruneri (Baker), and Oropsylla labis (Jordan & Rothschild) (Ceratophyllidae) using PCR-based single strand conformation polymorphism (SSCP) analyses and DNA sequencing. A 446 bp region of the nuclear 28S ribosomal RNA (rRNA) gene was used as the genetic marker. The results obtained for 36 reference specimens (i.e., fleas that were morphologically identified to species) revealed no intraspecific variation in DNA sequence, whereas the DNA sequences of the four species of Oropsylla differed from one another at two to six nucleotide positions. Each flea species also had a unique SSCP banding pattern. SSCP analyses were then used to identify another 84 fleas that had not been identified morphologically. DNA sequencing data confirmed the species identity of fleas subjected to SSCP. This demonstrates that PCR-SSCP combined with DNA sequencing of the 28S rRNA gene is a very effective approach for the delineation of four closely related species of flea.

Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. Here we develop and validate a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyze whole genome sequencing data for1,000 cell-free DNA samples from cancer patients and healthy controls using a bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.

Adequate silicon nutrition in plants has shown positive effects on the growth and yield of the crop and physico-chemical properties of the soil. Hence, this study was initiated to survey the plant-...

Lipid nanoparticles deliver mRNA to mouse fetuses, which may ultimately enable in utero therapy to treat fetal genetic diseases., Clinical advances enable the prenatal diagnosis of genetic diseases that are candidates for gene and enzyme therapies such as messenger RNA (mRNA)–mediated protein replacement. Prenatal mRNA therapies can treat disease before the onset of irreversible pathology with high therapeutic efficacy and safety due to the small fetal size, immature immune system, and abundance of progenitor cells. However, the development of nonviral platforms for prenatal delivery is nascent. We developed a library of ionizable lipid nanoparticles (LNPs) for in utero mRNA delivery to mouse fetuses. We screened LNPs for luciferase mRNA delivery and identified formulations that accumulate within fetal livers, lungs, and intestines with higher efficiency and safety compared to benchmark delivery systems, DLin-MC3-DMA and jetPEI. We demonstrate that LNPs can deliver mRNAs to induce hepatic production of therapeutic secreted proteins. These LNPs may provide a platform for in utero mRNA delivery for protein replacement and gene editing.

BackgroundBlood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion of cfDNA derived from tumor tissue in early-stage disease. A machine learning approach to discover signatures in cfDNA, potentially reflective of both tumor and non-tumor contributions, may represent a promising direction for the early detection of cancer.MethodsWhole-genome sequencing was performed on cfDNA extracted from plasma samples (N=546 colorectal cancer and 271 non-cancer controls). Reads aligning to protein-coding gene bodies were extracted, and read counts were normalized. cfDNA tumor fraction was estimated using IchorCNA. Machine learning models were trained using k-fold cross-validation and confounder-based cross-validation to assess generalization performance.ResultsIn a colorectal cancer cohort heavily weighted towards early-stage cancer (80% stage I/II), we achieved a mean AUC of 0.92 (95% CI 0.91-0.93) with a mean sensitivity of 85% (95% CI 83-86%) at 85% specificity. Sensitivity generally increased with tumor stage and increasing tumor fraction. Stratification by age, sequencing batch, and institution demonstrated the impact of these confounders and provided a more accurate assessment of generalization performance.ConclusionsA machine learning approach using cfDNA achieved high sensitivity and specificity in a large, predominantly early-stage, colorectal cancer cohort. The possibility of systematic technical and institution-specific biases warrants similar confounder analyses in other studies. Prospective validation of this machine learning method and evaluation of a multi-analyte approach are underway.

BACKGROUND We previously showed that the supraorbital ethmoid cell (SOEC) is a reliable landmark for identifying the anterior ethmoid artery (AEA). Recent data have suggested that Keros classification is also a dependable predictor. We aim to characterize the location of the AEA and its relation to the skull base in patients with and without SOEC using the Keros classification. METHODS Retrospective radiographic evaluation of computed tomography (CT) scans of 76 patients (40 with SOEC, 36 without) was conducted. Distance of AEA from skull base and prevalence of AEA outside of the skull base were measured on each side and compared between groups using the 2-sample t test and χ2 test, respectively. Subgroup analysis was carried out based on the Keros classification. RESULTS Mean distance of AEA from the skull base was 1.32 ± 1.5 mm in patients with SOEC and 0.47 ± 1.08 mm in those without (p < 0.001). Prevalence of AEA outside of the skull base was 53.8% in those with SOEC and 18.1% in those without (p < 0.001). Comparing patients with SOEC to those without, AEA was found below the skull base in 30% vs 0% of cases with Keros type 1 (p = 0.45), 58% vs 14.5% with Keros type 2 (p < 0.001), and 60% vs 50% with Keros type 3 (p = 0.72). CONCLUSION The presence of SOEC is associated with a higher prevalence of the AEA coursing below the level of the skull base in all Keros types, thus placing the artery at greater risk for injury. Careful surgical planning is needed to avoid potential orbital complications.

An eleven amino acid ribosomal peptide was shown to completely neutralize Western Diamondback Rattlesnake (Crotalus atrox) venom in mice when a lethal dose of the venom was pre-incubated with the peptide prior to intravenous injection. We have expressed the peptide as a concatenated chain of peptides and cleaved them apart from an immobilized metal affinity column using a protease. After ultrafiltration steps, the mixture was shown to partially neutralize rattlesnake venom in mice. Preliminary experiments are described here that suggest a potential life-saving therapy could be developed. To date, no recombinant therapies targeting cytotoxic envenomation have been reported. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:81-86, 2017.

Recent experimental evidence suggests that, during tornadogenesis and through the life a tornado, acoustic waves at frequencies below human hearing (infrasound) are produced. To date, acoustic data required to identify the fluid mechanism responsible for this infrasound has been limited—often gathered by large fixed installations. The design and deployment of a mobile Ground-based Local Infrasound Data Acquisition (GLINDA) system was completed at Oklahoma State University to expand the number of samples and enable close-range measurements which would mitigate the measurement uncertainty associated with long distance atmospheric propagation. GLINDA has been deployed alongside Oklahoma-based media storm chasers since May 2020 and has already returned data over multiple severe weather events, including tornadic measurements acquired with GLINDA on 22 May 2020 in Lakin, Kansas. The GLINDA-equipped storm chaser vehicle can additionally provide acoustic data on other weather events such as wildfires and winter weather storms as the vehicle is appropriate for sustained, close observation of these environments. This presentation will cover system design, measurement capabilities, and acoustic production by select weather phenomenon.

Deregulation of transcription factors (TFs) is an important driver of tumorigenesis. We developed and validated a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyzed whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a newly developed bioinformatics pipeline that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observed patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of early detection of colorectal carcinomas. Our approach for mapping tumor-specific transcription factor bindingin vivobased on blood samples makes a key part of the noncoding genome amenable to clinical analysis.

The frequency-dependent complex impedance of an atomic force microscope photodetector is measured. The inverse problem is solved obtaining the voltage that would have been collected with a hypothetical, perfectly flat-frequency-response photodetector from the experimentally available voltage. This information is used to study the distortion that the true input signal undergoes as it passes through the photodetector on the way to becoming the experimentally measured output signal. It is found that signals with features of interest shorter than 10 μs render noticeable differences between the true and measured raw voltages and forces. Signals with features shorter than 1 μs produce experimentally measured force curves that deviate substantially from the true force curves. A method is proposed for correcting the measured raw voltage signal.

Field studies were established on the alluvial floodplain soils in Louisiana, from 2013 to 2015, to evaluate the effect of silicate slag applications on productivity of wheat (Triticum aestivum), under sufficient and high nitrogen (N) application rates. Treatments were arranged in a randomized complete block design, with four replications consisting of twelve treatments: a factorial combination of two N (101 and 145 kg N ha−1) and five silicate slag rates (0, 1, 2, 4.5, and 9 Mg ha−1), and two control plots (with and without lime). Nitrogen had a greater impact on wheat productivity than silicate slag application. Wheat grain yield reached over 7000 kg ha−1 with applications of 145 kg N, and 9 Mg silicate slag per ha for soil having Si level

The ability to use a blood sample to determine the transcriptional state of cells that are releasing DNA into the bloodstream of a patient may be helpful in a variety of clinical applications. Here we present a case study of a gene expression prediction model that uses cell-free DNA (cfDNA) fragment coverage data generated by high-throughput sequencing to predict which genes are highly or lowly expressed in the cells contributing to that cfDNA. We evaluated a number of models, including a convolutional neural network that takes cfDNA fragment information (the density of both fragment midpoint and length by genomic position) over a transcription start site (TSS) as input, and outputs a predicted probability of whether that gene is highly expressed in cfDNA-producing cells. When we trained the convolutional model on a set of 554 genes with TSSs that were either constitutively expressed or unexpressed across leukocyte samples from the NIH Roadmap Epigenome Mapping Consortium, we achieved ~0.97 AUC in cross validation. With other models and splits of the data, we observed AUCs ranging from 0.95 to 0.99 on this gene-expression task. Next, we were interested in whether this trained model could answer specific clinical questions. For example, we hypothesized that we should see an increased influence of colon gene expression profiles in colorectal cancer patients with a higher fraction of circulating tumor DNA. To test this hypothesis, we applied our models to a set of genes with colon-specific expression, which generated a list of probabilities of each gene being expressed in each sample. We then applied simple models on the these lists of probabilities to predict whether a patient had CRC or was healthy. This yielded cross validation AUCs between 0.85 and 0.95 across many of the models we tested in differentiating healthy patients from colorectal cancer patients with tumor fraction over 5%. These results suggest a path forward for modeling transcriptional states using cfDNA sequencing data, which will enable greater insights from cfDNA that could augment those provided by other analytes. Citation Format: John A. St John, Erik Gafni, Brandon White, Ajay Kannan, Loren Hansen, Artur Jaroszewicz, Anshul Kundaje, Nathan Boley. Predicting gene expression from plasma cell-free DNA using both the fragment length and fragment position [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4349.