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Abstract Hypoxia is a common feature in various pathophysiological contexts, including tumor microenvironment, and IFN-γ is instrumental for anti-tumor immunity. HIF1α has long been known as a primary regulator of cellular adaptive responses to hypoxia, but its role in IFN-γ induction in hypoxic T cells is unknown. Here, we show that the HIF1α-glycolysis axis controls IFN-γ induction in both human and mouse T cells, activated under hypoxia. Specific deletion of HIF1α in T cells (Hif1α –/–) and glycolytic inhibition suppresses IFN-γ induction. Conversely, HIF1α stabilization by hypoxia and VHL deletion in T cells (Vhl –/–) increases IFN-γ production. Hypoxic Hif1α –/– T cells are less able to kill tumor cells in vitro, and tumor-bearing Hif1α –/– mice are not responsive to immune checkpoint blockade (ICB) therapy in vivo. Mechanistically, loss of HIF1α greatly diminishes glycolytic activity in hypoxic T cells, resulting in depleted intracellular acetyl-CoA and attenuated activation-induced cell death (AICD). Restoration of intracellular acetyl-CoA by acetate supplementation re-engages AICD, rescuing IFN-γ production in hypoxic Hif1α –/– T cells and re-sensitizing Hif1α –/– tumor-bearing mice to ICB. In summary, we identify HIF1α-regulated glycolysis as a key metabolic control of IFN-γ production in hypoxic T cells and ICB response.

In 2018/2019, two large Guillain–Barré Syndrome (GBS) outbreaks took place in Peru. Here, we report a comprehensive analysis of biological samples from GBS patients from the 2019 outbreak. We applied metagenomic, microbiologic, and serological analyses to different biological samples collected from GBS patients. Further phenotypic and genomic characterization was conducted on Campylobacter jejuni isolates from GBS samples. Microbiologic and metagenomic analyses revealed several patients with multiple co-infections, yet no common infectious agents were found other than C. jejuni. Four C. jejuni isolates were isolated from rectal swabs. Twenty-one patients had detectable IgG serum antibodies related to C. jejuni, of whom seven had IgM antibodies. Genomic analyses showed that these four strains were clonal (ST2993) and contained the class A lipooligosaccharide biosynthesis locus. These results further support the idea that that C. jejuni is the etiological agent that triggered the GBS outbreak in Peru in 2019 and that the strains are not restricted to Peru, hence could be regarded as a broad public health concern. Furthermore, though we cannot delineate the role played by co-infections in GBS development, results obtained herein highlight metagenomic analysis as a potential new tool for depicting a yet unknown area of research in GBS.

IntroductionSpontaneous control of chronic-phase HIV/SIV viremia is often associated with the expression of specific MHC class I allotypes. HIV/SIV-specific CD8+ cytotoxic T lymphocytes (CTLs) restricted by these MHC class I allotypes appear to be critical for viremic control. Establishment of the elite controller (EC) phenotype is predictable in SIVmac239-infected Indian rhesus macaques (RMs), with approximately 50% of Mamu-B*08+ RMs and 20% of Mamu-B*17+ RMs becoming ECs. Despite extensive characterization of EC-associated CTLs in HIV/SIV-infected individuals, the precise mechanistic basis of elite control remains unknown. Because EC and non-EC viral load trajectories begin diverging by day 14 post-infection, we hypothesized that hyperacute innate immune responses may contribute to viremic control.MethodsTo gain insight into the immunological factors involved in the determination of EC status, we vaccinated 16 Mamu-B*08+ RMs with Vif and Nef to elicit EC-associated CTLs, then subjected these 16 vaccinees and an additional 16 unvaccinated Mamu-B*08+ controls to repeated intrarectal SIVmac239 challenges. We then performed whole-blood transcriptomic analysis of all 32 SIVmac239-infected Mamu-B*08+ RMs and eight SIVmac239-infected Mamu-B*08– RMs during the first 14 days of infection.ResultsVaccination did not provide protection against acquisition, but peak and setpoint viremia were significantly lower in vaccinees relative to controls. We did not identify any meaningful correlations between vaccine-induced CTL parameters and SIVmac239 acquisition rate or chronic-phase viral loads. Ultimately, 13 of 16 vaccinees (81%) and 7 of 16 controls (44%) became ECs (viremia ≤ 10,000 vRNA copies/mL plasma for ≥ 4 weeks). We identified subsets of immunomodulatory genes differentially expressed (DE) between RM groupings based on vaccination status, EC status, and MHC class I genotype. These DE genes function in multiple innate immune processes, including the complement system, cytokine/chemokine signaling, pattern recognition receptors, and interferon-mediated responses.DiscussionA striking difference in the kinetics of differential gene expression among our RM groups suggests that Mamu-B*08-associated elite control is characterized by a robust, rapid innate immune response that quickly resolves. These findings indicate that, despite the association between MHC class I genotype and elite control, innate immune factors in hyperacute SIV infection preceding CTL response development may facilitate the establishment of the EC phenotype.

Current methods for cancer risk assessment are resource-intensive and not feasible for most of the thousands of untested chemicals. In earlier studies, we developed a new approach methodology (NAM) to identify liver tumorigens using gene expression biomarkers and associated tumorigenic activation levels (TALs) after short-term exposures in rats. The biomarkers are used to predict the six most common rodent liver cancer molecular initiating events. In the present study, we wished to confirm that our approach could be used to identify liver tumorigens at only one time point/dose and if the approach could be applied to (targeted) RNA-Seq analyses. Male rats were exposed for 4 days by daily gavage to 15 chemicals at doses with known chronic outcomes and liver transcript profiles were generated using Affymetrix arrays. Our approach had 75% or 85% predictive accuracy using TALs derived from the TG-GATES or DrugMatrix studies, respectively. In a dataset generated from the livers of male rats exposed to 16 chemicals at up to 10 doses for 5 days, we found that our NAM coupled with targeted RNA-Seq (TempO-Seq) could be used to identify tumorigenic chemicals with predictive accuracies of up to 91%. Overall, these results demonstrate that our NAM can be applied to both microarray and (targeted) RNA-Seq data generated from short-term rat exposures to identify chemicals, their doses, and mode of action that would induce liver tumors, one of the most common endpoints in rodent bioassays.

Melioidosis is a potentially severe disease caused by the gram-negative soil-dwelling bacterium called Burkholderia pseudomallei. The true breadth of the distribution of this tropical pathogen is starting to emerge with environmental and clinical isolates frequently characterized in new countries and regions. Even so, isolates, clinical cases, and genetic data from the continent of Africa remain scant. We previously confirmed the presence of B. pseudomallei in the environment of Ghana, unmasking a new area of endemicity for this pathogen. Here, we describe the genetic characteristics of isolates obtained from that environmental survey. Twenty-one isolates were subjected to whole genome sequencing and found to represent three discrete sequence types (ST), one of which was novel, and designated ST2058. Phylogenetic analysis places this novel isolate within a B. pseudomallei clade that includes genomes derived from the Americas, although it is closely related to a sub-clade that includes isolates from Africa. Importantly, phenotypic characterization demonstrates common features including API 20NE profiles and B. pseudomallei CPS to support existing diagnostics, and susceptibility to standard of care antibiotics often used in the clinical management of melioidosis. These findings add to our knowledge about the presence and distribution of B. pseudomallei in Africa and represent the first published genomes out of Ghana.

Infection with either Rickettsia prowazekii or Orientia tsutsugamushi is common, yet diagnostic capabilities are limited due to the short window for positive identification. Until now, although targeted enrichment had been applied to increase sensitivity of sequencing-based detection for various microorganisms, it had not been applied to sequencing of R. prowazekii in clinical samples. Additionally, hybridization-based targeted enrichment strategies had only scarcely been applied to qPCR of any pathogens in clinical samples. Therefore, we tested a targeted enrichment technique as a proof of concept and found that it dramatically reduced the limits of detection of these organisms by both qPCR and high throughput sequencing. The enrichment methodology was first tested in contrived clinical samples with known spiked-in concentrations of R. prowazekii and O. tsutsugamushi DNA. This method was also evaluated using clinical samples, resulting in the simultaneous identification and characterization of O. tsutsugamushi directly from clinical specimens taken from sepsis patients. We demonstrated that the targeted enrichment technique is helpful by lowering the limit of detection, not only when applied to sequencing, but also when applied to qPCR, suggesting the technique could be applied more broadly to include other assays and/or microbes for which there are limited diagnostic or detection modalities.

IntroductionWe sought to determine pre-infection correlates of protection against SARS-CoV-2 post-vaccine inzfections (PVI) acquired during the first Omicron wave in the United States.MethodsSerum and saliva samples from 176 vaccinated adults were collected from October to December of 2021, immediately before the Omicron wave, and assessed for SARS-CoV-2 Spike-specific IgG and IgA binding antibodies (bAb). Sera were also assessed for bAb using commercial assays, and for neutralization activity against several SARS-CoV-2 variants. PVI duration and severity, as well as risk and precautionary behaviors, were assessed by questionnaires.ResultsSerum anti-Spike IgG levels assessed by research assay, neutralization titers against Omicron subvariants, and low home risk scores correlated with protection against PVIs after multivariable regression analysis. Commercial assays did not perform as well as research assay, likely due to their lower dynamic range.DiscussionIn the 32 participants that developed PVI, anti-Spike IgG bAbs correlated with lower disease severity and shorter duration of illness.

Abstract Background Pulmonary exposure to multi-walled carbon nanotubes (MWCNTs) has been reported to exert strong pro-inflammatory and pro-fibrotic adjuvant effects in mouse models of allergic lung disease. However, the molecular mechanisms through which MWCNTs exacerbate allergen-induced lung disease remain to be elucidated. We hypothesized that protease-activated receptor 2 (PAR2), a G-protein coupled receptor previously implicated in the pathogenesis of various diseases including pulmonary fibrosis and asthma, may play an important role in the exacerbation of house dust mite (HDM) allergen-induced lung disease by MWCNTs. Methods Wildtype (WT) male C57BL6 mice and Par2 KO mice were exposed to vehicle, MWCNTs, HDM extract, or both via oropharyngeal aspiration 6 times over a period of 3 weeks and were sacrificed 3-days after the final exposure (day 22). Bronchoalveolar lavage fluid (BALF) was harvested to measure changes in inflammatory cells, total protein, and lactate dehydrogenase (LDH). Lung protein and RNA were assayed for pro-inflammatory or profibrotic mediators, and formalin-fixed lung sections were evaluated for histopathology. Results In both WT and Par2 KO mice, co-exposure to MWCNTs synergistically increased lung inflammation assessed by histopathology, and increased BALF cellularity, primarily eosinophils, as well as BALF total protein and LDH in the presence of relatively low doses of HDM extract that alone produced little, if any, lung inflammation. In addition, both WT and par2 KO mice displayed a similar increase in lung Cc1-11 mRNA, which encodes the eosinophil chemokine CCL-11, after co-exposure to MWCNTs and HDM extract. However, Par2 KO mice displayed significantly less airway fibrosis as determined by quantitative morphometry compared to WT mice after co-exposure to MWCNTs and HDM extract. Accordingly, at both protein and mRNA levels, the pro-fibrotic mediator arginase 1 (ARG-1), was downregulated in Par2 KO mice exposed to MWCNTs and HDM. In contrast, phosphorylation of the pro-inflammatory transcription factor NF-κB and the pro-inflammatory cytokine CXCL-1 was increased in Par2 KO mice exposed to MWCNTs and HDM. Conclusions Our study indicates that PAR2 mediates airway fibrosis but not eosinophilic lung inflammation induced by co-exposure to MWCNTs and HDM allergens.

Background: The purpose of this study was to determine whether cold therapy after the first exercise test influences the physical working capacity at the fatigue threshold (PWCFT) during the second exercise test. We hypothesized that cold therapy would delay the onset of PWCFT for the second exercise test relative to the control visit (i.e., no cold therapy). Methods: Eight healthy college-aged men volunteered for the present study. For each of the two visits, subjects performed incremental, single-leg, knee-extensor ergometer, followed by either resting for 30 min (control visit) or having a cold pack applied for 15 min and then resting for 15 min (experimental visit). Then, the same exercise test was performed. The order of visits (control vs. experimental) was randomized for each subject. The exercise indices and PWCFT were determined for each of the two visits and statistically analyzed using two-way repeated measures analysis of variance. Results: The results indicate no significant (p > 0.05) mean differences for maximal power output, heart rate at end-exercise, and PWCFT between the control and cold therapy visits. Moreover, there were no significant (p > 0.05) mean differences between the first and second exercise workbout within each visit. Conclusions: The findings of this study suggest that cold therapy did not influence neuromuscular fatigue.

Migration patterns are fundamentally linked to the spatio-temporal distributions of prey. How migrating animals can respond to changes in their prey's distribution and abundance remains largely unclear. During the last decade, humpback whales (Megaptera novaeangliae) used specific winter foraging sites in fjords of northern Norway, outside of their main summer foraging season, to feed on herring that started overwintering in the area. We used photographic matching to show that whales sighted during summer in the Barents Sea foraged in northern Norway from late October to February, staying up to three months and showing high inter-annual return rates (up to 82%). The number of identified whales in northern Norway totalled 866 individuals by 2019. Genetic sexing and hormone profiling in both areas demonstrate a female bias in northern Norway and suggest higher proportions of pregnancy in northern Norway. This may indicate that the fjord-based winter feeding is important for pregnant females before migration. Our results suggest that humpback whales can respond to foraging opportunities along their migration pathways, in some cases by continuing their feeding season well into winter. This provides an important reminder to implement dynamic ecosystem management that can account for changes in the spatio-temporal distribution of migrating marine mammals.

Abstract Interdisciplinary teams are on the rise as scientists attempt to address complex environmental issues. While the benefits of team science approaches are clear, researchers often struggle with its implementation, particularly for new team members. The challenges of large projects often weigh on the most vulnerable members of a team: trainees, including undergraduate students, graduate students, and post‐doctoral researchers. Trainees on big projects have to navigate their role on the team, with learning project policies, procedures, and goals, all while also training in key scientific tasks such as co‐authoring papers. To address these challenges, we created and participated in a project‐specific, graduate‐level team science course. The purposes of this course were to: (1) introduce students to the goals of the project, (2) build trainees' understanding of how big projects operate, and (3) allow trainees to explore how their research interests dovetailed with the overall project. Additionally, trainees received training regarding: (1) diversity, equity & inclusion, (2) giving and receiving feedback, and (3) effective communication. Onboarding through the team science course cultivated psychological safety and a collaborative student community across disciplines and institutions. Thus, we recommend a team science course for onboarding students to big projects to help students establish the skills necessary for collaborative research. Project‐based team science classes can benefit student advancement, enhance the productivity of the project, and accelerate the discovery of solutions to ecological issues by building community, establishing a shared project vocabulary, and building a workforce with collaborative skills to better answer ecological research questions.

We carry out three-dimensional computations of the accretion rate onto an object (of size R _sink and mass m ) as it moves through a uniform medium at a subsonic speed v _∞ . The object is treated as a fully absorbing boundary (e.g., a black hole). In contrast to early conjectures, we show that for an accretor with ${R}_{\mathrm{sink}}\ll {R}_{A}=2{Gm}/{v}_{\infty }^{2}$ in a gaseous medium with adiabatic index γ = 5/3, the accretion rate is independent of Mach number and is determined only by m and the gas entropy. Our numerical simulations are conducted using two different numerical schemes via the Athena++ and Arepo hydrodynamics solvers, which reach nearly identical steady-state solutions. We find that pressure gradients generated by the isentropic compression of the flow near the accretor are sufficient to suspend much of the surrounding gas in a near-hydrostatic equilibrium, just as predicted from the spherical Bondi–Hoyle calculation. Indeed, the accretion rates for steady flow match the Bondi–Hoyle rate, and are indicative of isentropic flow for subsonic motion where no shocks occur. We also find that the accretion drag may be predicted using the Safronov number, Θ = R _A / R _sink , and is much less than the dynamical friction for sufficiently small accretors ( R _sink ≪ R _A ).

A patient with a multidrug-resistant bacterial infection was successfully treated in 2016 using phage therapy. Here, the authors sequence the genomes of the therapeutic phages and three bacterial strains isolated before and during treatment, and show that the same mutations conferring phage resistance are found in in vitro-generated mutants and in phage-insensitive strains isolated from the patient.

The growing number of chemicals in the current consumer and industrial markets presents a major challenge for regulatory programs faced with the need to assess the potential risks they pose to human and ecological health. The increasing demand for hazard and risk assessment of chemicals currently exceeds the capacity to produce the toxicity data necessary for regulatory decision making, and the applied data is commonly generated using traditional approaches with animal models that have limited context in terms of human relevance. This scenario provides the opportunity to implement novel, more efficient strategies for risk assessment purposes. This study aims to increase confidence in the implementation of new approach methods in a risk assessment context by using a parallel analysis to identify data gaps in current experimental designs, reveal the limitations of common approaches deriving transcriptomic points of departure, and demonstrate the strengths in using high-throughput transcriptomics (HTTr) to derive practical endpoints. A uniform workflow was applied across six curated gene expression datasets from concentration-response studies containing 117 diverse chemicals, three cell types, and a range of exposure durations, to determine tPODs based on gene expression profiles. After benchmark concentration modeling, a range of approaches was used to determine consistent and reliable tPODs. High-throughput toxicokinetics were employed to translate in vitro tPODs (µM) to human-relevant administered equivalent doses (AEDs, mg/kg-bw/day). The tPODs from most chemicals had AEDs that were lower (i.e., more conservative) than apical PODs in the US EPA CompTox chemical dashboard, suggesting in vitro tPODs would be protective of potential effects on human health. An assessment of multiple data points for single chemicals revealed that longer exposure duration and varied cell culture systems (e.g., 3D vs. 2D) lead to a decreased tPOD value that indicated increased chemical potency. Seven chemicals were flagged as outliers when comparing the ratio of tPOD to traditional POD, thus indicating they require further assessment to better understand their hazard potential. Our findings build confidence in the use of tPODs but also reveal data gaps that must be addressed prior to their adoption to support risk assessment applications.

Abstract Background The advent of high-throughput transcriptomic screening technologies has resulted in a wealth of publicly available gene expression data associated with chemical treatments. From a regulatory perspective, data sets that cover a large chemical space and contain reference chemicals offer utility for the prediction of molecular initiating events associated with chemical exposure. Here, we integrate data from a large compendium of transcriptomic responses to chemical exposure with a comprehensive database of chemical-protein associations to train binary classifiers that predict mechanism(s) of action from transcriptomic responses. First, we linked reference chemicals present in the LINCS L1000 gene expression data collection to chemical identifiers in RefChemDB, a database of chemical-protein interactions. Next, we trained binary classifiers on MCF7 human breast cancer cell line derived gene expression profiles and chemical-protein labels using six classification algorithms to identify optimal analysis parameters. To validate classifier accuracy, we used holdout data sets, training-excluded reference chemicals, and empirical significance testing of null models derived from permuted chemical-protein associations. To identify classifiers that have variable predicting performance across training data derived from different cellular contexts, we trained a separate set of binary classifiers on the PC3 human prostate cancer cell line. Results We trained classifiers using expression data associated with chemical treatments linked to 51 molecular initiating events. This analysis identified and validated 9 high-performing classifiers with empirical p-values lower than 0.05 and internal accuracies ranging from 0.73 to 0.94 and holdout accuracies of 0.68 to 0.92. High-ranking predictions for training-excluded reference chemicals demonstrating that predictive accuracy extends beyond the set of chemicals used in classifier training. To explore differences in classifier performance as a function of training data cellular context, MCF7-trained classifier accuracies were compared to classifiers trained on the PC3 gene expression data for the same molecular initiating events. Conclusions This methodology can offer insight in prioritizing candidate perturbagens of interest for targeted screens. This approach can also help guide the selection of relevant cellular contexts for screening classes of candidate perturbagens using cell line specific model performance.

Yellow Rail (Coturnicops noveboracensis) are a highly specialized wetland obligate bird. They are a species at risk in Canada and very little is known about their abundance in the wetlands of the western boreal forest. Emerging technologies have enabled us to effectively survey for Yellow Rail and other wetland birds in remote areas by using ground-based remote sensors (autonomous recording units; ARUs) to conduct passive acoustic monitoring. We analyzed bird data from the first four years (2013–2016) of an ongoing monitoring program led by the Bioacoustic Unit at the Alberta Biodiversity Monitoring Institute. We developed species abundance models using satellite data from Sentinel-1 and Sentinel-2 processed in Google Earth Engine. We identified covariates from both synthetic aperture radar and optical remote sensing that had strong predictive capacity for this wetland bird (AUC = 0.96). Approximately 1.5% of available wetland habitat in our northeast Alberta study area was predicted to be highly suitable for Yellow Rail.

Abstract When confined within containers or conduits, drops and bubbles migrate to regions of minimum energy by the combined effects of surface tension, surface wetting, system geometry, and initial conditions. Such capillary phenomena are exploited for passive phase separation operations in micro-fluidic devices on earth and macro-fluidic devices aboard spacecraft. Our study focuses on the migration and ejection of large inertial-capillary drops confined between tilted planar hydrophobic substrates (a.k.a., wedges). In our experiments, the brief nearly weightless environment of a 2.1 s drop tower allows for the study of such capillary dominated behavior for up to 10 mL water drops with migration velocities up to 12 cm/s. We control ejection velocities as a function of drop volume, substrate tilt angle, initial confinement, and fluid properties. We then demonstrate how such geometries may be employed as passive no-moving-parts droplet generators for very large drop dynamics investigations. The method is ideal for hand-held non-oscillatory ‘droplet’ generation in low-gravity environments.

Background: As the COVID-19 pandemic began, wellness leadership at a large Mid-west public university anticipated an increase in mental health problems among faculty and staff. A two-part weekly webinar series entitled "Staying Calm and Well in the Midst of the COVID-19 Storm" was launched to assist faculty and staff in coping with stressful issues related to the pandemic and enhancing their well-being. This series provided the university community with evidence-based knowledge, skills, and resources to enhance their ability in taking good self-care. Aim: To assess participant mental health outcomes during the two-part mental health and well-being educational webinar series over time. Methods: A longitudinal outcomes evaluation was conducted. Evaluation data was obtained from the participants via an anonymous post-webinar survey, which included questions from the Patient-Health Questionnaire-4 (PHQ-4) to assess symptoms of anxiety and depression. The first series was conducted over the course of 8 weeks and the second series took place over 7 weeks. Descriptive statistics were used to assess responses to the PHQ-4 over time to evaluate outcomes of the webinar series. An open-ended question also asked participants about the 2 to 3 biggest concerns and worries they had at that moment. Results: The average amount of survey responses received were 1,470.25 (SD = ± 240.3) for Series One and 926.4 (SD = ± 164.3) for Series Two. Ninety-five percent of participants put the skills they learned during both series into practice. When participants reported experiencing anxiety or depressive symptoms, they most frequently reported experiencing them several days a week. The number of participants reporting no depressive or anxiety symptoms increased as the webinar series progressed over time. The types of concerns and worries reported varied across time. Conclusion: The Staying Calm and Well During the COVID-19 Pandemic webinar participants had a reduction in symptoms associated with anxiety and depression after completing the series.

Abstract Background Functional genome annotation is the process of labelling functional genomic regions with descriptive information. Manual curation can produce higher quality genome annotations than fully automated methods. Manual annotation efforts are time-consuming and complex; however, software can help reduce these drawbacks. Results We created Manual Annotation Studio (MAS) to improve the efficiency of the process of manual functional annotation prokaryotic and viral genomes. MAS allows users to upload unannotated genomes, provides an interface to edit and upload annotations, tracks annotation history and progress, and saves data to a relational database. MAS provides users with pertinent information through a simple point and click interface to execute and visualize results for multiple homology search tools (blastp, rpsblast, and HHsearch) against multiple databases (Swiss-Prot, nr, CDD, PDB, and an internally generated database). MAS was designed to accept connections over the local area network (LAN) of a lab or organization so multiple users can access it simultaneously. MAS can take advantage of high-performance computing (HPC) clusters by interfacing with SGE or SLURM and data can be exported from MAS in a variety of formats (FASTA, GenBank, GFF, and excel). Conclusions MAS streamlines and provides structure to manual functional annotation projects. MAS enhances the ability of users to generate, interpret, and compare results from multiple tools. The structure that MAS provides can improve project organization and reduce annotation errors. MAS is ideal for team-based annotation projects because it facilitates collaboration.

A possible undesired outcome of CRISPR-Cas9 germline editing is unwanted karyotype alterations. Here the authors track aberrations through three divisions of embryonic development following Cas9 editing.

The mechanisms underlying the activity of non-receptor tyrosine kinase, TNK1, in cancers are unclear. Here the authors show that MARK mediates 14-3-3 and TNK1 interaction which restrains TNK1 activity, while the release of TNK1 from 14-3-3 leads to TNK1 activation through its interaction with ubiquitin and thus results in TNK1-mediated tumor growth in vivo

The course of neuro-cognitive recovery following anaesthesia and surgery is distinctive and poorly understood. Our objective was to identify patterns of neuro-cognitive recovery of the domains routinely assessed for delirium diagnosis in the post anaesthesia care unit (PACU) and to compare them to the cognitive recovery patterns observed in other studies; thereby aiding in the identification of pathological (high risk) patterns of recovery in the PACU. We also compared which of the currently available tests (3D-CAM, CAM-ICU, and NuDESC) is the best to use in PACU. This was a post hoc secondary analysis of data from the Alpha Max study which involved 200 patients aged over 60 years, scheduled for elective surgery under general anaesthesia lasting more than 2 h. These patients were assessed for delirium at 30 min following arrival in the PACU, if they were adequately arousable (Richmond Agitation Sedation Score ≥ −2). All tests for delirium diagnosis (3D-CAM, CAM-ICU, and NuDESC) and the sub-domains assessed were compared to understand temporal recovery of neurocognitive domains. These data were also analysed to determine the best predictor of PACU delirium. We found the incidence of PACU delirium was 35% (3D-CAM). Individual cognitive domains were affected differently. Few individuals had vigilance deficits (6.5%, n = 10 CAM-ICU) or disorganized thinking (19% CAM-ICU, 27.5% 3D-CAM), in contrast attention deficits were common (72%, n = 144) and most of these patients (89.5%, n = 129) were not sedated (RASS ≥ −2). CAM-ICU (27%) and NuDESC (52.8%) detected fewer cases of PACU delirium compared to 3D-CAM. In conclusion, return of neurocognitive function is a stepwise process; Vigilance and Disorganized Thinking are the earliest cognitive functions to return to baseline and lingering deficits in these domains could indicate an abnormal cognitive recovery. Attention deficits are relatively common at 30 min in the PACU even in individuals who appear to be awake. The 3D CAM is a robust test to check for delirium in the PACU.

Early in the pandemic, in March of 2020, an outbreak of COVID-19 occurred aboard the aircraft carrier USS Theodore Roosevelt (CVN-71), during deployment in the Western Pacific. Out of the crew of 4,779 personnel, 1,331 service members were suspected or confirmed to be infected with SARS-CoV-2. The demographic, epidemiologic, and laboratory findings of service members from subsequent investigations have characterized the outbreak as widespread transmission of virus with relatively mild symptoms and asymptomatic infection among mostly young healthy adults. At the time, there was no available vaccination against COVID-19 and there was very limited knowledge regarding SARS-CoV-2 mutation, dispersal, and transmission patterns among service members in a shipboard environment. Since that time, other shipboard outbreaks from which data can be extracted have occurred, but these later shipboard outbreaks have occurred largely in settings where the majority of the crew were vaccinated, thereby limiting spread of the virus, shortening duration of the outbreaks, and minimizing evolution of the virus within those close quarters settings. On the other hand, since the outbreak on the CVN-71 occurred prior to widespread vaccination, it continued over the course of roughly two months, infecting more than 25% of the crew. In order to better understand genetic variability and potential transmission dynamics of COVID-19 in a shipboard environment of immunologically naïve, healthy individuals, we performed whole-genome sequencing and virus culture from eighteen COVID-19-positive swabs collected over the course of one week. Using the unique variants identified in those genomes, we detected seven discrete groups of individuals within the population aboard CVN-71 infected with viruses of distinct genomic signature. This is in stark contrast to a recent outbreak aboard another U.S. Navy ship with >98% vaccinated crew after a port visit in Reykjavik, Iceland, where the outbreak lasted only approximately 2 weeks and the virus was clonal. Taken together, these results demonstrate the utility of sequencing from complex clinical samples for molecular epidemiology and they also suggest that a high rate of vaccination among a population in close communities may greatly reduce spread, thereby restricting evolution of the virus.

Abstract The omaliine rove beetle genus Phlaeopterus Motschulsky, 1853 contains 22 species. The genus is distributed across northwestern North America and eastern Asia. These beetles occur primarily along the edges of alpine snowfields and streams, habitats that are particularly sensitive to the impacts of climate change. Two species have not been collected since 1979 and 1984, one of which, Phlaeopterus bakerensis Mullen and Campbell, 2018, is a contender for the largest-bodied species among the over 1,600 species of the subfamily Omaliinae. Here, we present the first phylogeny of the genus, using Bayesian and maximum likelihood analyses based on DNA sequences from the mitochondrial gene COI and morphological data. We tested previous taxonomic hypotheses and most were rejected by all three analyses. Phlaeopterus castaneus Casey, 1893 is non-monophyletic based on COI sequences and may have hybridized with P. loganensis Hatch, 1957. We found support for the monophyly of the genus Phlaeopterus. Our analyses suggest the common ancestor of the genus had small-bodied adults (maximum body size under 5 mm) with ocelli. Within this small-bodied radiation of species, ocelli were lost once and there were two separate evolutionary transitions to large-bodied adults. Although all the large-bodied species are snowfield-associated and only 25% of the small-bodied species are, we did not find statistical support for a relationship between large body size and use of snowfield habitats. These findings represent the first modern phylogenetic reconstruction of species-level relationships within the rove beetle subfamily Omaliinae using both morphological and molecular data.

To investigate the impact of experimental interventions on living biological tissue, ex vivo rodent brain slices are often used as a more controllable alternative to a live animal model. However, for meaningful results, the biological sample must be known to be healthy and viable. One of the gold-standard approaches to identifying tissue viability status is to measure the rate of tissue oxygen consumption under specific controlled conditions. Here, we work with thin (400 μm) slices of mouse cortical brain tissue which are sustained by a steady flow of oxygenated artificial cerebralspinal fluid (aCSF) at room temperature. To quantify tissue oxygen consumption (Q), we measure oxygen partial pressure (pO2) as a function of probe depth. The curvature of the obtained parabolic (or parabola-like) pO2 profiles can be used to extract Q, providing one knows the Krogh coefficient Kt, for the tissue. The oxygen trends are well described by a Fick’s law diffusion–consumption model developed by Ivanova and Simeonov, and expressed in terms of ratio (Q/K), being the rate of oxygen consumption in tissue divided by the Krogh coefficient (oxygen diffusivity × oxygen solubility) for tissue. If the fluid immediately adjacent to the tissue can be assumed to be stationary (i.e., nonflowing), one may invoke conservation of oxygen flux K·(∂P/∂x) across the interface to deduce (Kt/Kf), the ratio of Krogh coefficients for tissue and fluid. Using published interpolation formulas for the effect of salt content and temperature on oxygen diffusivity and solubility for pure water, we estimate Kf, the Krogh coefficient for aCSF, and hence deduce the Kt coefficient for tissue. We distinguish experimental uncertainty from natural biological variability by using pairs of repeated profiles at the same tissue location. We report a dimensionless Krogh ratio (Kt/Kf)=0.562±0.088 (mean ± SD), corresponding to a Krogh coefficient Kt=(1.29±0.21)×10−14 mol/(m·s·Pa) for mouse cortical tissue at room temperature, but acknowledge the experimental limitation of being unable to verify that the fluid boundary layer is truly stationary. We compare our results with those reported in the literature, and comment on the challenges and ambiguities caused by the extensive use of ‘biologically convenient’ non-SI units for tissue Krogh coefficient.

Infections with bacteria of the genus Sarcina are associated with gastric diseases of unclear etiology. Here, Owens et al. show that infection with a distinct Sarcina species is strongly associated with a lethal disease that affects sanctuary chimpanzees in Sierra Leone.

Hypoxic-ischaemic brain injury is a major cause of morbidity and mortality internationally. Using an in vitro isolated cortex model, this study investigated the optimal cerebrospinal fluid oxygenation parameters for rescuing metabolically challenged cortical tissue. In particular, we asked whether maximizing oxygen content with oxygen nanobubbles could support improved tissue recovery. Mouse cortical slices were metabolically starved, followed by recovery in artificial cerebrospinal fluid (aCSF) containing different levels of dissolved oxygen ranging from mean(SD) 2(0.5) to 39(1.0) mg/L; with and without oxygen nanobubbles. Tissue recovery was assessed by quantifying and comparing the amplitude, length, high frequency content and event frequency of seizure-like events generated in no-magnesium aCSF at the beginning and end of the protocol. In general, there was improved recovery with increasing oxygen content up to 25–34 mg/L. The outcome of slices recovered in nanobubbled aCSF was no different to conventionally oxygenated slices with similar dissolved oxygen content. Dissolved oxygen content above 34 mg/L afforded no additional benefit. In conclusion, aCSF dissolved oxygen content of approximately 30 mg/L is optimal for cortical tissue recovery from metabolic starvation, which is easily achievable using conventional oxygenation methods. Oxygen in the form of nanobubbles does not appear to be readily available for tissue oxidative processes in this model.

High-throughput transcriptomics has advanced through the introduction of TempO-seq, a targeted alternative to traditional RNA-seq. TempO-seq platforms use 50 nucleotide probes, each specifically designed to target a known transcript, thus allowing for reduced sequencing depth per sample compared with RNA-seq without compromising the accuracy of results. Thus far, studies using the TempO-seq method have relied on existing tools for processing the resulting short read data. However, these tools were originally designed for other data types. While they have been used for processing of early TempO-seq data, they have not been systematically assessed for accuracy or compared to determine an optimal framework for processing and analyzing TempO-seq data. In this work, we re-analyze several publicly available TempO-seq data sets covering a range of experimental designs and use corresponding RNA-seq data sets as a gold standard to rigorously assess accuracy at multiple levels. We compare 6 aligners and 5 normalization methods across various accuracy and performance metrics. Our results demonstrate the overall robust accuracy of the TempO-seq platform, independent of data processing methods. Complex aligners and advanced normalization methods do not appear to have any general advantage over simpler methods when it comes to analyzing TempO-seq data. The reduced complexity of the sequencing space, and the fact that TempO-seq probes are all equal length, appears to reduce the need for elaborate bioinformatic or statistical methods used to address these factors in RNA-seq data.

Despite 50 years of clinical use and experimental endeavor the anesthetic, analgesic, and psychomimetic effects of ketamine remain to be fully elucidated. While NMDA receptor antagonism has been long held as ketamine's fundamental molecular action, interrogation of bespoke ketamine analogs with known absent NMDA binding, yet profound anesthetic and analgesia fingerprints, suggests alternative targets are responsible for these effects. Herein we describe experimental findings utilizing such analogs as probes to explore ketamine-based analgesic molecular targets. We have focused on two-pore potassium leak channels, identifying TWIK channels as a rational target to pursue further. While the totality of ketamine's mechanistic action is yet to be fully determined, these investigations raise the intriguing prospect of separating out analgesia and anesthetic effects from ketamine's undesirable psychomimesis—and development of more specific analgesic medications.

The consumption of cycad (Cycas circinalis) seeds has been linked to the development of Amyotrophic Lateral Sclerosis-Parkinsonism Dementia Complex (ALS-PDC) in humans. ALS-PDC is a clinically variable disease presenting as a combination of symptoms typical of PD and/or ALS. Chronic consumption of β-sitosterol β-D-glucoside (BSSG), a component of the cycad seed, by rats (Rattus norvegicus) has been previously reported to initiate a progressive pathology that develops over several months and manifests as behavioural and histopathological changes that resemble characteristic features of Parkinson’s disease. As part of an independent multi-site validation study, we have tried to replicate and further characterize the BSSG model with a focus on motor function, and associated immunohistochemical markers. Beginning at 3 months of age, male CD® (Sprague Dawley) rats (N = 80) were dosed orally with either a flour pellet or a flour pellet containing BSSG (3 mg) daily (5×/week) for 16 weeks consistent with previous reports of the model. Following BSSG intoxication, separate cohorts of animals (n = 10/treatment) were exposed to a behavioural test battery at 16, 24, 32, or 40 weeks post-initial BSSG feeding. The test battery consisted of the open field test, cylinder test, and ultrasonic vocalization (USV) assessment. No changes in behaviour were observed at any time point. Following behavioural testing, animals were processed for immunohistochemical markers of substantia nigra integrity. Immunohistochemistry of brain tissue revealed no differences in the microglial marker, Iba1, or the dopaminergic integrity marker, tyrosine hydroxylase (TH), in the substantia nigra at any assessment point. The absence of any group differences in behaviour and immunhistochemistry indicates an inability to replicate previous reports. Further investigation into the sources of variability in the model is necessary prior to further utilization of the BSSG model in preclinical studies.

The emergence of SARS-CoV-2 variants complicates efforts to control the COVID-19 pandemic. Increasing genomic surveillance of SARS-CoV-2 is imperative for early detection of emerging variants, to trace the movement of variants, and to monitor effectiveness of countermeasures. Additionally, determining the amount of viable virus present in clinical samples is helpful to better understand the impact these variants have on viral shedding. In this study, we analyzed nasal swab samples collected between March 2020 and early November 2021 from a cohort of United States (U.S.) military personnel and healthcare system beneficiaries stationed worldwide as a part of the Defense Health Agency's (DHA) Global Emerging Infections Surveillance (GEIS) program. SARS-CoV-2 quantitative real time reverse-transcription PCR (qRT-PCR) positive samples were characterized by next-generation sequencing and a subset was analyzed for isolation and quantification of viable virus. Not surprisingly, we found that the Delta variant is the predominant strain circulating among U.S. military personnel beginning in July 2021 and primarily represents cases of vaccine breakthrough infections (VBIs). Among VBIs, we found a 50-fold increase in viable virus in nasal swab samples from Delta variant cases when compared to cases involving other variants. Notably, we found a 40-fold increase in viable virus in nasal swab samples from VBIs involving Delta as compared to unvaccinated personnel infected with other variants prior to the availability of approved vaccines. This study provides important insight about the genomic and virological characterization of SARS-CoV-2 isolates from a unique study population with a global presence.

Objectives:. We assessed the effect of implementing a protocol-directed strategy to determine when patients can be liberated from venovenous extracorporeal membrane oxygenation on extracorporeal membrane oxygenation duration, time to initiation of first sweep-off trial, duration of mechanical ventilation, ICU length of stay, hospital length of stay, and survival to hospital discharge. Design:. Single-center retrospective before and after study. Setting:. The medical ICU at an academic medical center. Patients:. One-hundred eighty patients with acute respiratory distress syndrome managed with venovenous extracorporeal membrane oxygenation at a single institution from 2013 to 2019. Interventions:. In 2016, our institution implemented a daily assessment of readiness for a trial off extracorporeal membrane oxygenation sweep gas (“sweep-off trial”). When patients met prespecified criteria, the respiratory therapist performed a sweep-off trial to determine readiness for discontinuation of venovenous extracorporeal membrane oxygenation. Measurements and Main Results:. Sixty-seven patients were treated before implementation of the sweep-off trial protocol, and 113 patients were treated after implementation. Patients managed using the sweep-off trial protocol had a significantly shorter extracorporeal membrane oxygenation duration (5.5 d [3–11 d] vs 11 d [7–15.5 d]; p < 0.001), time to first sweep-off trial (2.5 d [1–5 d] vs 7.0 d [5–11 d]; p < 0.001), duration of mechanical ventilation (15.0 d [9–31 d] vs 25 d [21–33 d]; p = 0.017), and ICU length of stay (18 d [10–33 d] vs 27.0 d [21–36 d]; p = 0.008). There were no observed differences in hospital length of stay or survival to hospital discharge. Conclusions:. In patients with acute respiratory distress syndrome managed with venovenous extracorporeal membrane oxygenation at our institution, implementation of a daily, respiratory therapist assessment of readiness for a sweep-off trial was associated with a shorter time to first sweep-off trial and shorter duration of extracorporeal membrane oxygenation. Among survivors, the postassessment group had a reduced duration of mechanical ventilation and ICU lengths of stay. There were no observed differences in hospital length of stay or inhospital mortality.

Abstract Background Antibiotic resistance is rising at disturbing rates and contributes to the deaths of millions of people yearly. Antibiotic resistant infections disproportionately affect those with immunocompromising conditions, chronic colonization, and frequent antibiotic use such as transplant patients or those with cystic fibrosis. However, clinicians lack the diagnostic tools to confidently diagnose and treat infections, leading to widespread use of empiric broad spectrum antimicrobials, often for prolonged duration. Case presentation A 22 year-old Caucasian female with cystic fibrosis received a bilateral orthotopic lung transplantation 5 months prior to the index hospitalization. She underwent routine surveillance bronchoscopy and was admitted for post-procedure fever. A clear cause of infection was not identified by routine methods. Imaging and bronchoscopic lung biopsy did not identify an infectious agent or rejection. She was treated with a prolonged course of antimicrobials targeting known colonizing organisms from prior bronchoalveolar lavage cultures (Pseudomonas, Staphylococcus aureus, and Aspergillus). However, we identified Stenotrophomonas maltophilia in two independent whole blood samples using direct-pathogen sequencing, which was not identified by other methods. Conclusions This case represents a common clinical conundrum: identification of infection in a high-risk, complex patient. Here, direct-pathogen sequencing identified a pathogen that would not otherwise have been identified by common techniques. Had results been clinically available, treatment could have been customized, avoiding a prolonged course of broad spectrum antimicrobials that would only exacerbate resistance. Direct-pathogen sequencing is poised to fill a diagnostic gap for pathogen identification, allowing early identification and customization of treatment in a culture-independent, pathogen-agnostic manner.

Abstract Objective The bone morphogenetic protein (BMP) signaling pathway comprises the largest subdivision of the transforming growth factor (TGFβ) superfamily. BMP signaling plays essential roles in both embryonic development and postnatal tissue homeostasis. Dysregulated BMP signaling underlies human pathologies ranging from pulmonary arterial hypertension to heterotopic ossification. Thus, understanding the basic mechanisms and regulation of BMP signaling may yield translational opportunities. Unfortunately, limited tools are available to evaluate this pathway, and genetic approaches are frequently confounded by developmental requirements or ability of pathway components to compensate for one another. Specific inhibitors for type 2 receptors are poorly represented. Thus, we sought to identify and validate an antibody that neutralizes the ligand-binding function of BMP receptor type 2 (BMPR2) extracellular domain (ECD). Results Using a modified, cell-free immunoprecipitation assay, we examined the neutralizing ability of the mouse monoclonal antibody 3F6 and found a dose-dependent inhibition of BMPR2-ECD ligand-binding. Consistent with this, 3F6 blocks endogenous BMPR2 function in the BMP-responsive cell line HEK293T. The specificity of 3F6 action was confirmed by demonstrating that this antibody has no effect on BMP-responsiveness in HEK293T cells in which BMPR2 expression is knocked-down. Our results provide important proof-of-concept data for future studies interrogating BMPR2 function.

Abstract Background Ketamine ester analogs, SN 35210 and SN 35563, demonstrate different pharmacological profiles to ketamine in animal models. Both confer hypnosis with predictably rapid offset yet, paradoxically, SN35563 induces a prolonged anti-nociceptive state. To explore underlying mechanisms, broad transcriptome changes were measured and compared across four relevant target regions of the rat brain. Results SN 35563 produced large-scale alteration of gene expression in the Basolateral Amygdala (BLA) and Paraventricular Nucleus of the Thalamus (PVT), in excess of 10x that induced by ketamine and SN 35210. A smaller and quantitatively similar number of gene changes were observed in the Insula (INS) and Nucleus Accumbens (ACB) for all three agents. In the BLA and PVT, SN 35563 caused enrichment for gene pathways related to the function and structure of glutamatergic synapses in respect to: release of neurotransmitter, configuration of postsynaptic AMPA receptors, and the underlying cytoskeletal scaffolding and alignment. Conclusion The analgesic ketamine ester analog SN 35563 induces profound large-scale changes in gene expression in key pain-related brain regions reflecting its unique prolonged pharmacodynamic profile.

The global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted the disparity between developed and developing countries for infectious disease surveillance and the sequencing of pathogen genomes. The majority of SARS-CoV-2 sequences published are from Europe, North America, and Asia. Between April 2020 and January 2022, 795 SARS-CoV-2-positive nares swabs from individuals in the U.S. Navy installation Camp Lemonnier, Djibouti, were collected, sequenced, and analyzed. In this study, we described the results of genomic sequencing and analysis for 589 samples, the first published viral sequences for Djibouti, including 196 cases of vaccine breakthrough infections. This study contributes to the knowledge base of circulating SARS-CoV-2 lineages in the under-sampled country of Djibouti, where only 716 total genome sequences are available at time of publication. Our analysis resulted in the detection of circulating variants of concern, mutations of interest in lineages in which those mutations are not common, and emerging spike mutations.

Coronaviruses represent a diverse family of enveloped positive-sense single stranded RNA viruses. COVID-19, caused by Severe Acute Respiratory Syndrome Coronavirus-2, is a highly contagious respiratory disease transmissible mainly via close contact and respiratory droplets which can result in severe, life-threatening respiratory pathologies. It is understood that glutathione, a naturally occurring antioxidant known for its role in immune response and cellular detoxification, is the target of various proinflammatory cytokines and transcription factors resulting in the infection, replication, and production of reactive oxygen species. This leads to more severe symptoms of COVID-19 and increased susceptibility to other illnesses such as tuberculosis. The emergence of vaccines against COVID-19, usage of monoclonal antibodies as treatments for infection, and implementation of pharmaceutical drugs have been effective methods for preventing and treating symptoms. However, with the mutating nature of the virus, other treatment modalities have been in research. With its role in antiviral defense and immune response, glutathione has been heavily explored in regard to COVID-19. Glutathione has demonstrated protective effects on inflammation and downregulation of reactive oxygen species, thereby resulting in less severe symptoms of COVID-19 infection and warranting the discussion of glutathione as a treatment mechanism.

Prostate cancer is one of the most common malignant tumors in men. Initially, it is androgen-dependent, but it eventually develops into castration-resistant prostate cancer (CRPC), which is incurable with current androgen receptor signaling target therapy and chemotherapy. Immunotherapy, specifically with immune checkpoint inhibitors, has brought hope for the treatment of this type of prostate cancer. Approaches such as vaccines, adoptive chimeric antigen receptor-T (CAR-T) cells, and immune checkpoint inhibitors have been employed to activate innate and adaptive immune responses to treat prostate cancer, but with limited success. Only Sipuleucel-T and the immune checkpoint inhibitor pembrolizumab are approved by the US FDA for the treatment of limited prostate cancer patients. Prostate cancer has a complex tumor microenvironment (TME) in which various immunosuppressive molecules and mechanisms coexist and interact. Additionally, prostate cancer is considered a “cold” tumor with low levels of tumor mutational burden, low amounts of antigen-presenting and cytotoxic T-cell activation, and high levels of immunosuppressive molecules including cytokines/chemokines. Thus, understanding the mechanisms of immunosuppressive signaling activation and immune evasion will help develop more effective treatments for prostate cancer. The purpose of this review is to summarize emerging advances in prostate cancer immunotherapy, with a particular focus on the molecular mechanisms that lead to immune evasion in prostate cancer. At the same time, we also highlight some potential therapeutic targets to provide a theoretical basis for the treatment of prostate cancer.

COVID-19 has resulted in extraordinary disruptions to the higher education landscape. Here, we provide a brief report on 295 students’ academic perceptions and emotional well-being in late May 2020. Students reported the high levels of uncertainty regarding their academic futures as well as significant levels of stress and difficulty coping with COVID-19 disruptions. These outcomes were related to the higher levels of neuroticism and an external locus of control. Female students reported worse emotional well-being compared to males, and the students of color reported the significantly higher levels of stress and uncertainty regarding their academic futures compared to White students. These results suggest that some students may be at particular risk for academic stress and poor emotional well-being due to the pandemic and highlight the urgent need for intervention and prevention strategies.

Introduction: Geriatric hip fractures are a major, costly public health issue, expected to increase in incidence and expense with the aging population. As healthcare transitions towards value-based care, understanding cost drivers of hip fracture treatment will be necessary to perform adequate risk adjustment. Historically, cost has been variable and difficult to determine. This study was purposed to identify variables that can predict the overall cost of care for geriatric intertrochanteric (IT) hip fractures and provide a better cost prediction to ensure the success of future bundled payment models. Methods: A retrospective review of operatively-managed geriatric hip fractures was performed at single urban level I academic trauma center between 2013 and 2017. Patient variables were collected via the electronic medical record (EMR) including CCI, ACCI, ASA, overall length of stay (LOS), AO/OTA fracture classification and demographics. Direct and indirect costs were calculated by activity-based costing by the hospital’s accounting software. Multivariable linear regression models evaluated which parameters predicted total inpatient cost of care. Results: The mean cost of care was $19,822, ranging from $9,128 to $64,211. Critical care comprised 16.9% of total costs, followed by implant costs (13.6%), and nursing costs (12.6%). Regression analysis identified both ASA ( p < 0.01) and ACCI ( p = 0.01) as statistically significant associative parameters, but only LOS ( r 2 = 0.77) as a strong correlative measure for inpatient care cost. Conclusion: This study found no correlation between ACCI or ASA and the total inpatient cost of care in isolated intertrochanteric geriatric hip fractures, suggesting that the inpatient episode-of-care costs cannot be accurately predicted by the patient demographics/comorbidities alone. Future bundled care payment models would have to be adjusted to account for variables beyond just patient characteristics. Level of Evidence: Diagnostic Level IV.

Category: Ankle; Trauma; Other Introduction/Purpose: Implant selection may provide an opportunity to reduce costs and improve value in healthcare, but most orthopaedic surgeons are unfamiliar with the cost of surgical implants. Large variation has been reported in the overall cost of the surgical treatment of ankle fractures, largely due to variations in implant selection. The purpose of this study is to evaluate the relationship between implant selection and the Reimbursed Cost of Care (RCC) over the total cost-of-care over the entire care episode. Methods: A single payer database was queried for isolated ankle fractures from 2010-2017. Patient characteristics, implant cost, RCC and total cost of care for one-year episodes were collected. Total cost of care was determined via Time Driven Activity Based Costing (TDABC). Analysis consisted of multivariable linear regression and goodness-of-fit tests. The relative proportion of the implant cost to the RCC was defined as Ic/RCC. Results: Construct costs (Inpatient: $1563.30 vs Outpatient: $1143.00; p

Introduction: Geriatric intertrochanteric (IT) femur fractures are a common and costly injury, expected to increase in incidence as the population ages. Understanding cost drivers will be essential for risk adjustments, and the surgeon’s choice of implant may be an opportunity to reduce the overall cost of care. This study was purposed to identify the relationship between implant type and inpatient cost of care for isolated geriatric IT fractures. Methods: A retrospective review of IT fractures from 2013-2017 was performed at an academic level I trauma center. Construct type and AO/OTA fracture classifications were obtained radiographically, and patient variables were collected via the electronic medical record (EMR). The total cost of care was obtained via time-driven activity-based costing (TDABC). Multivariable linear regression and goodness-of-fit analyses were used to determine correlation between implant costs, inpatient cost of care, construct type, patient characteristics, and injury characteristics. Results: Implant costs ranged from $765.17 to $5,045.62, averaging $2,699, and were highest among OTA 31-A3 fracture patterns (p < 0.01). Implant cost had a positive linear association with overall inpatient cost of care (p < 0.01), but remained highly variable (r 2 = 0.16). Total cost of care ranged from $9,129.18 to $64,210.70, averaging $19,822, and patients receiving a sliding hip screw (SHS) had the lowest mean total cost of care at $17,077, followed by short and long intramedullary nails ($19,314 and $21,372, respectively). When construct type and fracture pattern were compared to total cost, 31-A1 fracture pattern treated with SHS had significantly lower cost than 31-A2 and 31-A3 and less variation in cost. Conclusion: The cost of care for IT fractures is poorly understood and difficult to determine. With alternative payment models on the horizon, implant selection should be utilized as an opportunity to decrease costs and increase the value of care provided to patients. Level of Evidence: Diagnostic Level IV.

Epidemics of emerging and re-emerging infectious diseases are a danger to civilian and military populations worldwide. Health security and mitigation of infectious disease threats is a priority of the United States Government and the Department of Defense (DoD). Next generation sequencing (NGS) and Bioinformatics (BI) enhances traditional biosurveillance by providing additional data to understand transmission, identify resistance and virulence factors, make predictions, and update risk assessments. As more and more laboratories adopt NGS and BI technologies they encounter challenges in building local capacity. In addition to choosing the right sequencing platform and approach, considerations must also be made for the complexity of bioinformatics analyses, data storage, as well as personnel and computational requirements. To address these needs, a comprehensive training program was developed covering wet lab and bioinformatics approaches to NGS. The program is meant to be modular and adaptive to meet both common and individualized needs of medical research and public health laboratories across the DoD. The training program was first deployed internationally to the Basic Science Laboratory of the US Army Medical Research Directorate-Africa in Kisumu, Kenya, which is an overseas Lab of the Walter Reed Army Institute of Research (WRAIR). A week-long workshop with intensive focus on targeted sequencing and the bioinformatics of genome assembly (n = 24 participants) was held. Post-workshop self-assessment (completed by 21 participants) noted significant median gains in knowledge domains related to NGS targeted sequencing, bioinformatics for genome assembly, and sequence quality assessment. The participants also reported that the information on study design, sample preparation, sequencing quality control, data quality assessment, reporting, and basic and advanced bioinformatics analysis were the most useful information presented in the training. While longer-term evaluations are planned, the training resulted in significant short-term improvement of a laboratory’s self-reported wet lab and bioinformatics capabilities. This framework can be used for future DoD laboratory development in the area of NGS and BI for infectious disease surveillance, ultimately enhancing this global DoD capability.

The world's most consequential pathogens occur in regions with the fewest diagnostic resources, leaving the true burden of these diseases largely under-represented. During a prospective observational study of sepsis in Takeo Province Cambodia, we enrolled 200 patients over an 18-month period. By coupling traditional diagnostic methods such as culture, serology, and PCR to Next Generation Sequencing (NGS) and advanced statistical analyses, we successfully identified a pathogenic cause in 46.5% of our cohort. In all, we detected 25 infectious agents in 93 patients, including severe threat pathogens such as Burkholderia pseudomallei and viral pathogens such as Dengue virus. Approximately half of our cohort remained undiagnosed; however, an independent panel of clinical adjudicators determined that 81% of those patients had infectious causes of their hospitalization, further underscoring the difficulty of diagnosing severe infections in resource-limited settings. We garnered greater insight as to the clinical features of severe infection in Cambodia through analysis of a robust set of clinical data.

The invasion of exotic annual grass (EAG), e.g., cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), into rangeland ecosystems of the western United States is a broad-scale problem that affects wildlife habitats, increases wildfire frequency, and adds to land management costs. However, identifying individual species of EAG abundance from remote sensing, particularly at early stages of invasion or growth, can be problematic because of overlapping controls and similar phenological characteristics among native and other exotic vegetation. Subsequently, refining and developing tools capable of quantifying the abundance and phenology of annual and perennial grass species would be beneficial to help inform conservation and management efforts at local to regional scales. Here, we deploy an enhanced version of the U.S. Geological Survey Rangeland Exotic Plant Monitoring System to develop timely and accurate maps of annual (2016–2020) and intra-annual (May 2021 and July 2021) abundances of exotic annual and perennial grass species throughout the rangelands of the western United States. This monitoring system leverages field observations and remote-sensing data with artificial intelligence/machine learning to rapidly produce annual and early season estimates of species abundances at a 30-m spatial resolution. We introduce a fully automated and multi-task deep-learning framework to simultaneously predict and generate weekly, near-seamless composites of Harmonized Landsat Sentinel-2 spectral data. These data, along with auxiliary datasets and time series metrics, are incorporated into an ensemble of independent XGBoost models. This study demonstrates that inclusion of the Normalized Difference Vegetation Index and Normalized Difference Wetness Index time-series data generated from our deep-learning framework enables near real-time and accurate mapping of EAG (Median Absolute Error (MdAE): 3.22, 2.72, and 0.02; and correlation coefficient (r): 0.82, 0.81, and 0.73; respectively for EAG, cheatgrass, and medusahead) and native perennial grass abundance (MdAE: 2.51, r:0.72 for Sandberg bluegrass (Poa secunda)). Our approach and the resulting data provide insights into rangeland grass dynamics, which will be useful for applications, such as fire and drought monitoring, habitat suitability mapping, as well as land-cover and land-change modelling. Spatially explicit, timely, and accurate species-specific abundance datasets provide invaluable information to land managers.

We used epidemiologic and viral genetic information to identify a case of likely reinfection in an otherwise healthy, young Marine recruit enrolled in the prospective, longitudinal COVID-19 Health Action Response for Marines (CHARM) study, and we paired these findings with serological studies. This participant had a positive RT-PCR to SARS-CoV-2 upon routine sampling on study day 7, although he was asymptomatic at that time. He cleared the infection within seven days. On study day 46, he had developed symptoms consistent with COVID-19 and tested positive by RT-PCR for SARS-CoV-2 again. Viral whole genome sequencing was conducted from nares swabs at multiple time points. The day 7 sample was determined to be lineage B.1.340, whereas both the day 46 and day 49 samples were B.1.1. The first positive result for anti-SARS-CoV-2 IgM serology was collected on day 49 and for IgG on day 91. This case appears most consistent with a reinfection event. Our investigation into this case is unique in that we compared sequence data from more than just paired specimens, and we also assayed for immune response after both the initial infection and the later reinfection. These data demonstrate that individuals who have experienced an infection with SARS-CoV-2 may fail to generate effective or long-lasting immunity, similar to endemic human beta coronaviruses.