The Role Of Intraspecies And Interspecies Communication Of Pseudomonas Aeruginosa Pa14 Towards Phenazine Production And Virulence

Pseudomonas aeruginosa is an opportunistic pathogen and a model organism for studying quorum sensing (QS) - bacterial communication via secreted signaling factors (acyl homoserine lactones). P. aeruginosa also produces electrochemicallyactive compounds that are called phenazines, which help it to respire with an electrode in bioelectrochemical systems (BESs). Phenazine production by this microbe is strongly controlled by QS amongst other environmental stimuli. In the BES microbiota, we proposed that intraspecies and interspecies communication(s) could influence phenazine production by P. aeruginosa subsequently affecting current generation. Intraspecies communication: First, we showed that QS modulates the current production by P. aeruginosa in BESs by controlling phenazine production. The current and phenazine production by a wildtype strain (WT) and a mutant were investigated under conditions that favor or inhibit QS. As hypothesized, anaerobic current production by the mutant was 5.8-fold higher with extraneously supplied QS signaling lactones than without. i Interspecies communication: Next, we studied P. aeruginosa in association with a fermenter (Enterobacter aerogenes) and found that the current generation by this coculture was 14-fold higher than either of these two bacteria alone. This phenomenon was due to metabolite-based mutualism in which a fermentation product of E. aerogenes stimulated specific phenazine production (i.e., pyocyanin) by P. aeruginosa. E. aerogenes switched from fermentation to electrode respiration with pyocyanin. We further demonstrated that common fermentation products of several microorganisms, which co-habit infections with P. aeruginosa, significantly increase the virulence of P. aeruginosa compared to the common blood sugar - glucose. Finally, we demonstrated that in a defined mixed-culture BES, bacterial synergism between P. aeruginosa and E. aerogenes results in phenazine-based mediated electron transfer (MET) becoming equally important to direct electron transfer by Geobacter sulfurreducens. A mechanistic mathematical model revealed that in the synergism, E. aerogenes possessed faster kinetics of phenazine reduction, thereby, resulting in improved MET compared to a pure culture of P. aeruginosa. Overall, we showed that intermicrobial cooperation considerably affects the phenazine production and virulence of P. aeruginosa with implications in microbial communities outside BESs. i

Analysis of Implementing Best Practices for Co-Prescribing Naloxone in Your Agency Online CME Training Module via Pre- and Post- Knowledge Assessment.

The opioid epidemic poses substantial risk to society. Providers must ensure that their patients understand the uses and risks of both opioids and naloxone. One way to analyze this concept is via metacognition. This refers to a person’s knowledge about cognitive phenomena, and thus it regulates self-awareness abilities in decision making, such as planning and evaluating. It is not only important for providers to have knowledge on best practices, but also to have self-awareness, and confidence in their decision making to ensure optimal patient outcomes. True-false confidence weighted scoring can be utilized, whereby various levels of confidence are assessed from “I am confident this is true,” to “I think, but am unsure, if this is true,” and similarly for false answers. This study analyzed the efficacy of an online training module, “Implementing Best Practices for Co-Prescribing Naloxone in Your Agency” and used a metacognitive analysis approach to determine efficacy. The training module, pre- and post-tests were administered at Inspira Health Network on 9/12/22 and 9/13/22. This analysis finds a significant improvement in pre- and post-intervention scores, as well as significant improvement in provider confidence in their answer choices. Such an analysis provides insight not only to efficacy of an intervention, but also the likelihood of confidence, and continued use of the intervention

First Steps towards Parameter Optimization of Bioelectrochemical Systems using a Microsystems Engineering Approach

There is a growing interest in exploiting bioelectrochemical systems (BESs), such as microbial fuel cells, as an alternative energy source for sustainable living. Certain species of microorganisms, such as Pseudomonas aeruginosa 14 (PA14) wild type, produce electron carriers, Phenazines, which transfers electrons to the anode in the system and produce digital output signal. The electric current generation of BESs is influenced by many biophysical and biochemical parameters in the system, such as glucose level, cell culture community, cell density, PH, and oxygen level. The existing MFCs are at macroscale, and not suitable for parameter optimization; and as a result they are not yet cost effective. Here, we present our first effort in parameter optimization of BESs using a microfluidic device. Microfluidic device affords us an ability to quickly define a physical and chemical environment for PA14, and its compatibility with microscope allows us a real time observation of the responses. We will present experimental results on the roles of carbon sources in PA14 motility and promising results of Phenazines being a chemoattractant to PA14. We will discuss the relation between PA14 motility and biofilm formation, and subsequently electric current generation

Vertebrate Hosts as Islands: Dynamics of Selection, Immigration, Loss, Persistence, and Potential Function of Bacteria on Salamander Skin.

Skin bacterial communities can protect amphibians from a fungal pathogen; however, little is known about how these communities are maintained. We used a neutral model of community ecology to identify bacteria that are maintained on salamanders by selection or by dispersal from a bacterial reservoir (soil) and ecological drift. We found that 75% (9/12) of bacteria that were consistent with positive selection, <1% of bacteria that were consistent with random dispersal and none of the bacteria that were consistent under negative selection had a 97% or greater match to antifungal isolates. Additionally we performed an experiment where salamanders were either provided or denied a bacterial reservoir and estimated immigration and loss (emigration and local extinction) rates of bacteria on salamanders in both treatments. Loss was strongly related to bacterial richness, suggesting competition is important for structuring the community. Bacteria closely related to antifungal isolates were more likely to persist on salamanders with or without a bacterial reservoir, suggesting they had a competitive advantage. Furthermore, over-represented and under-represented operational taxonomic units (OTUs) had similar persistence on salamanders when a bacterial reservoir was present. However, under-represented OTUs were less likely to persist in the absence of a bacterial reservoir, suggesting that the over-represented and under-represented bacteria were selected against or for on salamanders through time. Our findings from the neutral model, migration and persistence analyses show that bacteria that exhibit a high similarity to antifungal isolates persist on salamanders, which likely protect hosts against pathogens and improve fitness. This research is one of the first to apply ecological theory to investigate assembly of host associated-bacterial communities, which can provide insights for probiotic bioaugmentation as a conservation strategy against disease

Electron spin resonance studies of the free radicals derived from tetraphenylhydrazine

The free radicals obtained from tetraphenylhydrazine, diphenylbenzidine and diphenylamine under different conditions have been investigated with electron spin resonance techniques. The identification and differentiation between the radicals were done on the basis of their g-values and the line-widths and hyperfine structure exhibited by their spectra. The formation of the diphenylamino radical, by the thermal dissociation of tetraphenylhydrazine in non-polar solvents has been confirmed. The same radical is obtained when tetraphenylhydrazine is subjected to atmospheric oxidation in a non-polar solvent. The tetraphenylhydrazinium radical ion, is formed (1) when a solution of tetraphenyl-hydrazine in acetic acid is subjected to prolonged atmospheric oxidation, (2) when a similar, freshly prepared solution is heated and (3) when diphenylamine or diphenylbenzidine is subjected to oxidation in an acetic acid medium. It is believed that the protonated hydrazinium radical, results if an acetic acid solution of tetraphenylhydrazine is treated with a few drops of concentrated sulphuric acid. During the course of this investigation, the g-value of a 0·002 M solution of DPPH in xylene was measured to be 2·00347±0·00004

Tracking smell loss to identify healthcare workers with SARS-CoV-2 infection

Introduction Healthcare workers (HCW) treating COVID-19 patients are at high risk for infection and may also spread infection through their contact with vulnerable patients. Smell loss has been associated with SARS-CoV-2 infection, but it is unknown whether monitoring for smell loss can be used to identify asymptomatic infection among high risk individuals. In this study we sought to determine if tracking smell sensitivity and loss using an at-home assessment could identify SARS-CoV-2 infection in HCW. Methods and findings We performed a prospective cohort study tracking 473 HCW across three months to determine if smell loss could predict SARS-CoV-2 infection in this high-risk group. HCW subjects completed a longitudinal, behavioral at-home assessment of olfaction with household items, as well as detailed symptom surveys that included a parosmia screening questionnaire, and real-time quantitative polymerase chain reaction testing to identify SARS-CoV-2 infection. Our main measures were the prevalence of smell loss in SARS-CoV-2-positive HCW versus SARS-CoV- 2-negative HCW, and timing of smell loss relative to SARS-CoV-2 test positivity. SARS-CoV-2 was identified in 17 (3.6%) of 473 HCW. HCW with SARS-CoV-2 infection were more likely to report smell loss than SARS-CoV-2-negative HCW on both the at-home assessment and the screening questionnaire (9/17, 53% vs 105/456, 23%, P < .01). 6/9 (67%) of SARS-CoV-2-positive HCW reporting smell loss reported smell loss prior to having a positive SARS-CoV-2 test, and smell loss was reported a median of two days before testing positive. Neurological symptoms were reported more frequently among SARS-CoV-2-positive HCW who reported smell loss compared to those without smell loss (9/9, 100% vs 3/8, 38%, P < .01). Conclusions In this prospective study of HCW, self-reported changes in smell using two different measures were predictive of SARS-CoV-2 infection. Smell loss frequently preceded a positive test and was associated with neurological symptoms

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

The Role Of Intraspecies And Interspecies Communication Of Pseudomonas Aeruginosa Pa14 Towards Phenazine Production And Virulence

Pseudomonas aeruginosa is an opportunistic pathogen and a model organism for studying quorum sensing (QS) - bacterial communication via secreted signaling factors (acyl homoserine lactones). P. aeruginosa also produces electrochemicallyactive compounds that are called phenazines, which help it to respire with an electrode in bioelectrochemical systems (BESs). Phenazine production by this microbe is strongly controlled by QS amongst other environmental stimuli. In the BES microbiota, we proposed that intraspecies and interspecies communication(s) could influence phenazine production by P. aeruginosa subsequently affecting current generation. Intraspecies communication: First, we showed that QS modulates the current production by P. aeruginosa in BESs by controlling phenazine production. The current and phenazine production by a wildtype strain (WT) and a mutant were investigated under conditions that favor or inhibit QS. As hypothesized, anaerobic current production by the mutant was 5.8-fold higher with extraneously supplied QS signaling lactones than without. i Interspecies communication: Next, we studied P. aeruginosa in association with a fermenter (Enterobacter aerogenes) and found that the current generation by this coculture was 14-fold higher than either of these two bacteria alone. This phenomenon was due to metabolite-based mutualism in which a fermentation product of E. aerogenes stimulated specific phenazine production (i.e., pyocyanin) by P. aeruginosa. E. aerogenes switched from fermentation to electrode respiration with pyocyanin. We further demonstrated that common fermentation products of several microorganisms, which co-habit infections with P. aeruginosa, significantly increase the virulence of P. aeruginosa compared to the common blood sugar - glucose. Finally, we demonstrated that in a defined mixed-culture BES, bacterial synergism between P. aeruginosa and E. aerogenes results in phenazine-based mediated electron transfer (MET) becoming equally important to direct electron transfer by Geobacter sulfurreducens. A mechanistic mathematical model revealed that in the synergism, E. aerogenes possessed faster kinetics of phenazine reduction, thereby, resulting in improved MET compared to a pure culture of P. aeruginosa. Overall, we showed that intermicrobial cooperation considerably affects the phenazine production and virulence of P. aeruginosa with implications in microbial communities outside BESs. i