Predictive phage therapy for Escherichia coli urinary tract infections: cocktail selection for therapy based on machine learning models

This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning (ML) models. For this purpose, ML models were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied to Escherichia coli associated with urinary tract infections. This is an important common infection in humans and companion animals from which multidrug-resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy. E. coli exhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection for E. coli is difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage was measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features, and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of &gt;0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive ML models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.</p

Sorption isotherms data and mathematical models for pear bartlett (Pyrus sp.) with and without osmotic dehydration

This research work obtains the experimental data of pears in natura and osmotically dehydrated (55°Brix and 40°C) for three different temperatures (40°C, 60°C and 80°C). The desorption isotherms were fitted by the most usual models: Langmuir, BET, linear BET, GAB, Halsey, Oswin, Peleg, Chung and Henderson. The average relative deviations between experimental and calculated data were obtained to select the best model. The best model, with a temperature parameter, obtained for with and without osmotic dehydration, was the Henderson. In relation to the isotherms models, without temperature parameter, the best models were Peleg, GAB and Oswin.Este trabalho aborda o estudo teórico-experimental da atividade de água de pêras in natura e desidratadas osmoticamente a 55ºBrix e 40ºC. As isotermas foram construídas para três níveis de temperatura (40ºC, 60ºC e 80ºC) e ajustadas pelos modelos mais usuais: Langmuir, BET, BET linear, GAB, Halsey, Oswin, Peleg, Chung e Henderson. O desvio relativo entre os valores experimentais e os valores estimados foi calculado para cada curva, a fim de se avaliar qual equação melhor se ajustou aos dados experimentais. O modelo que melhor tratou os resultados das isotermas de dessorção da pêra foi o de Henderson entre os modelos que englobam a temperatura. Em relação aos modelos que tratam as isotermas isoladamente, os modelos de Peleg, GAB e Oswin apresentaram o melhor ajuste para a pêra desidratada e in natura.737

Inhibition of Striatal Soluble Guanylyl Cyclase-cGMP Signaling Reverses Basal Ganglia Dysfunction and Akinesia in Experimental Parkinsonism

There is clearly a necessity to identify novel non-dopaminergic mechanisms as new therapeutic targets for Parkinson's disease (PD). Among these, the soluble guanylyl cyclase (sGC)-cGMP signaling cascade is emerging as a promising candidate for second messenger-based therapies for the amelioration of PD symptoms. In the present study, we examined the utility of the selective sGC inhibitor 1H-[1], [2], [4] oxadiazolo-[4,3-a]quinoxalin-1-one (ODQ) for reversing basal ganglia dysfunction and akinesia in animal models of PD.The utility of the selective sGC inhibitor ODQ for reversing biochemical, electrophysiological, histochemical, and behavioral correlates of experimental PD was performed in 6-OHDA-lesioned rats and mice chronically treated with MPTP.We found that one systemic administration of ODQ is sufficient to reverse the characteristic elevations in striatal cGMP levels, striatal output neuron activity, and metabolic activity in the subthalamic nucleus observed in 6-OHDA-lesioned rats. The latter outcome was reproduced after intrastriatal infusion of ODQ. Systemic administration of ODQ was also effective in improving deficits in forelimb akinesia induced by 6-OHDA and MPTP.Pharmacological inhibition of the sGC-cGMP signaling pathway is a promising non-dopaminergic treatment strategy for restoring basal ganglia dysfunction and attenuating motor symptoms associated with PD

Predictive phage therapy for Escherichia coli urinary tract infections: cocktail selection for therapy based on machine learning models

This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning models (MLM). For this purpose, MLM were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied to Escherichia coli (E. coli) associated with urinary tract infections. This is an important common infection in humans and companion animals from which multi-drug resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy. E. coli exhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection for E. coli is difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage were measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of &gt;0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.Significance Statement With the growing challenge of antimicrobial resistance there is an urgency for alternative treatments for common bacterial diseases including urinary tract infections (UTIs). Escherichia coli is the main causative agent of UTIs in both humans and companion animals with multidrug resistant strains such as the globally disseminated ST131 becoming more common. Bacteriophage (phage) are natural predators of bacteria and potentially an alternative therapy. However, a major barrier for phage therapy is the specificity of phage on target bacteria and therefore difficulty efficiently selecting the appropriate phage. Here, we demonstrate a genomics driven approach using machine learning prediction models combined with phage activity clustering to select phage cocktails based only on the genome sequence of the infecting bacterial strain

Atypical Integration of Sensory-to-Transmodal Functional Systems Mediates Symptom Severity in Autism.

A notable characteristic of autism spectrum disorder (ASD) is co-occurring deficits in low-level sensory processing and high-order social interaction. While there is evidence indicating detrimental cascading effects of sensory anomalies on the high-order cognitive functions in ASD, the exact pathological mechanism underlying their atypical functional interaction across the cortical hierarchy has not been systematically investigated. To address this gap, here we assessed the functional organisation of sensory and motor areas in ASD, and their relationship with subcortical and high-order trandmodal systems. In a resting-state fMRI data of 107 ASD and 113 neurotypical individuals, we applied advanced connectopic mapping to probe functional organization of primary sensory/motor areas, together with targeted seed-based intrinsic functional connectivity (iFC) analyses. In ASD, the connectopic mapping revealed topological anomalies (i.e., excessively more segregated iFC) in the motor and visual areas, the former of which patterns showed association with the symptom severity of restricted and repetitive behaviors. Moreover, the seed-based analysis found diverging patterns of ASD-related connectopathies: decreased iFCs within the sensory/motor areas but increased iFCs between sensory and subcortical structures. While decreased iFCs were also found within the higher-order functional systems, the overall proportion of this anomaly tends to increase along the level of cortical hierarchy, suggesting more dysconnectivity in the higher-order functional networks. Finally, we demonstrated that the association between low-level sensory/motor iFCs and clinical symptoms in ASD was mediated by the high-order transmodal systems, suggesting pathogenic functional interactions along the cortical hierarchy. Findings were largely replicated in the independent dataset. These results highlight that atypical integration of sensory-to-high-order systems contributes to the complex ASD symptomatology

Severe hypoxemia during veno-venous extracorporeal membrane oxygenation: exploring the limits of extracorporeal respiratory support

OBJECTIVE: Veno-venous extracorporeal oxygenation for respiratory support has emerged as a rescue alternative for patients with hypoxemia. However, in some patients with more severe lung injury, extracorporeal support fails to restore arterial oxygenation. Based on four clinical vignettes, the aims of this article were to describe the pathophysiology of this concerning problem and to discuss possibilities for hypoxemia resolution. METHODS: Considering the main reasons and rationale for hypoxemia during veno-venous extracorporeal membrane oxygenation, some possible bedside solutions must be considered: 1) optimization of extracorporeal membrane oxygenation blood flow; 2) identification of recirculation and cannula repositioning if necessary; 3) optimization of residual lung function and consideration of blood transfusion; 4) diagnosis of oxygenator dysfunction and consideration of its replacement; and finally 5) optimization of the ratio of extracorporeal membrane oxygenation blood flow to cardiac output, based on the reduction of cardiac output. CONCLUSION: Therefore, based on the pathophysiology of hypoxemia during veno-venous extracorporeal oxygenation support, we propose a stepwise approach to help guide specific interventions

The chemopreventive polyphenol Curcumin prevents hematogenous breast cancer metastases in immunodeficient mice

Dissemination of metastatic cells probably occurs long before diagnosis of the primary tumor. Metastasis during early phases of carcinogenesis in high risk patients is therefore a potential prevention target. The plant polyphenol Curcumin has been proposed for dietary prevention of cancer. We therefore examined its effects on the human breast cancer cell line MDA-MB-231 in vitro and in a mouse metastasis model. Curcumin strongly induces apoptosis in MDA- MB- 231 cells in correlation with reduced activation of the survival pathway NF kappa B, as a consequence of diminished I kappa B and p65 phosphorylation. Curcumin also reduces the expression of major matrix metalloproteinases (MMPs) due to reduced NF kappa B activity and transcriptional downregulation of AP-1. NF kappa B/p65 silencing is sufficient to downregulate c-jun and MMP expression. Reduced NF kappa B/AP-1 activity and MMP expression lead to diminished invasion through a reconstituted basement membrane and to a significantly lower number of lung metastases in immunodeficient mice after intercardiac injection of 231 cells (p=0.0035). 68% of Curcumin treated but only 17% of untreated animals showed no or very few lung metastases, most likely as a consequence of down-regulation of NF kappa B/AP-1 dependent MMP expression and direct apoptotic effects on circulating tumor cells but not on established metastases. Dietary chemoprevention of metastases appears therefore feasible. Copyright (c) 2007 S. Karger AG, Basel

Impacts of Bar-driven Shear and Shocks on Star Formation

Bars drive gas inflow. As the gas flows inward, shocks and shear occur along the bar dust lanes. Such shocks and shear can affect the star formation (SF) and change the gas properties. For four barred galaxies, we present Hα velocity gradient maps that highlight bar-driven shocks and shear using data from the PHANGS-MUSE and PHANGS-ALMA surveys, which allow us to study bar kinematics in unprecedented detail. Velocity gradients are enhanced along the bar dust lanes, where shocks and shear are shown to occur in numerical simulations. Velocity gradient maps also efficiently pick up H ii regions that are expanding or moving relative to the surroundings. We put pseudo-slits on the regions where velocity gradients are enhanced and find that Hα and CO velocities jump up to ∼170 km s−1, even after removing the effects of circular motions due to the galaxy rotation. Enhanced velocity gradients either coincide with the peak of CO intensity along the bar dust lanes or are slightly offset from CO intensity peaks, depending on the objects. Using the Baldwin–Philips–Terlevich BPT diagnostic, we identify the source of ionization on each spaxel and find that SF is inhibited in the high-velocity gradient regions of the bar, and the majority of those regions are classified as a low-ionization nuclear emission-line region (LINER) or composite. This implies that SF is inhibited where bar-driven shear and shocks are strong. Our results are consistent with the results from the numerical simulations that show SF is inhibited in the bar where the shear force is strong

Light-strand bias and enriched zones of embedded ribonucleotides are associated with DNA replication and transcription in the human-mitochondrial genome

Abundant ribonucleoside-triphosphate (rNTP) incorporation into DNA by DNA polymerases in the form of ribonucleoside monophosphates (rNMPs) is a widespread phenomenon in nature, resulting in DNA-structural change and genome instability. The rNMP distribution, characteristics, hotspots and association with DNA metabolic processes in human mitochondrial DNA (hmtDNA) remain mostly unknown. Here, we utilize the ribose-seq technique to capture embedded rNMPs in hmtDNA of six different cell types. In most cell types, the rNMPs are preferentially embedded on the light strand of hmtDNA with a strong bias towards rCMPs; while in the liver-tissue cells, the rNMPs are predominately found on the heavy strand. We uncover common rNMP hotspots and conserved rNMP-enriched zones across the entire hmtDNA, including in the control region, which links the rNMP presence to the frequent hmtDNA replication-failure events. We show a strong correlation between coding-sequence size and rNMP-embedment frequency per nucleotide on the non-template, light strand in all cell types, supporting the presence of transient RNA-DNA hybrids preceding light-strand replication. Moreover, we detect rNMP-embedment patterns that are only partly conserved across the different cell types and are distinct from those found in yeast mtDNA. The study opens new research directions to understand the biology of hmtDNA and genomic rNMPs.Graphical Abstrac

Differential Effects of Influenza Virus NA, HA Head, and HA Stalk Antibodies on Peripheral Blood Leukocyte Gene Expression during Human Infection.

In this study, we examined the relationships between anti-influenza virus serum antibody titers, clinical disease, and peripheral blood leukocyte (PBL) global gene expression during presymptomatic, acute, and convalescent illness in 83 participants infected with 2009 pandemic H1N1 virus in a human influenza challenge model. Using traditional statistical and logistic regression modeling approaches, profiles of differentially expressed genes that correlated with active viral shedding, predicted length of viral shedding, and predicted illness severity were identified. These analyses further demonstrated that challenge participants fell into three peripheral blood leukocyte gene expression phenotypes that significantly correlated with different clinical outcomes and prechallenge serum titers of antibodies specific for the viral neuraminidase, hemagglutinin head, and hemagglutinin stalk. Higher prechallenge serum antibody titers were inversely correlated with leukocyte responsiveness in participants with active disease and could mask expression of peripheral blood markers of clinical disease in some participants, including viral shedding and symptom severity. Consequently, preexisting anti-influenza antibodies may modulate PBL gene expression, and this must be taken into consideration in the development and interpretation of peripheral blood diagnostic and prognostic assays of influenza infection