Probing membrane hydration in microfluidic polymer electrolyte membrane electrolyzers via operando synchrotron Fourier-transform infrared spectroscopy.

Polymer electrolyte membrane (PEM) electrolyzers are renewable energy storage systems that produce high purity hydrogen fuel from electrochemical water splitting. The PEM in particular is a key component that acts as a solid electrolyte between electrodes and separates the reactants, but despite these benefits, its internal ion transport mechanisms are not fully understood. Here, the first microfluidic PEM electrolyzer that is semi-transparent in the infrared (IR) spectrum is developed as a platform for characterizing the PEM hydration during operation. The electrochemical performance of the chip is compared to its PEM hydration, which is measured via synchrotron Fourier-transform infrared (FTIR) spectroscopy. The PEM water content is directly probed in the operating electrolyzer by measuring the transmitted light intensity at wavelengths around 10 µm. By supplying the electrolyzer with reactant starving flow rates, mass transport driven cell failure is provoked, which coincides with membrane dehydration. Furthermore, higher operating temperatures are observed to improve the stability in membrane hydration through increasing the membrane water uptake. The methods presented here prove the viability of IR techniques for characterizing membrane hydration, and future extension towards imaging and thermography would enable further quantitative studies of internal membrane transport behaviors.

Observed and projected functional reorganization of riverine fish assemblages from global change.

Climate and land-use/land-cover change ("global change") are restructuring biodiversity, globally. Broadly, environmental conditions are expected to become warmer, potentially drier (particularly in arid regions), and more anthropogenically developed in the future, with spatiotemporally complex effects on ecological communities. We used functional traits to inform Chesapeake Bay Watershed fish responses to future climate and land-use scenarios (2030, 2060, and 2090). We modeled the future habitat suitability of focal species representative of key trait axes (substrate, flow, temperature, reproduction, and trophic) and used functional and phylogenetic metrics to assess variable assemblage responses across physiographic regions and habitat sizes (headwaters through large rivers). Our focal species analysis projected future habitat suitability gains for carnivorous species with preferences for warm water, pool habitats, and fine or vegetated substrates. At the assemblage level, models projected decreasing habitat suitability for cold-water, rheophilic, and lithophilic individuals but increasing suitability for carnivores in the future across all regions. Projected responses of functional and phylogenetic diversity and redundancy differed among regions. Lowland regions were projected to become less functionally and phylogenetically diverse and more redundant while upland regions (and smaller habitat sizes) were projected to become more diverse and less redundant. Next, we assessed how these model-projected assemblage changes 2005-2030 related to observed time-series trends (1999-2016). Halfway through the initial projecting period (2005-2030), we found observed trends broadly followed modeled patterns of increasing proportions of carnivorous and lithophilic individuals in lowland regions but showed opposing patterns for functional and phylogenetic metrics. Leveraging observed and predicted analyses simultaneously helps elucidate the instances and causes of discrepancies between model predictions and ongoing observed changes. Collectively, results highlight the complexity of global change impacts across broad landscapes that likely relate to differences in assemblages' intrinsic sensitivities and external exposure to stressors.

Explainable machine learning improves interpretability in the predictive modeling of biological stream conditions in the Chesapeake Bay Watershed, USA.

Anthropogenic alterations have resulted in widespread degradation of stream conditions. To aid in stream restoration and management, baseline estimates of conditions and improved explanation of factors driving their degradation are needed. We used random forests to model biological conditions using a benthic macroinvertebrate index of biotic integrity for small, non-tidal streams (upstream area ≤200 km2) in the Chesapeake Bay watershed (CBW) of the mid-Atlantic coast of North America. We utilized several global and local model interpretation tools to improve average and site-specific model inferences, respectively. The model was used to predict condition for 95,867 individual catchments for eight periods (2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019). Predicted conditions were classified as Poor, FairGood, or Uncertain to align with management needs and individual reach lengths and catchment areas were summed by condition class for the CBW for each period. Global permutation and local Shapley importance values indicated percent of forest, development, and agriculture in upstream catchments had strong impacts on predictions. Development and agriculture negatively influenced stream condition for model average (partial dependence [PD] and accumulated local effect [ALE] plots) and local (individual condition expectation and Shapley value plots) levels. Friedman's H-statistic indicated large overall interactions for these three land covers, and bivariate global plots (PD and ALE) supported interactions among agriculture and development. Total stream length and catchment area predicted in FairGood conditions decreased then increased over the 19-years (length/area: 66.6/65.4% in 2001, 66.3/65.2% in 2011, and 66.6/65.4% in 2019). Examination of individual catchment predictions between 2001 and 2019 showed those predicted to have the largest decreases in condition had large increases in development; whereas catchments predicted to exhibit the largest increases in condition showed moderate increases in forest cover. Use of global and local interpretative methods together with watershed-wide and individual catchment predictions support conservation practitioners that need to identify widespread and localized patterns, especially acknowledging that management actions typically take place at individual-reach scales.

Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?

Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape (e.g., elevation, longitude, latitude, geology) and land use (i.e., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality (e.g., total nitrogen and conductivity) and habitat (e.g., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species (e.g., Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.

Effects of Image Quantity and Image Source Variation on Machine Learning Histology Differential Diagnosis Models.

AIMS: Histology, the microscopic study of normal tissues, is a crucial element of most medical curricula. Learning tools focused on histology are very important to learners who seek diagnostic competency within this important diagnostic arena. Recent developments in machine learning (ML) suggest that certain ML tools may be able to benefit this histology learning platform. Here, we aim to explore how one such tool based on a convolutional neural network, can be used to build a generalizable multi-classification model capable of classifying microscopic images of human tissue samples with the ultimate goal of providing a differential diagnosis (a list of look-alikes) for each entity. METHODS: We obtained three institutional training datasets and one generalizability test dataset, each containing images of histologic tissues in 38 categories. Models were trained on data from single institutions, low quantity combinations of multiple institutions, and high quantity combinations of multiple institutions. Models were tested against withheld validation data, external institutional data, and generalizability test images obtained from Google image search. Performance was measured with macro and micro accuracy, sensitivity, specificity, and f1-score. RESULTS: In this study, we were able to show that such a model's generalizability is dependent on both the training data source variety and the total number of training images used. Models which were trained on 760 images from only a single institution performed well on withheld internal data but poorly on external data (lower generalizability). Increasing data source diversity improved generalizability, even when decreasing data quantity: models trained on 684 images, but from three sources improved generalization accuracy between 4.05% and 18.59%. Maintaining this diversity and increasing the quantity of training images to 2280 further improved generalization accuracy between 16.51% and 32.79%. CONCLUSIONS: This pilot study highlights the significance of data diversity within such studies. As expected, optimal models are those that incorporate both diversity and quantity into their platforms.s.

Predicting Motor Responsiveness to Deep Brain Stimulation with Machine Learning.

Deep brain stimulation is a complex movement disorder intervention that requires highly invasive brain surgery. Clinicians struggle to predict how patients will respond to this treatment. To address this problem, we are working toward developing a clinical tool to help neurologists predict deep brain stimulation response. We analyzed a cohort of 105 Parkinson's patients who underwent deep brain stimulation at Vanderbilt University Medical Center. We developed binary and multicategory models for predicting likelihood of motor symptom reduction after undergoing deep brain stimulation. We compared the performances of our best models to predictions made by neurologist experts in movement disorders. The strongest binary classification model achieved a 10-fold cross validation AUC of 0.90, outperforming the best neurologist predictions (0.56). These results are promising for future clinical applications, though more work is necessary to validate these findings in a larger cohort and taking into consideration broader quality of life outcome measures.

A Broken Antibiotic Market: Review of Strategies to Incentivize Drug Development.

The threat posed by infections arising from antimicrobial-resistant bacteria is a global concern. Despite this trend, the future development of new antimicrobial agents is currently very uncertain. The lack of commercial success for newly launched antimicrobial agents provides little incentive to invest in the development of new agents. To address this crisis, a number of push and pull incentives have been constructed to support antimicrobial drug development. Push incentives, which are designed to lower the cost of developing new antimicrobial agents, include grants, contracts, public-private partnerships, tax credits, and clinical trial networks. Pull incentives, which are designed to facilitate higher financial returns for a newly launched antimicrobial agent, include those that decrease the time for a regulatory review, extend patent exclusivity, or provide premium pricing. Such incentives may also include direct, advanced, or milestone payments or they may be insurance-based whereby healthcare systems pay for the right to access an antimicrobial agent rather than the number of units administered. Another strategy involves the re-evaluation of interpretive criteria for in vitro susceptibility testing (susceptibility breakpoints) of old antimicrobial agents using the same standards applied to that of new agents, which will allow for an accurate determination of antimicrobial resistance. Although each of the above-described strategies will be important to ensure that antimicrobial agents are developed in the decades to come, the update of susceptibility breakpoints for old agents is a strategy that could be implemented quickly and one that could be the most effective for incentivizing drug developers and financiers to reconsider the development of antimicrobial agents.

Bubble Formation in the Electrolyte Triggers Voltage Instability in CO2 Electrolyzers.

The electrochemical reduction of CO2 is promising for mitigating anthropogenic greenhouse gas emissions; however, voltage instabilities currently inhibit reaching high current densities that are prerequisite for commercialization. Here, for the first time, we elucidate that product gaseous bubble accumulation on the electrode/electrolyte interface is the direct cause of the voltage instability in CO2 electrolyzers. Although bubble formation in water electrolyzers has been extensively studied, we identified that voltage instability caused by bubble formation is unique to CO2 electrolyzers. The appearance of syngas bubbles within the electrolyte at the gas diffusion electrode (GDE)-electrolyte chamber interface (i.e. ∼10% bubble coverage of the GDE surface) was accompanied by voltage oscillations of 60 mV. The presence of syngas in the electrolyte chamber physically inhibited two-phase reaction interfaces, thereby resulting in unstable cell performance. The strategic incorporation of our insights on bubble growth behavior and voltage instability is vital for designing commercially relevant CO2 electrolyzers.

ARGONAUT II Study of the In Vitro Activity of Plazomicin against Carbapenemase-Producing Klebsiella pneumoniae.

Plazomicin was tested against 697 recently acquired carbapenem-resistant Klebsiella pneumoniae isolates from the Great Lakes region of the United States. Plazomicin MIC50 and MIC90 values were 0.25 and 1 mg/liter, respectively; 680 isolates (97.6%) were susceptible (MICs of ≤2 mg/liter), 9 (1.3%) intermediate (MICs of 4 mg/liter), and 8 (1.1%) resistant (MICs of >32 mg/liter). Resistance was associated with rmtF-, rmtB-, or armA-encoded 16S rRNA methyltransferases in all except 1 isolate.

Disentangling the potential effects of land-use and climate change on stream conditions.

Land-use and climate change are significantly affecting stream ecosystems, yet understanding of their long-term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land-use and climate scenarios on the condition of 70,772 small streams in the Chesapeake Bay watershed, United States. The Chesapeake Basin-wide Index of Biotic Integrity, a benthic macroinvertebrate multimetric index, was used to represent stream condition. Land-use scenarios included four Special Report on Emissions Scenarios (A1B, A2, B1, and B2) representing a range of potential landscape futures. Future climate scenarios included quartiles of future climate changes from downscaled Coupled Model Intercomparison Project - Phase 5 (CMIP5) and a watershed-wide uniform scenario (Lynch2016). We employed random forests analysis to model individual and combined effects of land-use and climate change on stream conditions. Individual scenarios suggest that by 2090, watershed-wide conditions may exhibit anywhere from large degradations (e.g., scenarios A1B, A2, and the CMIP5 25th percentile) to small degradations (e.g., scenarios B1, B2, and Lynch2016). Combined land-use and climate change scenarios highlighted their interaction and predicted, by 2090, watershed-wide degradation in 16.2% (A2 CMIP5 25th percentile) to 1.0% (B2 Lynch2016) of stream kilometers. A goal for the Chesapeake Bay watershed is to restore 10% of stream kilometers over a 2008 baseline; our results suggest meeting and sustaining this goal until 2090 may require improvement in 11.0%-26.2% of stream kilometers, dependent on land-use and climate scenario. These results highlight inherent variability among scenarios and the resultant uncertainty of predicted conditions, which reinforces the need to incorporate multiple scenarios of both land-use (e.g., development, agriculture, etc.) and climate change in future studies to encapsulate the range of potential future conditions.

Potent LpxC Inhibitors with In Vitro Activity against Multidrug-Resistant Pseudomonas aeruginosa.

New drugs with novel mechanisms of resistance are desperately needed to address both community and nosocomial infections due to Gram-negative bacteria. One such potential target is LpxC, an essential enzyme that catalyzes the first committed step of lipid A biosynthesis. Achaogen conducted an extensive research campaign to discover novel LpxC inhibitors with activity against Pseudomonas aeruginosa We report here the in vitro antibacterial activity and pharmacodynamics of ACHN-975, the only molecule from these efforts and the first ever LpxC inhibitor to be evaluated in phase 1 clinical trials. In addition, we describe the profiles of three additional LpxC inhibitors that were identified as potential lead molecules. These efforts did not produce an additional development candidate with a sufficiently large therapeutic window and the program was subsequently terminated.

Pharmacodynamics of plazomicin and a comparator aminoglycoside, amikacin, studied in an in vitro pharmacokinetic model of infection.

The new aminoglycoside plazomicin shows in vitro potency against multidrug-resistant Enterobacteriales. The exposure-response relationship of plazomicin and the comparator aminoglycoside amikacin was determined for Escherichia coli, while for Klebsiella pneumoniae only plazomicin was tested. An in vitro pharmacokinetic model was used. Five E. coli strains (two meropenem-resistant) and five K. pneumoniae strains (two meropenem-resistant) with plazomicin MICs of 0.5-4 mg/L were used. Antibacterial effect was assessed by changes in bacterial load and bacterial population profile. The correlation between change in initial inoculum after 24 h of drug exposure and the AUC/MIC ratio was good (plazomicin R2 ≥ 0.8302; amikacin R2 ≥ 0.9520). Escherichia coli plazomicin AUC/MIC ratios for 24-h static, -1, -2 and -3 log drop were 36.1 ± 18.4, 39.3 ± 20.9, 41.2 ± 21.9 and 44.8 ± 24.3, respectively, and for amikacin were 49.5 ± 12.7, 55.7 ± 14.8, 64.1 ± 19.2 and 73.3 ± 25.3. Klebsiella pneumoniae plazomicin AUC/MIC ratios for 24-h static, -1, -2 and -3 log drop were 34.0 ± 15.2, 46.8 ± 27.8, 67.4 ± 46.5 and 144.3 ±129.8. Plazomicin AUC/MIC ratios >66 and amikacin AUC/MIC ratios >57.7 were associated with suppression of E. coli growth on 4 × or 8 × MIC recovery plates. The equivalent plazomicin AUC/MIC to suppress resistance emergence with K. pneumoniae was >132. The plazomicin AUC/MIC for 24-h static effect and -1 log reduction in E. coli and K. pneumoniae bacterial load was in the range 30-60. Plazomicin AUC/MIC targets aligned with those of amikacin for E. coli.

Optimization of LpxC Inhibitors for Antibacterial Activity and Cardiovascular Safety.

UDP-3-O-(R-3-hydroxymyristoyl)-N-acetylglucosamine deacetylase (LpxC) is a Zn2+ deacetylase that is essential for the survival of most pathogenic Gram-negative bacteria. ACHN-975 (N-((S)-3-amino-1-(hydroxyamino)-3-methyl-1-oxobutan-2-yl)-4-(((1R,2R)-2-(hydroxymethyl)cyclopropyl)buta-1,3-diyn-1-yl)benzamide) was the first LpxC inhibitor to reach human clinical testing and was discovered to have a dose-limiting cardiovascular toxicity of transient hypotension without compensatory tachycardia. Herein we report the effort beyond ACHN-975 to discover LpxC inhibitors optimized for enzyme potency, antibacterial activity, pharmacokinetics, and cardiovascular safety. Based on its overall profile, compound 26 (LPXC-516, (S)-N-(2-(hydroxyamino)-1-(3-methoxy-1,1-dioxidothietan-3-yl)-2-oxoethyl)-4-(6-hydroxyhexa-1,3-diyn-1-yl)benzamide) was chosen for further development. A phosphate prodrug of 26 was developed that provided a solubility of >30 mg mL-1 for parenteral administration and conversion into the active drug with a t1/2 of approximately two minutes. Unexpectedly, and despite our optimization efforts, the prodrug of 26 still possesses a therapeutic window insufficient to support further clinical development.

Plazomicin Is Active Against Metallo-ß-Lactamase-Producing Enterobacteriaceae.

Plazomicin is an aminoglycoside that was approved in June 2018 by the US Food and Drug Administration for the treatment of complicated urinary tract infections, including pyelonephritis, due to Escherichia coli, Klebsiella pneumoniae, Enterobacter cloacae, and Proteus mirabilis. Plazomicin was engineered to overcome the most common aminoglycoside resistance mechanism, inactivation by aminoglycoside-modifying enzymes, but is not active against the less common 16S ribosomal RNA methyltransferases (16S-RMTase), which confer target site modification. As an aminoglycoside, plazomicin maintains activity against Enterobacteriaceae that express resistance mechanisms to other antibiotic classes, including metallo-ß-lactamases. Therefore, in the absence of a 16S-RMTase, plazomicin is active against metallo-ß-lactamase-producing Enterobacteriaceae.

Once-Daily Plazomicin for Complicated Urinary Tract Infections.

BACKGROUND: The increasing multidrug resistance among gram-negative uropathogens necessitates new treatments for serious infections. Plazomicin is an aminoglycoside with bactericidal activity against multidrug-resistant (including carbapenem-resistant) Enterobacteriaceae. METHODS: We randomly assigned 609 patients with complicated urinary tract infections (UTIs), including acute pyelonephritis, in a 1:1 ratio to receive intravenous plazomicin (15 mg per kilogram of body weight once daily) or meropenem (1 g every 8 hours), with optional oral step-down therapy after at least 4 days of intravenous therapy, for a total of 7 to 10 days of therapy. The primary objective was to show the noninferiority of plazomicin to meropenem in the treatment of complicated UTIs, including acute pyelonephritis, with a noninferiority margin of 15 percentage points. The primary end points were composite cure (clinical cure and microbiologic eradication) at day 5 and at the test-of-cure visit (15 to 19 days after initiation of therapy) in the microbiologic modified intention-to-treat population. RESULTS: Plazomicin was noninferior to meropenem with respect to the primary efficacy end points. At day 5, composite cure was observed in 88.0% of the patients (168 of 191 patients) in the plazomicin group and in 91.4% (180 of 197 patients) in the meropenem group (difference, -3.4 percentage points; 95% confidence interval [CI], -10.0 to 3.1). At the test-of-cure visit, composite cure was observed in 81.7% (156 of 191 patients) and 70.1% (138 of 197 patients), respectively (difference, 11.6 percentage points; 95% CI, 2.7 to 20.3). At the test-of-cure visit, a higher percentage of patients in the plazomicin group than in the meropenem group were found to have microbiologic eradication, including eradication of Enterobacteriaceae that were not susceptible to aminoglycosides (78.8% vs. 68.6%) and Enterobacteriaceae that produce extended-spectrum ß-lactamases (82.4% vs. 75.0%). At late follow-up (24 to 32 days after initiation of therapy), fewer patients in the plazomicin group than in the meropenem group had microbiologic recurrence (3.7% vs. 8.1%) or clinical relapse (1.6% vs. 7.1%). Increases in serum creatinine levels of 0.5 mg or more per deciliter (≥40 µmol per liter) above baseline occurred in 7.0% of patients in the plazomicin group and in 4.0% in the meropenem group. CONCLUSIONS: Once-daily plazomicin was noninferior to meropenem for the treatment of complicated UTIs and acute pyelonephritis caused by Enterobacteriaceae, including multidrug-resistant strains. (Funded by Achaogen and the Biomedical Advanced Research and Development Authority; EPIC ClinicalTrials.gov number, NCT02486627.).

In vitro activity of Plazomicin against Enterobacteriaceae isolates carrying genes encoding aminoglycoside-modifying enzymes most common in US Census divisions.

Aminoglycoside-nonsusceptible isolates of Escherichia coli, Klebsiella, Proteus, and Enterobacter species (480/3675) from US hospitals collected during 2014-2015 were screened for 16S rRNA methyltransferase and aminoglycoside-modifying enzyme (AME) genes. Only 5 isolates had high aminoglycoside MICs and carried 16S rRNA methyltransferases. AME genes were observed among 89.7% (426/475) of isolates and the most common genes were aac(3)-IIa (n = 270) and aac(6')-Ib (n = 269). Among other genes, ant(2″)-Ia, aac(3)-Iva, and aph(3')-VIa were observed among 36, 23, and 3 isolates, respectively. Forty-nine (10.3%) isolates yielded negative results for the investigated AME genes. Plazomicin (MIC50/90, 0.5/1 µg/ml) inhibited 99.3% of the AME-carrying isolates at its susceptible breakpoint while amikacin, gentamicin, and tobramycin inhibited 90.1%, 20.9%, and 18.3%, respectively. Plazomicin was approved by the US Food and Drug Administration in June 2018 for the treatment of complicated urinary tract infections when limited treatment options are available. This agent displayed activity against isolates carrying AMEs that were resistance to other aminoglycosides and comparator agents.

Aminoglycoside Revival: Review of a Historically Important Class of Antimicrobials Undergoing Rejuvenation.

Aminoglycosides are cidal inhibitors of bacterial protein synthesis that have been utilized for the treatment of serious bacterial infections for almost 80 years. There have been approximately 15 members of this class approved worldwide for the treatment of a variety of infections, many serious and life threatening. While aminoglycoside use declined due to the introduction of other antibiotic classes such as cephalosporins, fluoroquinolones, and carbapenems, there has been a resurgence of interest in the class as multidrug-resistant pathogens have spread globally. Furthermore, aminoglycosides are recommended as part of combination therapy for empiric treatment of certain difficult-to-treat infections. The development of semisynthetic aminoglycosides designed to overcome common aminoglycoside resistance mechanisms, and the shift to once-daily dosing, has spurred renewed interest in the class. Plazomicin is the first new aminoglycoside to be approved by the FDA in nearly 40 years, marking the successful start of a new campaign to rejuvenate the class.

Activity of plazomicin compared with other aminoglycosides against isolates from European and adjacent countries, including Enterobacteriaceae molecularly characterized for aminoglycoside-modifying enzymes and other resistance mechanisms.

Background: Plazomicin is a next-generation aminoglycoside that was developed to overcome common aminoglycoside-resistance mechanisms. Objectives: We evaluated the activity of plazomicin and comparators against clinical isolates collected from 26 European and adjacent countries during 2014 and 2015 as part of the Antimicrobial Longitudinal Evaluation and Resistance Trends (ALERT) global surveillance programme. Methods: All 4680 isolates collected from 45 hospitals were tested for susceptibility to antimicrobials using the reference broth microdilution method. Selected isolates were screened for genes encoding carbapenemases, aminoglycoside-modifying enzymes (AMEs) and 16S rRNA methyltransferases. Results: Plazomicin (MIC50/90 0.5/2 mg/L) inhibited 95.8% of Enterobacteriaceae at ≤2 mg/L, including carbapenem-resistant Enterobacteriaceae (MIC50/90 0.25/128 mg/L). Plazomicin was more active compared with other aminoglycosides against isolates carrying blaKPC (MIC50/90 0.25/2 mg/L), isolates carrying blaOXA-48-like (MIC50/90 0.25/16 mg/L) and carbapenemase-negative isolates (MIC50/90 0.25/1 mg/L). Approximately 60% of the isolates harbouring blaVIM and blaNDM-1 carried 16S rRNA methyltransferases (mainly rmtB and armA). AME genes were detected among 728 isolates and 99.0% of these were inhibited by plazomicin at ≤2 mg/L. Plazomicin activity against Pseudomonas aeruginosa (MIC50/90 4/8 mg/L) was similar to amikacin activity (MIC50/90 2/16 mg/L). Plazomicin demonstrated activity against CoNS (MIC50/90 0.12/0.25 mg/L) and Staphylococcus aureus (MIC50/90 0.5/1 mg/L). Plazomicin activity was limited against Acinetobacter spp. (MIC50/90 8/>128 mg/L), Enterococcus spp. (MIC50/90 32/128 mg/L) and Streptococcus pneumoniae (MIC50/90 32/64 mg/L). Conclusions: Plazomicin demonstrated activity against Enterobacteriaceae isolates tested in this study, including isolates carrying AMEs and a high percentage of the carbapenem-non-susceptible isolates. Plazomicin displayed activity against staphylococci.