Prediction of complete remission and survival in acute myeloid leukemia using supervised machine learning.

Achievement of complete remission signifies a crucial milestone in the therapy of acute myeloid leukemia (AML) while refractory disease is associated with dismal outcomes. Hence, accurately identifying patients at risk is essential to tailor treatment concepts individually to disease biology. We used nine machine learning (ML) models to predict complete remission and 2-year overall survival in a large multicenter cohort of 1,383 AML patients who received intensive induction therapy. Clinical, laboratory, cytogenetic and molecular genetic data were incorporated and our results were validated on an external multicenter cohort. Our ML models autonomously selected predictive features including established markers of favorable or adverse risk as well as identifying markers of so-far controversial relevance. De novo AML, extramedullary AML, double-mutated CEBPA, mutations of CEBPA-bZIP, NPM1, FLT3-ITD, ASXL1, RUNX1, SF3B1, IKZF1, TP53, and U2AF1, t(8;21), inv(16)/t(16;16), del(5)/del(5q), del(17)/del(17p), normal or complex karyotypes, age and hemoglobin concentration at initial diagnosis were statistically significant markers predictive of complete remission, while t(8;21), del(5)/del(5q), inv(16)/t(16;16), del(17)/del(17p), double-mutated CEBPA, CEBPA-bZIP, NPM1, FLT3-ITD, DNMT3A, SF3B1, U2AF1, and TP53 mutations, age, white blood cell count, peripheral blast count, serum lactate dehydrogenase level and hemoglobin concentration at initial diagnosis as well as extramedullary manifestations were predictive for 2-year overall survival. For prediction of complete remission and 2-year overall survival areas under the receiver operating characteristic curves ranged between 0.77-0.86 and between 0.63-0.74, respectively in our test set, and between 0.71-0.80 and 0.65-0.75 in the external validation cohort. We demonstrated the feasibility of ML for risk stratification in AML as a model disease for hematologic neoplasms, using a scalable and reusable ML framework. Our study illustrates the clinical applicability of ML as a decision support system in hematology.

Synthesis, biological evaluation, and molecular docking studies of aldotetronic acid-based LpxC inhibitors.

In order to develop novel inhibitors of the bacterial deacetylase LpxC bearing a substituent to target the UDP binding site of the enzyme, a series of aldotetronic acid-based hydroxamic acids was accessed in chiral pool syntheses starting from 4,6-O-benzylidene-d-glucose and l-arabinitol. The synthesized hydroxamic acids were tested for LpxC inhibitory activity in vitro, revealing benzyl ether 17a ((2S,3S)-4-(benzyloxy)-N,3-dihydroxy-2-[(4-{[4-(morpholinomethyl)phenyl]ethynyl}benzyl)oxy]butanamide) as the most potent LpxC inhibitor. This compound was additionally tested for antibacterial activity against a panel of clinically relevant Gram-negative bacteria, bacterial uptake, and susceptibility to efflux pumps. Molecular docking studies were performed to rationalize the observed structure-activity relationships.

Antibacterial activity of xylose-derived LpxC inhibitors - Synthesis, biological evaluation and molecular docking studies.

LpxC inhibitors represent a promising class of novel antibiotics selectively combating Gram-negative bacteria. In chiral pool syntheses starting from D- and L-xylose, a series of four 2r,3c,4t-configured C-furanosidic LpxC inhibitors was obtained. The synthesized hydroxamic acids were tested for antibacterial and LpxC inhibitory activity, the acquired biological data were compared with those of previously synthesized C-furanosides, and molecular docking studies were performed to rationalize the observed structure-activity relationships. Additionally, bacterial uptake and susceptibility to efflux pump systems were investigated for the most promising stereoisomers.

Detection of a Novel gyrB Mutation Associated With Fluoroquinolone-Nonsusceptible Salmonella enterica serovar Typhimurium Isolated From a Bloodstream Infection in Ghana.

A multidrug-resistant Salmonella enterica serovar Typhimurium with reduced susceptibility to ciprofloxacin was isolated from the blood of a hospitalized child in Ghana. DNA sequencing identified a novel gyrB mutation at codon 466 (Glu466Asp). An increase in fluoroquinolone susceptibility after the introduction of a wild-type gyrB(+) allele demonstrated that the gyrB466 mutation had a direct effect on fluoroquinolone susceptibility.

The Emergence of Reduced Ciprofloxacin Susceptibility in Salmonella enterica Causing Bloodstream Infections in Rural Ghana.

BACKGROUND: Salmonella ranks among the leading causes of bloodstream infections in sub-Saharan Africa. Multidrug resistant typhoidal and nontyphoidal Salmonella (NTS) isolates have been previously identified in this region. However, resistance to ciprofloxacin has rarely been reported in West Africa. This study aims to assess susceptibility against ciprofloxacin in Salmonella causing invasive bloodstream infections among children in rural Ghana. METHODS: From May 2007 until May 2012, children attending a rural district hospital in central Ghana were eligible for recruitment. Salmonella enterica isolated from blood cultures were assessed for ciprofloxacin susceptibility by Etest (susceptible minimum inhibitory concentration [MIC] ≤ 0.06 µg/mL). The gyrA, gyrB, parC, and parE genes were sequenced to identify mutations associated with changes in susceptibility to fluoroquinolones. RESULTS: Two hundred eighty-five Salmonella enterica isolates from 5211 blood cultures were most commonly identified as Salmonella enterica serovar Typhimurium (n = 129 [45%]), Salmonella enterica serovar Typhi (n = 89 [31%]), Salmonella enterica serovar Dublin (n = 20 [7%]), and Salmonella enterica serovar Enteritidis (n = 19 [7%]). All S. Typhi and S. Dublin were susceptible to ciprofloxacin. Reduced susceptibility (MIC >0.06 µg/mL) was found in 53% (10/19) of S. Enteritidis and in 2% (3/129) of S. Typhimurium isolates. Sequencing detected a single gyrB mutation (Glu466Asp) and a single gyrA mutation (Ser83Tyr) in all 3 S. Typhimurium isolates, while 9 of 10 S. Enteritidis harbored single gyrA mutations (Asp87Gly, Asp87Asn, or Asp87Tyr). No mutations were found in the parC and parE genes. CONCLUSIONS: Ciprofloxacin susceptibility in invasive NTS in rural Ghana is highly dependent on serotype. Although reduced ciprofloxacin susceptibility is low in S. Typhimurium, more than half of all S. Enteritidis isolates are affected. Healthcare practitioners in Ghana should be aware of potential treatment failure in patients with invasive S. Enteritidis infections.

Unsupervised meta-clustering identifies risk clusters in acute myeloid leukemia based on clinical and genetic profiles.

BACKGROUND: Increasingly large and complex biomedical data sets challenge conventional hypothesis-driven analytical approaches, however, data-driven unsupervised learning can detect inherent patterns in such data sets. METHODS: While unsupervised analysis in the medical literature commonly only utilizes a single clustering algorithm for a given data set, we developed a large-scale model with 605 different combinations of target dimensionalities as well as transformation and clustering algorithms and subsequent meta-clustering of individual results. With this model, we investigated a large cohort of 1383 patients from 59 centers in Germany with newly diagnosed acute myeloid leukemia for whom 212 clinical, laboratory, cytogenetic and molecular genetic parameters were available. RESULTS: Unsupervised learning identifies four distinct patient clusters, and statistical analysis shows significant differences in rate of complete remissions, event-free, relapse-free and overall survival between the four clusters. In comparison to the standard-of-care hypothesis-driven European Leukemia Net (ELN2017) risk stratification model, we find all three ELN2017 risk categories being represented in all four clusters in varying proportions indicating unappreciated complexity of AML biology in current established risk stratification models. Further, by using assigned clusters as labels we subsequently train a supervised model to validate cluster assignments on a large external multicenter cohort of 664 intensively treated AML patients. CONCLUSIONS: Dynamic data-driven models are likely more suitable for risk stratification in the context of increasingly complex medical data than rigid hypothesis-driven models to allow for a more personalized treatment allocation and gain novel insights into disease biology.

There are various ways in which clinicians can predict the risk of disease progression in patients with leukemia, helping them to treat the patients accordingly. However, these approaches are usually designed by human experts and might not fully capture the complexity of a patient's disease. Here, with a large cohort of patients with acute myeloid leukemia, we design an unsupervised machine learning model ­ a type of computer model that learns from patterns in data without human input­to separate these patients into subgroups according to risk. We identify four distinct groups which differ with regards to patient genetics, laboratory values, and clinical characteristics. These groups have differences in response to treatment and patient survival, and we validate our findings in another dataset. Our approach might help clinicians to better predict outcomes in patients with leukemia and make decisions on treatment.

Prominence of an O75 clonal group (clonal complex 14) among non-ST131 fluoroquinolone-resistant Escherichia coli causing extraintestinal infections in humans and dogs in Australia.

Fluoroquinolone (FQ)-resistant extraintestinal pathogenic Escherichia coli (FQ(r) ExPEC) strains from phylogenetic group B2 are undergoing epidemic spread. Isolates belonging to phylogenetic group B2 are generally more virulent than other E. coli isolates; therefore, resistance to FQs among group B2 isolates is concerning. Although clonal expansion of sequence type 131 (ST131) is a major factor, the contribution of additional clonal groups has not been quantified. Group B2 FQ(r) ExPEC isolates from humans (n = 250) and dogs (n = 12) in Australia were screened for ST131, a recently recognized and rapidly emerging multidrug-resistant and virulent clonal group that is important in both human and companion animal medicine. Non-ST131 isolates underwent virulence genotyping, PCR-based O typing, partial multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), and FQ resistance mechanism analysis. Of 49 non-ST131 isolates (45 human, 4 canine), 49% (24 human, 2 canine) represented O-type O75 and exhibited conserved virulence genotypes (F10 papA allele, iha, fimH, sat, vat, fyuA, iutA, kpsMII, usp, ompT, malX, K1/K5 capsule) and MLST allele profiles corresponding with clonal complex CC14. Two clusters, each containing canine and human isolates, were identified by PFGE (differentiated by K1 and K5 capsules). Australian FQ(r) O75 isolates exhibited commonality with an historical FQ-susceptible O75 urosepsis isolate (also CC14). The isolation from humans and dogs of highly similar FQ(r) derivatives of the classic O75:K1/K5 (CC14) ExPEC lineage suggests recent acquisition of FQ resistance and potential cross-host-species transfer. This lineage should be targeted with ST131 in future epidemiological investigations of FQ(r) ExPEC.

Commonality among fluoroquinolone-resistant sequence type ST131 extraintestinal Escherichia coli isolates from humans and companion animals in Australia.

Escherichia coli sequence type 131 (ST131), an emergent multidrug-resistant extraintestinal pathogen, has spread epidemically among humans and was recently isolated from companion animals. To assess for human-companion animal commonality among ST131 isolates, 214 fluoroquinolone-resistant extraintestinal E. coli isolates (205 from humans, 9 from companion animals) from diagnostic laboratories in Australia, provisionally identified as ST131 by PCR, selectively underwent PCR-based O typing and bla(CTX-M-15) detection. A subset then underwent multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE) analysis, extended virulence genotyping, antimicrobial susceptibility testing, and fluoroquinolone resistance genotyping. All isolates were O25b positive, except for two O16 isolates and one O157 isolate, which (along with six O25b-positive isolates) were confirmed by MLST to be ST131. Only 12% of isolates (25 human, 1 canine) exhibited bla(CTX-M-15). PFGE analysis of 20 randomly selected human and all 9 companion animal isolates showed multiple instances of ≥94% profile similarity across host species; 12 isolates (6 human, 6 companion animal) represented pulsotype 968, the most prevalent ST131 pulsotype in North America (representing 23% of a large ST131 reference collection). Virulence gene and antimicrobial resistance profiles differed minimally, without host species specificity. The analyzed ST131 isolates also exhibited a conserved, host species-independent pattern of chromosomal fluoroquinolone resistance mutations. However, eight (89%) companion animal isolates, versus two (10%) human isolates, possessed the plasmid-borne qnrB gene (P < 0.001). This extensive across-species strain commonality, plus the similarities between Australian and non-Australian ST131 isolates, suggest that ST131 isolates are exchanged between humans and companion animals both within Australia and intercontinentally.

Antibacterial activity of finafloxacin under different pH conditions against isogenic strains of Escherichia coli expressing combinations of defined mechanisms of fluoroquinolone resistance.

OBJECTIVES: Finafloxacin is an investigational fluoroquinolone exhibiting broad-spectrum activity that is enhanced under slightly acidic conditions (pH 5.0-6.5). The impact of individual and combinations of chromosomal mutations (gyrA, parC and marR) and the plasmid-mediated fluoroquinolone resistance mechanisms QepA1, QnrA1, QnrB1, QnrS1 and AAC(6')-Ib-cr were investigated. METHODS: The MICs of finafloxacin, compared with those of ciprofloxacin, levofloxacin and moxifloxacin, were determined at pH 5.8 and 7.2. RESULTS: MICs of finafloxacin compared with other fluoroquinolones at pH 5.8 were lower by a factor of 2-256. MICs of finafloxacin were unaffected by QepA1. Moreover, finafloxacin appeared not to be a substrate for AAC(6')-Ib-cr. CONCLUSIONS: Compared with ciprofloxacin, levofloxacin and moxifloxacin, finafloxacin shows higher activity especially at pH 5.8 against Escherichia coli mutants expressing known fluoroquinolone resistance determinants alone and in combinations.

Alcohols for skin antisepsis at clinically relevant skin sites.

The antiseptic efficacy of ethanol, isopropanol, and n-propanol at 60%, 70%, and 89.5% (all vol/vol) was analyzed after 2, 3, or 4 min of application to the forehead, back, and abdomen of 180 volunteers by the use of a standardized swab sampling method. Results of recolonization by the aerobic skin flora of the upper arms and backs of 20 volunteers were compared 72 h after treatment with 0.5%, 1%, or 2% chlorhexidine digluconate (CHG) in 89.5% n-propanol. The most effective alcohol at all skin sites was n-propanol, with a mean log(10) reduction of 1.82 after 2 min on the forehead. Efficacy against the aerobic flora of the forehead was mainly influenced by the type of alcohol (P < 0.001), followed by the concentration (P < 0.001) and the application time (P = 0.006). Ethanol and isopropanol were significantly less effective (both P < 0.001). Alcohol supplemented with 0.5% or more CHG was significantly more effective than alcohol alone in the suppression of recolonization (P < 0.05). An 89.5% solution of n-propanol was the most effective alcohol for the reduction of populations of aerobic skin flora. Its combination with CHG is appropriate whenever recolonization of the skin must be limited. Further studies are needed to determine the most effective concentration of CHG in n-propanol to provide the best protection against recolonization of the skin, e.g., for catheter site care.