Neutrophil-mediated hypoxia drives pathogenic CD8+ T cell responses in cutaneous leishmaniasis.

Cutaneous leishmaniasis caused by Leishmania parasites exhibits a wide range of clinical manifestations. Although parasites influence disease severity, cytolytic CD8+ T cell responses mediate disease. Although these responses originate in the lymph node, we found that expression of the cytolytic effector molecule granzyme B was restricted to lesional CD8+ T cells in Leishmania-infected mice, suggesting that local cues within inflamed skin induced cytolytic function. Expression of Blimp-1 (Prdm1), a transcription factor necessary for cytolytic CD8+ T cell differentiation, was driven by hypoxia within the inflamed skin. Hypoxia was further enhanced by the recruitment of neutrophils that consumed oxygen to produce ROS and ultimately increased the hypoxic state and granzyme B expression in CD8+ T cells. Importantly, lesions from patients with cutaneous leishmaniasis exhibited hypoxia transcription signatures that correlated with the presence of neutrophils. Thus, targeting hypoxia-driven signals that support local differentiation of cytolytic CD8+ T cells may improve the prognosis for patients with cutaneous leishmaniasis, as well as for other inflammatory skin diseases in which cytolytic CD8+ T cells contribute to pathogenesis.

In vitro activity of sulbactam-durlobactam against colistin-resistant and/or cefiderocol-non-susceptible, carbapenem-resistant Acinetobacter baumannii collected in U.S. hospitals.

The activity of a novel ß-lactamase inhibitor combination, sulbactam-durlobactam (SUL-DUR), was tested against 87 colistin-resistant and/or cefiderocol-non-susceptible carbapenem-resistant Acinetobacter baumannii clinical isolates collected from U.S. hospitals between 2017 and 2019. Among them, 89% and 97% were susceptible to SUL-DUR and imipenem plus SUL-DUR, with MIC50/MIC90 values of 2 µg/mL/8 µg/mL and 1 µg/mL/4 µg/mL, respectively. The presence of amino acid substitutions in penicillin-binding protein 3, including previously reported A515V or T526S, was associated with SUL-DUR non-susceptibility.

Reproductive risk factors for breast cancer and association with novel breast density measurements among Hispanic, Black, and White women.

PURPOSE: There are differences in the distributions of breast cancer incidence and risk factors by race and ethnicity. Given the strong association between breast density and breast cancer, it is of interest describe racial and ethnic variation in the determinants of breast density. METHODS: We characterized racial and ethnic variation in reproductive history and several measures of breast density for Hispanic (n = 286), non-Hispanic Black (n = 255), and non-Hispanic White (n = 1694) women imaged at a single hospital. We quantified associations between reproductive factors and percent volumetric density (PVD), dense volume (DV), non-dense volume (NDV), and a novel measure of pixel intensity variation (V) using multivariable-adjusted linear regression, and tested for statistical heterogeneity by race and ethnicity. RESULTS: Reproductive factors most strongly associated with breast density were age at menarche, parity, and oral contraceptive use. Variation by race and ethnicity was most evident for the associations between reproductive factors and NDV (minimum p-heterogeneity:0.008) and V (minimum p-heterogeneity:0.004) and least evident for PVD (minimum p-heterogeneity:0.042) and DV (minimum p-heterogeneity:0.041). CONCLUSION: Reproductive choices, particularly those related to childbearing and oral contraceptive use, may contribute to racial and ethnic variation in breast density.

Breast density analysis of digital breast tomosynthesis.

Mammography shifted to digital breast tomosynthesis (DBT) in the US. An automated percentage of breast density (PD) technique designed for two-dimensional (2D) applications was evaluated with DBT using several breast cancer risk prediction measures: normalized-volumetric; dense volume; applied to the volume slices and averaged (slice-mean); and applied to synthetic 2D images. Volumetric measures were derived theoretically. PD was modeled as a function of compressed breast thickness (CBT). The mean and standard deviation of the pixel values were investigated. A matched case-control (CC) study (n = 426 pairs) was evaluated. Odd ratios (ORs) were estimated with 95% confidence intervals. ORs were significant for PD: identical for volumetric and slice-mean measures [OR = 1.43 (1.18, 1.72)] and [OR = 1.44 (1.18, 1.75)] for synthetic images. A 2nd degree polynomial (concave-down) was used to model PD as a function of CBT: location of the maximum PD value was similar across CCs, occurring at 0.41 × CBT, and PD was significant [OR = 1.47 (1.21, 1.78)]. The means from the volume and synthetic images were also significant [ORs ~ 1.31 (1.09, 1.57)]. An alternative standardized 2D synthetic image was constructed, where each pixel value represents the percentage of breast density above its location. Several measures were significant and an alternative method for constructing a standardized 2D synthetic image was produced.

Pathogenic CD8 T cell responses are driven by neutrophil-mediated hypoxia in cutaneous leishmaniasis.

Cutaneous leishmaniasis caused by Leishmania parasites exhibits a wide range of clinical manifestations. Although parasites influence disease severity, cytolytic CD8 T cell responses mediate disease. While these responses originate in the lymph node, we find that expression of the cytolytic effector molecule granzyme B is restricted to lesional CD8 T cells in Leishmania - infected mice, suggesting that local cues within inflamed skin induce cytolytic function. Expression of Blimp-1 ( Prdm1 ), a transcription factor necessary for cytolytic CD8 T cell differentiation, is driven by hypoxia within the inflamed skin. Hypoxia is further enhanced by the recruitment of neutrophils that consume oxygen to produce reactive oxygen species, ultimately increasing granzyme B expression in CD8 T cells. Importantly, lesions from cutaneous leishmaniasis patients exhibit hypoxia transcription signatures that correlate with the presence of neutrophils. Thus, targeting hypoxia-driven signals that support local differentiation of cytolytic CD8 T cells may improve the prognosis for patients with cutaneous leishmaniasis, as well as other inflammatory skin diseases where cytolytic CD8 T cells contribute to pathogenesis.

Techniques to produce and evaluate realistic multivariate synthetic data.

Data modeling requires a sufficient sample size for reproducibility. A small sample size can inhibit model evaluation. A synthetic data generation technique addressing this small sample size problem is evaluated: from the space of arbitrarily distributed samples, a subgroup (class) has a latent multivariate normal characteristic; synthetic data can be generated from this class with univariate kernel density estimation (KDE); and synthetic samples are statistically like their respective samples. Three samples (n = 667) were investigated with 10 input variables (X). KDE was used to augment the sample size in X. Maps produced univariate normal variables in Y. Principal component analysis in Y produced uncorrelated variables in T, where the probability density functions were approximated as normal and characterized; synthetic data was generated with normally distributed univariate random variables in T. Reversing each step produced synthetic data in Y and X. All samples were approximately multivariate normal in Y, permitting the generation of synthetic data. Probability density function and covariance comparisons showed similarity between samples and synthetic samples. A class of samples has a latent normal characteristic. For such samples, this approach offers a solution to the small sample size problem. Further studies are required to understand this latent class.

Breast Density Analysis Using Digital Breast Tomosynthesis.

We evaluated an automated percentage of breast density (BD) technique (PDa) with digital breast tomosynthesis (DBT) data. The approach is based on the wavelet expansion followed by analyzing signal dependent noise. Several measures were investigated as risk factors: normalized volumetric; total dense volume; average of the DBT slices (slice-mean); a two-dimensional (2D) metric applied to the synthetic images; and the mean and standard deviations of the pixel values. Volumetric measures were derived theoretically, and PDa was modeled as a function of compressed breast thickness. An alternative method for constructing synthetic 2D mammograms was investigated using the volume results. A matched case-control study (n = 426 pairs) was analyzed. Conditional logistic regression modeling, controlling body mass index and ethnicity, was used to estimate odds ratios (ORs) for each measure with 95% confidence intervals provided parenthetically. There were several significant findings: volumetric measure [OR = 1.43 (1.18, 1.72)], which produced an identical OR as the slice-mean measure as predicted; [OR =1.44 (1.18, 1.75)] when applied to the synthetic images; and mean of the pixel values (volume or 2D synthetic) [ORs ~ 1.31 (1.09, 1.57)]. PDa was modeled as 2nd degree polynomial (concave-down): its maximum value occurred at 0.41×(compressed breast thickness), which was similar across case-control groups, and was significant from this position [OR = 1.47 (1.21, 1.78)]. A standardized 2D synthetic image was produced, where each pixel value represents the percentage of BD above its location. The significant findings indicate the validity of the technique. Derivations supported by empirical analyses produced a new synthetic 2D standardized image technique. Ancillary to the objectives, the results provide evidence for understanding the percentage of BD measure applied to 2D mammograms. Notwithstanding the findings, the study design provides a template for investigating other measures such as texture.

In Vitro Evolution of Cefiderocol Resistance in an NDM-Producing Klebsiella pneumoniae Due to Functional Loss of CirA.

By serially exposing an NDM-producing Klebsiella pneumoniae clinical strain to cefiderocol, we obtained a mutant with cefiderocol MIC of >128 µg/ml. The mutant contained an early stop codon in the iron transporter gene cirA, and its complementation fully restored susceptibility. The cirA-deficient mutant was competed out by the parental strain in vitro, suggesting reduced fitness. IMPORTANCE Cefiderocol, a newly approved cephalosporin agent with an extensive spectrum of activity against Gram-negative bacteria, is a siderophore cephalosporin that utilizes iron transporters to access the bacterial periplasm. Loss of functional CirA, an iron transporter, has been associated with cefiderocol resistance. Here, we show that such genetic change can be selected under selective pressure and cause high-level cefiderocol resistance, but with a high fitness cost. Whether these resistant mutants can survive beyond selective pressure will inform stewardship of this agent in the clinic.

Mammographic Variation Measures, Breast Density, and Breast Cancer Risk.

OBJECTIVE. Our previous work showed that variation measures, which represent breast architecture derived from mammograms, were significantly associated with breast cancer. For replication purposes, we examined the association of three variation measures (variation [V], which is measured in the image domain, and P1 and p1 [a normalized version of P1], which are derived from restricted regions in the Fourier domain) with breast cancer risk in an independent population. We also compared these measures to volumetric density measures (volumetric percent density [VPD] and dense volume [DV]) from a commercial product. MATERIALS AND METHODS. We examined 514 patients with breast cancer and 1377 control patients from a screening practice who were matched for age, date of examination, mammography unit, facility, and state of residence. Spearman rank-order correlation was used to evaluate the monotonic association between measures. Breast cancer associations were estimated using conditional logistic regression, after adjustment for age and body mass index. Odds ratios were calculated per SD increment in mammographic measure. RESULTS. These variation measures were strongly correlated with VPD (correlation, 0.68-0.80) but not with DV (correlation, 0.31-0.48). Similar to previous findings, all variation measures were significantly associated with breast cancer (odds ratio per SD: 1.30 [95% CI, 1.16-1.46] for V, 1.55 [95% CI, 1.35-1.77] for P1, and 1.51 [95% CI, 1.33-1.72] for p1). Associations of volumetric density measures with breast cancer were similar (odds ratio per SD: 1.54 [95% CI, 1.33-1.78] for VPD and 1.34 [95% CI, 1.20-1.50] for DV). When DV was included with each variation measure in the same model, all measures retained significance. CONCLUSION. Variation measures were significantly associated with breast cancer risk (comparable to the volumetric density measures) but were independent of the DV.

Automated percent mammographic density, mammographic texture variation, and risk of breast cancer: a nested case-control study.

Percent mammographic density (PMD) is a strong breast cancer risk factor, however, other mammographic features, such as V, the standard deviation (SD) of pixel intensity, may be associated with risk. We assessed whether PMD, automated PMD (APD), and V, yielded independent associations with breast cancer risk. We included 1900 breast cancer cases and 3921 matched controls from the Nurses' Health Study (NHS) and the NHSII. Using digitized film mammograms, we estimated PMD using a computer-assisted thresholding technique. APD and V were determined using an automated computer algorithm. We used logistic regression to generate odds ratios (ORs) and 95% confidence intervals (CIs). Median time from mammogram to diagnosis was 4.1 years (interquartile range: 1.6-6.8 years). PMD (OR per SD:1.52, 95% CI: 1.42, 1.63), APD (OR per SD:1.32, 95% CI: 1.24, 1.41), and V (OR per SD:1.32, 95% CI: 1.24, 1.40) were positively associated with breast cancer risk. Associations for APD were attenuated but remained statistically significant after mutual adjustment for PMD or V. Women in the highest quartile of both APD and V (OR vs Q1/Q1: 2.49, 95% CI: 2.02, 3.06), or PMD and V (OR vs Q1/Q1: 3.57, 95% CI: 2.79, 4.58) had increased breast cancer risk. An automated method of PMD assessment is feasible and yields similar, but somewhat weaker, estimates to a manual measure. PMD, APD and V are each independently, positively associated with breast cancer risk. Women with dense breasts and greater texture variation are at the highest relative risk of breast cancer.

Molecular characterization of clinical carbapenem-resistant Enterobacterales from Qatar.

One hundred forty-nine carbapenem-resistant Enterobacterales from clinical samples obtained between April 2014 and November 2017 were subjected to whole genome sequencing and multi-locus sequence typing. Klebsiella pneumoniae (81, 54.4%) and Escherichia coli (38, 25.5%) were the most common species. Genes encoding metallo-ß-lactamases were detected in 68 (45.8%) isolates, and OXA-48-like enzymes in 60 (40.3%). blaNDM-1 (45; 30.2%) and blaOXA-48 (29; 19.5%) were the most frequent. KPC-encoding genes were identified in 5 (3.6%) isolates. Most common sequence types were E. coli ST410 (8; 21.1%) and ST38 (7; 18.4%), and K. pneumoniae ST147 (13; 16%) and ST231 (7; 8.6%).

Initiatives to Reduce Maternal Mortality and Severe Maternal Morbidity in the United States : A Narrative Review.

Maternal mortality and severe maternal morbidity are critical health issues in the United States, with unacceptably high rates and racial, ethnic, and geographic disparities. Various factors contribute to these adverse maternal health outcomes, ranging from patient-level to health system-level factors. Furthermore, a majority of pregnancy-related deaths are preventable. This review briefly describes the epidemiology of maternal mortality and severe maternal morbidity in the United States and discusses selected initiatives to reduce maternal mortality and severe maternal morbidity in the areas of data and surveillance; clinical workforce training and patient education; telehealth; comprehensive models and strategies; and clinical guidelines, protocols, and bundles. Related Health Resources and Services Administration initiatives are also described.

KPC-3-Producing Serratia marcescens Outbreak between Acute and Long-Term Care Facilities, Florida, USA.

We describe an outbreak caused by Serratia marcescens carrying blaKPC-3 that was sourced to a long-term care facility in Florida, USA. Whole-genome sequencing and plasmid profiling showed involvement of 3 clonal lineages of S. marcescens and 2 blaKPC-3-carrying plasmids. Determining the resistance mechanism is critical for timely implementation of infection control measures.

Epidemiology of carbapenem-resistant Enterobacteriaceae in hospitals of a large healthcare system in Miami, Florida from 2012 to 2016: Five years of experience with an internal registry.

BACKGROUND: Carbapenem-resistant Enterobacteriaceae (CRE) is an urgent public health threat globally. Limited data are available regarding the epidemiology of CRE in South Florida. We describe the epidemiology of CRE within a large public healthcare system in Miami, FL, the experience with an internal registry, active surveillance testing, and the impact of infection prevention practices. METHODS: Retrospective cohort study in 4 hospitals from a large healthcare system in Miami-Dade County, FL from 2012 to 2016. The internal registry included all CRE cases from active surveillance testing from rectal and/or tracheal screening occurring in the intensive care units of 2 of the hospitals and clinical cultures across the healthcare system. All CRE cases were tagged in the electronic medical record and automatically entered into a platform for automatic infection control surveillance. The system alerted about new cases, readmissions, and transfers. RESULTS: A total of 371 CRE cases were identified. The overall prevalence was 0.077 cases per 100 patient-admissions; the admission prevalence was 0.019 per 100 patient-admissions, and the incidence density was 1.46 cases per 10,000 patient-days. Rates increased during the first 3 years of the study and declined later to a lower level than at the beginning of study period. CONCLUSIONS: Active surveillance testing and the use of an internal registry facilitated prompt identification of cases contributing to control increasing rates of CRE by rapid implementation of infection prevention strategies.

Empirically-derived synthetic populations to mitigate small sample sizes.

Limited sample sizes can lead to spurious modeling findings in biomedical research. The objective of this work is to present a new method to generate synthetic populations (SPs) from limited samples using matched case-control data (n = 180 pairs), considered as two separate limited samples. SPs were generated with multivariate kernel density estimations (KDEs) with unconstrained bandwidth matrices. We included four continuous variables and one categorical variable for each individual. Bandwidth matrices were determined with Differential Evolution (DE) optimization by covariance comparisons. Four synthetic samples (n = 180) were derived from their respective SPs. Similarity between observed samples with synthetic samples was compared assuming their empirical probability density functions (EPDFs) were similar. EPDFs were compared with the maximum mean discrepancy (MMD) test statistic based on the Kernel Two-Sample Test. To evaluate similarity within a modeling context, EPDFs derived from the Principal Component Analysis (PCA) scores and residuals were summarized with the distance to the model in X-space (DModX) as additional comparisons. Four SPs were generated from each sample. The probability of selecting a replicate when randomly constructing synthetic samples (n = 180) was infinitesimally small. MMD tests indicated that the observed sample EPDFs were similar to the respective synthetic EPDFs. For the samples, PCA scores and residuals did not deviate significantly when compared with their respective synthetic samples. The feasibility of this approach was demonstrated by producing synthetic data at the individual level, statistically similar to the observed samples. The methodology coupled KDE with DE optimization and deployed novel similarity metrics derived from PCA. This approach could be used to generate larger-sized synthetic samples. To develop this approach into a research tool for data exploration purposes, additional evaluation with increased dimensionality is required. Moreover, given a fully specified population, the degree to which individuals can be discarded while synthesizing the respective population accurately will be investigated. When these objectives are addressed, comparisons with other techniques such as bootstrapping will be required for a complete evaluation.

Early-Life and Adult Anthropometrics in Relation to Mammographic Image Intensity Variation in the Nurses' Health Studies.

BACKGROUND: The V measure captures grayscale intensity variation on a mammogram and is positively associated with breast cancer risk, independent of percent mammographic density (PMD), an established marker of breast cancer risk. We examined whether anthropometrics are associated with V, independent of PMD. METHODS: The analysis included 1,700 premenopausal and 1,947 postmenopausal women without breast cancer within the Nurses' Health Study (NHS) and NHSII. Participants recalled their body fatness at ages 5, 10, and 20 years using a 9-level pictogram (level 1: most lean) and reported weight at age 18 years, current adult weight, and adult height. V was estimated by calculating standard deviation of pixels on screening mammograms. Linear mixed models were used to estimate beta coefficients (ß) and 95% confidence intervals (CI) for the relationships between anthropometric measures and V, adjusting for confounders and PMD. RESULTS: V and PMD were positively correlated (Spearman r = 0.60). Higher average body fatness at ages 5 to 10 years (level ≥ 4.5 vs. 1) was significantly associated with lower V in premenopausal (ß = -0.32; 95% CI, -0.48 to -0.16) and postmenopausal (ß = -0.24; 95% CI, -0.37 to -0.10) women, independent of current body mass index (BMI) and PMD. Similar inverse associations were observed with average body fatness at ages 10 to 20 years and BMI at age 18 years. Current BMI was inversely associated with V, but the associations were largely attenuated after adjustment for PMD. Height was not associated with V. CONCLUSIONS: Our data suggest that early-life body fatness may reflect lifelong impact on breast tissue architecture beyond breast density. However, further studies are needed to confirm the results. IMPACT: This study highlights strong inverse associations of early-life adiposity with mammographic image intensity variation.

Spatial Correlation and Breast Cancer Risk.

We present a novel method for evaluating local spatial correlation structure in two-dimensional (2D) mammograms and evaluate its capability for risk prediction as one possible application. Two matched case-control studies were analyzed. Study 1 included women (N = 588 pairs) with mammograms acquired with either Hologic Selenia full field digital mammography (FFDM) units or Hologic Dimensions digital breast tomosynthesis units. Study 2 included women (N =180 pairs) with mammograms acquired with a General Electric Senographe 2000D FFDM unit. Matching variables included age, HRT usage/duration, screening history, and mammography unit. Local autocorrelation functions were determined with Fourier analysis and compared with a template defined as a 2D double-sided exponential function with one spatial extent parameter: n = 4, 12, 24, 50, 74, 100, and 124, where (n+1)×(n+1) is the area of the local spatial extent measured in pixels. The difference between the local correlation and template was gauged within an adjustable parameter kernel and summarized, producing two measures: the mean (mn+1), and standard deviation (sn+1). Both adjustable parameters were varied in Study 1. Select measures that produced significant associations with breast cancer were translated to Study 2. Breast cancer associations were evaluated with conditional logistic regression, adjusted for body mass index and ethnicity. Odds ratios (ORs) were estimated as per standard deviation increment with 95% confidence intervals (CIs). Two measures were selected for breast cancer association analysis in Study 1: m75 and s25. Both measures revealed significant associations with breast cancer: OR = 1.45 (1.23, 1.66) for m75 and OR = 1.30 (1.14, 1.49) for s25. When translating to Study 2, these measures also revealed significant associations: OR = 1.49 (1.12, 1.96) for m75 and OR = 1.34 (1.06, 1.69) for s25. Novel correlation metrics presented in this work produced significant associations with breast cancer risk. This approach is general and may have applications beyond mammography.

Technical challenges in generalizing calibration techniques for breast density measurements.

PURPOSE: We are developing a calibration methodology for full-field digital mammography (FFDM). Calibration compensates for image acquisition technique influences on the pixel representation, ideally producing improved inter-image breast density estimates. This approach relies on establishing references with rigid breast tissue-equivalent phantoms (BTEs) and requires an accurate estimate of the compressed breast thickness because the system readout is nominal. There is also an attenuation mismatch between adipose breast tissue and the adipose BTE that was noted in our previous work. It is referred to as the "attenuation anomaly" and addressed in this report. The objectives are to evaluate methods to correct for the compressed breast thickness and compensate for the attenuation anomaly. METHODS: Thickness correction surfaces were established with a deformable phantom (DP) using both image and physical measurements for three direct x-ray conversion FFDM units. The Cumulative Sum serial quality control procedure was established to ensure the thickness correction measurements were stable over time by imaging and calibrating DPs biweekly in lieu of physical measurements. The attenuation anomaly was addressed by evaluating adipose image regions coupled with an optimization technique to adjust the adipose calibration data. We compared calibration consistency across matched left and right cranial caudal (CC) mammographic views (n = 199) with and without corrections using Bland-Altman plots. These plots were complemented by comparing the right and left breast calibrated average (µa ) and population distribution mean (ma ) with 95% confidence intervals and difference distribution variances with the F-test for uncorrected and corrected data. RESULTS: Thickness correction surfaces were well approximated as tilted planes and were dependent upon compression force. A correction was developed for the attenuation anomaly. All paddles (large and small paddles for all units) exhibited similar tilt as a function of force. Without correction, ma  = 0.92 (-1.77, 3.62) was not significantly different from zero with many negative µa samples. The thickness correction produced a significant shift in the µa distribution in the positive direction with ma  = 13.99 (11.17, 16.80) and reduced the difference distribution variance significantly (P < 0.0001). Applying both corrections in tandem gave ma  = 22.83 (20.32, 25.34), representing another significant positive shift in comparison with the thickness correction in isolation. Thickness corrections were stable over approximately a 2-year timeframe for all units. CONCLUSION: These correction techniques are valid approaches for addressing technical problems with calibration that relies on reference phantoms. The efficacy of the calibration methodology will require validation with clinical endpoints in future studies.

Calibrated Breast Density Measurements.

RATIONALE AND OBJECTIVES: Mammographic density is an important risk factor for breast cancer, but translation to the clinic requires assurance that prior work based on mammography is applicable to current technologies. The purpose of this work is to evaluate whether a calibration methodology developed previously produces breast density metrics predictive of breast cancer risk when applied to a case-control study. MATERIALS AND METHODS: A matched case control study (n = 319 pairs) was used to evaluate two calibrated measures of breast density. Two-dimensional mammograms were acquired from six Hologic mammography units: three conventional Selenia two-dimensional full-field digital mammography systems and three Dimensions digital breast tomosynthesis systems. We evaluated the capability of two calibrated breast density measures to quantify breast cancer risk: the mean (PGm) and standard deviation (PGsd) of the calibrated pixels. Matching variables included age, hormone replacement therapy usage/duration, screening history, and mammography unit. Calibrated measures were compared to the percentage of breast density (PD) determined with the operator-assisted Cumulus method. Conditional logistic regression was used to generate odds ratios (ORs) from continuous and quartile (Q) models with 95% confidence intervals. The area under the receiver operating characteristic curve (Az) was also used as a comparison metric. Both univariate models and models adjusted for body mass index and ethnicity were evaluated. RESULTS: In adjusted models, both PGsd and PD were statistically significantly associated with breast cancer with similar Az of 0.61-0.62. The corresponding ORs and confidence intervals were also similar. For PGsd, the OR was 1.34 (1.09, 1.66) for the continuous measure and 1.83 (1.11, 3.02), 2.19 (1.28, 3.73), and 2.20 (1.26, 3.85) for Q2-Q4. For PD, the OR was 1.43 (1.16, 1.76) for the continuous measure and 0.84 (0.52, 1.38), 1.96 (1.19, 3.23), and 2.27 (1.29, 4.00) for Q2-Q4. The results for PGm were slightly attenuated and not statistically significant. The OR was 1.22 (0.99, 1.51) with Az = 0.60 for the continuous measure and 1.24 (0.78, 1.97), 0.98 (0.60, 1.61), and 1.26, (0.77, 2.07) for Q2-Q4 with Az = 0.60. CONCLUSION: The calibrated PGsd measure provided significant associations with breast cancer comparable to those given by PD. The calibrated PGm performed slightly worse. These findings indicate that the calibration approach developed previously replicates under more general conditions.

A Prospective Study of Acinetobacter baumannii Complex Isolates and Colistin Susceptibility Monitoring by Mass Spectrometry of Microbial Membrane Glycolipids.

Acinetobacter baumannii is a prevalent nosocomial pathogen with a high incidence of multidrug resistance. Treatment of infections due to this organism with colistin, a last-resort antibiotic of the polymyxin class, can result in the emergence of colistin-resistant strains. Colistin resistance primarily occurs via modifications of the terminal phosphate moieties of lipopolysaccharide-derived lipid A, which reduces overall membrane electronegativity. These modifications are readily identified by mass spectrometry (MS). In this study, we prospectively collected Acinetobacter baumannii complex clinical isolates from a hospital system in Pennsylvania over a 3-year period. All isolates were evaluated for colistin resistance using standard MIC testing by both agar dilution and broth microdilution, as well as genospecies identification and lipid A profiling using MS analyses. Overall, an excellent correlation between colistin susceptibility and resistance, determined by MIC testing, and the presence of a lipid A modification, determined by MS, was observed with a sensitivity of 92.9% and a specificity of 94.0%. Additionally, glycolipid profiling was able to differentiate A. baumannii complex organisms based on their membrane lipids. With the growth of MS use in clinical laboratories, a reliable MS-based glycolipid phenotyping method that identifies colistin resistance in A. baumannii complex clinical isolates, as well as other Gram-negative organisms, represents an alternative or complementary approach to existing diagnostics.