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ObjectiveThe A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance.MethodsThe A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping.ResultsThirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p

Background The Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 multicenter trial helped confirm the potential of diffusion-weighted MRI for improving differential diagnosis of suspicious breast abnormalities and reducing unnecessary biopsies. A prespecified secondary objective was to explore the relative value of different approaches for quantitative assessment of lesions at diffusion-weighted MRI. Purpose To determine whether alternate calculations of apparent diffusion coefficient (ADC) can help further improve diagnostic performance versus mean ADC values alone for analysis of suspicious breast lesions at MRI. Materials and Methods This prospective trial (ClinicalTrials.gov identifier: NCT02022579) enrolled consecutive women (from March 2014 to April 2015) with a Breast Imaging Reporting and Data System category of 3, 4, or 5 at breast MRI. All study participants underwent standardized diffusion-weighted MRI (b = 0, 100, 600, and 800 sec/mm2). Centralized ADC measures were performed, including manually drawn whole-lesion and hotspot regions of interest, histogram metrics, normalized ADC, and variable b-value combinations. Diagnostic performance was estimated by using the area under the receiver operating characteristic curve (AUC). Reduction in biopsy rate (maintaining 100% sensitivity) was estimated according to thresholds for each ADC metric. Results Among 107 enrolled women, 81 lesions with outcomes (28 malignant and 53 benign) in 67 women (median age, 49 years; interquartile range, 41-60 years) were analyzed. Among ADC metrics tested, none improved diagnostic performance versus standard mean ADC (AUC, 0.59-0.79 vs AUC, 0.75; P = .02-.84), and maximum ADC had worse performance (AUC, 0.52; P < .001). The 25th-percentile ADC metric provided the best performance (AUC, 0.79; 95% CI: 0.70, 0.88), and a threshold using median ADC provided the greatest reduction in biopsy rate of 23.9% (95% CI: 14.8, 32.9; 16 of 67 BI-RADS category 4 and 5 lesions). Nonzero minimum b value (100, 600, and 800 sec/mm2) did not improve the AUC (0.74; P = .28), and several combinations of two b values (0 and 600, 100 and 600, 0 and 800, and 100 and 800 sec/mm2; AUC, 0.73-0.76) provided results similar to those seen with calculations of four b values (AUC, 0.75; P = .17-.87). Conclusion Mean apparent diffusion coefficient calculated with a two-b-value acquisition is a simple and sufficient diffusion-weighted MRI metric to augment diagnostic performance of breast MRI compared with more complex approaches to apparent diffusion coefficient measurement. © RSNA, 2020 Online supplemental material is available for this article.

To measure associations between gardening with different compost amendments and the human gut microbiota composition, gardeners (n = 25) were provided with one of three types of compost: chicken manure (CM), dairy manure and plant material (DMP), or plant-based (P). Stool samples were collected before gardening (T1), after compost amendment (T2), and at peak garden harvest (T3). Compost and soil samples were collected. DNA was extracted, 16S rRNA libraries were established, and libraries were sequenced by Illumina MiSeq. Sequences were processed using mothur, and data were analyzed in R software version 4.2.2. Fast expectation-maximization microbial source tracking analysis was used to determine stool bacteria sources. At T2/T3, the gut microbiotas of P participants had the lowest Shannon alpha diversity, which was also the trend at T1. In stool from T2, Ruminococcus 1 were less abundant in the microbiotas of those using P compost as compared to those using CM or DMP. At T2, Prevotella 9 had the highest abundance in the microbiotas of those using CM compost. In participants who used CM compost to amend their gardening plots, a larger proportion of the human stool bacteria were sourced from CM compared to soil. Soil exposure through gardening was associated with a small but detectable change in the gardeners’ gut microbiota composition. These results suggest that human interactions with soil through gardening could potentially impact health through alterations to the gut microbiota.

Introduction The prevalence of type 2 diabetes (T2D) is increasing in the Latinx community. Despite telehealth and technology becoming more available, these resources are not reaching the Latinx population. Diabetes education is a cornerstone of treatment; however, access to culturally tailored content is a barrier to the Latinx population. Real-time continuous glucose monitoring (RT-CGM) is a patient-empowering tool that can improve glycaemic control, but it is not readily available for Latinx patients with T2D. We aim to evaluate a culturally tailored diabetes self-management education and support (DSMES) curriculum, using a team-based approach to improve glycaemic control, promote healthy behaviours and enhance patient access with the use of telehealth in Latinx individuals. The primary aim of the study is to evaluate the additive effectiveness of RT-CGM on glycaemia and behavioural changes among Latinx patients undergoing a culturally tailored DSMES. A sub aim of the study is to evaluate family members’ change in behaviours.Methods We propose a randomised controlled trial of blinded versus RT-CGM with 100 Latinx participants with T2D who will receive DSMES via telemedicine over 12 weeks (n=50 per group). The study will be conducted at a single large federally qualified health centre system. The control group will receive culturally tailored DSMES and blinded CGM. The intervention group will receive DSMES and RT-CGM. The DSMES is conducted by community health educators weekly over 12 weeks in Spanish or English, based on participant’s language preference. Patients in the RT-CGM group will have cyclical use with a goal of 50 days wear time. The primary outcomes are changes in haemoglobin A1c and CGM-derived metrics at 3 and 6 months. The secondary outcomes include participants’ self-management knowledge and behaviour and household members’ change in lifestyle.Ethics and dissemination The study proposal was approved by the University of Washington ethics/institutional review board (IRB) Committee as minimal risk (IRB ID: STUDY00014396) and the Sea Mar IRB committee.Trial registration number ClinicalTrials.gov identifier: NCT05394844

Oxygen minimum zones (OMZs) are expanding due to increased sea surface temperatures, subsequent increased oxygen demand through respiration, reduced oxygen solubility, and thermal stratification driven in part by anthropogenic climate change. Devil’s Hole, Bermuda is a model ecosystem to study OMZ microbial biogeochemistry because the formation and subsequent overturn of the suboxic zone occur annually. During thermally driven stratification, suboxic conditions develop, with organic matter and nutrients accumulating at depth. In this study, the bioavailability of the accumulated dissolved organic carbon (DOC) and the microbial community response to reoxygenation of suboxic waters was assessed using a simulated overturn experiment. The surface inoculated prokaryotic community responded to the deep (formerly suboxic) 0.2 μm filtrate with cell densities increasing 2.5-fold over 6 days while removing 5 μmol L−1 of DOC. After 12 days, the surface community began to shift, and DOC quality became less diagenetically altered along with an increase in SAR202, a Chloroflexi that can degrade recalcitrant dissolved organic matter (DOM). Labile DOC production after 12 days coincided with an increase of Nitrosopumilales, a chemoautotrophic ammonia oxidizing archaea (AOA) that converts ammonia to nitrite based on the ammonia monooxygenase (amoA) gene copy number and nutrient data. In comparison, the inoculation of the deep anaerobic prokaryotic community into surface 0.2 μm filtrate demonstrated a die-off of 25.5% of the initial inoculum community followed by a 1.5-fold increase in cell densities over 6 days. Within 2 days, the prokaryotic community shifted from a Chlorobiales dominated assemblage to a surface-like heterotrophic community devoid of Chlorobiales. The DOM quality changed to less diagenetically altered material and coincided with an increase in the ribulose-1,5-bisphosphate carboxylase/oxygenase form I (cbbL) gene number followed by an influx of labile DOM. Upon reoxygenation, the deep DOM that accumulated under suboxic conditions is bioavailable to surface prokaryotes that utilize the accumulated DOC initially before switching to a community that can both produce labile DOM via chemoautotrophy and degrade the more recalcitrant DOM.

Introduction:Coxiella burnetii is a zoonotic Gram-negative obligate intracellular bacterial pathogen and the causative agent of query (Q) fever in humans. Contamination of milk by C. burnetii, as a consequence of livestock infection, is a significant public health concern. Effective methods to inactivate C. burnetii in milk are a critical aspect of food safety. Implementation of non-thermal UV-C processing technologies in the dairy industry can effectively preserve the sensory and nutritional quality of raw milk products while ensuring their safety, making them a viable alternative to traditional high-temperature short-time (HTST) pasteurization methods.Methods: Optical light attenuation factors, such as the absorption, scattering, and reflection by skim milk (SM) were evaluated using a spectrophotometer. SM inoculated with an avirulent strain of C. burnetii was irradiated using a collimated beam device equipped with a low-pressure UV-C 254 nm lamp at doses from 0 to 12 mJ/cm2. Optical properties were considered for the evaluation of the delivered UV-C dose. The pasteurization treatment was conducted using a lab scale HTST pasteurizer (72°C/15 s). The verification studies were conducted using Escherichia coli ATCC 25922 inoculated in a phosphate buffer (transparent fluid) and humic acid (opaque fluid). Salmonella enterica serovar Muenchen ATCC BAA 1674 inoculated in SM was tested for its suitability as a surrogate for C. burnetii, a bacterium that requires specialized equipment and expertise for experimentation.Results and Discussion: Absorption, reduced scattering coefficient, and the reflectance of SM at 254 nm were measured as 19 ± 0.3/cm, 26 ± 0.5/cm, and 10.6%, respectively. The UV-C results showed a log-linear inactivation of C. burnetii in SM with the UV-C sensitivity (D10) value of 4.1 ± 0.04 mJ/cm2. The results of HTST pasteurization revealed that C. burnetii was heat-sensitive with a D value of 1.75 min. Salmonella Muenchen showed similar UV inactivation kinetics and is, thereby, suggested as a suitable surrogate to C. burnetii for the pilot-scale UV-C processing studies of SM.

ABSTRACT The soil bacterium Myxococcus xanthus is a model organism with a set of diverse behaviors. These behaviors include the starvation-induced multicellular development program, in which cells move collectively to assemble multicellular aggregates. After initial aggregates have formed, some will disperse, with smaller aggregates having a higher chance of dispersal. Initial aggregation is driven by two changes in cell behavior: cells slow down inside of aggregates and bias their motion by reversing direction less frequently when moving toward aggregates. However, the cell behaviors that drive dispersal are unknown. Here, we use fluorescent microscopy to quantify changes in cell behavior after initial aggregates have formed. We observe that after initial aggregate formation, cells adjust the bias in reversal timings by initiating reversals more rapidly when approaching unstable aggregates. Using agent-based modeling, we then show dispersal is predominantly generated by this change in bias, which is strong enough to overcome slowdown inside aggregates. Notably, the change in reversal bias is correlated with the nearest aggregate size, connecting cellular activity to previously observed correlations between aggregate size and fate. To determine if this connection is consistent across strains, we analyze a second M. xanthus strain with reduced levels of dispersal. We find that far fewer cells near smaller aggregates modified their bias. This implies that aggregate dispersal is under genetic control, providing a foundation for further investigations into the role it plays in the life cycle of M. xanthus. Importance Understanding the processes behind bacterial biofilm formation, maintenance, and dispersal is essential for addressing their effects on health and ecology. Within these multicellular communities, various cues can trigger differentiation into distinct cell types, allowing cells to adapt to their specific local environment. The soil bacterium Myxococcus xanthus forms biofilms in response to starvation, marked by cells aggregating into mounds. Some aggregates persist as spore-filled fruiting bodies, while others disperse after initial formation for unknown reasons. Here, we use a combination of cell tracking analysis and computational simulations to identify behaviors at the cellular level that contribute to aggregate dispersal. Our results suggest that cells in aggregates actively determine whether to disperse or persist and undergo a transition to sporulation based on a self-produced cue related to the aggregate size. Identifying these cues is an important step in understanding and potentially manipulating bacterial cell-fate decisions.

Scarlet Royal, a mid-season ripening table grape, is one of the popular red grape varieties in California. However, its berries develop an undesirable astringent taste under certain conditions. Among the various factors contributing to the degradation of berry attributes, the levels and compositions of polyphenols play a fundamental role in defining berry quality and sensory characteristics. To comprehend the underlying mechanism of astringency development, Scarlet Royal berries with non-astringent attributes at the V7 vineyard were compared to astringent ones at the V9 vineyard. Biochemical analysis revealed that the divergence in berry astringency stemmed from alterations in its polyphenol composition, particularly tannins, during the late ripening stage at the V9 vineyard. Furthermore, transcriptomic profiling of berries positively associated nineteen flavonoid/proanthocyanidins (PAs) structural genes with the accumulation of PAs in V9 berries. The identification of these genes holds significance for table grape genetic improvement programs. At a practical level, the correlation between the taste panel and tannin content revealed a threshold level of tannins causing an astringent taste at approximately 400 mg/L. Additionally, berry astringency at the V9 vineyard was linked to a lower number of clusters and yield during the two study seasons, 2016 and 2017. Furthermore, petiole nutrient analysis at bloom showed differences in nutrient levels between the two vineyards, including higher levels of nitrogen and potassium in V9 vines compared to V7. It’s worth noting that V9 berries at harvest displayed a lower level of total soluble solids and higher titratable acidity compared to V7 berries. In conclusion, our results indicate that the accumulation of tannins in berries during the ripening process results in a reduction in their red color intensity but significantly increases the astringency taste, thereby degrading the berry quality attributes. This study also highlights the association of high nitrogen nutrient levels and a lower crop load with berry astringency in table grapes, paving the way for further research in this area

In this work, we propose a deep learning method for breast mass segmentation in ultrasound (US). Variations in breast mass size and image characteristics make the automatic segmentation difficult. To address this issue, we developed a selective kernel (SK) U-Net convolutional neural network. The aim of the SKs was to adjust network's receptive fields via an attention mechanism, and fuse feature maps extracted with dilated and conventional convolutions. The proposed method was developed and evaluated using US images collected from 882 breast masses. Moreover, we used three datasets of US images collected at different medical centers for testing (893 US images). On our test set of 150 US images, the SK-U-Net achieved mean Dice score of 0.826, and outperformed regular U-Net, Dice score of 0.778. When evaluated on three separate datasets, the proposed method yielded mean Dice scores ranging from 0.646 to 0.780. Additional fine-tuning of our better-performing model with data collected at different centers improved mean Dice scores by ~6%. SK-U-Net utilized both dilated and regular convolutions to process US images. We found strong correlation, Spearman's rank coefficient of 0.7, between the utilization of dilated convolutions and breast mass size in the case of network's expansion path. Our study shows the usefulness of deep learning methods for breast mass segmentation. SK-U-Net implementation and pre-trained weights can be found at github.com/mbyr/bus_seg.

Functional near-infrared spectroscopy (fNIRS) provides an alternative to functional magnetic resonance imaging (fMRI) for assessing changes in cortical hemodynamics. To establish the utility of fNIRS for measuring differential recruitment of the motor network during the production of timing-based actions, we measured cortical hemodynamic responses in 10 healthy adults while they performed two versions of a finger-tapping task. The task, used in an earlier fMRI study (Jantzen et al., 2004), was designed to track the neural basis of different timing behaviors. Participants paced their tapping to a metronomic tone, then continued tapping at the established pace without the tone. Initial tapping was either synchronous or syncopated relative to the tone. This produced a 2 × 2 design: synchronous or syncopated tapping and pacing the tapping with or continuing without a tone. Accuracy of the timing of tapping was tracked while cortical hemodynamics were monitored using fNIRS. Hemodynamic responses were computed by canonical statistical analysis across trials in each of the four conditions. Task-induced brain activation resulted in significant increases in oxygenated hemoglobin concentration (oxy-Hb) in a broad region in and around the motor cortex. Overall, syncopated tapping was harder behaviorally and produced more cortical activation than synchronous tapping. Thus, we observed significant changes in oxy-Hb in direct relation to the complexity of the task.

Oral microbiome dysbiosis has been associated with various local and systemic human diseases such as dental caries, periodontal disease, obesity, and cardiovascular disease. Bacterial composition may be affected by age, oral health, diet, and geography, although information about the natural variation found in the general public is still lacking. In this study, citizen-scientists used a crowdsourcing model to obtain oral bacterial composition data from guests at the Denver Museum of Nature & Science to determine if previously suspected oral microbiome associations with an individual's demographics, lifestyle, and/or genetics are robust and generalizable enough to be detected within a general population. Consistent with past research, we found bacterial composition to be more diverse in youth microbiomes when compared to adults. Adult oral microbiomes were predominantly impacted by oral health habits, while youth microbiomes were impacted by biological sex and weight status. The oral pathogen Treponema was detected more commonly in adults without recent dentist visits and in obese youth. Additionally, oral microbiomes from participants of the same family were more similar to each other than to oral microbiomes from non-related individuals. These results suggest that previously reported oral microbiome associations are observable in a human population containing the natural variation commonly found in the general public. Furthermore, these results support the use of crowdsourced data as a valid methodology to obtain community-based microbiome data.

OBJECTIVE: To determine survival outcomes in women with breast cancer detected at combined screening with breast MRI and mammography versus screening mammography alone. METHODS: This is an institutional review board-approved retrospective study, and the need for informed consent was waived. A total of 3002 women with an increased risk of breast cancer were screened between 2001 and 2004. Of the 3002 women, 1534 (51.1%) had 2780 combined screenings (MRI and mammography) and 1468 (48.9%) had 4811 mammography-only screenings. The Χ 2 test and the Kaplan-Meier method were used to compare cancer detection rates and survival rates. RESULTS: The overall cancer detection rate was significantly higher in the MRI plus mammography group compared with the mammography-only group (1.4% [40 of 2780] vs 0.5% [23 of 4811]; P < 0.001). No interval cancers occurred in the MRI plus mammography group, whereas 9 interval cancers were found in the mammography-only group. During a median follow-up of 10.9 years (range: 0.7 to 15.2), a total of 11 recurrences and 5 deaths occurred. Of the 11 recurrences, 6 were in the MRI plus mammography group and 5 were in the mammography-only group. All five deaths occurred in the mammography-only group. Disease-free survival showed no statistically significant difference between the two groups (P = 0.32). However, overall survival was significantly improved in the MRI plus mammography group (P = 0.002). CONCLUSION: Combined screening with MRI and mammography in women at elevated risk of breast cancer improves cancer detection and overall survival.

Bacterioplankton consume about half of the dissolved organic matter (DOM) produced by phytoplankton. DOM released from phytoplankton consists of a myriad of compounds that span a range of biological reactivity from labile to recalcitrant. Linking specific bacterioplankton lineages to the incorporation of DOM compounds into biomass is important to understand microbial niche partitioning. We conducted a series of DNA-stable isotope probing (SIP) experiments using 13C-labeled substrates of varying lability including amino acids, cyanobacteria lysate, and DOM from diatom and cyanobacteria isolates concentrated on solid phase extraction PPL columns (SPE-DOM). Amendments of substrates into Sargasso Sea bacterioplankton communities were conducted to explore microbial response and DNA-SIP was used to determine which lineages of Bacteria and Archaea were responsible for uptake and incorporation. Greater increases in bacterioplankton abundance and DOC removal were observed in incubations amended with cyanobacteria-derived lysate and amino acids compared to the SPE-DOM, suggesting that the latter retained proportionally more recalcitrant DOM compounds. DOM across a range of bioavailability was utilized by diverse prokaryotic taxa with copiotrophs becoming the most abundant 13C-incorporating taxa in the amino acid treatment and oligotrophs becoming the most abundant 13C-incorporating taxa in SPE-DOM treatments. The lineages that responded to SPE-DOM amendments were also prevalent in the mesopelagic of the Sargasso Sea, suggesting that PPL extraction of phytoplankton-derived DOM isolates compounds of ecological relevance to oligotrophic heterotrophic bacterioplankton. Our study indicates that DOM quality is an important factor controlling the diversity of the microbial community response, providing insights into the roles of different bacterioplankton in resource exploitation and efficiency of marine carbon cycling.

In this article, we review recent advances in research on rhythm and musical beat perception, focusing on the role of predictive processes in auditory motor interactions. We suggest that experimental evidence of the motor system's role in beat perception, including in passive listening, may be explained by the generation and maintenance of internal predictive models, concordant with the Active Inference framework of sensory processing. We highlight two complementary hypotheses for the neural underpinnings of rhythm perception: The Action Simulation for Auditory Prediction hypothesis (Patel and Iversen, 2014) and the Gradual Audiomotor Evolution hypothesis (Merchant and Honing, 2014) and review recent experimental progress supporting each of these hypotheses. While initial formulations of ASAP and GAE explain different aspects of beat-based timing-the involvement of motor structures in the absence of movement, and physical entrainment to an auditory beat respectively-we suggest that work under both hypotheses provide converging evidence toward understanding the predictive role of the motor system in the perception of rhythm, and the specific neural mechanisms involved. We discuss future experimental work necessary to further evaluate the causal neural mechanisms underlying beat and rhythm perception.

Background and aimsThe Veterans Health Administration (VA) cares for over 80,000 Veterans with cirrhosis annually. Given the importance of understanding patient reported outcomes in this complex population, we aimed to assess the associations between attitudes towards care, disease knowledge, and health related quality of life (HRQoL) in a national sample.MethodsIn this cross-sectional study, we mailed paper surveys to a random sample of Veterans with cirrhosis, oversampling those with decompensated disease. Surveys included the Veterans RAND 12-Item Health Survey (measuring HRQoL) and questions about demographics, characteristics of care, satisfaction with care ("attitudes towards care"), and symptoms of cirrhosis. Those who reported being "unsure" about whether they had decompensation events were defined as "unsure about cirrhosis symptoms" ("disease knowledge"). We used multivariable regression models to assess the factors associated with HRQoL.ResultsOf 1374 surveys, 551 (40%) completed surveys were included for analysis. Most Veterans (63%) were "satisfied" or "very satisfied" with VA liver care. Patients often self-reported being unsure about whether they had experienced hepatic decompensation events (34%). Overall average physical (PCS) and mental (MCS) component scores of HRQoL were 30±11 and 41±12. In multivariable regression models, hepatic decompensation (PCS:β = -3.8, MCS:β = -2.2), medical comorbidities (β = --2.0, β = -1.7), and being unsure about cirrhosis symptoms (β = -1.9, β = -3.3) were associated with worse HRQoL, while age (β = 0.1, β = 0.2) and satisfaction with care (β = 0.6; β = 1.6) were associated with significantly better HRQoL.ConclusionsHepatic decompensation, lower satisfaction with care, and being unsure about cirrhosis symptoms were associated with reduced QOL scores in this national cohort.

To the Editor.--As perinatal pathologists, we acknowledge that some families would like to take their placenta home with them from the hospital for various sociocultural and/or religious beliefs and practices [...]

Some recent district-level teacher leadership programs have incorporated both instructional coaching and formal evaluations into teacher leaders' (TLs) responsibilities, which research suggests could challenge the relational dynamics necessary for effective coaching. Using a sensemaking lens, we conducted a qualitative case study of one district's effort to integrate coaching and formal evaluation in their teacher leadership policy. We conducted a total of 26 semistructured interviews with district administrators and school leaders, TLs, and teachers in two schools, and seven observations of teacher leadership activities. We coded interview transcripts and field notes deductively and inductively. We found that when granted autonomy, principals drew on varied sources for making sense of and enacting this policy, and the messages they conveyed through school leadership norms deeply influenced how teachers and TLs enacted and experienced the integration. The integrated district policy in and of itself did not hinder relationships between teachers and TLs; rather, what mattered most for teachers was the extent to which they perceived their TLs as part of a larger system of support or accountability. This study suggests that the school norms that school leaders put into place when enacting teacher leadership policies deeply influence teachers' perceived relational dynamics with TLs. Teacher leaders have a unique role in implementation that is shaped by school-level norms and conceptions of effective leadership and coaching.

Abstract Nanosized perovskite ferroelectrics are widely employed in several electromechanical, photonics, and thermoelectric applications. Scaling of ferroelectric materials entails a severe reduction in the lattice (phonon) thermal conductivity, particularly at sub‐100 nm length scales. Such thermal conductivity reduction can be accurately predicted using the information of phonon mean free path (MFP) distribution. The current understanding of phonon MFP distribution in perovskite ferroelectrics is still inconclusive despite the critical thermal management implications. Here, high‐quality single‐crystalline barium titanate (BTO) thin films, a representative perovskite ferroelectric material, are grown at several thicknesses. Using experimental thermal conductivity measurements and first‐principles based modeling (including four‐phonon scattering), the phonon MFP distribution is determined in BTO. The simulation results agree with the measured thickness‐dependent thermal conductivity. The results show that the phonons with sub‐100 nm MFP dominate the thermal transport in BTO, and phonons with MFP exceeding 10 nm contribute ≈35% to the total thermal conductivity, in significant contrast to previously published experimental results. The experimentally validated phonon MFP distribution is consistent with the theoretical predictions of other complex crystals with strong anharmonicity. This work paves the way for thermal management in nanostructured and ferroelectric‐domain‐engineered systems for oxide perovskite‐based functional materials.

Though studies in animals and humans link the gut microbiota to brain development and control of behavior, little research has examined this connection in healthy infants. This prospective study could determine associations between infant gut microbiota at 3 months, and infant temperament at 9 months, in a prospective pregnancy cohort (Michigan Archive for Research on Child Health; n = 159). Microbiota profiling with 16S rRNA gene sequencing was conducted on fecal samples obtained at 3 months of age. Based on the relative abundance of gut microbiotas, three groups were identified, and each group was characterized by different microbes. Infant temperament outcomes were reported by mothers using the Infant Behavior Questionnaire-Revised Very Short Form at a mean age of 9.4 months. Fully adjusted multivariate linear regression models showed that certain clusters were associated with higher negative emotionality scores, prominently among infants who had poor vitamin D intake. However, no associations were evident between gut microbiota clusters and temperament scales after FDR correction. After using three differential abundance tools, Firmicutes was associated with higher positive affect/surgency scores, whereas Clostridioides was associated with lower scores. An association between the gut microbiota and early infancy temperament was observed; thus, this study warrants replication, with a particular focus on vitamin D moderation.

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.IMPORTANCE Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.

BackgroundContrast agent-enhanced digital mammography (CEDM) has been shown to be more sensitive and specific than two-dimensional full-field digital mammography in the diagnostic setting. Few studies have reported on its performance in the screening setting.PurposeTo evaluate the performance of CEDM for breast cancer screening.Materials and MethodsThis retrospective study included women who underwent dual-energy CEDM for breast cancer screening from December 2012 through April 2016. Medical records were reviewed for age, risk factors, short-interval follow-up and biopsies recommended, and cancers detected. Sensitivity, specificity, positive predictive value of abnormal findings at screening (PPV1), positive predictive value of biopsy performed (PPV3), and negative predictive value were determined.ResultsIn the study period 904 baseline CEDMs were performed. Mean age was 51.8 years ± 9.4 (standard deviation). Of 904 patients, 700 (77.4%) had dense breasts, 247 (27.3%) had a family history of breast cancer in a first-degree relative age 50 years or younger, and 363 (40.2%) a personal history of breast cancer. The final Breast Imaging Reporting and Data System score was 1 or 2 in 832 of 904 (92.0%) patients, score of 3 in 25 of 904 (2.8%) patients, and score of 4 or 5 in 47 of 904 (5.2%) patients. By using CEDM, 15 cancers were diagnosed in 14 of 904 women (cancer detection rate, 15.5 of 1000). PPV3 was 29.4% (15 of 51). At least 1-year follow up was available in 858 women. There were two interval cancers. Sensitivity was 50.0% (eight of 16; 95% confidence interval [CI]: 24.7%, 75.3%) on the low-energy images compared with 87.5% (14 of 16; 95% CI: 61.7%, 98.4%) for the entire study (low-energy and iodine images; P = .03). Specificity was 93.7% (789 of 842; 95% CI: 91.8%, 95.2%); PPV1 was 20.9% (14 of 67; 95% CI: 11.9%, 32.6%), and negative predictive value was 99.7% (789 of 791; 95% CI: 99.09%, 99.97%).ConclusionContrast-enhanced digital mammography is a promising technique for screening women with higher-than-average risk for breast cancer.© RSNA, 2019.

Background: Studies of the cystic fibrosis (CF) lung microbiome have consistently shown that lung function decline is associated with decreased microbial diversity due to the dominance of opportunistic pathogens. However, how this phenomenon is reflected in the metabolites and chemical environment of lung secretions remains poorly understood. Methods: Here we investigated the microbial and molecular composition of CF sputum samples using 16S rRNA gene amplicon sequencing and untargeted tandem mass spectrometry to determine their interrelationships and associations with clinical measures of disease severity. Results: The CF metabolome was found to exist in two states: one from patients with more severe disease that had higher molecular diversity and more Pseudomonas aeruginosa and the other from patients with better lung function having lower metabolite diversity and fewer pathogenic bacteria. The two molecular states were differentiated by the abundance and diversity of peptides and amino acids. Patients with severe disease and more pathogenic bacteria had higher levels of peptides. Analysis of the carboxyl terminal residues of these peptides indicated that neutrophil elastase and cathepsin G were responsible for their generation, and accordingly, these patients had higher levels of proteolytic activity from these enzymes in their sputum. The CF pathogen Pseudomonas aeruginosa was correlated with the abundance of amino acids and is known to primarily feed on them in the lung. Conclusions: In cases of severe CF lung disease, proteolysis by host enzymes creates an amino acid-rich environment that P. aeruginosa comes to dominate, which may contribute to the pathogen's persistence by providing its preferred carbon source.

PURPOSE: We propose a deep learning-based approach to breast mass classification in sonography and compare it with the assessment of four experienced radiologists employing breast imaging reporting and data system 4th edition lexicon and assessment protocol. METHODS: Several transfer learning techniques are employed to develop classifiers based on a set of 882 ultrasound images of breast masses. Additionally, we introduce the concept of a matching layer. The aim of this layer is to rescale pixel intensities of the grayscale ultrasound images and convert those images to red, green, blue (RGB) to more efficiently utilize the discriminative power of the convolutional neural network pretrained on the ImageNet dataset. We present how this conversion can be determined during fine-tuning using back-propagation. Next, we compare the performance of the transfer learning techniques with and without the color conversion. To show the usefulness of our approach, we additionally evaluate it using two publicly available datasets. RESULTS: Color conversion increased the areas under the receiver operating curve for each transfer learning method. For the better-performing approach utilizing the fine-tuning and the matching layer, the area under the curve was equal to 0.936 on a test set of 150 cases. The areas under the curves for the radiologists reading the same set of cases ranged from 0.806 to 0.882. In the case of the two separate datasets, utilizing the proposed approach we achieved areas under the curve of around 0.890. CONCLUSIONS: The concept of the matching layer is generalizable and can be used to improve the overall performance of the transfer learning techniques using deep convolutional neural networks. When fully developed as a clinical tool, the methods proposed in this paper have the potential to help radiologists with breast mass classification in ultrasound.

Ceilometer measurements of aerosol backscatter profiles have been widely used to provide continuous planetary boundary layer height (PBLHT) estimations. To investigate the robustness of ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using multiple years of U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) ceilometer and balloon-borne sounding data at ARM fixed-location atmospheric observatories and from ARM mobile facilities deployed around the world for various field campaigns. These observatories cover from the tropics to the polar regions and over both ocean and land surfaces. Statistical comparisons of ceilometer-estimated PBLHTs from the Vaisala CL31 ceilometer data with radiosonde-estimated PBLHTs from the ARM PBLHT-SONDE Value-added Product (VAP) are performed under different atmospheric conditions including stable and unstable atmospheric boundary layer, low-level cloud-free conditions, and cloudy conditions at these ARM observatories. Under unstable conditions, good comparisons are found between ceilometer- and radiosonde-estimated PBLHTs at ARM low- and mid-latitude land observatories. However, it is still challenging to obtain reliable PBLHT estimations over ocean surfaces even using radiosonde data. Under stable conditions, ceilometer- and radiosonde-estimated PBLHTs have weak correlations. We compare different PBLHT estimations utilizing the Heffter, the Liu–Liang, and the bulk Richardson number methods applied to radiosonde data with ceilometer-estimated PBLHT. We find that ceilometer-estimated PBLHT compares better with the Liu–Liang method under unstable conditions and compares better with the bulk Richardson number method under stable conditions.

The bacterium Phocaeicola vulgatus is commonly found in the human gut. Here, the authors show that the microorganism produces an antibacterial toxin that targets the LPS core glycan of closely related species and induces a response that partially protects cells from multiple antimicrobial toxins.