Complete circular assembly of Histophilus somni PDS1537697-81-1 genome and phenotypic characterization of its antibiotic susceptibility.

A Histophilus somni isolate from a clinically healthy, fall-placed calf was obtained upon arrival to a commercial feedlot. Fall-placed calves are commonly viewed to be at high risk for the development of bovine respiratory disease. The isolate was phenotyped for antimicrobial susceptibility and sequenced to obtain a complete, circular, genome assembly.

Bacterial enrichment prior to third-generation metagenomic sequencing improves detection of BRD pathogens and genetic determinants of antimicrobial resistance in feedlot cattle.

Introduction: Bovine respiratory disease (BRD) is one of the most important animal health problems in the beef industry. While bacterial culture and antimicrobial susceptibility testing have been used for diagnostic testing, the common practice of examining one isolate per species does not fully reflect the bacterial population in the sample. In contrast, a recent study with metagenomic sequencing of nasal swabs from feedlot cattle is promising in terms of bacterial pathogen identification and detection of antimicrobial resistance genes (ARGs). However, the sensitivity of metagenomic sequencing was impeded by the high proportion of host biomass in the nasal swab samples. Methods: This pilot study employed a non-selective bacterial enrichment step before nucleic acid extraction to increase the relative proportion of bacterial DNA for sequencing. Results: Non-selective bacterial enrichment increased the proportion of bacteria relative to host sequence data, allowing increased detection of BRD pathogens compared with unenriched samples. This process also allowed for enhanced detection of ARGs with species-level resolution, including detection of ARGs for bacterial species of interest that were not targeted for culture and susceptibility testing. The long-read sequencing approach enabled ARG detection on individual bacterial reads without the need for assembly. Metagenomics following non-selective bacterial enrichment resulted in substantial agreement for four of six comparisons with culture for respiratory bacteria and substantial or better correlation with qPCR. Comparison between isolate susceptibility results and detection of ARGs was best for macrolide ARGs in Mannheimia haemolytica reads but was also substantial for sulfonamide ARGs within M. haemolytica and Pasteurella multocida reads and tetracycline ARGs in Histophilus somni reads. Discussion: By increasing the proportion of bacterial DNA relative to host DNA through non-selective enrichment, we demonstrated a corresponding increase in the proportion of sequencing data identifying BRD-associated pathogens and ARGs in deep nasopharyngeal swabs from feedlot cattle using long-read metagenomic sequencing. This method shows promise as a detection strategy for BRD pathogens and ARGs and strikes a balance between processing time, input costs, and generation of on-target data. This approach could serve as a valuable tool to inform antimicrobial management for BRD and support antimicrobial stewardship.

Maternal vaginal microbiome composition does not affect development of the infant gut microbiome in early life.

Birth mode has been implicated as a major factor influencing neonatal gut microbiome development, and it has been assumed that lack of exposure to the maternal vaginal microbiome is responsible for gut dysbiosis among caesarean-delivered infants. Consequently, practices to correct dysbiotic gut microbiomes, such as vaginal seeding, have arisen while the effect of the maternal vaginal microbiome on that of the infant gut remains unknown. We conducted a longitudinal, prospective cohort study of 621 Canadian pregnant women and their newborn infants and collected pre-delivery maternal vaginal swabs and infant stool samples at 10-days and 3-months of life. Using cpn60-based amplicon sequencing, we defined vaginal and stool microbiome profiles and evaluated the effect of maternal vaginal microbiome composition and various clinical variables on the development of the infant stool microbiome. Infant stool microbiomes showed significant differences in composition by delivery mode at 10-days postpartum; however, this effect could not be explained by maternal vaginal microbiome composition and was vastly reduced by 3 months. Vaginal microbiome clusters were distributed across infant stool clusters in proportion to their frequency in the overall maternal population, indicating independence of the two communities. Intrapartum antibiotic administration was identified as a confounder of infant stool microbiome differences and was associated with lower abundances of Escherichia coli, Bacteroides vulgatus, Bifidobacterium longum and Parabacteroides distasonis. Our findings demonstrate that maternal vaginal microbiome composition at delivery does not affect infant stool microbiome composition and development, suggesting that practices to amend infant stool microbiome composition focus factors other than maternal vaginal microbes.

Evaluating the potential of third generation metagenomic sequencing for the detection of BRD pathogens and genetic determinants of antimicrobial resistance in chronically ill feedlot cattle.

BACKGROUND: Bovine respiratory disease (BRD) is an important cause of morbidity and mortality and is responsible for most of the injectable antimicrobial use in the feedlot industry. Traditional bacterial culture can be used to diagnose BRD by confirming the presence of causative pathogens and to support antimicrobial selection. However, given that bacterial culture takes up to a week and early intervention is critical for treatment success, culture has limited utility for informing rapid therapeutic decision-making. In contrast, metagenomic sequencing has the potential to quickly resolve all nucleic acid in a sample, including pathogen biomarkers and antimicrobial resistance genes. In particular, third-generation Oxford Nanopore Technology sequencing platforms provide long reads and access to raw sequencing data in real-time as it is produced, thereby reducing the time from sample collection to diagnostic answer. The purpose of this study was to compare the performance of nanopore metagenomic sequencing to traditional culture and sensitivity methods as applied to nasopharyngeal samples from segregated groups of chronically ill feedlot cattle, previously treated with antimicrobials for nonresponsive pneumonia or lameness. RESULTS: BRD pathogens were isolated from most samples and a variety of different resistance profiles were observed across isolates. The sequencing data indicated the samples were dominated by Moraxella bovoculi, Mannheimia haemolytica, Mycoplasma dispar, and Pasteurella multocida, and included a wide range of antimicrobial resistance genes (ARGs), encoding resistance for up to seven classes of antimicrobials. Genes conferring resistance to beta-lactams were the most commonly detected, while the tetH gene was detected in the most samples overall. Metagenomic sequencing detected the BRD pathogens of interest more often than did culture, but there was limited concordance between phenotypic resistance to antimicrobials and the presence of relevant ARGs. CONCLUSIONS: Metagenomic sequencing can reduce the time from sampling to results, detect pathogens missed by bacterial culture, and identify genetically encoded determinants of resistance. Increasing sequencing coverage of target organisms will be an essential component of improving the reliability of this technology, such that it can be better used for the surveillance of pathogens of interest, genetic determinants of resistance, and to inform diagnostic decisions.

CaptureSeq: Hybridization-Based Enrichment of cpn60 Gene Fragments Reveals the Community Structures of Synthetic and Natural Microbial Ecosystems.

BACKGROUND: The molecular profiling of complex microbial communities has become the basis for examining the relationship between the microbiome composition, structure and metabolic functions of those communities. Microbial community structure can be partially assessed with "universal" PCR targeting taxonomic or functional gene markers. Increasingly, shotgun metagenomic DNA sequencing is providing more quantitative insight into microbiomes. However, both amplicon-based and shotgun sequencing approaches have shortcomings that limit the ability to study microbiome dynamics. METHODS: We present a novel, amplicon-free, hybridization-based method (CaptureSeq) for profiling complex microbial communities using probes based on the chaperonin-60 gene. Molecular profiles of a commercially available synthetic microbial community standard were compared using CaptureSeq, whole metagenome sequencing, and 16S universal target amplification. Profiles were also generated for natural ecosystems including antibiotic-amended soils, manure storage tanks, and an agricultural reservoir. RESULTS: The CaptureSeq method generated a microbial profile that encompassed all of the bacteria and eukaryotes in the panel with greater reproducibility and more accurate representation of high G/C content microorganisms compared to 16S amplification. In the natural ecosystems, CaptureSeq provided a much greater depth of coverage and sensitivity of detection compared to shotgun sequencing without prior selection. The resulting community profiles provided quantitatively reliable information about all three domains of life (Bacteria, Archaea, and Eukarya) in the different ecosystems. The applications of CaptureSeq will facilitate accurate studies of host-microbiome interactions for environmental, crop, animal and human health. CONCLUSIONS: cpn60-based hybridization enriched for taxonomically informative DNA sequences from complex mixtures. In synthetic and natural microbial ecosystems, CaptureSeq provided sequences from prokaryotes and eukaryotes simultaneously, with quantitatively reliable read abundances. CaptureSeq provides an alternative to PCR amplification of taxonomic markers with deep community coverage while minimizing amplification biases.

Learning to be well in the health workplace: an integrated model.

This article was migrated. The article was marked as recommended. Introduction: Problems with the well-being of workers in health is a crisis that directly impacts on health care workers themselves and on the quality of care provided. Academic inquiry has utilised a broad diversity of perspectives. There is an urgent need for theory that guides interventions and mediates between the perspectives taken. Methods: An initial model was generated by mapping concepts from a meta-synthesis of systematic reviews of resilience, burnout, well- being and compassion fatigue. An iterative process identifying and critically applying additional literature refined the model. Results: The final model addressed positive /negative; individual/organisational and focal or global perspectives. It was structured on the Job-demands resources model with stressors mediated by cognitive appraisal, and organisational climate. A cycle of learning in practice was identified as the key to adaptation. The relevant educational domains include learning to be, believe, feel, do, Interact and adapt to maximise well-being. Discussion: An integrated, evidence based learning model of well-being in the health workplace has been developed which may act as a guide for both individuals and organisation to maximise well-being. Implications of the model have been discussed.

An intensive multilocation temporal dataset of fungal and bacterial communities in the root and rhizosphere of Brassica napus.

The plant microbiome has been recently recognized as a plant phenotype to help in the food security of the future population. However, global plant microbiome datasets are insufficient to be used effectively for breeding this new generation of crop plants. We surveyed the diversity and temporal composition of bacterial and fungal communities in the root and rhizosphere of Brassica napus, the world's second largest oilseed crop, weekly in eight diverse lines at one site and every three weeks in sixteen lines, at three sites in 2016 and 2017 in the Canadian Prairies. We sequenced the bacterial 16S ribosomal RNA gene generating a total of 127.7 million reads and the fungal internal transcribed spacer (ITS) region generating 113.4 million reads. 14,944 unique fungal amplicon sequence variants (ASV) were detected, with an average of 43 ASVs per root and 105 ASVs per rhizosphere sample. We detected 10,882 unique bacterial ASVs with an average of 249 ASVs per sample. Temporal, site-to-site, and line-driven variability were key determinants of microbial community structure. This dataset is a valuable resource to systematically extract information on the belowground microbiome of diverse B. napus lines in different environments, at different times in the growing season, in order to adapt effective varieties for sustainable crop production systems.

Finding common ground: meta-synthesis of communication frameworks found in patient communication, supervision and simulation literature.

BACKGROUND: Effective communication between patients-clinicians, supervisors-learners and facilitators-participants within a simulation is a key priority in health profession education. There is a plethora of frameworks and recommendations to guide communication in each of these contexts, and they represent separate discourses with separate communities of practice and literature. Finding common ground within these frameworks has the potential to minimise cognitive load and maximise efficiency, which presents an opportunity to consolidate messages, strategies and skills throughout a communication curriculum and the possibility of expanding the research agenda regarding communication, feedback and debriefing in productive ways. METHODS: A meta-synthesis of the feedback, debriefing and clinical communication literature was conducted to achieve these objectives. RESULTS: Our analysis revealed that the concepts underlying the framework can be usefully categorised as stages, goals, strategies, micro-skills and meta-skills. Guidelines for conversations typically shared a common structure, and strategies aligned with a stage. Core transferrable communication skills (i.e., micro-skills) were identified across various types of conversation, and the major differences between frameworks were related to the way that power was distributed in the conversation and the evolution of conversations along the along the path of redistributing power. As part of the synthesis, an overarching framework "prepare-EMPOWER enact" was developed to capture these shared principles across discourses. CONCLUSIONS: Adopting frameworks for work-based communication that promote dialogue and empower individuals to contribute may represent an important step towards learner-centred education and person-centred care for patients.

Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection.

BACKGROUND: Antimicrobial resistance (AMR) is a major threat to global public health because it makes standard treatments ineffective and contributes to the spread of infections. It is important to understand AMR's biological mechanisms for the development of new drugs and more rapid and accurate clinical diagnostics. The increasing availability of whole-genome SNP (single nucleotide polymorphism) information, obtained from whole-genome sequence data, along with AMR profiles provides an opportunity to use feature selection in machine learning to find AMR-associated mutations. This work describes the use of a supervised feature selection approach using deep neural networks to detect AMR-associated genetic factors from whole-genome SNP data. RESULTS: The proposed method, DNP-AAP (deep neural pursuit - average activation potential), was tested on a Neisseria gonorrhoeae dataset with paired whole-genome sequence data and resistance profiles to five commonly used antibiotics including penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime. The results show that DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae, and also provide a list of candidate genomic features (SNPs) that might lead to the discovery of novel AMR determinants. Logistic regression classifiers were built with the identified SNPs and the prediction AUCs (area under the curve) for penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime were 0.974, 0.969, 0.949, 0.994, and 0.976, respectively. CONCLUSIONS: DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae. It also provides a list of candidate genes and intergenic regions that might lead to novel AMR factor discovery. More generally, DNP-AAP can be applied to AMR analysis of any bacterial species with genomic variants and phenotype data. It can serve as a useful screening tool for microbiologists to generate genetic candidates for further lab experiments.

Evaluation of Phase II Trial Design in Advanced Pancreatic Cancer.

OBJECTIVES: We evaluated how well phase II trials in locally advanced and metastatic pancreatic cancer (LAMPC) meet current recommendations for trial design. METHODS: We conducted a systematic review of phase II first-line treatment trial for LAMPC. We assessed baseline characteristics, type of comparison, and primary end point to examine adherence to the National Cancer Institute recommendations for trial design. RESULTS: We identified 148 studies (180 treatment arms, 7505 participants). Forty-seven (32%) studies adhered to none of the 5 evaluated National Cancer Institute recommendations, 62 (42%) followed 1, 31 (21%) followed 2, and 8 (5%) followed 3 recommendations. Studies varied with respect to the proportion of patients with good performance status (range, 0%-80%) and locally advanced disease (range, 14%-100%). Eighty-two (55%) studies concluded that investigational agents should progress to phase III testing; of these, 24 (16%) had documented phase III trials. Three (8%) phase III trials demonstrated clinically meaningful improvements for investigational agents. One of 38 phase II trials that investigated biological investigational agents was enriched for a biomarker. CONCLUSIONS: Phase II trials do not conform well to current recommendations for trial design in LAMPC.

Discourses of professionalism: Metaphors, theory and practice.

Professionalism is a contested concept and different discourses have differed by scope and epistemology. The theory of communicative action integrates epistemology (knowledge interests) with that of scope (lifeworld). AIM: To pragmatically inform learning of professionalism. METHODS: apply the theory of communicative action to professionalism discourses. RESULTS: Previous professionalism discourses translated into four frames: technical; communicative; improvement, and critical. These can be viewed as four metaphors the scale; conversation; consensus conference, and protest. The theory of communicative action demonstrated that a critical frame was often lacking from discussions of professionalism and emphasized critiquing the assumptions made, the way power was utilized, and the ends to which actions were directed. Using these frameworks connected discourses on professionalism to other key medical discourses particularly quality improvement, patient centeredness, social justice, and the professional well-being. CONCLUSION: The theory of communicative action adds value by introducing criteria for the evaluation of individual truth claims that expands the discussion beyond accuracy to include sincerity, ethics and coherence; and it emphasizes promoting free speech and the inclusion of diverse views and stakeholders. The theory of communicative action provides a coherent and useful framework for viewing professionalism that integrates with broader discussions about philosophy, truth claims, and post-modern society.

Core and Differentially Abundant Bacterial Taxa in the Rhizosphere of Field Grown Brassica napus Genotypes: Implications for Canola Breeding.

Modifying the rhizosphere microbiome through targeted plant breeding is key to harnessing positive plant-microbial interrelationships in cropping agroecosystems. Here, we examine the composition of rhizosphere bacterial communities of diverse Brassica napus genotypes to identify: (1) taxa that preferentially associate with genotypes, (2) core bacterial microbiota associated with B. napus, (3) heritable alpha diversity measures at flowering and whole growing season, and (4) correlation between microbial and plant genetic distance among canola genotypes at different growth stages. Our aim is to identify and describe signature microbiota with potential positive benefits that could be integrated in B. napus breeding and management strategies. Rhizosphere soils of 16 diverse genotypes sampled weekly over a 10-week period at single location as well as at three time points at two additional locations were analyzed using 16S rRNA gene amplicon sequencing. The B. napus rhizosphere microbiome was characterized by diverse bacterial communities with 32 named bacterial phyla. The most abundant phyla were Proteobacteria, Actinobacteria, and Acidobacteria. Overall microbial and plant genetic distances were highly correlated (R = 0.65). Alpha diversity heritability estimates were between 0.16 and 0.41 when evaluated across growth stage and between 0.24 and 0.59 at flowering. Compared with a reference B. napus genotype, a total of 81 genera were significantly more abundant and 71 were significantly less abundant in at least one B. napus genotype out of the total 558 bacterial genera. Most differentially abundant genera were Proteobacteria and Actinobacteria followed by Bacteroidetes and Firmicutes. Here, we also show that B. napus genotypes select an overall core bacterial microbiome with growth-stage-related patterns as to how taxa joined the core membership. In addition, we report that sets of B. napus core taxa were consistent across our three sites and 2 years. Both differential abundance and core analysis implicate numerous bacteria that have been reported to have beneficial effects on plant growth including disease suppression, antifungal properties, and plant growth promotion. Using a multi-site year, temporally intensive field sampling approach, we showed that small plant genetic differences cause predictable changes in canola microbiome and are potential target for direct and indirect selection within breeding programs.

Treatment-related toxicities of immune checkpoint inhibitors in advanced cancers: A meta-analysis.

BACKGROUND: We performed a meta-analysis to quantify toxic death, adverse events (AEs) and treatment discontinuation due to AEs from checkpoint inhibitors (CI). METHODS: We searched for randomized trials with adequate reporting for toxicity outcomes. Pooled risk ratios were estimated for CI versus chemotherapy or different combinations of these agents. RESULTS: Twenty trials of five different cancers with 10 794 patients with performance status 0 or 1 were identified. Toxic deaths from CI were infrequent (0.6%). Treatment discontinuations were less frequent for programmed-death-1 (PD-1) or PD-ligand-1 (PD-L1) inhibitors (5.8% vs 13.3%, P < 0.001) and cytotoxic-T-lymphocyte-associated-antigen-4 (CTLA-4) inhibitors (6.2% vs 11.4%, P = 0.002) than chemotherapy. PD-1/PD-L1 inhibitors had less grade 3, 4, and 5 (G3/4/5) AEs than chemotherapy (13.8% vs 39.8%, P < 0.001) or CTLA-4 inhibitors (13.4% vs 22.8%, P < 0.001). Combination CI had higher discontinuation (37.8% vs 11.6%, P < 0.001) and higher G3/4/5 AEs (55.3% vs 21.9%, P < 0.001) than CI monotherapy. Endocrinopathy (11.2% vs 0.9%), rash (10.1% vs 4.3%) and pneumonitis (3.1% vs 0.7%) were associated with CI, and alopecia (25.9% vs 1.0%), neutropenia (16.6% vs 0.6%) and neuropathy (7.6% vs 3.0%) with chemotherapy. CONCLUSIONS: CI inhibitors have different toxicity profiles to chemotherapy. These findings are useful for patient counselling and planning of future trials.

Clinical and Molecular Characteristics Associated With Survival Among Patients Treated With Checkpoint Inhibitors for Advanced Non-Small Cell Lung Carcinoma: A Systematic Review and Meta-analysis.

IMPORTANCE: Checkpoint inhibitors have replaced docetaxel as the new standard second-line therapy in advanced non-small cell lung carcinoma (NSCLC), but little is known about the potential predictive value of clinical and molecular characteristics. OBJECTIVE: To estimate the relative efficacy of checkpoint inhibitor vs docetaxel overall and in subgroups defined by clinicopathological characteristics. DATA SOURCES: This systematic review and meta-analysis searched MEDLINE, Embase, PubMed, and the Cochrane Central Register of Controlled Trials for randomized clinical trials published in the English language between January 1, 1996, and January 30, 2017. STUDY SELECTION: Randomized clinical trials that compared a checkpoint inhibitor (nivolumab, pembrolizumab, or atezolizumab) with docetaxel. For each trial included in this study, the trial name, year of publication or conference presentation, patients' clinicopathological characteristics, type of chemotherapy, and type of checkpoint inhibitor were extracted. Data collection for this study took place from February 1 to March 31, 2017. DATA EXTRACTION AND SYNTHESIS: Two reviewers performed study selection, data abstraction, and risk of bias assessment. Hazard ratios (HR) and 95% CIs for the overall population and subgroups were extracted. Pooled treatment estimates were calculated using the inverse-variance-weighted method. RESULTS: In total, 5 trials involving 3025 patients with advanced NSCLC were included in this meta-analysis. These patients were randomized to receive a checkpoint inhibitor (nivolumab, 427 [14.1%]; pembrolizumab, 691 [22.8%]; or atezolizumab, 569 [18.8%]) or docetaxel (1338 [44.2%]). Checkpoint inhibitors were associated with prolonged overall survival, compared with docetaxel (HR, 0.69; 95% CI, 0.63-0.75; P < .001). They prolonged overall survival in the EGFR wild-type subgroup (HR, 0.67; 95% CI, 0.60-0.75; P < .001), but not in the EGFR mutant subgroup (HR, 1.11; 95% CI, 0.80-1.53; P = .54; interaction, P = .005), and they prolonged overall survival in the KRAS mutant subgroup (HR, 0.65; 95% CI, 0.44-0.97; P = .03) but not in the KRAS wild-type subgroup (HR, 0.86; 95% CI, 0.67-1.11; P = .24; interaction, P = .24). The relative treatment benefits were similar according to smoking status (never smokers [HR, 0.79] vs ever smokers [HR, 0.69]; interaction, P = .40), performance status (0 [HR, 0.69] vs 1 [HR, 0.68]; interaction, P = .85), age (<65 years [HR, 0.71] vs ≥65 years [HR, 0.69]; interaction, P = .74), histology (squamous [HR, 0.67] vs nonsquamous [HR, 0.70]; interaction, P = .71), or sex (male [HR, 0.69] vs female [HR, 0.70]; interaction, P = .82). CONCLUSION AND RELEVANCE: Checkpoint inhibitors, compared with docetaxel, are associated with significantly prolong overall survival in second-line therapy in NSCLC. The finding of no overall survival benefit for patients with EGFR mutant tumors suggests that checkpoint inhibitors should be considered only after other effective therapies have been exhausted. The findings of this meta-analysis could also assist in the design and interpretation of future trials and in economic analyses.

Beyond competency-based continuing professional development.

Competency based medical education (CBME) has become the default for undergraduate and post-graduate medical education (PGME) but its role in continuing professional development (CPD) is under discussion. Some critical differences between CPD and PGME are identified and these differences applied to: the relative roles of competence and performance; existing criticisms of CBME; heutagogy as a learning theory; and post-modernism as an underlying philosophical perspective. The argument is made that the characteristics of CPD fit with performance based medical education, a heutagogical learning theory, a focus on capabilities, rather than competencies; and a post-modern perspective.

Quantitative molecular diagnostic assays of grain washes for Claviceps purpurea are correlated with visual determinations of ergot contamination.

We examined the epiphytic microbiome of cereal grain using the universal barcode chaperonin-60 (cpn60). Microbial community profiling of seed washes containing DNA extracts prepared from field-grown cereal grain detected sequences from a fungus identified only to Class Sordariomycetes. To identify the fungal sequence and to improve the reference database, we determined cpn60 sequences from field-collected and reference strains of the ergot fungus, Claviceps purpurea. These data allowed us to identify this fungal sequence as deriving from C. purpurea, and suggested that C. purpurea DNA is readily detectable on agricultural commodities, including those for which ergot was not identified as a grading factor. To get a sense of the prevalence and level of C. purpurea DNA in cereal grains, we developed a quantitative PCR assay based on the fungal internal transcribed spacer (ITS) and applied it to 137 samples from the 2014 crop year. The amount of Claviceps DNA quantified correlated strongly with the proportion of ergot sclerotia identified in each grain lot, although there was evidence that non-target organisms were responsible for some false positives with the ITS-based assay. We therefore developed a cpn60-targeted loop-mediated isothermal amplification assay and applied it to the same grain wash samples. The time to positive displayed a significant, inverse correlation to ergot levels determined by visual ratings. These results indicate that both laboratory-based and field-adaptable molecular diagnostic assays can be used to detect and quantify pathogen load in bulk commodities using cereal grain washes.