Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing.

OBJECTIVE: Leverage electronic health record (EHR) audit logs to develop a machine learning (ML) model that predicts which notes a clinician wants to review when seeing oncology patients. MATERIALS AND METHODS: We trained logistic regression models using note metadata and a Term Frequency Inverse Document Frequency (TF-IDF) text representation. We evaluated performance with precision, recall, F1, AUC, and a clinical qualitative assessment. RESULTS: The metadata only model achieved an AUC 0.930 and the metadata and TF-IDF model an AUC 0.937. Qualitative assessment revealed a need for better text representation and to further customize predictions for the user. DISCUSSION: Our model effectively surfaces the top 10 notes a clinician wants to review when seeing an oncology patient. Further studies can characterize different types of clinician users and better tailor the task for different care settings. CONCLUSION: EHR audit logs can provide important relevance data for training ML models that assist with note-writing in the oncology setting.

Interplay between particle size and microbial ecology in the gut microbiome.

Physical particles can serve as critical abiotic factors that structure the ecology of microbial communities. For non-human vertebrate gut microbiomes, fecal particle size (FPS) has been known to be shaped by chewing efficiency and diet. However, little is known about what drives FPS in the human gut. Here, we analyzed FPS by laser diffraction across a total of 76 individuals and found FPS to be strongly individualized. Surprisingly, a behavioral intervention with 41 volunteers designed to increase chewing efficiency did not impact FPS. Dietary patterns could also not be associated with FPS. Instead, we found evidence that mammalian and human gut microbiomes shaped FPS. Fecal samples from germ-free and antibiotic-treated mice exhibited increased FPS relative to colonized mice. In humans, markers of longer transit time were correlated with smaller FPS. Gut microbiota diversity and composition were also associated with FPS. Finally, ex vivo culture experiments using human fecal microbiota from distinct donors showed that differences in microbiota community composition can drive variation in particle size. Together, our results support an ecological model in which the human gut microbiome plays a key role in reducing the size of food particles during digestion, and that the microbiomes of individuals vary in this capacity. These new insights also suggest FPS in humans to be governed by processes beyond those found in other mammals and emphasize the importance of gut microbiota in shaping their own abiotic environment.

Metaproteomics and DNA metabarcoding as tools to assess dietary intake in humans.

Objective biomarkers of food intake are a sought-after goal in nutrition research. Most biomarker development to date has focused on metabolites detected in blood, urine, skin or hair, but detection of consumed foods in stool has also been shown to be possible via DNA sequencing. An additional food macromolecule in stool that harbors sequence information is protein. However, the use of protein as an intake biomarker has only been explored to a very limited extent. Here, we evaluate and compare measurement of residual food-derived DNA and protein in stool as potential biomarkers of intake. We performed a pilot study of DNA sequencing-based metabarcoding (FoodSeq) and mass spectrometry-based metaproteomics in five individuals' stool sampled in short, longitudinal bursts accompanied by detailed diet records (n=27 total samples). Dietary data provided by stool DNA, stool protein, and written diet record independently identified a strong within-person dietary signature, identified similar food taxa, and had significantly similar global structure in two of the three pairwise comparisons between measurement techniques (DNA-to-protein and DNA-to-diet record). Metaproteomics identified proteins including myosin, ovalbumin, and beta-lactoglobulin that differentiated food tissue types like beef from dairy and chicken from egg, distinctions that were not possible by DNA alone. Overall, our results lay the groundwork for development of targeted metaproteomic assays for dietary assessment and demonstrate that diverse molecular components of food can be leveraged to study food intake using stool samples.

Direct-to-Consumer Genetic Testing: A Comprehensive Review.

Emerged in the early 2000s, direct-to-consumer (DTC) genetic testing has helped consumers access and understand their genetic information without the involvement of a healthcare provider. Unlike traditional clinical-based testing, in which a healthcare provider is responsible for ordering, testing, interpreting, and communicating the results, DTC testing provides valuable insights directly to individuals about their genetic information. It empowers consumers and their families to be proactive about their health and lifestyle. The online testing format has become increasingly popular due to its accessibility and affordability. However, it raises concerns about the accuracy and reliability of the results, data security and how to ensure privacy for consumers and regulators. A hybrid model combining elements from both DTC and clinical-based genetic testing has surfaced in the market recently. In the US, current health-related DTC genetic tests are not recognized for diagnostic purposes; instead, these tests are intended to provide genetic information that is associated with certain conditions, which may encourage consumers to take the opportunity to discuss the results and their implications with a healthcare provider. This DTC genetic testing review focuses on the fundamental concepts, applications, benefits, limitations, risks, and consumer concerns, as well as the state of the DTC framework compared with the clinical-based and hybrid models. Additionally, the regulatory oversight, data protection, and healthcare professional perspective on DTC genetic testing in the US will be discussed, including current policies and regulations.

Diversity of plant DNA in stool is linked to dietary quality, age, and household income.

Eating a varied diet is a central tenet of good nutrition. Here, we develop a molecular tool to quantify human dietary plant diversity by applying DNA metabarcoding with the chloroplast trnL-P6 marker to 1,029 fecal samples from 324 participants across two interventional feeding studies and three observational cohorts. The number of plant taxa per sample (plant metabarcoding richness or pMR) correlated with recorded intakes in interventional diets and with indices calculated from a food frequency questionnaire in typical diets (ρ = 0.40 to 0.63). In adolescents unable to collect validated dietary survey data, trnL metabarcoding detected 111 plant taxa, with 86 consumed by more than one individual and four (wheat, chocolate, corn, and potato family) consumed by >70% of individuals. Adolescent pMR was associated with age and household income, replicating prior epidemiologic findings. Overall, trnL metabarcoding promises an objective and accurate measure of the number and types of plants consumed that is applicable to diverse human populations.

Ecological memory of prior nutrient exposure in the human gut microbiome.

Many ecosystems have been shown to retain a memory of past conditions, which in turn affects how they respond to future stimuli. In microbial ecosystems, community disturbance has been associated with lasting impacts on microbiome structure. However, whether microbial communities alter their response to repeated stimulus remains incompletely understood. Using the human gut microbiome as a model, we show that bacterial communities retain an "ecological memory" of past carbohydrate exposures. Memory of the prebiotic inulin was encoded within a day of supplementation among a cohort of human study participants. Using in vitro gut microbial models, we demonstrated that the strength of ecological memory scales with nutrient dose and persists for days. We found evidence that memory is seeded by transcriptional changes among primary degraders of inulin within hours of nutrient exposure, and that subsequent changes in the activity and abundance of these taxa are sufficient to enhance overall community nutrient metabolism. We also observed that ecological memory of one carbohydrate species impacts microbiome response to other carbohydrates, and that an individual's habitual exposure to dietary fiber was associated with their gut microbiome's efficiency at digesting inulin. Together, these findings suggest that the human gut microbiome's metabolic potential reflects dietary exposures over preceding days and changes within hours of exposure to a novel nutrient. The dynamics of this ecological memory also highlight the potential for intra-individual microbiome variation to affect the design and interpretation of interventions involving the gut microbiome.

Microbiota responses to different prebiotics are conserved within individuals and associated with habitual fiber intake.

BACKGROUND: Short-chain fatty acids (SCFAs) derived from gut bacteria are associated with protective roles in diseases ranging from obesity to colorectal cancers. Intake of microbially accessible dietary fibers (prebiotics) lead to varying effects on SCFA production in human studies, and gut microbial responses to nutritional interventions vary by individual. It is therefore possible that prebiotic therapies will require customizing to individuals. RESULTS: Here, we explored prebiotic personalization by conducting a three-way crossover study of three prebiotic treatments in healthy adults. We found that within individuals, metabolic responses were correlated across the three prebiotics. Individual identity, rather than prebiotic choice, was also the major determinant of SCFA response. Across individuals, prebiotic response was inversely related to basal fecal SCFA concentration, which, in turn, was associated with habitual fiber intake. Experimental measures of gut microbial SCFA production for each participant also negatively correlated with fiber consumption, supporting a model in which individuals' gut microbiota are limited in their overall capacity to produce fecal SCFAs from fiber. CONCLUSIONS: Our findings support developing personalized prebiotic regimens that focus on selecting individuals who stand to benefit, and that such individuals are likely to be deficient in fiber intake. Video Abstract.

Systematically exploring repurposing effects of antihypertensives.

With availability of voluminous sets of observational data, an empirical paradigm to screen for drug repurposing opportunities (i.e., beneficial effects of drugs on nonindicated outcomes) is feasible. In this article, we use a linked claims and electronic health record database to comprehensively explore repurposing effects of antihypertensive drugs. We follow a target trial emulation framework for causal inference to emulate randomized controlled trials estimating confounding adjusted effects of antihypertensives on each of 262 outcomes of interest. We then fit hierarchical models to the results as a form of postprocessing to account for multiple comparisons and to sift through the results in a principled way. Our motivation is twofold. We seek both to surface genuinely intriguing drug repurposing opportunities and to elucidate through a real application some study design decisions and potential biases that arise in this context.

Measuring and mitigating PCR bias in microbiota datasets.

PCR amplification plays an integral role in the measurement of mixed microbial communities via high-throughput DNA sequencing of the 16S ribosomal RNA (rRNA) gene. Yet PCR is also known to introduce multiple forms of bias in 16S rRNA studies. Here we present a paired modeling and experimental approach to characterize and mitigate PCR NPM-bias (PCR bias from non-primer-mismatch sources) in microbiota surveys. We use experimental data from mock bacterial communities to validate our approach and human gut microbiota samples to characterize PCR NPM-bias under real-world conditions. Our results suggest that PCR NPM-bias can skew estimates of microbial relative abundances by a factor of 4 or more, but that this bias can be mitigated using log-ratio linear models.

State of the Art Causal Inference in the Presence of Extraneous Covariates: A Simulation Study.

The central task of causal inference is to remove (via statistical adjustment) confounding bias that would be present in naive unadjusted comparisons of outcomes in different treatment groups. Statistical adjustment can roughly be broken down into two steps. In the first step, the researcher selects some set of variables to adjust for. In the second step, the researcher implements a causal inference algorithm to adjust for the selected variables and estimate the average treatment effect. In this paper, we use a simulation study to explore the operating characteristics and robustness of state-of-the-art methods for step two (statistical adjustment for selected variables) when step one (variable selection) is performed in a realistically sub-optimal manner. More specifically, we study the robustness of a cross-fit machine learning based causal effect estimator to the presence of extraneous variables in the adjustment set. The take-away for practitioners is that there is value to, if possible, identifying a small sufficient adjustment set using subject matter knowledge even when using machine learning methods for adjustment.

Interindividual Variation in Dietary Carbohydrate Metabolism by Gut Bacteria Revealed with Droplet Microfluidic Culture.

Culture and screening of gut bacteria enable testing of microbial function and therapeutic potential. However, the diversity of human gut microbial communities (microbiota) impedes comprehensive experimental studies of individual bacterial taxa. Here, we combine advances in droplet microfluidics and high-throughput DNA sequencing to develop a platform for separating and assaying growth of microbiota members in picoliter droplets (MicDrop). MicDrop enabled us to cultivate 2.8 times more bacterial taxa than typical batch culture methods. We then used MicDrop to test whether individuals possess similar abundances of carbohydrate-degrading gut bacteria, using an approach which had previously not been possible due to throughput limitations of traditional bacterial culture techniques. Single MicDrop experiments allowed us to characterize carbohydrate utilization among dozens of gut bacterial taxa from distinct human stool samples. Our aggregate data across nine healthy stool donors revealed that all of the individuals harbored gut bacterial species capable of degrading common dietary polysaccharides. However, the levels of richness and abundance of polysaccharide-degrading species relative to monosaccharide-consuming taxa differed by up to 2.6-fold and 24.7-fold, respectively. Additionally, our unique dataset suggested that gut bacterial taxa may be broadly categorized by whether they can grow on single or multiple polysaccharides, and we found that this lifestyle trait is correlated with how broadly bacterial taxa can be found across individuals. This demonstration shows that it is feasible to measure the function of hundreds of bacterial taxa across multiple fecal samples from different people, which should in turn enable future efforts to design microbiota-directed therapies and yield new insights into microbiota ecology and evolution.IMPORTANCE Bacterial culture and assay are components of basic microbiological research, drug development, and diagnostic screening. However, community diversity can make it challenging to comprehensively perform experiments involving individual microbiota members. Here, we present a new microfluidic culture platform that makes it feasible to measure the growth and function of microbiota constituents in a single set of experiments. As a proof of concept, we demonstrate how the platform can be used to measure how hundreds of gut bacterial taxa drawn from different people metabolize dietary carbohydrates. Going forward, we expect this microfluidic technique to be adaptable to a range of other microbial assay needs.

Microbial nitrogen limitation in the mammalian large intestine.

Resource limitation is a fundamental factor governing the composition and function of ecological communities. However, the role of resource supply in structuring the intestinal microbiome has not been established and represents a challenge for mammals that rely on microbial symbionts for digestion: too little supply might starve the microbiome while too much might starve the host. We present evidence that microbiota occupy a habitat that is limited in total nitrogen supply within the large intestines of 30 mammal species. Lowering dietary protein levels in mice reduced their faecal concentrations of bacteria. A gradient of stoichiometry along the length of the gut was consistent with the hypothesis that intestinal nitrogen limitation results from host absorption of dietary nutrients. Nitrogen availability is also likely to be shaped by host-microbe interactions: levels of host-secreted nitrogen were altered in germ-free mice and when bacterial loads were reduced via experimental antibiotic treatment. Single-cell spectrometry revealed that members of the phylum Bacteroidetes consumed nitrogen in the large intestine more readily than other commensal taxa did. Our findings support a model where nitrogen limitation arises from preferential host use of dietary nutrients. We speculate that this resource limitation could enable hosts to regulate microbial communities in the large intestine. Commensal microbiota may have adapted to nitrogen-limited settings, suggesting one reason why excess dietary protein has been associated with degraded gut-microbial ecosystems.

CREB3L1 as a potential biomarker predicting response of triple negative breast cancer to doxorubicin-based chemotherapy.

BACKGROUND: Doxorubicin-based chemotherapy is currently the most frequently used treatment for triple negative breast cancer (TNBC), yet the response rate is not high due to the lack of a biomarker allowing identification of responsive patients before the chemotherapy is initiated. We have demonstrated that doxorubicin inhibits proliferation of cancer cells through proteolytic activation of a transcription factor called CREB3L1 (cAMP response element binding protein 3-like 1), and that CREB3L1 expression in cancer cells is a key determinant of their sensitivity to doxorubicin when they are cultured in vitro or established as xenograft tumors in mice. The purpose of this study is to determine whether CREB3L1 expression in tumor cells of TNBC patients can be established as a biomarker to predict outcomes of doxorubicin-based chemotherapy. METHODS: We performed a retrospective analysis on breast core biopsy tissue samples taken from 18 TNBC patients before they were treated with doxorubicin-based chemotherapy. CREB3L1 expression in the cancer cells was analyzed by immunohistochemistry and quantified using the Immunoreactive Score (IRS). Outcomes of the chemotherapy were measured by the residual cancer burden (RCB) system. RESULTS: CREB3L1 expression levels in TNBC responsive to doxorubicin-based chemotherapy (RCB class 0-2) were significantly higher than that in resistant cancers (RCB class 3) (unpaired two-tailed t test, p = 0.0005; Statistical power 99.8 at 95% confidence level). All cancers expressing higher levels of CREB3L1 (IRS 4-12) responded to doxorubicin-based chemotherapy, whereas all cancers resisting the treatment expressed lower levels of CREB3L1 (IRS 0-3). CONCLUSIONS: These results suggest that CREB3L1 expression level may be used as a biomarker to identify TNBC patients who are more likely to benefit from doxorubicin-based chemotherapy.

Antibiotic-induced changes in the microbiota disrupt redox dynamics in the gut.

How host and microbial factors combine to structure gut microbial communities remains incompletely understood. Redox potential is an important environmental feature affected by both host and microbial actions. We assessed how antibiotics, which can impact host and microbial function, change redox state and how this contributes to post-antibiotic succession. We showed gut redox potential increased within hours of an antibiotic dose in mice. Host and microbial functioning changed under treatment, but shifts in redox potentials could be attributed specifically to bacterial suppression in a host-free ex vivo human gut microbiota model. Redox dynamics were linked to blooms of the bacterial family Enterobacteriaceae. Ecological succession to pre-treatment composition was associated with recovery of gut redox, but also required dispersal from unaffected gut communities. As bacterial competition for electron acceptors can be a key ecological factor structuring gut communities, these results support the potential for manipulating gut microbiota through managing bacterial respiration.

The Prevalence of Antibiotic-Resistant Staphylococcus aureus Nasal Carriage among Industrial Hog Operation Workers, Community Residents, and Children Living in Their Households: North Carolina, USA.

BACKGROUND: Antibiotic use in industrial hog operations (IHOs) can support the emergence of antibiotic-resistant (ABR) Staphylococcus aureus. The extent of ABR S. aureus exposure in IHO workers and children living in their households remains unclear. OBJECTIVE: We investigated ABR S. aureus nasal carriage prevalence among adults with versus without occupational exposure to IHOs and among children living in their households. METHODS: In total, 198 IHO worker-child household pairs and 202 community referent (CR) adult-child household pairs completed a questionnaire and provided a nasal swab which was analyzed for S. aureus, methicillin-resistant S. aureus (MRSA), multidrug-resistant S. aureus (MDRSA), absence of scn (putative marker of livestock association), and spa type. RESULTS: S. aureus nasal carriage prevalence was higher among IHO (53%) compared with CR (31%) adults [adjusted prevalence ratio (aPR): 1.40; 95% confidence interval (CI): 1.07, 1.83], but MRSA nasal carriage prevalence was uncommon (2-3%) in IHO and CR adults. MDRSA nasal carriage prevalence was similar among IHO workers and CR adults (12% vs. 8%; aPR: 1.14; 95% CI: 0.56, 2.29). Nasal carriage prevalence was higher among IHO compared with CR children for S. aureus (49% vs. 31%; aPR: 1.50; 95% CI: 1.13, 1.99), MRSA (14% vs. 6%; aPR: 2.37; 95% CI: 1.14, 4.92), and MDRSA (23% vs. 8%; aPR: 2.64; 95% CI: 1.47, 4.75). We also found suggestive evidence of a higher prevalence of S. aureus, MRSA, and MDRSA among children living with an IHO worker who did versus did not report taking personal protective equipment (PPE) home from the IHO. Livestock-associated S. aureus nasal carriage predominated among IHO workers. CONCLUSION: Our findings support the importance of further research on the prevalence and potential sources of exposure to ABR S. aureus among children living with IHO workers.

Decay of Coliphages in Sewage-Contaminated Freshwater: Uncertainty and Seasonal Effects.

Understanding the fate of enteric viruses in water is vital for protection of water quality. However, the decay of enteric viruses is not well characterized, and its uncertainty has not been examined yet. In this study, the decay of coliphages, an indicator for enteric viruses, was investigated in situ under both sunlit and shaded conditions as well as in summer and winter. The decay rates of coliphages and their uncertainties were analyzed using a Bayesian approach. The results from the summer experiments revealed that the decay rates of somatic coliphages were significantly higher in sunlight (1.29 ± 0.06 day-1) than in shade (0.96 ± 0.04 day-1), but the decay rates of male-specific (F+) coliphages were not significantly different between sunlight (1.09 ± 0.09 day-1) and shaded treatments (1.11 ± 0.08 day-1). The decay rates of both F+ coliphages (0.25 ± 0.02 day-1) and somatic coliphages (0.12 ± 0.01 day-1) in winter were considerably lower than those in summer. Temperature and chlorophyll a (chla) concentration varied significantly (p < 0.001) between the two seasons, suggesting that these parameters might be important contributors to the seasonal variation of coliphage decay. Additionally, the Bayesian approach provided full distributions of decay rates and reduced the uncertainty, offering useful information for comparing decay rates under different conditions.

FrzS regulates social motility in Myxococcus xanthus by controlling exopolysaccharide production.

Myxococcus xanthus Social (S) motility occurs at high cell densities and is powered by the extension and retraction of Type IV pili which bind ligands normally found in matrix exopolysaccharides (EPS). Previous studies showed that FrzS, a protein required for S-motility, is organized in polar clusters that show pole-to-pole translocation as cells reverse their direction of movement. Since the leading cell pole is the site of both the major FrzS cluster and type IV pilus extension/retraction, it was suggested that FrzS might regulate S-motility by activating pili at the leading cell pole. Here, we show that FrzS regulates EPS production, rather than type IV pilus function. We found that the frzS phenotype is distinct from that of Type IV pilus mutants such as pilA and pilT, but indistinguishable from EPS mutants, such as epsZ. Indeed, frzS mutants can be rescued by the addition of purified EPS, 1% methylcellulose, or co-culturing with wildtype cells. Our data also indicate that the cell density requirement in S-motility is likely a function of the ability of cells to construct functional multicellular clusters surrounding an EPS core.

In silico pharmacogenetics of warfarin metabolism.

Pharmacogenetic approaches can be instrumental for predicting individual differences in response to a therapeutic intervention. Here we used a recently developed murine haplotype-based computational method to identify a genetic factor regulating the metabolism of warfarin, a commonly prescribed anticoagulant with a narrow therapeutic index and a large variation in individual dosing. After quantification of warfarin and nine of its metabolites in plasma from 13 inbred mouse strains, we correlated strain-specific differences in 7-hydroxywarfarin accumulation with genetic variation within a chromosomal region encoding cytochrome P450 2C (Cyp2c) enzymes. This computational prediction was experimentally confirmed by showing that the rate-limiting step in biotransformation of warfarin to its 7-hydroxylated metabolite was inhibited by tolbutamide, a Cyp2c isoform-specific substrate, and that this transformation was mediated by expressed recombinant Cyp2c29. We show that genetic variants responsible for interindividual pharmacokinetic differences in drug metabolism can be identified by computational genetic analysis in mice.

In vitro selected Con1 subgenomic replicons resistant to 2'-C-methyl-cytidine or to R1479 show lack of cross resistance.

The HCV polymerase is an attractive target for the development of new and specific anti-HCV drugs. Herein, the characterization of the inhibitory effect of 2'-C-Methyl-Cytidine shows that it is a potent inhibitor of both genotype 1b and 1a HCV replicon replication, both of laboratory-optimized as well as of NS5B clinical isolates-chimera replicons. The corresponding 5'-triphosphate derivative is a potent inhibitor of native HCV replicase isolated from replicon cells and of the recombinant genotype 1b and 1a HCV polymerase-mediated RNA synthesis. Resistance to 2'-C-Methyl-Cytidine was mapped to amino acid substitution S282T in the NS5B coding region. Cross-resistance was observed to 2'-C-Methyl-Adenosine but not to interferon alpha-2a, to non-nucleoside HCV polymerase inhibitors or to R1479, a new and potent nucleoside inhibitor of NS5B polymerase. In vitro studies mapped resistance to R1479 to amino acid substitutions S96T and S96T/N142T of the NS5B polymerase. These mutations did not confer resistance to 2-C-Methyl-Cytidine, thus confirming the lack of cross-resistance between these two HCV inhibitors. These data will allow the optimization of new polymerase inhibitors and their use in combination therapy.

Impact of infarct size on clinical and echocardiographic outcome in patients undergoing nonsurgical septal reduction therapy.

BACKGROUND: Nonsurgical septal reduction therapy (NSRT) with ethanol improves clinical and hemodynamic parameters in patients with symptomatic hypertrophic obstructive cardiomyopathy. The purpose of this study was to examine the impact of infarct size induced by ethanol injection on clinical and echocardiographic outcome after the procedure. METHODS AND RESULTS: The first 261 consecutive patients were included. The mean age was 51 +/- 6 years, and 127 patients were women. The mean creatine kinase (CK) after NSRT was 1411 +/- 653 units. Men had larger infarcts than women (P =.0028). Injecting ethanol as a bolus (P <.001), injecting >1 septal branch (P <.001), or injecting >3 cc of ethanol per septal branch (P <.001) were all determinants of infarct size. When the patients were divided into 4 groups according to peak CK, the New York Heart Association dyspnea score after NRST, the septal thickness, and left ventricular outflow tract gradient were more significantly reduced in patients with peak CK >1000 U/dL compared to those with peak CK <1000 U/dL. Patients with peak CK >1500 U/dL had a significant drop in left ventricular ejection fraction at 6 weeks (70 +/- 6 vs 63 +/- 6, P =.035). CONCLUSION: An average size infarct (peak CK 1000-1500 U/dL) seems to lead to the optimal outcome after NSRT.