Strain-level diversity of symbiont communities between individuals and populations of a bioluminescent fish.

The bioluminescent symbiosis involving the urchin cardinalfish, Siphamia tubifer, and Photobacterium mandapamensis, a luminous member of the Vibrionaceae, is highly specific compared to other bioluminescent fish-bacteria associations. Despite this high degree of specificity, patterns of genetic diversity have been observed for the symbionts from hosts sampled over relatively small spatial scales. We characterized and compared sub-species, strain-level symbiont diversity within and between S. tubifer hosts sampled from the Philippines and Japan using PCR fingerprinting. We then carried out whole genome sequencing of the unique symbiont genotypes identified to characterize the genetic diversity of the symbiont community and the symbiont pangenome. We determined that an individual light organ contains six symbiont genotypes on average, but varied between 1-13. Additionally, we found that there were few genotypes shared between hosts from the same location. A phylogenetic analysis of the unique symbiont strains indicated location-specific clades, suggesting some genetic differentiation in the symbionts between host populations. We also identified symbiont genes that were variable between strains, including luxF, a member of the lux operon, which is responsible for light production. We quantified the light emission and growth rate of two strains missing luxF along with the other strains isolated from the same light organs and determined that strains lacking luxF were dimmer but grew faster than most of the other strains, suggesting a potential metabolic trade-off. This study highlights the importance of strain-level diversity in microbial associations and provides new insight into the underlying genetic architecture of intraspecific symbiont communities within a host.

Bayesian screening for feature selection.

Biomedical applications such as genome-wide association studies screen large databases with high-dimensional features to identify rare, weakly expressed, and important continuous-valued features for subsequent detailed analysis. We describe an exact, rapid Bayesian screening approach with attractive diagnostic properties using a Gaussian random mixture model focusing on the missed discovery rate (the probability of failing to identify potentially informative features) rather than the false discovery rate ordinarily used with multiple hypothesis testing. The method provides the likelihood that a feature merits further investigation, as well as distributions of the effect magnitudes and the proportion of features with the same expected responses under alternative conditions. Important features include the dependence of the critical values on clinical and regulatory priorities and direct assessment of the diagnostic properties.

A framework for assessing the impact of accelerated approval.

The FDA's Accelerated Approval program (AA) is a regulatory program to expedite availability of products to treat serious or life-threatening illnesses that lack effective treatment alternatives. Ideally, all of the many stakeholders such as patients, physicians, regulators, and health technology assessment [HTA] agencies that are affected by AA should benefit from it. In practice, however, there is intense debate over whether evidence supporting AA is sufficient to meet the needs of the stakeholders who collectively bring an approved product into routine clinical care. As AAs have become more common, it becomes essential to be able to determine their impact objectively and reproducibly in a way that provides for consistent evaluation of therapeutic decision alternatives. We describe the basic features of an approach for evaluating AA impact that accommodates stakeholder-specific views about potential benefits, risks, and costs. The approach is based on a formal decision-analytic framework combining predictive distributions for therapeutic outcomes (efficacy and safety) based on statistical models that incorporate findings from AA trials with stakeholder assessments of various actions that might be taken. The framework described here provides a starting point for communicating the value of a treatment granted AA in the context of what is important to various stakeholders.

Chromosome-Level Genome Assembly of the Bioluminescent Cardinalfish Siphamia tubifer: An Emerging Model for Symbiosis Research.

The bioluminescent symbiosis involving the sea urchin cardinalfish Siphamia tubifer and the luminous bacterium Photobacterium mandapamensis is an emerging vertebrate model for the study of microbial symbiosis. However, little genetic data are available for the host, limiting the scope of research that can be implemented with this association. We present a chromosome-level genome assembly for S. tubifer using a combination of PacBio HiFi sequencing and Hi-C technologies. The final assembly was 1.2 Gb distributed on 23 chromosomes and contained 32,365 protein coding genes with a BUSCO score of 99%. A comparison of the S. tubifer genome to that of another nonluminous species of cardinalfish revealed a high degree of synteny, whereas a comparison to a more distant relative in the sister order Gobiiformes revealed the fusion of two chromosomes in the cardinalfish genomes. The complete mitogenome of S. tubifer was also assembled, and an inversion in the vertebrate WANCY tRNA genes as well as heteroplasmy in the length of the control region were discovered. A phylogenetic analysis based on whole the mitochondrial genome indicated that S. tubifer is divergent from the rest of the cardinalfish family, highlighting the potential role of the bioluminescent symbiosis in the initial divergence of Siphamia. This high-quality reference genome will provide novel opportunities for the bioluminescent S. tubifer-P. mandapamensis association to be used as a model for symbiosis research.

Characteristics of patients with diabetes hospitalised for COVID-19 infection-a brief case series report.

OBJECTIVES: Diabetes has been shown to be a risk factor for corona virus disease-2019 (COVID-19) infection. The characteristics of patients with diabetes vulnerable to this infection are less specified. We aim to present the characteristics of patients with diabetes admitted to hospital with COVID-19. DESIGN: A retrospective case series. SETTING: A single clinical centre in the UK. METHODS: We have retrospectively collected the demographics, medical characteristics and outcome of all patients with diabetes admitted to hospital over two-week period with COVID-19 infection. All cases were diagnosed by a reverse transcription polymerase chain reaction (RT-PCR) of pharyngeal and nasal swabs. RESULTS: A total of 71 COVID-19 patients were admitted during the study period of whom 16 (22.5%) patients had diabetes and were included in this case series. There was no significant difference between patients with compared to those without diabetes regarding age, gender or clinical presentation. However, comorbidities were more common in patients with diabetes specially hypertension {75% v 36.4%, a difference of 38.6%, 95% confidence interval (CI) 6.5-58.3} and chronic kidney disease (37.5 v 5.5, a difference of 32% (1.6-51.6). Patients with diabetes were significantly more obese than those without diabetes (56.2% v 21.8% a difference of 34.4%, 95% CI 7.7-61.1). About one third (31.3%) of patients with diabetes were frail. Mean {standard deviation (SD)} duration of diabetes was 10 (2.8) years and mean (SD) HbA1c was 60.3 (15.6) mmol/mol. The use of angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs) and non-steroidal anti-inflammatory drugs (NSAIDs) was common (37.5%, 25% and 18.8% respectively). There was no significant difference in the outcomes between patients with compared to those without diabetes. CONCLUSION: Patients with diabetes hospitalised for COVID-19 were significantly more obese and had high prevalence of comorbidities than those without diabetes. Other features of patients with diabetes and COVID-19 infection included long duration of diabetes, less tight glycaemic control and common use of ACE inhibitors, ARBs and NSAIDs.

Chinese and British Hospitalised Patients with COVID-19-a Comparative Case Series Analysis.

The COVID-19 pandemic initially started in China then spread to Europe. It is not known whether COVID-19 affects patients differently across the two continents. We aimed to describe our cohort of patients admitted to a single British centre with COVID-19 in comparison to a Chinese cohort of similar size and admitted over a similar time period to Chinese centres. We present a comparison of 62 Chinese and 71 British cases hospitalised for COVID-19. Cases in both sites were confirmed by a positive RT-PCR of nasopharyngeal swabs. Comparison analysis highlighted some differences between both populations. The most striking difference is the significantly older age of the British population (72% of the British ≥ 66 years compared to only 3% of the Chinese patients, difference of 69%, 95% confidence interval (CI) 68.3% to 69.7%, respectively) and the associated significant premorbid conditions (85% of patients vs 32%, difference of 53%, 95% CI 52 to 54%, respectively). Gastrointestinal and general symptoms were more common clinical presentation in the British while respiratory symptoms were more prominent in the Chinese cohort. Mortality was significantly higher in the British cohort 14% compared to none in the Chinese cohort (difference of 14%, 95% CI 13.7 to 14.3%). We conclude that COVID-19 does present differently in these two cohorts, but the apparent differences in the clinical presentations could be explained by the inherent differences in the demographics and case mix between both countries.

Evaluation of early clinical failure criteria for gram-negative bloodstream infections.

OBJECTIVES: The aim was the development of early clinical failure criteria (ECFC) to predict unfavourable outcomes in patients with Gram-negative bloodstream infections (GN-BSI). METHODS: Adults with community-onset GN-BSI who survived hospitalization for ≥72 hr at Prisma Health-Midlands hospitals in Columbia, SC, USA from January 1, 2010 to June 30, 2015 were identified. Multivariable logistic regression was used to examine the association between clinical variables between 72 and 96 hr after GN-BSI and unfavourable outcomes (28-day mortality or hospital length of stay >14 days from GN-BSI onset). RESULTS: Among 766 patients, 225 (29%) had unfavourable outcomes. After adjustments for Charlson Comorbidity Index and appropriateness of empirical antimicrobial therapy in multivariable model, predictors of unfavourable outcomes included systolic blood pressure <100 mmHg or vasopressor use (adjusted odds ratio (aOR) 1.8, 95% confidence interval (CI) 1.2-2.9), heart rate >100 beats/minute (aOR 1.7, 95% CI 1.1-2.5), respiratory rate ≥22 breaths/minute or mechanical ventilation (aOR 2.1, 95% CI 1.4-3.3), altered mental status (aOR 4.5, 95% CI 2.8-7.1), and white blood cell count >12 000/mm3 (aOR 2.7, 95% CI 1.8-4.1) between 72 and 96 hr after index GN-BSI. Area under receiver operating characteristic curve of ECFC model in predicting unfavourable outcomes was 0.77 (0.84 and 0.71 in predicting 28-day mortality and prolonged hospitalization, respectively). CONCLUSIONS: Risk of 28-day mortality or prolonged hospitalization can be estimated between 72 and 96 hr after GN-BSI using ECFC. These criteria may have clinical utility in management of GN-BSI and may improve methodology of future investigations assessing response to antimicrobial therapy based on a standard evidence-based definition of early clinical failure.

Obesity, dieting, and multiple sclerosis.

BACKGROUND: Obesity is common in the United States and is associated with a higher risk of relapse and comorbidities, and increased disease progression, in people with MS. METHODS: We examined the prevalence of overweight and obesity in the MS Sunshine Study, a matched case-control study of multiple sclerosis in Southern California (470 cases, 519 controls). We reported the proportion of participants who adopted a specific diet for nutrition or weight loss purposes, and identified independent predictors of dieting. RESULTS: In the total population, 32% and 37% were overweight and obese, respectively. Case participants were no more likely to adopt a specific diet for nutrition or weight loss purposes than control participants (10% and 11%, respectively). Being obese, younger, female or non-Hispanic were independently associated with dieting. CONCLUSION: Despite the evidence that obesity can worsen MS prognosis, and the high prevalence of overweight/obesity, case participants were no more likely to adopt a specific diet than control participants. Improved nutrition education may help people with MS make healthy dietary changes for nutrition or weight loss purposes.

BMA-Mod: A Bayesian model averaging strategy for determining dose-response relationships in the presence of model uncertainty.

Successful pharmaceutical drug development requires finding correct doses. The issues that conventional dose-response analyses consider, namely whether responses are related to doses, which doses have responses differing from a control dose response, the functional form of a dose-response relationship, and the dose(s) to carry forward, do not need to be addressed simultaneously. Determining if a dose-response relationship exists, regardless of its functional form, and then identifying a range of doses to study further may be a more efficient strategy. This article describes a novel estimation-focused Bayesian approach (BMA-Mod) for carrying out the analyses when the actual dose-response function is unknown. Realizations from Bayesian analyses of linear, generalized linear, and nonlinear regression models that may include random effects and covariates other than dose are optimally combined to produce distributions of important secondary quantities, including test-control differences, predictive distributions of possible outcomes from future trials, and ranges of doses corresponding to target outcomes. The objective is similar to the objective of the hypothesis-testing based MCP-Mod approach, but provides more model and distributional flexibility and does not require testing hypotheses or adjusting for multiple comparisons. A number of examples illustrate the application of the method.

Unified screening for potential elevated adverse event risk and other associations.

Patients in large clinical trials and in studies employing large observational databases report many different adverse events, most of which will not have been anticipated at the outset. Conventional hypothesis testing of between group differences for each adverse event can be problematic: Lack of significance does not mean lack of risk, the tests usually are not adjusted for multiplicity, and the data determine which hypotheses are tested. This article describes a Bayesian screening approach suitable for clinical trials and large observational databases that do not test hypotheses, are self-adjusting for multiplicity, provide a direct assessment of the likelihood of no material drug-event association, and quantify the strength of the observed association. Clinical and/or regulatory considerations define the criteria for assessing drug-event associations. The diagnostic properties of this new approach can be evaluated analytically. The result of comparison of the results from the method relative to current methods when applied to a commonly used data set indicates that the findings are largely similar, but with some interesting differences that may be relevant in application. Applying the method to a large vaccine trial reduces the number of adverse events that might require further investigation substantially.

Genomic analysis of a cardinalfish with larval homing potential reveals genetic admixture in the Okinawa Islands.

Discrepancies between potential and observed dispersal distances of reef fish indicate the need for a better understanding of the influence of larval behaviour on recruitment and dispersal. Population genetic studies can provide insight on the degree to which populations are connected, and the development of restriction site-associated sequencing (RAD-Seq) methods has made such studies of nonmodel organisms more accessible. We applied double-digest RAD-Seq methods to test for population differentiation in the coral reef-dwelling cardinalfish, Siphamia tubifer, which based on behavioural studies, have the potential to use navigational cues to return to natal reefs. Analysis of 11,836 SNPs from fish collected at coral reefs in Okinawa, Japan, from eleven locations over 3 years reveals little genetic differentiation between groups of S. tubifer at spatial scales from 2 to 140 km and between years at one location: pairwise FST values were between 0.0116 and 0.0214. These results suggest that the Kuroshio Current largely influences larval dispersal in the region, and in contrast to expectations based on studies of other cardinalfishes, there is no evidence of population structure for S. tubifer at the spatial scales examined. However, analyses of outlier loci putatively under selection reveal patterns of temporal differentiation that indicate high population turnover and variable larval supply from divergent source populations between years. These findings highlight the need for more studies of fishes across various geographic regions that also examine temporal patterns of genetic differentiation to better understand the potential connections between early life-history traits and connectivity of reef fish populations.

Monitoring potential adverse event rate differences using data from blinded trials: the canary in the coal mine.

The development of drugs and biologicals whose mechanisms of action may extend beyond their target indications has led to a need to identify unexpected potential toxicities promptly even while blinded clinical trials are under way. One component of recently issued FDA rules regarding safety reporting requirements raises the possibility of breaking the blind for pre-identified serious adverse events that are not the clinical endpoints of a blinded study. Concern has been expressed that unblinding individual cases of frequently occurring adverse events could compromise the overall validity of the study. However, if external information is available about adverse event rates among patients not receiving the test product in populations similar to the study population, then it may be possible to address the potential for elevated risk without unblinding the trial. This article describes a Bayesian approach for determining the likelihood of elevated risk suitable binomial or Poisson likelihoods that applies regardless of the metric used to express the difference. The method appears to be particularly appropriate for routine monitoring of safety information for project development programs that include large blinded trials. Copyright © 2016 John Wiley & Sons, Ltd.

Evaluation of the Stop Smoking Wales NHS Dental Practice Incentive Scheme.

In December 2014, Public Health Wales introduced a proof-of-concept incentive scheme, aiming to encourage National Health Service (NHS) dental practitioners in Wales to provide brief intervention for smoking cessation and increase referrals to Stop Smoking Wales (SSW). The scheme ran for 11 weeks. Practitioners were advised to only refer patients who agreed with the referral. Practices were reimbursed £7 for every referral sent to SSW. Eighty-three dental practices signed up to participate, equating to 18% of NHS sites across Wales. SSW received 308 referrals, of which 297 (96%) were considered new contacts. One hundred and fifty-eight individuals (51%) accepted an assessment. Of these, 48 actually attended (30%). Thirty-two individuals became treated smokers (attending both an assessment and treatment session). Of these, 22 became self-reported quitters; 19 of these were validated through carbon monoxide (CO) monitoring. The cost to receive individuals into SSW via the dental incentive scheme was approximately £98 per self-reported quitter. The scheme greatly increased the number of referrals to SSW from dentists, compared to previous records and so fulfilled its aims. Amendments to the process could improve cost-effectiveness of a similar scheme.

Control charts for monitoring accumulating adverse event count frequencies from single and multiple blinded trials.

Conventional practice monitors accumulating information about drug safety in terms of the numbers of adverse events reported from trials in a drug development program. Estimates of between-treatment adverse event risk differences can be obtained readily from unblinded trials with adjustment for differences among trials using conventional statistical methods. Recent regulatory guidelines require monitoring the cumulative frequency of adverse event reports to identify possible between-treatment adverse event risk differences without unblinding ongoing trials. Conventional statistical methods for assessing between-treatment adverse event risks cannot be applied when the trials are blinded. However, CUSUM charts can be used to monitor the accumulation of adverse event occurrences. CUSUM charts for monitoring adverse event occurrence in a Bayesian paradigm are based on assumptions about the process generating the adverse event counts in a trial as expressed by informative prior distributions. This article describes the construction of control charts for monitoring adverse event occurrence based on statistical models for the processes, characterizes their statistical properties, and describes how to construct useful prior distributions. Application of the approach to two adverse events of interest in a real trial gave nearly identical results for binomial and Poisson observed event count likelihoods. Copyright © 2016 John Wiley & Sons, Ltd.

Life history of the symbiotically luminous cardinalfish Siphamia tubifer (Perciformes: Apogonidae).

Characteristics of the life history of the coral reef-dwelling cardinalfish Siphamia tubifer, from Okinawa, Japan, were defined. A paternal mouthbrooder, S. tubifer, is unusual in forming a bioluminescent symbiosis with Photobacterium mandapamensis. The examined S. tubifer (n = 1273) ranged in size from 9·5 to 43·5 mm standard length (LS ), and the minimum size at sexual maturity was 22 mm LS . The number of S. tubifer associated during the day among the spines of host urchins was 22·9 ± 16·1 (mean ± s.d.; Diadema setosum) and 3·6 ± 3·2 (Echinothrix calamaris). Diet consisted primarily of crustacean zooplankton. Batch fecundity (number of eggs; FB ) was related to LS by the equations: males (fertilized eggs) FB = 27·5LS - 189·46; females (eggs) FB = 31·3LS - 392·63. Individual mass (M; g) as a function of LS was described by the equation: M=9·74×10-5LS2·68. Growth, determined from otolith microstructure analysis, was described with the von Bertalanffy growth function with the following coefficients: L∞ = 40·8 mm LS , K = 0·026 day(-1) and t0 = 23·25 days. Planktonic larval duration was estimated to be 30 days. The age of the oldest examined individual was 240 days. The light organ of S. tubifer, which harbours the symbiotic population of P. mandapamensis, increased linearly in diameter as S. tubifer LS increased, and the bacterial population increased logarithmically with S. tubifer LS . These characteristics indicate that once settled, S. tubifer grows quickly, reproduces early and typically survives much less than 1 year in Okinawa. These characteristics are generally similar to other small reef fishes but they indicate that S. tubifer experiences higher mortality.

Joint modeling of survival and longitudinal non-survival data: current methods and issues. Report of the DIA Bayesian joint modeling working group.

Explicitly modeling underlying relationships between a survival endpoint and processes that generate longitudinal measured or reported outcomes potentially could improve the efficiency of clinical trials and provide greater insight into the various dimensions of the clinical effect of interventions included in the trials. Various strategies have been proposed for using longitudinal findings to elucidate intervention effects on clinical outcomes such as survival. The application of specifically Bayesian approaches for constructing models that address longitudinal and survival outcomes explicitly has been recently addressed in the literature. We review currently available methods for carrying out joint analyses, including issues of implementation and interpretation, identify software tools that can be used to carry out the necessary calculations, and review applications of the methodology.

Principled Structured Incorporation of Clinical Knowledge Into Strategic Development Decisions.

Efficient use of limited pharmaceutical product development resources requires integrating multiple attributes, such as efficacy, safety, pharmacology, and so on, to decide at any stage whether the development of a product should proceed aggressively or slowly or be terminated. The decision process proceeds most effectively when the knowledge and experience of a product development team are transparently and reproducibly integrated with the findings from completed experiments and trials. In this article, the authors describe an approach for quantitatively and objectively assessing evidence at any stage of development, one based on a mathematical combination of sets of pairwise comparisons. The attributes of the process and the rules for combining its elements to guide decisions are determined by the project team and other stakeholders before obtaining the determinative data to facilitate exploration of the sensitivity of a recommended action to various assumptions. Its statistical properties can be evaluated with standard statistical decision analysis methods.

Methods and Issues to Consider for Detection of Safety Signals From Spontaneous Reporting Databases: A Report of the DIA Bayesian Safety Signal Detection Working Group.

Spontaneous reporting (SR) adverse event system databases, large observational databases, large clinical trials, and large health records databases comprise repositories of information that may be useful for early detection of potential harms associated with drugs, devices, and vaccines. All of the data sources include many different adverse events and many medical products, so that any approach designed to detect "important" signals of potential harm must have adequate specificity to protect against false alarms yet provide satisfactory sensitivity for detecting issues that really need further investigation. Algorithms for evaluating potential risks using information from these sources, especially SR databases, have been described in the literature. The algorithms may seek to identify potential product-event associations without any prior specifications, to identify events associated with a particular product or set of products, or to identify products associated with a particular event or set of events. This article provides recommendations for using information from postmarketing spontaneous adverse event reporting databases to provide insight into risks of potential harm expressed by safety signals and offers guidance regarding appropriate methods, both frequentist and Bayesian, to use in various situations as a function of the objective of the analysis.

Exoplanet detection. A terrestrial planet in a ~1-AU orbit around one member of a ~15-AU binary.

Using gravitational microlensing, we detected a cold terrestrial planet orbiting one member of a binary star system. The planet has low mass (twice Earth's) and lies projected at ~0.8 astronomical units (AU) from its host star, about the distance between Earth and the Sun. However, the planet's temperature is much lower, <60 Kelvin, because the host star is only 0.10 to 0.15 solar masses and therefore more than 400 times less luminous than the Sun. The host itself orbits a slightly more massive companion with projected separation of 10 to 15 AU. This detection is consistent with such systems being very common. Straightforward modification of current microlensing search strategies could increase sensitivity to planets in binary systems. With more detections, such binary-star planetary systems could constrain models of planet formation and evolution.