Population Monte Carlo algorithms

We give a cross-disciplinary survey on ``population'' Monte Carlo algorithms. In these algorithms, a set of ``walkers'' or ``particles'' is used as a representation of a high-dimensional vector. The computation is carried out by a random walk and split/deletion of these objects. The algorithms are developed in various fields in physics and statistical sciences and called by lots of different terms -- ``quantum Monte Carlo'', ``transfer-matrix Monte Carlo'', ``Monte Carlo filter (particle filter)'',``sequential Monte Carlo'' and ``PERM'' etc. Here we discuss them in a coherent framework. We also touch on related algorithms -- genetic algorithms and annealed importance sampling.Comment: Title is changed (Population-based Monte Carlo -> Population Monte Carlo). A number of small but important corrections and additions. References are also added. Original Version is read at 2000 Workshop on Information-Based Induction Sciences (July 17-18, 2000, Syuzenji, Shizuoka, Japan). No figure

Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes:the TriMaster study

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: To minimize the risk of patient re-identification, de-identified individual patient-level clinical data are available under restricted access. Requests for access to anonymized individual participant data and study documents should be made to the corresponding author and will be reviewed by the Peninsula Research Bank Steering Committee. Access to data through the Peninsula Research Bank will be granted for requests with scientifically valid questions by academic teams with the necessary skills appropriate for the research. Data that can be shared will be released with the relevant transfer agreement.Code availability: Requests for access to code should be made to the corresponding author and will be reviewed by the Peninsula Research Bank Steering Committee. Access to code through the Peninsula Research Bank will be granted for requests with scientifically valid questions by academic teams with the necessary skills appropriate for the research. Code will be released by the lead statistician.Precision medicine aims to treat an individual based on their clinical characteristics. A differential drug response, critical to using these features for therapy selection, has never been examined directly in type 2 diabetes. In this study, we tested two hypotheses: (1) individuals with body mass index (BMI) > 30 kg/m2, compared to BMI ≤ 30 kg/m2, have greater glucose lowering with thiazolidinediones than with DPP4 inhibitors, and (2) individuals with estimated glomerular filtration rate (eGFR) 60-90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, have greater glucose lowering with DPP4 inhibitors than with SGLT2 inhibitors. The primary endpoint for both hypotheses was the achieved HbA1c difference between strata for the two drugs. In total, 525 people with type 2 diabetes participated in this UK-based randomized, double-blind, three-way crossover trial of 16 weeks of treatment with each of sitagliptin 100 mg once daily, canagliflozin 100 mg once daily and pioglitazone 30 mg once daily added to metformin alone or metformin plus sulfonylurea. Overall, the achieved HbA1c was similar for the three drugs: pioglitazone 59.6 mmol/mol, sitagliptin 60.0 mmol/mol and canagliflozin 60.6 mmol/mol (P = 0.2). Participants with BMI > 30 kg/m2, compared to BMI ≤ 30 kg/m2, had a 2.88 mmol/mol (95% confidence interval (CI): 0.98, 4.79) lower HbA1c on pioglitazone than on sitagliptin (n = 356, P = 0.003). Participants with eGFR 60-90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, had a 2.90 mmol/mol (95% CI: 1.19, 4.61) lower HbA1c on sitagliptin than on canagliflozin (n = 342, P = 0.001). There were 2,201 adverse events reported, and 447/525 (85%) randomized participants experienced an adverse event on at least one of the study drugs. In this precision medicine trial in type 2 diabetes, our findings support the use of simple, routinely available clinical measures to identify the drug class most likely to deliver the greatest glycemic reduction for a given patient. (ClinicalTrials.gov registration: NCT02653209 ; ISRCTN registration: 12039221 .).Medical Research Council (MRC)National Institute for Health and Care Research (NIHR

Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes:a retrospective cohort study

Background: Current treatment guidelines do not provide recommendations to support the selection of treatment for most people with type 2 diabetes. We aimed to develop and validate an algorithm to allow selection of optimal treatment based on glycaemic response, weight change, and tolerability outcomes when choosing between SGLT2 inhibitor or DPP-4 inhibitor therapies. Methods: In this retrospective cohort study, we identified patients initiating SGLT2 and DPP-4 inhibitor therapies after Jan 1, 2013, from the UK Clinical Practice Research Datalink (CPRD). We excluded those who received SGLT2 or DPP-4 inhibitors as first-line treatment or insulin at the same time, had estimated glomerular filtration rate (eGFR) of less than 45 mL/min per 1·73 m2, or did not have a valid baseline glycated haemoglobin (HbA1c) measure (<53 or ≥120 mmol/mol). The primary efficacy outcome was the HbA1c value reached 6 months after drug initiation, adjusted for baseline HbA1c. Clinical features associated with differential HbA1c outcome on the two therapies were identified in CPRD (n=26 877), and replicated in reanalysis of 14 clinical trials (n=10 414). An algorithm to predict individual-level differential HbA1c outcome on the two therapies was developed in CPRD (derivation; n=14 069) and validated in head-to-head trials (n=2499) and CPRD (independent validation; n=9376). In CPRD, we further explored heterogeneity in 6-month weight change and treatment discontinuation. Findings: Among 10 253 patients initiating SGLT2 inhibitors and 16 624 patients initiating DPP-4 inhibitors in CPRD, baseline HbA1c, age, BMI, eGFR, and alanine aminotransferase were associated with differential HbA1c outcome with SGLT2 inhibitor and DPP-4 inhibitor therapies. The median age of participants was 62·0 years (IQR 55·0–70·0). 10 016 (37·3%) were women and 16 861 (62·7%) were men. An algorithm based on these five features identified a subgroup, representing around four in ten CPRD patients, with a 5 mmol/mol or greater observed benefit with SGLT2 inhibitors in all validation cohorts (CPRD 8·8 mmol/mol [95% CI 7·8–9·8]; CANTATA-D and CANTATA-D2 trials 5·8 mmol/mol [3·9–7·7]; BI1245.20 trial 6·6 mmol/mol [2·2–11·0]). In CPRD, predicted differential HbA1c response with SGLT2 inhibitor and DPP-4 inhibitor therapies was not associated with weight change. Overall treatment discontinuation within 6 months was similar in patients predicted to have an HbA1c benefit with SGLT2 inhibitors over DPP-4 inhibitors (median 15·2% [13·2–20·3] vs 14·4% [12·9–16·7]). A smaller subgroup predicted to have greater HbA1c reduction with DPP-4 inhibitors were twice as likely to discontinue SGLT2 inhibitors than DPP-4 inhibitors (median 26·8% [23·4–31·0] vs 14·8% [12·9–16·8]). Interpretation: A validated treatment selection algorithm for SGLT2 inhibitor and DPP-4 inhibitor therapies can support decisions on optimal treatment for people with type 2 diabetes. Funding: BHF-Turing Cardiovascular Data Science Award and the UK Medical Research Council

On the influence of the companion star in Eta Carinae: 2D radiative transfer modeling of the ultraviolet and optical spectra

We present 2D radiative transfer modeling of the Eta Carinae binary system accounting for the presence of a wind-wind collision (WWC) cavity carved in the optically-thick wind of the primary star. By comparing synthetic line profiles with HST/STIS spectra obtained near apastron, we show that the WWC cavity has a strong influence on multi-wavelength diagnostics. This influence is regulated by the modification of the optical depth in the continuum and spectral lines. We find that H-alpha, H-beta, and Fe II lines are the most affected by the WWC cavity, since they form over a large volume of the primary wind. These spectral lines depend on latitude and azimuth since, according to the orientation of the cavity, different velocity regions of a spectral line are affected. For 2D models with orientation corresponding to orbital inclination angle 110deg < i < 140deg and longitude of periastron 210deg < omega < 330deg, the blueshifted and zero-velocity regions of the line profiles are the most affected. These orbital orientations are required to simultaneously fit the UV and optical spectrum of Eta Car, for a half-opening angle of the cavity in the range 50-70deg. We find that the excess P-Cygni absorption seen in H-alpha, H-beta and optical Fe II lines in spherical models becomes much weaker or absent in the 2D models, in agreement with the observations. The observed UV spectrum of Eta Car, dominated by Fe II absorption lines, is superbly reproduced by our 2D cavity models. Small discrepancies still remain, as H-gamma and H-delta absorptions are overestimated by our models. We suggest that photoionization of the wind of the primary by the hot companion star is responsible for the weak absorption seen in these lines. Our CMFGEN models indicate that the primary star has a mass-loss rate of 8.5x10e-4 Msun/yr and wind terminal velocity of 420 km/s around the 2000 apastron.Comment: 20 pages, 14 figures, accepted for publication in MNRA

Biochemical and histopathological correlation in liver transplant: The first 180 days

It is not known whether the histopathology of the liver allograft can be predicted from biochemical measurements in serum with the same confidence as in the native liver. To answer this question we compared the histopathological diagnoses in 170 biopsy specimens from 70 adult transplant recipients obtained during the first 180 days, with the concentrations of the serum bilirubin and the activities of AST, ALT and alkaline phosphatase measured at the same time. The most frequent diagnosis was cholestasis (n = 45), which was mild, moderate or severe and which may have been complicated by rejection (n = 28) or ischemia (n = 14). Hepatitis (n = 14), ischemia with rejection (n = 6) and spotty focal necrosis (n = 6) were diagnosed less frequently. Fifteen biopsy specimens were reported as histopathologically normal. In general, biochemical measurements discriminated poorly between different histopathological diagnoses. The histopathologically normal liver often showed an abnormal pattern of enzymes and an increase in the serum bilirubin level. As a result histopathologically normal biopsy specimens were indistinguishable biochemically from those with hepatitis. When two pathological conditions were found to coexist (e.g., cholestasis with either rejection or ischemic necrosis, or ischemic necrosis with rejection), the effect on the serum biochemistry was usually not additive and in some instances returned the biochemical abnormalities toward normal. With the exception of the serum bilirubin level, which increased with the severity of uncomplicated cholestasis, we could not identify a specific pattern of biochemical changes corresponding to a given histopathological diagnosis. We suggest that until more specific noninvasive methods of monitoring the transplanted liver are developed protocol liver biopsies offer the best means of identifying significant pathological conditions in liver allografts. (H EPATOLOGY 1992;16:688–693.)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/38382/1/1840160312_ftp.pd

A genome-wide association study identifies protein quantitative trait loci (pQTLs)

There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10 -57), CCL4L1 (p = 3.9×10-21), IL18 (p = 6.8×10-13), LPA (p = 4.4×10-10), GGT1 (p = 1.5×10-7), SHBG (p = 3.1×10-7), CRP (p = 6.4×10-6) and IL1RN (p = 7.3×10-6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10-40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways. © 2008 Melzer et al

Variation in herbivore space use: comparing two savanna ecosystems with different anthrax outbreak patterns in southern Africa

Abstract Background The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen. Methods We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and Kruger National Park, South Africa, where the main host species and outbreak sizes differ. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species. Results Range size differences among species were not linearly related to anthrax case numbers. In Kruger the main host species had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent. Conclusions Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens

A double-blind, randomized, placebo-controlled trial of prostaglandin E 1 in liver transplantation

A double-blind placebo-controlled trial of intravenous prostaglandin PGE 1 (40 Μg/h) was conducted in adult orthotopic liver transplant recipients. Infusion was started intraoperatively and continued for up to 21 days. Patients were followed up for 180 days postoperatively. Among 172 patients eligible for treatment in the study, 160 could be evaluated (78 PGE 1 ; 82 placebo). Patient and graft survival were similar (PGE 1 : 16 deaths, 9 retransplantations [7 survivors]; controls: 15 deaths, 6 retransplantations [3 survivors]). In patients with surviving grafts, however, PGE 1 administration resulted in a 23% shorter mean duration of hospitalization following transplantation (PGE 1 : 24.4 days; controls: 31.8 days; P = .02) and 40% shorter length of time postoperatively in the intensive care unit (PGE 1 : 8.2 days; controls 13.7 days; P = .05). Reduced needs for renal support ( P = .03) or surgical intervention other than retransplantation ( P = .02) were also noted with PGE 1 use. Further, PGE 1 administration resulted in a trend toward improved survival rates in patients with mild renal impairment (preoperative serum creatinine 1.5 mg percent or greater; P = .08). Neither the incidence of acute cellular rejection nor of primary nonfunction was significantly different in the two groups. Phlebitis was the only complication that was more common during PGE 1 administration, (PGE 1 : 9; controls: 4). These results suggest that PGE 1 use in hepatic allograft recipients reduces morbidity and may result in sizable cost reductions. (H EPATOLOGY 1995;21:366–372.)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/38409/1/1840210216_ftp.pd

The Origin of Glucocorticoid Hormone Oscillations

Characterization of a peripheral hormonal system identifies the origin and mechanisms of regulation of glucocorticoid hormone oscillations in rats

A meta-analysis of the investment-uncertainty relationship

In this article we use meta-analysis to investigate the investment-uncertainty relationship. We focus on the direction and statistical significance of empirical estimates. Specifically, we estimate an ordered probit model and transform the estimated coefficients into marginal effects to reflect the changes in the probability of finding a significantly negative estimate, an insignificant estimate, or a significantly positive estimate. Exploratory data analysis shows that there is little empirical evidence for a positive relationship. The regression results suggest that the source of uncertainty, the level of data aggregation, the underlying model specification, and differences between short- and long-run effects are important sources of variation in study outcomes. These findings are, by and large, robust to the introduction of a trend variable to capture publication trends in the literature. The probability of finding a significantly negative relationship is higher in more recently published studies. JEL Classification: D21, D80, E22 1