Preparing for the Rising Tide

On October 29, 2012, one of the largest Atlantic basin storms in recorded history hit the East Coast. Although Superstorm Sandy centered around New Jersey and New York when it made landfall, the massive storm system spanned 1,000 miles north to south, over three times the size of a typical hurricane. Luckily for Boston, Sandy’s storm surge hit the city near low tide, causing relatively minor coastal flooding. Had the storm hit 5½ hours earlier, 6.6 percent of the city could have been flooded, with floodwaters reaching City Hall. Events such as Superstorm Sandy highlight the growing relevance of climate change and draw attention to the importance of taking steps today to be prepared for the likely events of tomorrow. Preparing for the Rising Tide provides policy makers, planners and property owners with site-specific examples of how to assess vulnerability and increase resilience to coastal flooding over time. The United Nations Intergovernmental Panel on Climate Change (IPCC) defines vulnerability as the degree to which a system is susceptible to, and unable to cope with, adverse effects of climate change, including climate variability and extremes.” Vulnerability assessments focus action on highly sensitive populations, locations and infrastructure. Preparedness plans need to be robust enough to handle any future condition, and/or flexible enough change over time to meet needs as they arise. Ideally they include “no-regret” and co-benefit” solutions that extend beyond flood control goals. Cost-effective preparedness plans will result in both “here and now” and “prepare and monitor” actions based on threshold triggers such as sea level rise. Previous reports have described a range of large-scale adaptation strategies. This report takes those recommendations and applies them to specific properties in Boston. Some cities such as Seattle, WA and Charleston, SC are developing “floodable zones” that preserve the city’s access to its waterfront while minimizing damage when periodic flooding occurs. This concept of “living with water” is an option to consider in Boston as well

Biodiversity of Borrelia burgdorferi Strains in Tissues of Lyme Disease Patients

Plant and animal biodiversity are essential to ecosystem health and can provide benefits to humans ranging from aesthetics to maintaining air quality. Although the importance of biodiversity to ecology and conservation biology is obvious, such measures have not been applied to strains of an invasive bacterium found in human tissues during infection. In this study, we compared the strain biodiversity of Borrelia burgdorferi found in tick populations with that found in skin, blood, synovial fluid or cerebrospinal fluid of Lyme disease patients. The biodiversity of B. burgdorferi strains is significantly greater in tick populations than in the skin of patients with erythema migrans. In turn, strains from skin are significantly more diverse than strains at any of the disseminated sites. The cerebrospinal fluid of patients with neurologic Lyme disease harbored the least pathogen biodiversity. These results suggest that human tissues act as niches that can allow entry to or maintain only a subset of the total pathogen population. These data help to explain prior clinical observations on the natural history of B. burgdorferi infection and raise several questions that may help to direct future research to better understand the pathogenesis of this infection

Search for the lepton-flavor-violating decays Bs0→e±μ∓ and B0→e±μ∓

A search for the lepton-flavor-violating decays Bs0→e±μ∓ and B0→e±μ∓ is performed with a data sample, corresponding to an integrated luminosity of 1.0  fb-1 of pp collisions at √s=7  TeV, collected by the LHCb experiment. The observed number of Bs0→e±μ∓ and B0→e±μ∓ candidates is consistent with background expectations. Upper limits on the branching fractions of both decays are determined to be B(Bs0→e±μ∓)101  TeV/c2 and MLQ(B0→e±μ∓)>126  TeV/c2 at 95% C.L., and are a factor of 2 higher than the previous bounds

LEADER 5: prevalence and cardiometabolic impact of obesity in cardiovascular high-risk patients with type 2 diabetes mellitus: baseline global data from the LEADER trial

Background: Epidemiological data on obesity are needed, particularly in patients with type 2 diabetes mellitus (T2DM) and high cardiovascular (CV) risk. We used the baseline data of liraglutide effect and action in diabetes: evaluation of CV outcome results—A long term Evaluation (LEADER) (a clinical trial to assess the CV safety of liraglutide) to investigate: (i) prevalence of overweight and obesity; (ii) relationship of the major cardiometabolic risk factors with anthropometric measures of adiposity [body mass index (BMI) and waist circumference (WC)]; and (iii) cardiometabolic treatment intensity in relation to BMI and WC. Methods: LEADER enrolled two distinct populations of high-risk patients with T2DM in 32 countries: (1) aged ≥50 years with prior CV disease; (2) aged ≥60 years with one or more CV risk factors. Associations of metabolic variables, demographic variables and treatment intensity with anthropometric measurements (BMI and WC) were explored using regression models (ClinicalTrials.gov identifier: NCT01179048). Results: Mean BMI was 32.5 ± 6.3 kg/m2 and only 9.1 % had BMI <25 kg/m2. The prevalence of healthy WC was also extremely low (6.4 % according to International Joint Interim Statement for the Harmonization of the Metabolic Syndrome criteria). Obesity was associated with being younger, female, previous smoker, Caucasian, American, with shorter diabetes duration, uncontrolled blood pressure (BP), antihypertensive agents, insulin plus oral antihyperglycaemic treatment, higher levels of triglycerides and lower levels of high-density lipoprotein cholesterol. Conclusions: Overweight and obesity are prevalent in high CV risk patients with T2DM. BMI and WC are related to the major cardiometabolic risk factors. Furthermore, treatment intensity, such as insulin, statins or oral antihypertensive drugs, is higher in those who are overweight or obese; while BP and lipid control in these patients are remarkably suboptimal. LEADER confers a unique opportunity to explore the longitudinal effect of weight on CV risk factors and hard endpoints

Association of Cardiometabolic Multimorbidity With Mortality.

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing. OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy. RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity

Association of Cardiometabolic Multimorbidity With Mortality.

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing. OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy. RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity

Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: A comparative risk assessment

Background: High blood pressure, blood glucose, serum cholesterol, and BMI are risk factors for cardiovascular diseases and some of these factors also increase the risk of chronic kidney disease and diabetes. We estimated mortality from cardiovascular diseases, chronic kidney disease, and diabetes that was attributable to these four cardiometabolic risk factors for all countries and regions from 1980 to 2010. Methods: We used data for exposure to risk factors by country, age group, and sex from pooled analyses of population-based health surveys. We obtained relative risks for the effects of risk factors on cause-specific mortality from meta-analyses of large prospective studies. We calculated the population attributable fractions for each risk factor alone, and for the combination of all risk factors, accounting for multicausality and for mediation of the effects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specific population attributable fractions by the number of disease-specific deaths. We obtained cause-specific mortality from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all the inputs to the final estimates. Findings: In 2010, high blood pressure was the leading risk factor for deaths due to cardiovascular diseases, chronic kidney disease, and diabetes in every region, causing more than 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths, and high cholesterol for more than 10%. After accounting for multicausality, 63% (10·8 million deaths, 95% CI 10·1-11·5) of deaths from these diseases in 2010 were attributable to the combined effect of these four metabolic risk factors, compared with 67% (7·1 million deaths, 6·6-7·6) in 1980. The mortality burden of high BMI and glucose nearly doubled from 1980 to 2010. At the country level, age-standardised death rates from these diseases attributable to the combined effects of these four risk factors surpassed 925 deaths per 100 000 for men in Belarus, Kazakhstan, and Mongolia, but were less than 130 deaths per 100 000 for women and less than 200 for men in some high-income countries including Australia, Canada, France, Japan, the Netherlands, Singapore, South Korea, and Spain. Interpretation: The salient features of the cardiometabolic disease and risk factor epidemic at the beginning of the 21st century are high blood pressure and an increasing effect of obesity and diabetes. The mortality burden of cardiometabolic risk factors has shifted from high-income to low-income and middle-income countries. Lowering cardiometabolic risks through dietary, behavioural, and pharmacological interventions should be a part of the global response to non-communicable diseases. Funding: UK Medical Research Council, US National Institutes of Health. © 2014 Elsevier Ltd

Measurement of cos⁡2β\cos{2\beta} in B0→D(∗)h0B^{0} \to D^{(*)} h^{0} with D→KS0π+π−D \to K_{S}^{0} \pi^{+} \pi^{-} decays by a combined time-dependent Dalitz plot analysis of BaBar and Belle data

We report measurements of $\sin{2\beta}$ and $\cos{2\beta}$ from a time-dependent Dalitz plot analysis of $B^{0} \to D^{(*)} h^{0}$ with $D \to K_{S}^{0} \pi^{+} \pi^{-}$ decays, where the light unflavored and neutral hadron $h^{0}$ is a $\pi^{0}$, $\eta$, or $\omega$ meson. The analysis is performed with a combination of the final data sets of the \babar\ and Belle experiments containing $471 \times 10^{6}$ and $772 \times 10^{6}$ $B\bar{B}$ pairs collected at the $\Upsilon\left(4S\right)$ resonance at the asymmetric-energy B factories PEP-II at SLAC and KEKB at KEK, respectively. We measure $\sin{2\beta} = 0.80 \pm 0.14 \,(\rm{stat.}) \pm 0.06 \,(\rm{syst.}) \pm 0.03 \,(\rm{model})$ and $\cos{2\beta} = 0.91 \pm 0.22 \,(\rm{stat.}) \pm 0.09 \,(\rm{syst.}) \pm 0.07 \,(\rm{model})$. The result for the direct measurement of the angle is $\beta = \left( 22.5 \pm 4.4 \,(\rm{stat.}) \pm 1.2 \,(\rm{syst.}) \pm 0.6 \,(\rm{model}) \right)^{\circ}$. The last quoted uncertainties are due to the composition of the $D^{0} \to K_{S}^{0} \pi^{+} \pi^{-}$ decay amplitude model, which is newly established by a Dalitz plot amplitude analysis of a high-statistics $e^{+}e^{-} \to c\bar{c}$ data sample as part of this analysis. We find the first evidence for $\cos2\beta>0$ at the level of $3.7$ standard deviations. The measurement excludes the trigonometric multifold solution $\pi/2 - \beta = (68.1 \pm 0.7)^{\circ}$ at the level of $7.3$ standard deviations and therefore resolves an ambiguity in the determination of the apex of the CKM Unitarity Triangle. The hypothesis of $\beta = 0^{\circ}$ is ruled out at the level of $5.1$ standard deviations, and thus CP violation is observed in $B^{0} \to D^{(*)} h^{0}$ decays.Comment: To be submitted to Physical Review

Les droits disciplinaires des fonctions publiques : « unification », « harmonisation » ou « distanciation ». A propos de la loi du 26 avril 2016 relative à la déontologie et aux droits et obligations des fonctionnaires

The production of tt‾ , W+bb‾ and W+cc‾ is studied in the forward region of proton–proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98±0.02 fb−1 . The W bosons are reconstructed in the decays W→ℓν , where ℓ denotes muon or electron, while the b and c quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions.The production of $t\overline{t}$, $W+b\overline{b}$ and $W+c\overline{c}$ is studied in the forward region of proton-proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98 $\pm$ 0.02 \mbox{fb}^{-1}. The $W$ bosons are reconstructed in the decays $W\rightarrow\ell\nu$, where $\ell$ denotes muon or electron, while the $b$ and $c$ quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions