Chemical structures of oligosaccharides in milks of the American black bear (Ursus americanus americanus) and cheetah (Acinonyx jubatus)

The milk oligosaccharides were studied for two species of the Carnivora: the American black bear (Ursus americanus, family Ursidae, Caniformia), and the cheetah, (Acinonyx jubatus, family Felidae, Feliformia). Lactose was the most dominant saccharide in cheetah milk, while this was a minor saccharide and milk oligosaccharides predominated over lactose in American black bear milk. The structures of 8 neutral saccharides from American black bear milk were found to be Gal(β1-4)Glc (lactose), Fuc(α1-2)Gal(β1-4)Glc (2’-fucosyllactose), Gal(α1-3)Gal(β1-4)Glc (isoglobotriose), Gal(α1-3)[Fuc(α1-2)]Gal(β1-4)Glc (B-tetrasaccharide), Gal(α1-3)[Fuc(α1-2)]Gal(β1-4)[Fuc(α1-3)]Glc (B-pentasaccharide), Fuc(α1-2)Gal(β1-4)[Fuc(α1-3)]GlcNAc(β1-3)Gal(β1-4)Glc (difucosyl lacto-N-neotetraose), Gal(α1-3)Gal(β1-4)[Fuc(α1-3)]GlcNAc(β1-3)Gal(β1-4)Glc (monogalactosyl monofucosyl lacto-N-neotetraose) and Gal(α1-3)Gal(β1-4)GlcNAc(β1-3)Gal(β1-4)Glc. Structures of 5 acidic saccharides were also identified in black bear milk: Neu5Ac(α2-3)Gal(β1-4)Glc (3’-sialyllactose), Neu5Ac(α2-6)Gal(β1-4)GlcNAc(β1-3)[Fuc(α1-2)Gal(β1-4)GlcNAc(β1-6)]Gal(β1-4)Glc (monosialyl monofucosyl lacto-N-neohexaose), Neu5Ac(α2-6)Gal(β1-4)GlcNAc(β1-3)[Gal(α1-3)Gal(β1-4)GlcNAc(β1-6)]Gal(β1-4)Glc (monosialyl monogalactosyl lacto-N-neohexaose), Neu5Ac(α2-6)Gal(β1-4)GlcNAc(β1-3){Gal(α1-3)Gal(β1-4)[Fuc(α1-3)]GlcNAc(β1-6)}Gal(β1-4)Glc (monosialyl monogalactosyl monofucosyl lacto-N-neohexaose), and Neu5Ac(α2-6)Gal(β1-4)GlcNAc(β1-3){Gal(α1-3)[Fuc(α1-2)]Gal(β1-4)[Fuc(α1-3)]GlcNAc(β1-6)}Gal(β1-4)Glc (monosialyl monogalactosyl difucosyl lacto-N-neohexaose). A notable feature of some of these milk oligosaccharides is the presence of B-antigen (Gal(α1-3)[Fuc(α1-2)]Gal), α-Gal epitope (Gal(α1-3)Gal(β1-4)Glc(NAc)) and Lewis x (Gal(β1-4)[Fuc(α1-3)]GlcNAc) structures within oligosaccharides. By comparison to American black bear milk, cheetah milk had a much smaller array of oligosaccharides. Two cheetah milks contained Gal(α1-3)Gal(β1-4)Glc (isoglobotriose), while another cheetah milk did not, but contained Gal(β1-6)Gal(β1-4)Glc (6’-galactosyllactose) and Gal(β1-3)Gal(β1-4)Glc (3’-galactosyllactose). Two cheetah milks contained Gal(β1-4)GlcNAc(β1-3)[Gal(β1-4)GlcNAc(β1-6)]Gal(β1-4)Glc (lacto-N-neohexaose), and one cheetah milk contained Gal(β1-4)Glc-3’-O-sulfate. Neu5Ac(α2-8)Neu5Ac(α2-3)Gal(β1-4)Glc (disialyllactose) was the only sialyl oligosaccharide identified in cheetah milk. The heterogeneity of milk oligosaccharides was found between both species with respect of the presence/absence of B-antigen and Lewis x. The variety of milk oligosaccharides was much greater in the American black bear than in the cheetah. The ratio of milk oligosaccharides-to-lactose was lower in cheetah (1:1-1:2) than American black bear (21:1) which is likely a reflection of the requirement for a dietary supply of N-acetyl neuraminic acid (sialic acid), in altricial ursids compared to more precocial felids, given the role of these oligosaccharides in the synthesis of brain gangliosides and the polysialic chains on neural cell adhesion

Effect of lactation stage and concurrent pregnancy on milk composition in the bottlenose dolphin

Although many toothed whales (Cetacea: Odontoceti) lactate for 2–3 years or more, it is not known whether milk composition is affected by lactation stage in any odontocete species. We collected 64 pooled milk samples spanning 1–30 months postpartum from three captive bottlenose dolphins Tursiops truncatus. Milks were assayed for water, fat, crude protein (TN × 6.38) and sugar; gross energy was calculated. Ovulation and pregnancy were determined via monitoring of milk progesterone. Based on analysis of changes in milk composition for each individual dolphin, there were significant increases (P<0.05) in fat (in all three dolphins) and crude protein (in two of three), and a decrease (P<0.05) in water (in two of three) over the course of lactation, but the sugar content did not change. In all three animals, the energy content was positively correlated with month of lactation, but the percentage of energy provided by crude protein declined slightly but significantly (P<0.05). At mid-lactation (7–12 months postpartum, n=17), milk averaged 73.0±1.0% water, 12.8±1.0% fat, 8.9±0.5% crude protein, 1.0±0.1% sugar, 1.76±0.09 kcal g−1 (=7.25 kJ g−1) and 30.3±1.3% protein:energy per cent. This protein:energy per cent was surprisingly high compared with other cetaceans and in relation to the growth rates of calves. Milk progesterone indicated that dolphins ovulated and conceived between 413 and 673 days postpartum, following an increase in milk energy density. The significance of these observed compositional changes to calf nutrition will depend on the amounts of milk produced at different stages of lactation, and how milk composition and yield are influenced by sampling procedure, maternal diet and maternal condition, none of which are known

Long-term exposure to low ambient air pollution concentrations and mortality among 28 million people: results from seven large European cohorts within the ELAPSE project

Background Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE). Methods In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000-11; follow-up until 2011-17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM2·5), nitrogen dioxide (NO2), black carbon, and tropospheric warm-season ozone (O3) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis. Findings We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM2·5, NO2, and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021-1·085) per 5 μg/m3 increment in PM2·5, 1·044 (1·019-1·069) per 10 μg/m3 NO2, and 1·039 (1·018-1·059) per 0·5 × 10−5/m black carbon. Associations with PM2·5, NO2, and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O3 was negatively associated with both non-accidental and cause-specific mortality. Associations were stronger at low concentrations: HRs for non-accidental mortality at concentrations lower than the WHO 2005 air quality guideline values for PM2·5 (10 μg/m3) and NO2 (40 μg/m3) were 1·078 (1·046-1·111) per 5 μg/m3 PM2·5 and 1·049 (1·024-1·075) per 10 μg/m3 NO2. Similarly, the association between black carbon and non-accidental mortality was highest at low concentrations, with a HR of 1·061 (1·032-1·092) for exposure lower than 1·5× 10−5/m, and 1·081 (0·966-1·210) for exposure lower than 1·0× 10−5/m. Interpretation Long-term exposure to concentrations of PM2·5 and NO2 lower than current annual limit values was associated with non-accidental, cardiovascular, non-malignant respiratory, and lung cancer mortality in seven large European cohorts. Continuing research on the effects of low concentrations of air pollutants is expected to further inform the process of setting air quality standards in Europe and other global regions

Gaps in knowledge relevant to the “guidelines for limiting exposure to time-varying electric and magnetic fields (1 Hz-100 kHz)"

Sources of low-frequency fields are widely found in modern society. All wires or devices carrying or using electricity generate extremely low frequency (ELF) electric fields (EFs) and magnetic fields (MFs), but they decline rapidly with distance to the source. High magnetic flux densities are usually found in the vicinity of power lines and close to equipment using strong electrical currents, but can also be found in buildings with unbalanced return currents, or indoor transformer stations. For decades, epidemiological as well as experimental studies have addressed possible health effects of exposure to ELF-MFs. The main goal of ICNIRP is to protect people and the environment from detrimental exposure to all forms of non-ionizing radiation (NIR). To this end, ICNIRP provides advice and guidance by developing and disseminating exposure guidelines based on the available scientific research. Research in the low-frequency range began more than 40 years ago, and there is now a large body of literature available on which ICNIRP set its protection guidelines. A review of the literature has been carried out to identify possible relevant knowledge gaps, and the aim of this statement is to describe data gaps in research that would, if addressed, assist ICNIRP in further developing guidelines and setting revised recommendations on limiting exposure to electric and magnetic fields. It is articulated in two parts: the main document, which reviews the science related to LF data gaps, and the annex, which explains the methodology used to identify the data gaps

Traffic-related pollution and asthma prevalence in children. Quantification of associations with nitrogen dioxide.

Ambient nitrogen dioxide is a widely available measure of traffic-related air pollution and is inconsistently associated with the prevalence of asthma symptoms in children. The use of this relationship to evaluate the health impact of policies affecting traffic management and traffic emissions is limited by the lack of a concentration-response function based on systematic review and meta-analysis of relevant studies. Using systematic methods, we identified papers containing quantitative estimates for nitrogen dioxide and the 12 month period prevalence of asthma symptoms in children in which the exposure contrast was within-community and dominated by traffic pollution. One estimate was selected from each study according to an a priori algorithm. Odds ratios were standardised to 10 μg/m(3) and summary estimates were obtained using random- and fixed-effects estimates. Eighteen studies were identified. Concentrations of nitrogen dioxide were estimated for the home address (12) and/or school (8) using a range of methods; land use regression (6), study monitors (6), dispersion modelling (4) and interpolation (2). Fourteen studies showed positive associations but only two associations were statistically significant at the 5 % level. There was moderate heterogeneity (I(2) = 32.8 %) and the random-effects estimate for the odds ratio was 1.06 (95 % CI 1.00 to 1.11). There was no evidence of small study bias. Individual studies tended to have only weak positive associations between nitrogen dioxide and asthma prevalence but the summary estimate bordered on statistical significance at the 5 % level. Although small, the potential impact on asthma prevalence could be considerable because of the high level of baseline prevalence in many cities. Whether the association is causal or indicates the effects of a correlated pollutant or other confounders, the estimate obtained by the meta-analysis would be appropriate for estimating impacts of traffic pollution on asthma prevalence

Assessment of potential effects of the electromagnetic fields of mobile phones on hearing

BACKGROUND: Mobile phones have become indispensable as communication tools; however, to date there is only a limited knowledge about interaction between electromagnetic fields (EMF) emitted by mobile phones and auditory function. The aim of the study was to assess potential changes in hearing function as a consequence of exposure to low-intensity EMF's produced by mobile phones at frequencies of 900 and 1800 MHz. METHODS: The within-subject study was performed on thirty volunteers (age 18–30 years) with normal hearing to assess possible acute effect of EMF. Participants attended two sessions: genuine and sham exposure of EMF. Hearing threshold levels (HTL) on pure tone audiometry (PTA) and transient evoked otoacoustic emissions (TEOAE's) were recorded before and immediately after 10 min of genuine and/or sham exposure of mobile phone EMF. The administration of genuine or sham exposure was double blind and counterbalanced in order. RESULTS: Statistical analysis revealed no significant differences in the mean HTLs of PTA and mean shifts of TEOAE's before and after genuine and/or sham mobile phone EMF 10 min exposure. The data collected showed that average TEOAE levels (averaged across a frequency range) changed less than 2.5 dB between pre- and post-, genuine and sham exposure. The greatest individual change was 10 dB, with a decrease in level from pre- to post- real exposure. CONCLUSION: It could be concluded that a 10-min close exposure of EMFs emitted from a mobile phone had no immediate after-effect on measurements of HTL of PTA and TEOAEs in young human subjects and no measurable hearing deterioration was detected in our study

Особливості державного регулювання інвестиційно-інноваційної діяльності, в сфері екології

BACKGROUND: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. METHODS: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. RESULTS: The 245,782 cohort members contributed 3,229,220 person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5 ng/m(3)), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m(3)), PM10 S (1.58; 1.03-2.44 per 200 ng/m(3)), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m(3)) and PM10 K (1.17; 1.02-1.33 per 100 ng/m(3)). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. CONCLUSIONS: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important

Development of Europe-Wide Models for Particle Elemental Composition Using Supervised Linear Regression and Random Forest.

We developed Europe-wide models of long-term exposure to eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) in particulate matter with diameter <2.5 μm (PM2.5) using standardized measurements for one-year periods between October 2008 and April 2011 in 19 study areas across Europe, with supervised linear regression (SLR) and random forest (RF) algorithms. Potential predictor variables were obtained from satellites, chemical transport models, land-use, traffic, and industrial point source databases to represent different sources. Overall model performance across Europe was moderate to good for all elements with hold-out-validation R-squared ranging from 0.41 to 0.90. RF consistently outperformed SLR. Models explained within-area variation much less than the overall variation, with similar performance for RF and SLR. Maps proved a useful additional model evaluation tool. Models differed substantially between elements regarding major predictor variables, broadly reflecting known sources. Agreement between the two algorithm predictions was generally high at the overall European level and varied substantially at the national level. Applying the two models in epidemiological studies could lead to different associations with health. If both between- and within-area exposure variability are exploited, RF may be preferred. If only within-area variability is used, both methods should be interpreted equally

Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project.

BACKGROUND: We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM2.5 and NO2) and health (natural-cause mortality and cerebrovascular, coronary and lung cancer incidence). METHODS: We applied five approaches in a multivariable Cox model to account for the first level of clustering corresponding to cohort specification: (1) not accounting for the cohort or using (2) indicator variables, (3) strata, (4) a frailty term in frailty Cox models, (5) a random intercept under a mixed Cox, for cohort identification. We accounted for the second level of clustering due to common characteristics in the residential area by (1) a random intercept per small area or (2) applying variance correction. We assessed the stratified, frailty and mixed Cox approach through simulations under different scenarios for heterogeneity in the underlying hazards and the air pollution effects. RESULTS: Effect estimates were stable under approaches used to adjust for cohort but substantially differed when no adjustment was applied. Further adjustment for the small area grouping increased the effect estimates' standard errors. Simulations confirmed identical results between the stratified and frailty models. In ELAPSE we selected a stratified multivariable Cox model to account for between-cohort heterogeneity without adjustment for small area level, due to the small number of subjects and events in the latter. CONCLUSIONS: Our study supports the need to account for between-cohort heterogeneity in multi-center collaborations using pooled individual level data

Long term exposure to low level air pollution and mortality in eight European cohorts within the ELAPSE project: pooled analysis.

OBJECTIVE: To investigate the associations between air pollution and mortality, focusing on associations below current European Union, United States, and World Health Organization standards and guidelines. DESIGN: Pooled analysis of eight cohorts. SETTING: Multicentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) in six European countries. PARTICIPANTS: 325 367 adults from the general population recruited mostly in the 1990s or 2000s with detailed lifestyle data. Stratified Cox proportional hazard models were used to analyse the associations between air pollution and mortality. Western Europe-wide land use regression models were used to characterise residential air pollution concentrations of ambient fine particulate matter (PM2.5), nitrogen dioxide, ozone, and black carbon. MAIN OUTCOME MEASURES: Deaths due to natural causes and cause specific mortality. RESULTS: Of 325 367 adults followed-up for an average of 19.5 years, 47 131 deaths were observed. Higher exposure to PM2.5, nitrogen dioxide, and black carbon was associated with significantly increased risk of almost all outcomes. An increase of 5 µg/m3 in PM2.5 was associated with 13% (95% confidence interval 10.6% to 15.5%) increase in natural deaths; the corresponding figure for a 10 µg/m3 increase in nitrogen dioxide was 8.6% (7% to 10.2%). Associations with PM2.5, nitrogen dioxide, and black carbon remained significant at low concentrations. For participants with exposures below the US standard of 12 µg/m3 an increase of 5 µg/m3 in PM2.5 was associated with 29.6% (14% to 47.4%) increase in natural deaths. CONCLUSIONS: Our study contributes to the evidence that outdoor air pollution is associated with mortality even at low pollution levels below the current European and North American standards and WHO guideline values. These findings are therefore an important contribution to the debate about revision of air quality limits, guidelines, and standards, and future assessments by the Global Burden of Disease