Are Intervention-Design Characteristics More Predictive than Baseline Participant Characteristics on Participant Attendance to a Paediatric, Community Weight Management Programme?

BACKGROUND: Approximately 50% of participants complete a paediatric weight management programme, yet the predictors of attendance and dropout are inconsistent. This study investigates subject and intervention-design characteristics associated with attendance at a group based, family weight management programme. SETTING AND SUBJECTS: Secondary data analysis of 2948 subjects (Age 10.4±2.8 years, BMI 26.0±5.7kg/m2, Standardised BMI (BMI SDS) 2.48±0.87, White 70.3%) from 244 MoreLife (UK) programmes. Subjects attend weekly for 10-12 weeks, sessions last 2-3 hours. Sessions include lifestyle guidance and physical activity. METHOD: Subject characteristics (demographics, psychological (body satisfaction & self-esteem) and sedentary behaviour) were gathered at first contact and BMI SDS was noted weekly. Intervention-design characteristics were recorded (year, length (weeks), group size, age segregation and day of session). Attendance was calculated as total number of sessions attended (%). Multivariate linear regression examined predictors of attendance and multiple imputation countered missing data. RESULTS: Average attendance was 59.4%±29.3%. Baseline subject characteristics were ‘poor’ predictors of attendance. Intervention year, group size and day of session significantly predicted attendance (Tables 1 & 2). Yet, the most predictive marker of attendance was a change in BMI SDS during the programme (B = -0.38, 95% CI = -0.43 - -0.33). CONCLUSION: A reduction in BMI was seen to predict greater attendance. However, baseline subject characteristics were weakly associated with attendance, refuting past findings. Dominant intervention characteristics (large groups, weekend sessions and recent delivery) predicted lower attendance. Future programmes may be better informed

Preconception Phthalate Exposure and Women’s Reproductive Health: Pregnancy, Pregnancy Loss, and Underlying Mechanisms

Background: Phthalates are endocrine-disrupting chemicals linked to adverse pregnancy outcomes. Despite the sensitivity of female reproductive processes to oxidation–reduction reaction stress and endocrine disruption, evidence for the impact of women’s phthalate exposure on the ability to establish and maintain pregnancy has been inconclusive. Objectives: We aimed to determine the relationship of preconception phthalate metabolite exposure with a) fecundability and pregnancy loss and b) markers of potential biological mechanisms, including reproductive hormones, inflammation, and oxidative stress. Methods: Data were collected from the Effects of Aspirin in Gestation and Reproduction (EAGeR) trial, a preconception study following 1,228 women who were attempting pregnancy, for up to six menstrual cycles and throughout pregnancy if they became pregnant. Twenty phthalate metabolites were measured in a consecutive 3-d pooled urine sample at enrollment. Pregnancy was determined through urinary human chorionic gonadotropin (hCG) at the expected date of menses during each cycle and pregnancy loss as an observed loss following positive hCG. Highly sensitive C-reactive protein (hsCRP) and isoprostanes were measured at enrollment, and reproductive hormones were measured during the follicular phase, ovulation, and luteal phase. Discrete-time Cox proportional hazards models evaluated the relationship of phthalate metabolites with fecundability and weighted Poisson models with robust variance evaluated the risk of pregnancy loss. Results: An interquartile range (IQR) higher mono-(2-ethylhexyl) phthalate [fecundability odds ratio (FOR)=0.88; 95% confidence interval (CI): 0.78, 1.00], mono-butyl phthalate (FOR=0.82; 95% CI: 0.70, 0.96), and mono-benzyl phthalate (FOR=0.85; 95% CI: 0.74, 0.98) was associated with lower fecundability. No consistent associations were observed with pregnancy loss. Preconception phthalates were consistently associated with higher hsCRP and isoprostanes, as well as lower estradiol and higher follicle-stimulating hormone across the menstrual cycle

Comparison of eigenvalues for a fourth-order four-point boundary value problem

We establish the existence of a smallest eigenvalue for the fourth-order four-point boundary value problem $\left (\phi_p(u''(t)) \right )'' = \lambda h(t) u(t), \, u'(0) = 0, \, \beta_0 u(\eta_0) = u(1), \, \phi_p'(u''(0)) = 0, \, \beta_1\phi_p(u''(\eta_1)) = \phi_p(u''(1))$, $p > 2$, $0 < \eta_1,\eta_0 < 1, 0 < \beta_1, \beta_0 < 1$, using the theory of u$_0$-positive operators with respect to a cone in a Banach space. We then obtain a comparison theorem for the smallest positive eigenvalues, $\lambda_1$ and $\lambda_2$, for the differential equations $\left ( \phi_p(u''(t)) \right )'' = \lambda_1 f(t) u(t)$ and $\left ( \phi_p(u''(t)) \right )'' =\lambda_2 g(t) u(t)$ where $0 \leq f(t) \leq g(t), t \in [0,1]$

The measurements of vehicle glow on the Space Shuttle

From the combined data set of glow observations on STS-3, STS-4 and STS-5 some of the properties of the shuttle glow were observed. Comparison of the STS-3 (240 km) and STS-5 (305 km) photographs show that the intensity of the glow is about a factor of 3.5 brighter on the low altitude (STS-3) flight. The orbiter was purposely rotated about the x axis in an experiment on STS-5 to observe the dependence of the intensity on the angle of incidence between the spacecraft surface normal and the velocity vector. For a relatively large angle between the velocity vector and the surface normal there is an appreciable glow, provided the surface is not shadowed by some other spacecraft structure. As the angle becomes less the glow intensifies. The grating experiments (STS-4 photography only, STS-5 image intensifier photography) provided a preliminary low resolution spectra of the spacecraft glow. Accurate wavelength calibrations of the STS-5 instrument permitted measuring of the spectrum and intensity of the Earth's airglow

Evaluating the effects of turf-replacement programs in Los Angeles

Water utilities incentivize turf replacement to promote water conservation, but the effects of such programs have received limited evaluations. In 2014, the Metropolitan Water District of Southern California (MWD) undertook an unprecedented investment to incentive turf replacement throughout Southern California in response to a serious Statewide drought. MWD devoted $350 million to the program, resulting in more than 46,000 rebate payments (25,000 in Los Angeles County) to remove 15.3 million square meters of turf. The program implementation provided a unique opportunity to address research gaps on turf replacement implementation. We analyzed socioeconomic and spatial trends of program participants and assessed landscape changes from turf replacement using a random sample of properties (4% of LA County participants in 2014–16). Specifically, we used a novel and cost-effective approach Google Earth Street View to characterize landscapes in front yards and created a typology of land cover types. Results showed: post-replacement landscapes had a diversity of land cover types – diverse yards with several land cover types, as well as more homogenous yards with a single land cover such as woodchips, bare soil, gravel, and artificial turf. Analysis also indicated some evidence of “neighborhood adoption” effects. We describe the need for longitudinal studies to understand long-term effects of turf replacement and associated water use, and suggest that water utilities should also evaluate results in backyards, which requires site visits. This study provides a novel contribution that can be replicated over space and time to further knowledge of turf replacement program implementations and evaluation

Feasibility study of the solar scientific instruments for Spacelab/Orbiter

The feasibility and economics of mounting and operating a set of solar scientific instruments in the backup Skylab Apollo Telescope Mount (ATM) hardware was evaluated. The instruments used as the study test payload and integrated into the ATM were: the Solar EUV Telescope/Spectrometer; the Solar Active Region Observing Telescope; and the Lyman Alpha White Light Coronagraph. The backup ATM hardware consists of a central cruciform structure, called the "SPAR', a "Sun End Canister' and a "Multiple Docking Adapter End Canister'. Basically, the ATM hardware and software provides a structural interface for the instruments; a closely controlled thermal environment; and a very accurate attitude and pointing control capability. The hardware is an identical set to the hardware that flow on Skylab

Docking And Molecular Dynamic Of Microalgae Compounds As Potential Inhibitors Of Beta-Lactamase

Bacterial resistance is responsible for a wide variety of health problems, both in children and adults. The persistence of symptoms and infections are mainly treated with beta-lactam antibiotics. The increasing resistance to those antibiotics by bacterial pathogens generated the emergence of extended-spectrum beta-lactamases (ESBLs), an actual public health problem. This is due to rapid mutations of bacteria when exposed to antibiotics. In this case, beta-lactamases are enzymes used by bacteria to hydrolyze the beta-lactam rings present in the antibiotics. Therefore, it was necessary to explore novel molecules as potential beta-lactamases inhibitors to find antibacterial compounds against infection caused by ESBLs. A computational methodology based on molecular docking and molecular dynamic simulations was used to find new microalgae metabolites inhibitors of beta-lactamase. Six 3D beta-lactamase proteins were selected, and the molecular docking revealed that the metabolites belonging to the same structural families, such as phenylacridine (4-Ph), quercetin (Qn), and cryptophycin (Cryp), exhibit a better binding score and binding energy than commercial clinical medicine beta-lactamase inhibitors, such as clavulanic acid, sulbactam, and tazobactam. These results indicate that 4-Ph, Qn, and Cryp molecules, homologous from microalgae metabolites, could be used, likely as novel beta-lactamase inhibitors or as structural templates for new in-silico pharmaceutical designs, with the possibility of combatting beta-lactam resistanc

Building a Systems Map:Applying Systems Thinking to Unhealthy Commodity Industry Influence on Public Health Policy

Background Unhealthy commodity industries (UCIs) engage in political practices to influence public health policy, which poses barriers to protecting and promoting public health. Such influence exhibits characteristics of a complex system. Systems thinking would therefore appear to be a useful lens through which to study this phenomenon, potentially deepening our understanding of how UCI influence are interconnected with one another through their underlying political, economic and social structures. As such this study developed a qualitative systems map to depict the complex pathways through which UCIs influence public health policy and how they are interconnected with underlying structures. Methods Online participatory systems mapping workshops were conducted between November 2021 and February 2022. As a starting point for the workshops, a preliminary systems map was developed based on recent research. Twenty-three online workshops were conducted with 52 geographically diverse stakeholders representing academia, civil society (CS), public office, and global governance organisations (CGO). Analysis of workshop data in NVivo and feedback from participants resulted in a final systems map. Results The preliminary systems map consisted of 40 elements across six interdependent themes. The final systems map consisted of 64 elements across five interdependent themes, representing key pathways through which UCIs impact health policy-making: (1) direct access to public sector decision-makers; (2) creation of confusion and doubt about policy decisions; (3) corporate prioritisation of commercial profits and growth; (4) industry leveraging the legal and dispute settlement processes; and (5) industry leveraging policy-making, norms, rules, and processes. Conclusion UCI influence on public health policy is highly complex, involves interlinked practices, and is not reducible to a single point within the system. Instead, pathways to UCI influence emerge from the complex interactions between disparate national and global political, economic and social structures. These pathways provide numerous avenues for UCIs to influence public health policy, which poses challenges to formulating a singular intervention or limited set of interventions capable of effectively countering such influence. Using participatory methods, we made transparent the interconnections that could help identify interventions in future work