Early Life Microbiota Colonization at Six Months of Age: A Transitional Time Point

Background: Early life gut microbiota is involved in several biological processes, particularly metabolism, immunity, and cognitive neurodevelopment. Perturbation in the infant's gut microbiota increases the risk for diseases in early and later life, highlighting the importance of understanding the connections between perinatal factors with early life microbial composition. The present research paper is aimed at exploring the prenatal and postnatal factors influencing the infant gut microbiota composition at six months of age. Methods: Gut microbiota of infants enrolled in the longitudinal, prospective, observational study "A.MA.MI" (Alimentazione MAmma e bambino nei primi MIlle giorni) was analyzed. We collected and analyzed 61 fecal samples at baseline (meconium, T0); at six months of age (T2), we collected and analyzed 53 fecal samples. Samples were grouped based on maternal and gestational weight factors, type of delivery, type of feeding, time of weaning, and presence/absence of older siblings. Alpha and beta diversities were evaluated to describe microbiota composition. Multivariate analyses were performed to understand the impact of the aforementioned factors on the infant's microbiota composition at six months of age. Results: Different clustering hypotheses have been tested to evaluate the impact of known metadata factors on the infant microbiota. Neither maternal body mass index nor gestational weight gain was able to determine significant differences in infant microbiota composition six months of age. Concerning the type of feeding, we observed a low alpha diversity in exclusive breastfed infants; conversely, non-exclusively breastfed infants reported an overgrowth of Ruminococcaceae and Flavonifractor. Furthermore, we did not find any statistically significant difference resulting from an early introduction of solid foods (before 4 months of age). Lastly, our sample showed a higher abundance of clostridial patterns in firstborn babies when compared to infants with older siblings in the family. Conclusion: Our findings showed that, at this stage of life, there is not a single factor able to affect in a distinct way the infants' gut microbiota development. Rather, there seems to be a complex multifactorial interaction between maternal and neonatal factors determining a unique microbial niche in the gastrointestinal tract

Prenatal and postnatal determinants in shaping offspring's microbiome in the first 1000 days: Study protocol and preliminary results at one month of life

Background: Fetal programming during in utero life defines the set point of physiological and metabolic responses that lead into adulthood; events happening in "the first 1,000 days" (from conception to 2-years of age), play a role in the development of non-communicable diseases (NCDs). The infant gut microbiome is a highly dynamic organ, which is sensitive to maternal and environmental factors and is one of the elements driving intergenerational NCDs' transmission. The A.MA.MI (Alimentazione MAmma e bambino nei primi MIlle giorni) project aims at investigating the correlation between several factors, from conception to the first year of life, and infant gut microbiome composition. We described the study design of the A.MA.MI study and presented some preliminary results. Methods: A.MA.MI is a longitudinal, prospective, observational study conducted on a group of mother-infant pairs (n = 60) attending the Neonatal Unit, Fondazione IRCCS Policlinico San Matteo, Pavia (Italy). The study was planned to provide data collected at T0, T1, T2 and T3, respectively before discharge, 1,6 and 12 months after birth. Maternal and infant anthropometric measurements were assessed at each time. Other variables evaluated were: Pre-pregnancy/gestational weight status (T0), maternal dietary habits/physical activity (T1-T3); infant medical history, type of feeding, antibiotics/probiotics/supplements use, environment exposures (e.g cigarette smoking, pets, environmental temperature) (T1-T3). Infant stool samples were planned to be collected at each time and analyzed using metagenomics 16S ribosomal RNA gene sequence-based methods. Results: Birth mode (cesarean section vs. vaginal delivery) and maternal pre pregnancy BMI (BMI < 25 Kg/m2 vs. BMI ≥ 25 Kg/m2), significant differences were found at genera and species levels (T0). Concerning type of feeding (breastfed vs. formula-fed), gut microbiota composition differed significantly at genus and species level (T1). Conclusion: These preliminary and explorative results confirmed that pre-pregnancy, mode of delivery and infant factors likely impact infant microbiota composition at different levels. Trial registration: ClinicalTrials.gov identifier: NCT04122612

Radiation damage in the LHCb vertex locator

The LHCb Vertex Locator (VELO) is a silicon strip detector designed to reconstruct charged particle trajectories and vertices produced at the LHCb interaction region. During the first two years of data collection, the 84 VELO sensors have been exposed to a range of fluences up to a maximum value of approximately 45 × 1012 1 MeV neutron equivalent (1 MeV neq). At the operational sensor temperature of approximately −7 °C, the average rate of sensor current increase is 18 μA per fb−1, in excellent agreement with predictions. The silicon effective bandgap has been determined using current versus temperature scan data after irradiation, with an average value of Eg = 1.16±0.03±0.04 eV obtained. The first observation of n+-on-n sensor type inversion at the LHC has been made, occurring at a fluence of around 15 × 1012 of 1 MeV neq. The only n+-on-p sensors in use at the LHC have also been studied. With an initial fluence of approximately 3 × 1012 1 MeV neq, a decrease in the Effective Depletion Voltage (EDV) of around 25 V is observed. Following this initial decrease, the EDV increases at a comparable rate to the type inverted n+-on-n type sensors, with rates of (1.43±0.16) × 10−12 V/ 1 MeV neq and (1.35±0.25) × 10−12 V/ 1 MeV neq measured for n+-on-p and n+-on-n type sensors, respectively. A reduction in the charge collection efficiency due to an unexpected effect involving the second metal layer readout lines is observed

Machine-learning derived algorithms for prediction of radiographic progression in early axial spondyloarthritis

OBJECTIVES:To compare machine learning (ML) to traditional models to predict radiographic progression in patients with early axial spondyloarthritis (axSpA).METHODS:We carried out a prospective French multicentric DESIR cohort study with 5 years of follow-up that included patients with chronic back pain for RESULTS:10-fold cv-AUC for traditional models were 0.79 and 0.78 for M2 and M3, respectively. The three best models in the ML algorithms were the GAM, the DBARTS and the Super Learner models, with 10-fold cv-AUC of: 0.77, 0.76 and 0.74, respectively.CONCLUSIONS:Two traditional models predicted radiographic progression as good as the eight ML models tested in this population. Pathophysiology and treatment of rheumatic disease

Triangulation of gravitational wave sources with a network of detectors

There is significant benefit to be gained by pursuing multi-messenger astronomy with gravitational wave and electromagnetic observations. In order to undertake electromagnetic follow-ups of gravitational wave signals, it will be necessary to accurately localize them in the sky. Since gravitational wave detectors are not inherently pointing instruments, localization will occur primarily through triangulation with a network of detectors. We investigate the expected timing accuracy for observed signals and the consequences for localization. In addition, we discuss the effect of systematic uncertainties in the waveform and calibration of the instruments on the localization of sources. We provide illustrative results of timing and localization accuracy as well as systematic effects for coalescing binary waveforms.Comment: 20 pages, 5 figure

Accurate calibration of test mass displacement in the LIGO interferometers

We describe three fundamentally different methods we have applied to calibrate the test mass displacement actuators to search for systematic errors in the calibration of the LIGO gravitational-wave detectors. The actuation frequencies tested range from 90 Hz to 1 kHz and the actuation amplitudes range from 1e-6 m to 1e-18 m. For each of the four test mass actuators measured, the weighted mean coefficient over all frequencies for each technique deviates from the average actuation coefficient for all three techniques by less than 4%. This result indicates that systematic errors in the calibration of the responses of the LIGO detectors to differential length variations are within the stated uncertainties.Comment: 10 pages, 6 figures, submitted on 31 October 2009 to Classical and Quantum Gravity for the proceedings of 8th Edoardo Amaldi Conference on Gravitational Wave

Precision luminosity measurements at LHCb

Measuring cross-sections at the LHC requires the luminosity to be determined accurately at each centre-of-mass energy √s. In this paper results are reported from the luminosity calibrations carried out at the LHC interaction point 8 with the LHCb detector for √s = 2.76, 7 and 8 TeV (proton-proton collisions) and for √sNN = 5 TeV (proton-lead collisions). Both the "van der Meer scan" and "beam-gas imaging" luminosity calibration methods were employed. It is observed that the beam density profile cannot always be described by a function that is factorizable in the two transverse coordinates. The introduction of a two-dimensional description of the beams improves significantly the consistency of the results. For proton-proton interactions at √s = 8 TeV a relative precision of the luminosity calibration of 1.47% is obtained using van der Meer scans and 1.43% using beam-gas imaging, resulting in a combined precision of 1.12%. Applying the calibration to the full data set determines the luminosity with a precision of 1.16%. This represents the most precise luminosity measurement achieved so far at a bunched-beam hadron collider

Performance of the LHCb vertex locator

The Vertex Locator (VELO) is a silicon microstrip detector that surrounds the proton-proton interaction region in the LHCb experiment. The performance of the detector during the first years of its physics operation is reviewed. The system is operated in vacuum, uses a bi-phase CO2 cooling system, and the sensors are moved to 7 mm from the LHC beam for physics data taking. The performance and stability of these characteristic features of the detector are described, and details of the material budget are given. The calibration of the timing and the data processing algorithms that are implemented in FPGAs are described. The system performance is fully characterised. The sensors have a signal to noise ratio of approximately 20 and a best hit resolution of 4 μm is achieved at the optimal track angle. The typical detector occupancy for minimum bias events in standard operating conditions in 2011 is around 0.5%, and the detector has less than 1% of faulty strips. The proximity of the detector to the beam means that the inner regions of the n+-on-n sensors have undergone space-charge sign inversion due to radiation damage. The VELO performance parameters that drive the experiment's physics sensitivity are also given. The track finding efficiency of the VELO is typically above 98% and the modules have been aligned to a precision of 1 μm for translations in the plane transverse to the beam. A primary vertex resolution of 13 μm in the transverse plane and 71 μm along the beam axis is achieved for vertices with 25 tracks. An impact parameter resolution of less than 35 μm is achieved for particles with transverse momentum greater than 1 GeV/c

Search for gravitational-wave bursts in LIGO data from the fourth science run

The fourth science run of the LIGO and GEO 600 gravitational-wave detectors, carried out in early 2005, collected data with significantly lower noise than previous science runs. We report on a search for short-duration gravitational-wave bursts with arbitrary waveform in the 64-1600 Hz frequency range appearing in all three LIGO interferometers. Signal consistency tests, data quality cuts, and auxiliary-channel vetoes are applied to reduce the rate of spurious triggers. No gravitational-wave signals are detected in 15.5 days of live observation time; we set a frequentist upper limit of 0.15 per day (at 90% confidence level) on the rate of bursts with large enough amplitudes to be detected reliably. The amplitude sensitivity of the search, characterized using Monte Carlo simulations, is several times better than that of previous searches. We also provide rough estimates of the distances at which representative supernova and binary black hole merger signals could be detected with 50% efficiency by this analysis.Comment: Corrected amplitude sensitivities (7% change on average); 30 pages, submitted to Classical and Quantum Gravit