Bose-Einstein Condensation in a Surface Micro Trap

Bose-Einstein condensation has been achieved in a magnetic surface micro trap with 4x10^5 87Rb atoms. The strongly anisotropic trapping potential is generated by a microstructure which consists of microfabricated linear copper conductors at a width ranging from 3 to 30 micrometer. After loading a high number of atoms from a pulsed thermal source directly into a magneto-optical trap (MOT) the magnetically stored atoms are transferred into the micro trap by adiabatic transformation of the trapping potential. The complete in vacuo trap design is compatible with ultrahigh vacuum below 2x10^(-11) mbar.Comment: 4 pages, 4 figure

Identifying a Milk-Replacer and Weaning Strategy for Holstein Calves Using Automated Behavioral Measures of Lying and Environmental Enrichment Device Use

In dairy production, “weaning readiness” is often based on solid feed intake. The goal of this study was to determine weaning readiness using feed-intake, lying-behaviors, and the use of an environmental enrichment device (EED) in calves that underwent 1 of 4 milk-replacer and weaning protocols. Twenty-eight male Holstein calves (95 ± 2.6 lb BW at 1 d of age) were housed in individual pens and initially fed one type of milk replacer (25% crude protein (CP), 17% fat, 1.45 lb of dry matter (DM)) via nipplebuckets twice a day (AM and PM), and one type of textured calf starter (ad libitum; 20% CP and 37% starch). At age 3 days, calves were randomly assigned to one of the four nutrition-weaning strategies:1. MOD-STEP - 1.46 lb per day of milk replacer; 2-step weaned, initiated at age 6 weeks, completed 3 days later; 2. HI-STEP - 2.4 lb per day of milk replacer; 2-step weaned, initiated at age 5 weeks and completed 1 week later; 3. HI-LATE - 2.4 lb per day of milk replacer; 2-step weaned, initiated at age 7 weeks and completed 1 week later; and 4. HI-GRAD - 2.4 lb per day of milk replacer; 5-step weaned, initiated at age 6 week and completed 2 weeks later. Each calf’s pen had an EED, which included a dummy-nipple attached to a bottle and holder. A sensor and automated logger tracked each event (1 Hz) that the calf manipulated the EED (25 Hz sensitivity). Each calf was fitted with an accelerometer on the back leg to automatically measure lying behaviors. The device collected the y-axis (lie vs. stand) and z-axis (right or left percent during lying) of the calf every minute. For this experiment, 3-day sample periods were analyzed before and after weaning was initiated. In addition, the 3 days following weaning-completion were sampled. Feed intake among MOD-STEP calves increased by 1.0 ± 0.19 lb after the first bottle was removed (P ≤ 0.05), and then by 1.5 ± 0.19 SE lb after completion of weaning (P ≤ 0.05). The use of EED did not change among MOD-STEP calves (P \u3e 0.05), but after weaning, they increased their lying time, especially on their left side (P ≤ 0.05). These changes in lying-behaviors may indicate increased comfort and maturity of the rumen. On the contrary, calves in the HI-STEP treatment ate the least amount of feed overall (P \u3c 0.05), and they used the EED the most (P \u3e 0.05). Calves in the HI-STEP treatment showed reduced lying bouts after weaning (P ≤ 0.05), but no other lying-measures changed (P \u3e 0.05). The HI-LATE calves had similar feed intake and EED use compared to MOD-STEP calves. These findings suggest that weaning age needs to be more than 8 weeks for calves fed 2.4 lb of milk replacer per day. Gradual weaning may also improve feed intake and reduce EED use. When calves were gradually weaned starting at age 6 weeks and completed at age 8 weeks, they had the same amount of solid feed intake as HI-LATE calves. More research is needed to determine if increased feed intake and reduced EED use are also indicators that cross-sucking is less likely to occur when calves are grouped after weaning

An iterative block-shifting approach to retention time alignment that preserves the shape and area of gas chromatography-mass spectrometry peaks

<p>Abstract</p> <p>Background</p> <p>Metabolomics, petroleum and biodiesel chemistry, biomarker discovery, and other fields which rely on high-resolution profiling of complex chemical mixtures generate datasets which contain millions of detector intensity readings, each uniquely addressed along dimensions of <it>time </it>(<it>e.g.</it>, <it>retention time </it>of chemicals on a chromatographic column), a <it>spectral value </it>(<it>e.g., mass-to-charge ratio </it>of ions derived from chemicals), and the <it>analytical run number</it>. They also must rely on data preprocessing techniques. In particular, inter-run variance in the retention time of chemical species poses a significant hurdle that must be cleared before feature extraction, data reduction, and knowledge discovery can ensue. <it>Alignment methods</it>, for calibrating retention reportedly (and in our experience) can misalign matching chemicals, falsely align distinct ones, be unduly sensitive to chosen values of input parameters, and result in distortions of peak shape and area.</p> <p>Results</p> <p>We present an iterative block-shifting approach for retention-time calibration that detects chromatographic features and qualifies them by retention time, spectrum, and the effect of their inclusion on the quality of alignment itself. Mass chromatograms are aligned pairwise to one selected as a reference. In tests using a 45-run GC-MS experiment, block-shifting reduced the absolute deviation of retention by greater than 30-fold. It compared favourably to COW and XCMS with respect to alignment, and was markedly superior in preservation of peak area.</p> <p>Conclusion</p> <p>Iterative block-shifting is an attractive method to align GC-MS mass chromatograms that is also generalizable to other two-dimensional techniques such as HPLC-MS.</p

Metabolite Profiling of Alzheimer's Disease Cerebrospinal Fluid

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive loss of cognitive functions. Today the diagnosis of AD relies on clinical evaluations and is only late in the disease. Biomarkers for early detection of the underlying neuropathological changes are still lacking and the biochemical pathways leading to the disease are still not completely understood. The aim of this study was to identify the metabolic changes resulting from the disease phenotype by a thorough and systematic metabolite profiling approach. For this purpose CSF samples from 79 AD patients and 51 healthy controls were analyzed by gas and liquid chromatography-tandem mass spectrometry (GC-MS and LC-MS/MS) in conjunction with univariate and multivariate statistical analyses. In total 343 different analytes have been identified. Significant changes in the metabolite profile of AD patients compared to healthy controls have been identified. Increased cortisol levels seemed to be related to the progression of AD and have been detected in more severe forms of AD. Increased cysteine associated with decreased uridine was the best paired combination to identify light AD (MMSE>22) with specificity and sensitivity above 75%. In this group of patients, sensitivity and specificity above 80% were obtained for several combinations of three to five metabolites, including cortisol and various amino acids, in addition to cysteine and uridine

Dendritic Core-Shell Macromolecules Soluble in Supercritical Carbon Dioxide

International audienceSupercritical carbon dioxide has found strong interest as a reaction medium recently.1,2 As an alternative to organic solvents, compressed carbon dioxide is toxicologically harmless, nonflammable, inexpensive, and environmentally benign.3 Its accessible critical temperature and pressure (Tc ) 31 °C, Pc ) 7.38 MPa, Fc ) 0.468 g cm-3)4 and the possibility of tuning the solvent-specific properties between the ones of liquid and gas are very attractive

Determinants of SARS-CoV-2 transmission to guide vaccination strategy in an urban area.

Transmission chains within small urban areas (accommodating ∼30 per cent of the European population) greatly contribute to case burden and economic impact during the ongoing coronavirus pandemic and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in a European urban area, Basel-City (Switzerland). We combined detailed epidemiological, intra-city mobility and socio-economic data sets with whole-genome sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44 per cent of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60 per cent of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare system burden (intensive care unit (ICU) occupancy). Transmissions were driven by socio-economically weaker and highly mobile population groups with mostly cryptic transmissions which lacked genetic and identifiable epidemiological links. Amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90 per cent transmission reduction and 70-90 per cent reduction of severe cases showed that prioritising mobile, socio-economically weaker populations for vaccination would effectively reduce case numbers. However, long-term ICU occupation would also be effectively reduced if senior population groups were prioritised, provided there were no changes in testing and prevention strategies. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules