Performance improvement of whey-driven microbial fuel cells by acclimation of indigenous anodophilic microbes

Various methods are available for the recycling and treatment of cheese whey with the objective of enhancing sustainable manufacturing. Currently, an increasing interest is on the anaerobic bioremediation of whey with the added benefit of generating electricity in microbial fuel cells (MFCs). Since microorganisms are the biocatalysts in MFCs, their initial density plays a paramount role both towards electricity generation and bioremediation. Hence, this study was aimed at evaluating the effects of anode enrichment with microorganisms on power generation. Anodes were enriched with microorganisms inherent to whey for periods of 30 and 90 days before their application in wheypowered MFCs. At the termination of reactor cycles, the one-month-old pre-incubated anodes had 0.13% coulombic efficiency (εcb), 88.3% total chemical oxygen demand (tCOD) removal efficiency and maximum power density (Pd) was 29.1 ± 4.9 W/m2, whereas the three-month-old pre-incubated anode had εcb = 80.9 and 92.8%, tCOD removal and maximum Pd was 1800 ± 120 W/m2. Two non-acclimated anodes used as control in separate setups exhibited 0.17% coulombic efficiency, 71.6% tCOD removal and maximum Pd of 30.9 ± 4.2 W//m2. Microscopy analyses revealed different morphologies on anode surfaces depending on the length of the enrichment periods and further molecular analyses of electrode communities indicated up to 92% identity to various species from the Lactobacillus genus. This study established that, an initial acclimation step ahead of MFC setups significantly improved the performance of reactors utilising live cheese whey as fuel.Key words: Cheese whey, microbial fuel cell, enrichment, alternative energy, bioelectricity, bioremediation

Testing the carbohydrate insulin model in mice : Erroneous critique does not alter previous conclusion

We are grateful to Dr Kevin Hall of the NIH for comments on an earlier draft of this paper, and Dr Stephan Guyenet for his informative blog posts on the CIM. Our study of mouse diets was funded by the strategic research program of the Chinese Academy of Sciences (XDB13030100).Peer reviewedPublisher PD

A novel biosensor for the detection and monitoring of -d-galactosidase of faecal origin in water

A voltammetric sensor prepared by the immobilization of metallophthalocyanine complexes onto a glassy carbon electrode has been developed for the detection of β-d-galactosidase (B-GAL) of faecal origin in water. Electrooxidation of chlorophenol red, a breakdown product of the chromogenic substrate chlorophenol red β-d-galactopyranoside, was used as a measure of β-d-galactosidase activity. At metallophthalocyanine modified electrodes, in particular copper(II) phthalocyanine, a decrease in electrode fouling was observed. The sensor was sensitive to fluctuations in pH, not significantly affected by temperature variations and could detect one colony forming unit/100 mL in 15 min. Loss of 40% sensitivity was observed over a period of 30 days. A strong correlation between sensor sensitivity and colony forming units was observed. The sensor is capable of detecting viable but nonculturable bacteria, overcoming this drawback of the use of culture media for detection of coliforms

Search for massive rare particles with the SLIM experiment

The search for magnetic monopoles in the cosmic radiation remains one of the main aims of non-accelerator particle astrophysics. Experiments at high altitude allow lower mass thresholds with respect to detectors at sea level or underground. The SLIM experiment is a large array of nuclear track detectors at the Chacaltaya High Altitude Laboratory (5290 m a.s.l.). The results from the analysis of 171 m$^2$ exposed for more than 3.5 y are here reported. The completion of the analysis of the whole detector will allow to set the lowest flux upper limit for Magnetic Monopoles in the mass range 10$^5$ - 10$^{12}$ GeV. The experiment is also sensitive to SQM nuggets and Q-balls, which are possible Dark Matter candidates.Comment: Presented at the 29-th ICRC, Pune, India (2005

Search for Intermediate Mass Magnetic Monopoles and Nuclearites with the SLIM experiment

SLIM is a large area experiment (440 m2) installed at the Chacaltaya cosmic ray laboratory since 2001, and about 100 m2 at Koksil, Himalaya, since 2003. It is devoted to the search for intermediate mass magnetic monopoles (107-1013 GeV/c2) and nuclearites in the cosmic radiation using stacks of CR39 and Makrofol nuclear track detectors. In four years of operation it will reach a sensitivity to a flux of about 10-15 cm-2 s-1 sr-1. We present the results of the calibration of CR39 and Makrofol and the analysis of a first sample of the exposed detector.Comment: Presented at the 22nd ICNTS, Barcelona 200

Time variations in the deep underground muon flux measured by MACRO

More than 30 million of high-energy muons collected with the MACRO detector at the underground Gran Sasso Laboratory have been used to search for flux variations of different natures. Two kinds of studies were carried out: search for periodic variations and for the occurrence of clusters of events. Different analysis methods, including Lomb-Scargle spectral analysis and Scan Test statistics have been applied to the data.Comment: 6 pages, 4 EPS figures. Talk given at the 29th ICRC, Pune, India, 3-10 August 200

Search for strange quark matter and Q-balls with the SLIM experiment

We report on the search for Strange Quark Matter (SQM) and charged Q-balls with the SLIM experiment at the Chacaltaya High Altitude Laboratory (5230 m a.s.l.) from 2001 to 2005. The SLIM experiment was a 427 m$^{2}$ array of Nuclear Track Detectors (NTDs) arranged in modules of $24 \times 24$ cm$^{2}$ area. SLIM NTDs were exposed to the cosmic radiation for 4.22 years after which they were brought back to the Bologna Laboratory where they were etched and analyzed. We estimate the properties and energy losses in matter of nuclearites (large SQM nuggets), strangelets (small charged SQM nuggets) and Q-balls; and discuss their detection with the SLIM experiment. The flux upper limits in the CR of such downgoing particles are at the level of $1.3 10^{-15}$/cm$^{2}$/s/sr (90% CL).Comment: 4 pages, 7 eps figures. Talk given at the 24th International Conference on Nuclear Tracks in Solids, Bologna, Italy, 1-5 September 200

Functional connectivity-based classification of rapid eye movement sleep behavior disorder

BACKGROUND: Isolated rapid eye movement sleep behavior disorder (iRBD) is a clinically important parasomnia syndrome preceding α-synucleinopathies, thereby prompting us to develop methods for evaluating latent brain states in iRBD. Resting-state functional magnetic resonance imaging combined with a machine learning-based classification technology may help us achieve this purpose. METHODS: We developed a machine learning-based classifier using functional connectivity to classify 55 patients with iRBD and 97 healthy elderly controls (HC). Selecting 55 HCs randomly from the HC dataset 100 times, we conducted a classification of iRBD and HC for each sampling, using functional connectivity. Random forest ranked the importance of functional connectivity, which was subsequently used for classification with logistic regression and a support vector machine. We also conducted correlation analysis of the selected functional connectivity with subclinical variations in motor and non-motor functions in the iRBDs. RESULTS: Mean classification performance using logistic regression was 0.649 for accuracy, 0.659 for precision, 0.662 for recall, 0.645 for f1 score, and 0.707 for the area under the receiver operating characteristic curve (p < 0.001 for all). The result was similar in the support vector machine. The classifier used functional connectivity information from nine connectivities across the motor and somatosensory areas, parietal cortex, temporal cortex, thalamus, and cerebellum. Inter-individual variations in functional connectivity were correlated with the subclinical motor and non-motor symptoms of iRBD patients. CONCLUSIONS: Machine learning-based classifiers using functional connectivity may be useful to evaluate latent brain states in iRBD

Time variations in the deep underground muon flux

More than 35 million high-energy muons collected with the MACRO detector at the underground Gran Sasso Laboratory have been used to search for flux variations of different nature. Two kinds of studies were carried out: a search for the occurrence of clusters of events and a search for periodic variations. Different analysis methods, including the Scan Statistics test and the Lomb-Scargle spectral analysis have been applied to the data.Comment: 7 pages, 5 figures, accepted by EP