Ultrafiltration based purification strategies for surfactin produced by bacillus subtilis lb5a using cassava wastewater as substrate

BACKGROUND: Bacillus subtilis synthesizes surfactin, a powerful surface-active agent. It has interesting potential applications. However, due to its high cost of production, commercial use is impracticable. The downstream processing represents ≈60% of production costs and the culture medium ≈30%. Many reports focused, separately, on production of surfactin using by-products (reduced cost) or the purification using synthetic medium. Therefore, the aim of this work was to evaluate, for the first time, the impact of using a by-product as fermentation medium on the downstream processing based on membrane filtration. RESULTS: Membranes of PES-100-kDa efficiently retained surfactin micelles - the first step of ultrafiltration, whereas, the second step required membranes of 50-kDa to separate surfactin monomers from proteins. Ultrafiltration of crude biosurfactant was associated with fouling and/or concentration polarization resulting in lower purity than when synthetic medium was used. Further improvement in purity was achieved by partial removal of proteins prior to ultrafiltration by precipitation and extraction. The RMN and MALDI-TOFMS analyses identified 11 potential surfactin homologous composed by two amino acid sequences. CONCLUSION: Production of surfactin using cassava wastewater as a low-cost culture medium and its purification by the 2-step ultrafiltration process is feasible, nevertheless, the higher protein content of this medium as compared to the synthetic one leads to a lower purity product; further increase in purity can be achieved by applying additional purification steps prior to ultrafiltration with the subsequent increased in process cost

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Demographic, clinical, and service-use characteristics related to the clinician’s recommendation to transition from child to adult mental health services

Purpose: The service configuration with distinct child and adolescent mental health services (CAMHS) and adult mental health services (AMHS) may be a barrier to continuity of care. Because of a lack of transition policy, CAMHS clinicians have to decide whether and when a young person should transition to AMHS. This study describes which characteristics are associated with the clinicians’ advice to continue treatment at AMHS. Methods: Demographic, family, clinical, treatment, and service-use characteristics of the MILESTONE cohort of 763 young people from 39 CAMHS in Europe were assessed using multi-informant and standardized assessment tools. Logistic mixed models were fitted to assess the relationship between these characteristics and clinicians’ transition recommendations. Results: Young people with higher clinician-rated severity of psychopathology scores, with self- and parent-reported need for ongoing treatment, with lower everyday functional skills and without self-reported psychotic experiences were more likely to be recommended to continue treatment. Among those who had been recommended to continue treatment, young people who used psychotropic medication, who had been in CAMHS for more than a year, and for whom appropriate AMHS were available were more likely to be recommended to continue treatment at AMHS. Young people whose parents indicated a need for ongoing treatment were more likely to be recommended to stay in CAMHS. Conclusion: Although the decision regarding continuity of treatment was mostly determined by a small set of clinical characteristics, the recommendation to continue treatment at AMHS was mostly affected by service-use related characteristics, such as the availability of appropriate services

Cohort profile : demographic and clinical characteristics of the MILESTONE longitudinal cohort of young people approaching the upper age limit of their child mental health care service in Europe

Purpose: The presence of distinct child and adolescent mental health services (CAMHS) and adult mental health services (AMHS) impacts continuity of mental health treatment for young people. However, we do not know the extent of discontinuity of care in Europe nor the effects of discontinuity on the mental health of young people. Current research is limited, as the majority of existing studies are retrospective, based on small samples or used non-standardised information from medical records. The MILESTONE prospective cohort study aims to examine associations between service use, mental health and other outcomes over 24 months, using information from self, parent and clinician reports. Participants: Seven hundred sixty-three young people from 39 CAMHS in 8 European countries, their parents and CAMHS clinicians who completed interviews and online questionnaires and were followed up for 2 years after reaching the upper age limit of the CAMHS they receive treatment at. Findings to date: This cohort profile describes the baseline characteristics of the MILESTONE cohort. The mental health of young people reaching the upper age limit of their CAMHS varied greatly in type and severity: 32.8% of young people reported clinical levels of self-reported problems and 18.6% were rated to be ‘markedly ill’, ‘severely ill’ or ‘among the most extremely ill’ by their clinician. Fifty-seven per cent of young people reported psychotropic medication use in the previous half year. Future plans: Analysis of longitudinal data from the MILESTONE cohort will be used to assess relationships between the demographic and clinical characteristics of young people reaching the upper age limit of their CAMHS and the type of care the young person uses over the next 2 years, such as whether the young person transitions to AMHS. At 2 years follow-up, the mental health outcomes of young people following different care pathways will be compared. Trial registration number: NCT03013595

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)