Antagonistic peptide technology for functional dissection of CLE peptides revisited.

In the Arabidopsis thaliana genome, over 1000 putative genes encoding small, presumably secreted, signalling peptides can be recognized. However, a major obstacle in identifying the function of genes encoding small signalling peptides is the limited number of available loss-of-function mutants. To overcome this, a promising new tool, antagonistic peptide technology, was recently developed. Here, this antagonistic peptide technology was tested on selected CLE peptides and the related IDA peptide and its usefulness in the context of studies of peptide function discussed. Based on the analyses, it was concluded that the antagonistic peptide approach is not the ultimate means to overcome redundancy or lack of loss-of-function lines. However, information collected using antagonistic peptide approaches (in the broad sense) can be very useful, but these approaches do not work in all cases and require a deep insight on the interaction between the ligand and its receptor to be successful. This, as well as peptide ligand structure considerations, should be taken into account before ordering a wide range of synthetic peptide variants and/or generating transgenic plants.

New Algorithm for Managing Childhood Illness Using Mobile Technology (ALMANACH): A Controlled Non-Inferiority Study on Clinical Outcome and Antibiotic Use in Tanzania.

INTRODUCTION: The decline of malaria and scale-up of rapid diagnostic tests calls for a revision of IMCI. A new algorithm (ALMANACH) running on mobile technology was developed based on the latest evidence. The objective was to ensure that ALMANACH was safe, while keeping a low rate of antibiotic prescription. METHODS: Consecutive children aged 2-59 months with acute illness were managed using ALMANACH (2 intervention facilities), or standard practice (2 control facilities) in Tanzania. Primary outcomes were proportion of children cured at day 7 and who received antibiotics on day 0. RESULTS: 130/842 (15∙4%) in ALMANACH and 241/623 (38∙7%) in control arm were diagnosed with an infection in need for antibiotic, while 3∙8% and 9∙6% had malaria. 815/838 (97∙3%;96∙1-98.4%) were cured at D7 using ALMANACH versus 573/623 (92∙0%;89∙8-94∙1%) using standard practice (p<0∙001). Of 23 children not cured at D7 using ALMANACH, 44% had skin problems, 30% pneumonia, 26% upper respiratory infection and 13% likely viral infection at D0. Secondary hospitalization occurred for one child using ALMANACH and one who eventually died using standard practice. At D0, antibiotics were prescribed to 15∙4% (12∙9-17∙9%) using ALMANACH versus 84∙3% (81∙4-87∙1%) using standard practice (p<0∙001). 2∙3% (1∙3-3.3) versus 3∙2% (1∙8-4∙6%) received an antibiotic secondarily. CONCLUSION: Management of children using ALMANACH improve clinical outcome and reduce antibiotic prescription by 80%. This was achieved through more accurate diagnoses and hence better identification of children in need of antibiotic treatment or not. The building on mobile technology allows easy access and rapid update of the decision chart. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR201011000262218.

Studying social interactions through immersive virtual environment technology: Virtues, pitfalls, and future challenges

Thegoalofthepresentreviewistoexplainhowimmersivevirtualenvironmenttechnology(IVET)canbeusedforthestudyofsocialinteractionsandhowtheuseofvirtualhumansinimmersivevirtualenvironmentscanadvanceresearchandapplicationinmanydifferentfields.Researchersstudyingindividualdifferencesinsocialinteractionsaretypicallyinterestedinkeepingthebehaviorandtheappearanceoftheinteractionpartnerconstantacrossparticipants.WithIVETresearchershavefullcontrolovertheinteractionpartners,canstandardizethemwhilestillkeepingthesimulationrealistic.Virtualsimulationsarevalid:growingevidenceshowsthatindeedstudiesconductedwithIVETcanreplicatesomewell-knownfindingsofsocialpsychology.Moreover,IVETallowsresearcherstosubtlymanipulatecharacteristicsoftheenvironment(e.g.,visualcuestoprimeparticipants)orofthesocialpartner(e.g.,his/herrace)toinvestigatetheirinfluencesonparticipants'behaviorandcognition.Furthermore,manipulationsthatwouldbedifficultorimpossibleinreallife(e.g.,changingparticipants'height)canbeeasilyobtainedwithIVET.Besidetheadvantagesfortheoreticalresearch,weexplorethemostrecenttrainingandclinicalapplicationsofIVET,itsintegrationwithothertechnologies(e.g.,socialsensing)andfuturechallengesforresearchers(e.g.,makingthecommunicationbetweenvirtualhumansandparticipantssmoother).