Search

Abstract The multi-staged XENON program at INFN Laboratori Nazionali del Gran Sasso aims to detect dark matter with two-phase liquid xenon time projection chambers of increasing size and sensitivity. The XENONnT experiment is the latest detector in the program, planned to be an upgrade of its predecessor XENON1T. It features an active target of 5.9 tonnes of cryogenic liquid xenon (8.5 tonnes total mass in cryostat). The experiment is expected to extend the sensitivity to WIMP dark matter by more than an order of magnitude compared to XENON1T, thanks to the larger active mass and the significantly reduced background, improved by novel systems such as a radon removal plant and a neutron veto. This article describes the XENONnT experiment and its sub-systems in detail and reports on the detector performance during the first science run.

Epifluorescence microscopy is an essential tool for obtaining reliable estimates of the abundance of marine microorganisms including viruses. However, computational analysis is required to gain consistent and quantitative data from digital microscopy images. Many imaging programs are proprietary and cost-prohibitive. The currently available free imaging programs are often platform specific and/or lack the flexibility to analyze microscopy images from natural samples, such as the planktonic environment, which can contain challenges such as debris and high background signals. Here we describe two MATLAB-based open-source image analysis programs that work across computer platforms and provide the tools to analyze a range of image types and cell sizes with a user-friendly interface. The Microbial Image Analysis (MiA) program aims to provide flexibility for the selection, identification, and quantification of cells that vary in size and fluorescence intensity within natural microbial communities. The Viral Image Analysis (ViA) program aims to provide an effective means for quantifying viral abundances from epifluorescence images as well as enumerating the intensity of a primary and secondary stain. In this paper, we provide an overview of the functionality of the MiA and ViA programs and highlight specific program features through several microbial image case studies.

Background: Probiotics may help to prevent symptoms of anxiety and depression through several putative mechanisms. Objective: The aim of this study was to evaluate the effect of Lactobacillus rhamnosus HN001 (HN001) given in pregnancy and postpartum on symptoms of maternal depression and anxiety in the postpartum period. This was a secondary outcome, the primary outcome being eczema in the offspring at 12 months of age. Design, Setting, Participants: A randomised, double-blind, placebo-controlled trial of the effect of HN001 on postnatal mood was conducted in 423 women in Auckland and Wellington, New Zealand. Women were recruited at 14–16 weeks gestation. Intervention: Women were randomised to receive either placebo or HN001 daily from enrolment until 6 months postpartum if breastfeeding. Outcome Measures: Modified versions of the Edinburgh Postnatal Depression Scale and State Trait Anxiety Inventory were used to assess symptoms of depression and anxiety postpartum. Trial Registration: Australia NZ Clinical Trials Registry: ACTRN12612000196842. Findings: 423 women were recruited between December 2012 and November 2014. 212 women were randomised to HN001 and 211 to placebo. 380 women (89.8%) completed the questionnaire on psychological outcomes, 193 (91.0%) in the treatment group and 187 (88.6%) in the placebo group. Mothers in the probiotic treatment group reported significantly lower depression scores (HN001 mean = 7·7 (SD = 5·4), placebo 9·0 (6·0); effect size -1·2, (95% CI -2·3, -0·1), p = 0·037) and anxiety scores (HN001 12·0 (4·0), placebo 13·0 (4·0); effect size -1·0 (-1·9, -0·2), p = 0·014) than those in the placebo group. Rates of clinically relevant anxiety on screening (score > 15) were significantly lower in the HN001 treated mothers (OR = 0·44 (0·26, 0·73), p = 0·002). Interpretation: Women who received HN001 had significantly lower depression and anxiety scores in the postpartum period. This probiotic may be useful for the prevention or treatment of symptoms of depression and anxiety postpartum. Funding Source: Health Research Council of New Zealand (11/318) and Fonterra Co-operative Group Ltd.

Diabetic non-healing wounds are a major clinical problem. The mechanisms leading to poor wound healing in diabetes are multifactorial but unresolved inflammation may be a major contributing factor. The complement system (CS) is the most potent inflammatory cascade in humans and contributes to poor wound healing in animal models. Signal transducer and activator of transcription 4 (STAT4) is a transcription factor expressed in immune and adipose cells and contributes to upregulation of some inflammatory chemokines and cytokines. Persistent CS and STAT4 expression in diabetic wounds may thus contribute to chronic inflammation and delayed healing. The purpose of this study was to characterize CS and STAT4 in early diabetic wounds using db/db mice as a diabetic skin wound model. The CS was found to be activated early in the diabetic wounds as demonstrated by increased anaphylatoxin C5a in wound fluid and C3-fragment deposition by immunostaining. These changes were associated with a 76% increase in nucleated cells in the wounds of db/db mice vs.The novel classical CS inhibitor, Peptide Inhibitor of Complement C1 (PIC1) reduced inflammation when added directly or saturated in an acellular skin scaffold, as reflected by reduced CS components and leukocyte infiltration. A significant increase in expression of STAT4 and the downstream macrophage chemokine CCL2 and its receptor CCR2 were also found in the early wounds of db/db mice compared to non-diabetic controls. These studies provide evidence for two new promising targets to reduce unresolved inflammation and to improve healing of diabetic skin wounds.