Predictors of Aged Residential Care Placement in Patients Newly Diagnosed with Dementia at a New Zealand Memory Service

Background: Aged residential care (ARC) is a significant cost of dementia care. However, little is known about the predictors of ARC placement in New Zealand (NZ), which is important for service planning and funding. The aim of this study was to investigate the sociodemographic and clinical characteristics that predict future ARC placement among people who received a new diagnosis of dementia at a NZ memory service. Methods: Routinely collected baseline sociodemographic and clinical data in a memory service from 14/06/13 and 14/12/19 were linked with administrative LTC admission data up to 24/1/2020. Survival analysis was carried out using multivariate Cox regression models to determine significant risk factors and their association with ARC placement. Results: A total of 657 NZ European, Māori and Pacific Islander patients were included in the analyses. There were significant differences by ethnicity including age, living situation, comorbidity and ARC placement. Adjusted analyses showed that risk of ARC placement was increased by older age (HR 1.02 per year, 95%CI:1.00–1.05), moderate dementia (HR 1.45, 95%CI:1.05–1.99), severe dementia (HR 2.25, 95%CI:1.33–3.81), and antipsychotics (HR 1.55, 95%CI:1.04–2.32); while risk was reduced in Māori (HR 0.35, 95%CI:0.18–0.68) and Pacific Islanders (HR 0.32, 95%CI:0.20–0.51). Conclusions: Despite having more severe dementia and higher comorbidity, Māori and Pacific Islanders had reduced risks of ARC placement. There is an urgent need to better understand dementia care issues and to ensure culturally safe and responsive dementia services are accessible by Māori and Pacific Islanders living in the community

Tomato Pathogenesis-related Protein Genes are Expressed in Response to Trialeurodes vaporariorum and Bemisia tabaci Biotype B Feeding

The temporal and spatial expression of tomato wound- and defense-response genes to Bemisia tabaci biotype B (the silverleaf whitefly) and Trialeurodes vaporariorum (the greenhouse whitefly) feeding were characterized. Both species of whiteflies evoked similar changes in tomato gene expression. The levels of RNAs for the methyl jasmonic acid (MeJA)- or ethylene-regulated genes that encode the basic β-1,3-glucanase (GluB), basic chitinase (Chi9), and Pathogenesis-related protein-1 (PR-1) were monitored. GluB and Chi9 RNAs were abundant in infested leaves from the time nymphs initiated feeding (day 5). In addition, GluB RNAs accumulated in apical non-infested leaves. PR-1 RNAs also accumulated after whitefly feeding. In contrast, the ethylene- and salicylic acid (SA)-regulated Chi3 and PR-4 genes had RNAs that accumulated at low levels and GluAC RNAs that were undetectable in whitefly-infested tomato leaves. The changes in Phenylalanine ammonia lyase5 (PAL5) were variable; in some, but not all infestations, PAL5 RNAs increased in response to whitefly feeding. PAL5 RNA levels increased in response to MeJA, ethylene, and abscisic acid, and declined in response to SA. Transcripts from the wound-response genes, leucine aminopeptidase (LapA1) and proteinase inhibitor 2 (pin2), were not detected following whitefly feeding. Furthermore, whitefly infestation of transgenic LapA1:GUS tomato plants showed that whitefly feeding did not activate the LapA1 promoter, although crushing of the leaf lamina increased GUS activity up to 40 fold. These studies indicate that tomato plants perceive B. tabaci and T. vaporariorum in a manner similar to baterical pathogens and distinct from tissue-damaging insects

Salivary Glucose Oxidase from Caterpillars Mediates the Induction of Rapid and Delayed-Induced Defenses in the Tomato Plant

Caterpillars produce oral secretions that may serve as cues to elicit plant defenses, but in other cases these secretions have been shown to suppress plant defenses. Ongoing work in our laboratory has focused on the salivary secretions of the tomato fruitworm, Helicoverpa zea. In previous studies we have shown that saliva and its principal component glucose oxidase acts as an effector by suppressing defenses in tobacco. In this current study, we report that saliva elicits a burst of jasmonic acid (JA) and the induction of late responding defense genes such as proteinase inhibitor 2 (Pin2). Transcripts encoding early response genes associated with the JA pathway were not affected by saliva. We also observed a delayed response to saliva with increased densities of Type VI glandular trichomes in newly emerged leaves. Proteomic analysis of saliva revealed glucose oxidase (GOX) was the most abundant protein identified and we confirmed that it plays a primary role in the induction of defenses in tomato. These results suggest that the recognition of GOX in tomato may represent a case for effector-triggered immunity. Examination of saliva from other caterpillar species indicates that saliva from the noctuids Spodoptera exigua and Heliothis virescens also induced Pin2 transcripts

Potent cross-reactive antibodies following Omicron breakthrough in vaccinees

Highly transmissible Omicron variants of SARS-CoV-2 currently dominate globally. Here, we compare neutralization of Omicron BA.1, BA.1.1 and BA.2. BA.2 RBD has slightly higher ACE2 affinity than BA.1 and slightly reduced neutralization by vaccine serum, possibly associated with its increased transmissibility. Neutralization differences between sub-lineages for mAbs (including therapeutics) mostly arise from variation in residues bordering the ACE2 binding site, however, more distant mutations S371F (BA.2) and R346K (BA.1.1) markedly reduce neutralization by therapeutic antibody Vir-S309. In-depth structure-and-function analyses of 27 potent RBD-binding mAbs isolated from vaccinated volunteers following breakthrough Omicron-BA.1 infection reveals that they are focussed in two main clusters within the RBD, with potent right-shoulder antibodies showing increased prevalence. Selection and somatic maturation have optimized antibody potency in less-mutated epitopes and recovered potency in highly mutated epitopes. All 27 mAbs potently neutralize early pandemic strains and many show broad reactivity with variants of concern

Antibody escape of SARS-CoV-2 Omicron BA.4 and BA.5 from vaccine and BA.1 serum

The Omicron lineage of SARS-CoV-2, first described in November 2021, spread rapidly to become globally dominant and has split into a number of sub-lineages. BA.1 dominated the initial wave but has been replaced by BA.2 in many countries. Recent sequencing from South Africa’s Gauteng region uncovered two new sub-lineages, BA.4 and BA.5 which are taking over locally, driving a new wave. BA.4 and BA.5 contain identical spike sequences and, although closely related to BA.2, contain further mutations in the receptor binding domain of spike. Here, we study the neutralization of BA.4/5 using a range of vaccine and naturally immune serum and panels of monoclonal antibodies. BA.4/5 shows reduced neutralization by serum from triple AstraZeneca or Pfizer vaccinated individuals compared to BA.1 and BA.2. Furthermore, using serum from BA.1 vaccine breakthrough infections there are likewise, significant reductions in the neutralization of BA.4/5, raising the possibility of repeat Omicron infections

Plant-arthropod interactions: who is the winner?

Herbivorous arthropods have interacted with plants for millions of years. During feeding they release chemical cues that allow plants to detect the attack and mount an efficient defense response. A signaling cascade triggers the expression of hundreds of genes, which encode defensive proteins and enzymes for synthesis of toxic metabolites. This direct defense is often complemented by emission of volatiles that attract beneficial parasitoids. In return, arthropods have evolved strategies to interfere with plant defenses, either by producing effectors to inhibit detection and downstream signaling steps, or by adapting to their detrimental effect. In this review, we address the current knowledge on the molecular and chemical dialog between plants and herbivores, with an emphasis on co-evolutionary aspects

Multiple Resolution Segmentation of Textured Images

This paper presents a multiple resolution algorithm for segmenting images into regions with differing statistical behavior. In addition, an algorithm is developed for determining the number of statistically distinct regions in an image and estimating the parameters of those regions. Both algorithms use a causal Gaussian autoregressive (AR) model to describe the mean, variance and spatial correlation of the image textures. Together the algorithms may be used to perform unsupervised texture segmentation. The multiple resolution segmentation algorithm first segments images at coarse resolution and then progresses to finer resolutions until individual pixels are classified. This method results in accurate segmentations and requires significantly less computation than some previously known methods. The field containing the classification of each pixel in the image is modeled as a Markov random field (MRF). Segmentation at each resolution is then performed by maximizing the a posteriori prob..