Balancing photosynthetic electron flow is critical for cyanobacterial acclimation to nitrogen limitation

AbstractNitrogen limitation forces photosynthetic organisms to reallocate available nitrogen to essential functions. At the same time, it increases the probability of photo-damage by limiting the rate of energy-demanding metabolic processes, downstream of the photosynthetic apparatus. Non-diazotrophic cyanobacteria cope with this situation by decreasing the size of their phycobilisome antenna and by modifying their photosynthetic apparatus. These changes can serve two purposes: to provide extra amino-acids and to decrease excitation pressure. We examined the effects of nitrogen limitation on the form and function of the photosynthetic apparatus. Our aim was to study which of the two demands serve as the driving force for the remodeling of the photosynthetic apparatus, under different growth conditions. We found that a drastic reduction in light intensity allowed cells to maintain a more functional photosynthetic apparatus: the phycobilisome antenna was bigger, the activity of both photosystems was higher and the levels of photosystem (PS) proteins were higher. Pre-acclimating cells to Mn limitation, under which the activity of both PSI and PSII is diminished, results in a very similar response. The rate of PSII photoinhibition, in nitrogen limited cells, was found to be directly related to the activity of the photosynthetic apparatus. These data indicate that, under our experimental conditions, photo-damage avoidance was the more prominent determinant during the acclimation process. The combinations of limiting factors tested here is by no means artificial. Similar scenarios can take place under environmental conditions and should be taken into account when estimating nutrient limitations in nature

Explainable automated recognition of emotional states from canine facial expressions: the case of positive anticipation and frustration.

In animal research, automation of affective states recognition has so far mainly addressed pain in a few species. Emotional states remain uncharted territories, especially in dogs, due to the complexity of their facial morphology and expressions. This study contributes to fill this gap in two aspects. First, it is the first to address dog emotional states using a dataset obtained in a controlled experimental setting, including videos from (n = 29) Labrador Retrievers assumed to be in two experimentally induced emotional states: negative (frustration) and positive (anticipation). The dogs' facial expressions were measured using the Dogs Facial Action Coding System (DogFACS). Two different approaches are compared in relation to our aim: (1) a DogFACS-based approach with a two-step pipeline consisting of (i) a DogFACS variable detector and (ii) a positive/negative state Decision Tree classifier; (2) An approach using deep learning techniques with no intermediate representation. The approaches reach accuracy of above 71% and 89%, respectively, with the deep learning approach performing better. Secondly, this study is also the first to study explainability of AI models in the context of emotion in animals. The DogFACS-based approach provides decision trees, that is a mathematical representation which reflects previous findings by human experts in relation to certain facial expressions (DogFACS variables) being correlates of specific emotional states. The deep learning approach offers a different, visual form of explainability in the form of heatmaps reflecting regions of focus of the network's attention, which in some cases show focus clearly related to the nature of particular DogFACS variables. These heatmaps may hold the key to novel insights on the sensitivity of the network to nuanced pixel patterns reflecting information invisible to the human eye

Explainable automated recognition of emotional states from canine facial expressions: the case of positive anticipation and frustration

In animal research, automation of affective states recognition has so far mainly addressed pain in a few species. Emotional states remain uncharted territories, especially in dogs, due to the complexity of their facial morphology and expressions. This study contributes to fill this gap in two aspects. First, it is the first to address dog emotional states using a dataset obtained in a controlled experimental setting, including videos from (n = 29) Labrador Retrievers assumed to be in two experimentally induced emotional states: negative (frustration) and positive (anticipation). The dogs’ facial expressions were measured using the Dogs Facial Action Coding System (DogFACS). Two different approaches are compared in relation to our aim: (1) a DogFACS-based approach with a two-step pipeline consisting of (i) a DogFACS variable detector and (ii) a positive/negative state Decision Tree classifier; (2) An approach using deep learning techniques with no intermediate representation. The approaches reach accuracy of above 71% and 89%, respectively, with the deep learning approach performing better. Secondly, this study is also the first to study explainability of AI models in the context of emotion in animals. The DogFACS-based approach provides decision trees, that is a mathematical representation which reflects previous findings by human experts in relation to certain facial expressions (DogFACS variables) being correlates of specific emotional states. The deep learning approach offers a different, visual form of explainability in the form of heatmaps reflecting regions of focus of the network’s attention, which in some cases show focus clearly related to the nature of particular DogFACS variables. These heatmaps may hold the key to novel insights on the sensitivity of the network to nuanced pixel patterns reflecting information invisible to the human eye

Rheumatologists lack confidence in their knowledge of cannabinoids pertaining to the management of rheumatic complaints

Background: Arthritis pain is reported as one of the most common reasons for persons using medical herbal cannabis in North America. “Severe arthritis” is the condition justifying legal use of cannabis in over half of all authorizations in Canada, where cannabis remains a controlled substance. As champions for the care of persons with arthritis, rheumatologists must be knowledgeable of treatment modalities both traditional and non-traditional, used by their patients. As study of cannabinoid molecules in medicine is recent, we have examined the confidence in the knowledge of cannabinoids expressed by Canadian rheumatologists. Methods: The confidence of rheumatologists in their knowledge of cannabinoid molecules and mechanisms relevant to rheumatology, and their ability to advise patients about cannabinoid treatments was recorded by an online questionnaire circulated via email to the entire Canadian Rheumatology Association membership. Results: Over three quarters of the 128 respondents lacked confidence in their knowledge of cannabinoid molecules. While 45% of respondents believed there was no current role for cannabinoids in rheumatology patient care, only 25% supported any use of herbal cannabis. With 70% never having previously prescribed or recommended any cannabinoid treatment, uncertainty regarding good prescribing practices was prevalent. Concerns about risks of cannabis use were in line with the current literature. Conclusions: Rheumatologists lacked confidence in their knowledge of cannabinoid molecules in general and in their competence to prescribe any cannabinoid for rheumatic complaints. In line with this uncertainty, there is reticence to prescribe cannabinoid preparations for rheumatology patients. Guidance is required to inform rheumatologists on the evidence regarding cannabinoids.Arts, Faculty ofMedicine, Department ofMedicine, Faculty ofPsychology, Department ofRheumatology, Division ofNon UBCReviewedFacult

Communities catalyzing change with data to mitigate an invisible menace, traffic-related air pollution

Abstract Objectives To identify strategies and tactics communities use to translate research into environmental health action. Methods We employed a qualitative case study design to explore public health action conducted by residents, organizers, and public health planners in two Massachusetts communities as part of a community based participatory (CBPR) research study. Data sources included key informant interviews (n = 24), reports and direct observation of research and community meetings (n = 10) and project meeting minutes from 2016–2021. Data were coded deductively drawing on the community organizing and implementation frameworks. Results In Boston Chinatown, partners drew broad participation from community-based organizations, residents, and municipal leaders, which resulted in air pollution mitigation efforts being embedded in the master planning process. In Somerville, partners focused on change at multiple levels, developer behavior, and separate from the funded research, local legislative efforts, and litigation. Conclusions CBPR affords communities the ability to environmental health efforts in a way that is locally meaningful, leveraging their respective strengths. External facilitation can support the continuity and sustainment of community led CBPR efforts

Epithelial cells detect functional type III secretion system of enteropathogenic <i>Escherichia coli</i> through a novel NF-κB signaling pathway

<div><p>Enteropathogenic <i>Escherichia coli</i> (EPEC), a common cause of infant diarrhea, is associated with high risk of mortality in developing countries. The primary niche of infecting EPEC is the apical surface of intestinal epithelial cells. EPEC employs a type three secretion system (TTSS) to inject the host cells with dozens of effector proteins, which facilitate attachment to these cells and successful colonization. Here we show that EPEC elicit strong NF-κB activation in infected host cells. Furthermore, the data indicate that active, pore-forming TTSS <i>per se</i> is necessary and sufficient for this NF-κB activation, regardless of any specific effector or protein translocation. Importantly, upon infection with wild type EPEC this NF-κB activation is antagonized by anti-NF-κB effectors, including NleB, NleC and NleE. Accordingly, this NF-κB activation is evident only in cells infected with EPEC mutants deleted of <i>nleB</i>, <i>nleC</i>, and <i>nleE</i>. The TTSS-dependent NF-κB activation involves a unique pathway, which is independent of TLRs and Nod1/2 and converges with other pathways at the level of TAK1 activation. Taken together, our results imply that epithelial cells have the capacity to sense the EPEC TTSS and activate NF-κB in response. Notably, EPEC antagonizes this capacity by delivering anti-NF-κB effectors into the infected cells.</p></div

TTSS-mediated NF-κB activation is not dependent on MyD88.

<p>HeLa cells stably expressing MyD88-targeting shRNA or the control shRNA (marked as wt) were infected with EPEC (A) or W3100/pLEE (B) strains or treated with TNFα or IL-1β (C), as indicated. (D) Primary fibroblasts were extracted from wt or MyD88 knock-out C57Bl/6 mice and infected with EPEC strains or treated with TNFα or IL-1β. The cells were fixed, stained for p65 and quantified for nuclear p65 by microscopy. Bars represent standard deviation. Data are presented as mean±SE. Asterisks indicate a significant difference (*P < 0.05, **P < 0.01) using Student’s t test.</p

Productive contact of the TTSS with the host cell is required for NF-κB activation.

<p>(A) HEK293 cells transfected with the NF-κB reporter plasmid were infected with two W3110 strains carrying mutated pLEE plasmids, one deleted of <i>espG</i> and the region between <i>espH</i> and <i>cesT</i> (Δ<i>espG</i>, <i>ΔespH-cesT</i>), and the other deleted of <i>espB</i> (Δ<i>espB</i>). Uninfected (UI) cells were used as negative control. NF-κB activation was determined by the dual luciferase assay. (B) HeLa cells were infected with wild type W3110 (wt), or W3110 containing, as indicated, different combinations of the following plasmids: pPerC (expressing PerC [<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006472#ppat.1006472.ref056" target="_blank">56</a>]), pGrlA (expressing GrlA, <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006472#ppat.1006472.s007" target="_blank">S4 Fig</a>) and variants of the pLEE plasmid, including wild type (pLEE) or pLEE deleted of <i>escV</i> (Δ<i>escV</i>) or <i>espB</i> (Δ<i>espB</i>). Cells were fixed, stained for p65 and nuclear p65 was quantified by microscopy. (C) HeLa cells were infected as in (B), proteins were extracted and the levels of cytosolic IκB were determined by Western blot using anti-IκB antibody. (D) W3110 containing pLEE and pGrlA, or pLEE,Δ<i>escV</i> were grown under conditions that activate TTSS formation. Were stated, gentamicin was added to block translation, during a 10 min incubation. Bacteria were then spun on HeLa cells pre-seeded on cover slips (200 g, 10 min, room temperature), and infected cells were incubated for 30 min, 37°C, 5% CO₂. Cells were washed, fixed and stained for p65 and actin. The fraction (%) of cells with nuclear p65 and percentage of cells containing actin-pedestals was determined by microscopy.</p

TTSS-mediated NF-κB activation is not dependent on TRAF6 or RIP2.

<p>(A) TRAF6^-/- or RIP2^-/- or wt HEK293 cells were transfected with the NF-κB reporter plasmid and infected with W3110 strains, as indicated. NF-κB activation was determined by the dual luciferase assay. Two independent clones of TRAF6^-/- and RIP2^-/- were tested. (B) TRAF6^-/- mouse embryonic fibroblasts were treated with IL-1β, or infected with different EPEC strains, as indicated. The cells were then fixed, stained for p65 and quantified for nuclear p65 by microscopy. (C) HEK393 cells co-transfected with the NF-κB reporter plasmid and a plasmid expressing dominant negative RIP2 (DN-RIP2) were treated with MDP, tri-DAP, or infected with EPEC or W3110 strains, as indicated. NF-κB activation was determined by the luciferase assay.</p

Single components of the TTSS do not trigger NF-κB activation.

<p>(A) HeLa cells were transfected with plasmids expressing mCherry-conjugants of the indicated bacterial proteins. Cells were stained for p65 translocation and quantified by microscopy. Representative images are shown in (B). Cells treated with IL-1β were used as positive control for p65 activation. Size-bar represents 50 microns.</p