Antibacterial Activity of Phenolic Compounds Against the Phytopathogen Xylella fastidiosa

Xylella fastidiosa is a pathogenic bacterium that causes diseases in many crop species, which leads to considerable economic loss. Phenolic compounds (a group of secondary metabolites) are widely distributed in plants and have shown to possess antimicrobial properties. The anti-Xylella activity of 12 phenolic compounds, representing phenolic acid, coumarin, stilbene and flavonoid, was evaluated using an in vitro agar dilution assay. Overall, these phenolic compounds were effective in inhibiting X. fastidiosa growth, as indicated by low minimum inhibitory concentrations (MICs). In addition, phenolic compounds with different structural features exhibited different anti-Xylella capacities. Particularly, catechol, caffeic acid and resveratrol showed strong anti-Xylella activities. Differential response to phenolic compounds was observed among X. fastidiosa strains isolated from grape and almond. Elucidation of secondary metabolite-based host resistance to X. fastidiosa will have broad implication in combating X. fastidiosa-caused plant diseases. It will facilitate future production of plants with improved disease resistance properties through genetic engineering or traditional breeding approaches and will significantly improve crop yield

The Herschel–ATLAS data release 2, Paper I. Submillimeter and far-infrared images of the South and North Galactic Poles: the largest Herschel survey of the extragalactic sky

We present the largest submillimeter images that have been made of the extragalactic sky. The Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) is a survey of 660 deg2 with the PACS and SPIRE cameras in five photometric bands: 100, 160, 250, 350, and 500 μm. In this paper we present the images from our two largest fields, which account for ~75% of the survey. The first field is 180.1 deg2 in size, centered on the north Galactic pole (NGP), and the second is 317.6 deg2 in size, centered on the south Galactic pole. The NGP field serendipitously contains the Coma cluster. Over most (~80%) of the images, the pixel noise, including both instrumental noise and confusion noise, is approximately 3.6, and 3.5 mJy pix−1 at 100 and 160 μm, and 11.0, 11.1 and 12.3 mJy beam−1 at 250, 350 and 500 μm, respectively, but reaches lower values in some parts of the images. If a matched filter is applied to optimize point-source detection, our total 1σ map sensitivity is 5.7, 6.0, and 7.3 mJy at 250, 350, and 500 μm, respectively. We describe the results of an investigation of the noise properties of the images. We make the most precise estimate of confusion in SPIRE maps to date, finding values of 3.12 ± 0.07, 4.13 ± 0.02, and 4.45 ± 0.04 mJy beam−1 at 250, 350, and 500 μm in our un-convolved maps. For PACS we find an estimate of the confusion noise in our fast-parallel observations of 4.23 and 4.62 mJy beam−1 at 100 and 160 μm. Finally, we give recipes for using these images to carry out photometry, both for unresolved and extended sources

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

Antibacterial Activity of Phenolic Compounds Against the Phytopathogen Xylella fastidiosa

Xylella fastidiosa is a pathogenic bacterium that causes diseases in many crop species, which leads to considerable economic loss. Phenolic compounds (a group of secondary metabolites) are widely distributed in plants and have shown to possess antimicrobial properties. The anti-Xylella activity of 12 phenolic compounds, representing phenolic acid, coumarin, stilbene and flavonoid, was evaluated using an in vitro agar dilution assay. Overall, these phenolic compounds were effective in inhibiting X. fastidiosa growth, as indicated by low minimum inhibitory concentrations (MICs). In addition, phenolic compounds with different structural features exhibited different anti-Xylella capacities. Particularly, catechol, caffeic acid and resveratrol showed strong anti-Xylella activities. Differential response to phenolic compounds was observed among X. fastidiosa strains isolated from grape and almond. Elucidation of secondary metabolite-based host resistance to X. fastidiosa will have broad implication in combating X. fastidiosa-caused plant diseases. It will facilitate future production of plants with improved disease resistance properties through genetic engineering or traditional breeding approaches and will significantly improve crop yield

Factors Influencing the Use of Cognitive-Behavioral Therapy with Autistic Adults: A Survey of Community Mental Health Clinicians

Cognitive–behavioral therapy (CBT) can improve anxiety and depression in autistic adults, but few autistic adults receive this treatment. We examined factors that may influence clinicians’ use of CBT with autistic adults. One hundred clinicians completed an online survey. Clinicians reported stronger intentions (p = .001), more favorable attitudes (p \u3c .001), greater normative pressure (p \u3c .001), and higher self-efficacy (p \u3c .001) to start CBT with non-autistic adults than with autistic adults. The only significant predictor of intentions to begin CBT with clients with anxiety or depression was clinicians’ attitudes (p \u3c .001), with more favorable attitudes predicting stronger intentions. These findings are valuable for designing effective, tailored implementation strategies to increase clinicians’ adoption of CBT for autistic adults. Autistic adults have high rates of anxiety and depression (Buck et al. 2014; Croen et al. 2015), and often do not receive quality mental healthcare for these or other co-occurring conditions (Maddox et al. 2019; Roux et al. 2015; Shattuck et al. 2011). Developing strategies to address co-occurring psychiatric conditions is a high research priority for stakeholders in the autistic community (Frazier et al. 2018; Pellicano et al. 2014). Recent research suggests that cognitive–behavioral therapy (CBT) is effective at treating anxiety and depression in autistic adults (Spain et al. 2015), but many autistic adults do not receive CBT (Roux et al. 2015). This study examined factors that may influence community mental health clinicians’ use of CBT with autistic adults with co-occurring anxiety or depression. Identifying factors that influence clinicians’ use of CBT is crucial for developing mental health services and clinician training programs for autistic adults. The current study focuses on CBT because (1) CBT is a well-established evidence-based treatment for anxiety and depression among adults in the general population, making it the “current gold standard of psychotherapy” (David et al. 2018, p. 1), and (2) CBT is the most studied and supported psychosocial treatment for anxiety and depression in autistic adults (Weiss and Lunsky 2010; White et al. 2018). Few studies have examined reasons why mental health clinicians who work with—or could work with—autistic adults may or may not use CBT with this population. Cooper et al. (2018) surveyed 50 therapists in the UK about their experiences adapting CBT for autistic clients (of any age) and their confidence working with this population. An important study limitation is that the survey respondents were recruited through a training workshop about adapting CBT for autistic people. In this self-selected sample, 64% of therapists had not received prior training on working with autistic clients. On average, they reported feeling moderately confident about using their core therapeutic skills with autistic people (i.e., being empathetic, developing a therapeutic relationship, and gathering information from an autistic client to understand his or her difficulties), and reported less confidence in using other key skills, such as identifying effective therapeutic approaches for autistic clients and using their knowledge of mental health treatments to help autistic clients. However, this study did not test which factors influence the therapists’ intention to use CBT or actual use of CBT with their autistic clients. How can we increase clinicians’ use of CBT with autistic adult clients who present with anxiety or depression? To explore this question, we applied the theory of planned behavior (TPB; Ajzen 1991), a leading causal model of behavior change. The TPB posits that an individual’s attitudes, perceived norms, and/or self-efficacy influence intentions to perform a behavior, and that intentions predict behavior, under circumstances that permit the individual to act (Fig. 1). While the TPB has been used to predict and understand many health-related behaviors (Armitage and Conner 2001), it has only recently been applied to the implementation of evidence-based practices for autistic children in community settings (Fishman et al. 2018, 2019; Ingersoll et al. 2018). For example, Fishman and colleagues (2018) found that autism support classroom teachers’ intentions to use visual schedules with their students strongly predicted their subsequent use of this evidence-based practice. These findings highlight the value of measuring intentions to use specific practices. Fig. 1 The proximal determinants of intention and behavior, as defined by the theory of planned behavior (Ajzen 1991) Full size image The present study is the first to assess TPB constructs in the context of community mental health clinicians providing CBT to autistic adults with co-occurring anxiety or depression. Specifically, we measured community mental health clinicians’ intention, or motivation, to start CBT with their autistic adult clients with co-occurring anxiety or depression, and four potential determinants of this intention (described below): attitudes, descriptive norms, injunctive norms, and self-efficacy towards starting CBT with autistic adults with co-occurring anxiety or depression. To determine whether these associations were specific to working with autistic adults, we also asked about clinicians’ intentions and potential determinants of intentions to start CBT with non-autistic adult clients with anxiety or depression. For the current study, intention to start CBT is a more appropriate outcome than the actual use of CBT with autistic adults because many community mental health clinicians have few to no autistic clients on their caseload and lack training in autism (Maddox et al. 2019). In the TPB, intentions are the most proximal determinant of behavior (Fishbein and Ajzen 2010). Thus, understanding clinicians’ intentions to use a specific evidence-based practice can directly inform future efforts to change clinician behavior and address barriers to treatment access (Fishman et al. 2018; Moullin et al. 2018). In this study, attitudes refer to the clinicians’ perceptions of the advantages and disadvantages of starting CBT with their adult clients with co-occurring anxiety or depression. Normative pressure refers to the clinicians’ perceptions of what others like them do (descriptive norms) and what others expect them to do (injunctive norms) when offering anxiety or depression treatment to an adult client. Self-efficacy (also called perceived behavioral control) refers to the clinicians’ sense of agency to start CBT with an adult client. One advantage of considering these factors is that they are malleable and could be targeted with tailored implementation strategies to improve implementation of evidence-based practice (Fishman et al. 2019). However, it is important to note that these factors are only a small subset of possible barriers to clinicians delivering CBT to autistic adults. For example, we do not examine financial or funding issues, agency leadership engagement, implementation climate, organizational policies, or characteristics of the clients (Damschroder et al. 2009). The current study represents a first step in better understanding the research-to-practice gap related to mental health services for autistic adults

Loneliness is closely associated with depression outcomes and suicidal ideation among military veterans in primary care

Background: Although the substantial influence of social relationships on health is well-known, studies that concurrently examine the influence of varying dimensions of social connectedness on major depression are more limited. This study\u27s aim was to determine to what degree several facets of social connectedness (number of confidants, social support, interpersonal conflict, social norms, and loneliness) are correlated with depressionrelated outcomes. Methods: Participants were primary care patients (n = 301) with probable major depression at a Veterans Health Administration hospital and its satellite clinics. Social connectedness was primarily measured using multi-item instruments from the NIH Toolbox of Adult Social Relationship Scales. Primary outcomes were clinical symptoms (depression and suicidal ideation) and secondary outcomes were self-reported health-related behaviors (medication adherence, patient activation, and help-seeking intentions). Results: In multivariate models adjusting for potential confounders and other facets of connectedness, loneliness was associated with higher levels of depression and suicidal ideation, as well as lower patient activation and help-seeking intentions. Social support and social norms about depression treatment were each associated with higher patient activation and help-seeking intentions. Social connectedness was not associated with medication adherence. Limitations: The limitations of this study are primarily related to its cross-sectional survey design and study population. Conclusions: Multiple aspects of social connectedness are associated with depression outcomes among military veterans with depression. Loneliness may represent the most important component of connectedness, as it is associated with depression severity, suicidality, and health-related behaviors