Cell-penetrating peptide-conjugated copper complexes for redox-mediated anticancer therapy

Metal-based chemotherapeutics like cisplatin are widely employed in cancer treatment. In the last years, the design of redox-active (transition) metal complexes, such as of copper (Cu), has attracted high interest as alternatives to overcome platinum-induced side-effects. However, several challenges are still faced, including optimal aqueous solubility and efficient intracellular delivery, and strategies like the use of cell-penetrating peptides have been encouraging. In this context, we previously designed a Cu(II) scaffold that exhibited significant reactive oxygen species (ROS)-mediated cytotoxicity. Herein, we build upon the promising Cu(II) redox-active metallic core and aim to potentiate its anticancer activity by rationally tailoring it with solubility- and uptake-enhancing functionalizations that do not alter the ROS-generating Cu(II) center. To this end, sulfonate, arginine and arginine-rich cell-penetrating peptide (CPP) derivatives have been prepared and characterized, and all the resulting complexes preserved the parent Cu(II) coordination core, thereby maintaining its reported redox capabilities. Comparative in vitro assays in several cancer cell lines reveal that while specific solubility-targeting derivatizations (i.e., sulfonate or arginine) did not translate into an improved cytotoxicity, increased intracellular copper delivery via CPP-conjugation promoted an enhanced anticancer activity, already detectable at short treatment times. Additionally, immunofluorescence assays show that the Cu(II) peptide-conjugate distributed throughout the cytosol without lysosomal colocalization, suggesting potential avoidance of endosomal entrapment. Overall, the systematic exploration of the tailored modifications enables us to provide further understanding on structure-activity relationships of redox-active metal-based (Cu(II)) cytotoxic complexes, which contributes to rationalize and improve the design of more efficient redox-mediated metal-based anticancer therapy

A personalized intervention to prevent depression in primary care based on risk predictive algorithms and decision support systems: protocol of the e-predictD study

The predictD is an intervention implemented by general practitioners (GPs) to prevent depression, which reduced the incidence of depression-anxiety and was cost-effective. The e-predictD study aims to design, develop, and evaluate an evolved predictD intervention to prevent the onset of major depression in primary care based on Information and Communication Technologies, predictive risk algorithms, decision support systems (DSSs), and personalized prevention plans (PPPs). A multicenter cluster randomized trial with GPs randomly assigned to the e-predictD intervention + care-as-usual (CAU) group or the active-control + CAU group and 1-year follow-up is being conducted. The required sample size is 720 non-depressed patients (aged 18–55 years), with moderate-to-high depression risk, under the care of 72 GPs in six Spanish cities. The GPs assigned to the e-predictD-intervention group receive brief training, and those assigned to the control group do not. Recruited patients of the GPs allocated to the e-predictD group download the e-predictD app, which incorporates validated risk algorithms to predict depression, monitoring systems, and DSSs. Integrating all inputs, the DSS automatically proposes to the patients a PPP for depression based on eight intervention modules: physical exercise, social relationships, improving sleep, problem-solving, communication skills, decision-making, assertiveness, and working with thoughts. This PPP is discussed in a 15-min semi-structured GP-patient interview. Patients then choose one or more of the intervention modules proposed by the DSS to be self-implemented over the next 3 months. This process will be reformulated at 3, 6, and 9 months but without the GP–patient interview. Recruited patients of the GPs allocated to the control-group+CAU download another version of the e-predictD app, but the only intervention that they receive via the app is weekly brief psychoeducational messages (active-control group). The primary outcome is the cumulative incidence of major depression measured by the Composite International Diagnostic Interview at 6 and 12 months. Other outcomes include depressive symptoms (PHQ-9) and anxiety symptoms (GAD-7), depression risk (predictD risk algorithm), mental and physical quality of life (SF-12), and acceptability and satisfaction (‘e-Health Impact' questionnaire) with the intervention. Patients are evaluated at baseline and 3, 6, 9, and 12 months. An economic evaluation will also be performed (cost-effectiveness and cost-utility analysis) from two perspectives, societal and health systems.Trial registrationClinicalTrials.gov, identifier: NCT03990792

Circulating concentrations of GDF11 are positively associated with TSH levels in humans

Growth differentiation factor 11 (GDF11) is a member of the transforming growth factor (TGF)-beta superfamily which declines with age and has been proposed as an anti-aging factor with regenerative effects in skeletal muscle in mice. However, recent data in humans and mice are conflicting, casting doubts about its true functional actions. The aim of the present study was to analyze the potential involvement of GFD11 in energy homeostasis in particular in relation with thyroid hormones. Serum concentrations of GDF11 were measured by enzyme-linked immunosorbent assay (ELISA) in 287 subjects. A highly significant positive correlation was found between GDF11 and thyroid-stimulating hormone (TSH) concentrations (r = 0.40, p 0.05 for both) with GDF11 levels. In a multiple linear regression analysis, the model that best predicted logGDF11 included logTSH, leptin, body mass index (BMI), age, and C-reactive protein (logCRP). This model explained 37% of the total variability of logGDF11 concentrations (p < 0.001), with only logTSH being a significant predictor of logGDF11. After segregating subjects by TSH levels, those within the low TSH group exhibited significantly decreased (p < 0.05) GDF11 concentrations as compared to the normal TSH group or the high TSH group. A significant correlation of GDF11 levels with logCRP (r = 0.19, p = 0.025) was found. GDF11 levels were not related to the presence of hypertension or cardiopathy. In conclusion, our results show that circulating concentrations of GDF11 are closely associated with TSH concentrations and reduced in subjects with low TSH levels. However, GDF11 is not related to the regulation of energy expenditure. Our data also suggest that GDF11 may be involved in the regulation of inflammation, without relation to cardiac function. Further research is needed to elucidate the role of GDF11 in metabolism and its potential involvement in thyroid pathophysiology

A personalized intervention to prevent depression in primary care based on risk predictive algorithms and decision support systems: protocol of the e-predictD study

The predictD is an intervention implemented by general practitioners (GPs) to prevent depression, which reduced the incidence of depression-anxiety and was cost-effective. The e-predictD study aims to design, develop, and evaluate an evolved predictD intervention to prevent the onset of major depression in primary care based on Information and Communication Technologies, predictive risk algorithms, decision support systems (DSSs), and personalized prevention plans (PPPs). A multicenter cluster randomized trial with GPs randomly assigned to the e-predictD intervention + care-as-usual (CAU) group or the active-control + CAU group and 1-year follow-up is being conducted. The required sample size is 720 non-depressed patients (aged 18–55 years), with moderate-to-high depression risk, under the care of 72 GPs in six Spanish cities. The GPs assigned to the e-predictD-intervention group receive brief training, and those assigned to the control group do not. Recruited patients of the GPs allocated to the e-predictD group download the e-predictD app, which incorporates validated risk algorithms to predict depression, monitoring systems, and DSSs. Integrating all inputs, the DSS automatically proposes to the patients a PPP for depression based on eight intervention modules: physical exercise, social relationships, improving sleep, problem-solving, communication skills, decision-making, assertiveness, and working with thoughts. This PPP is discussed in a 15-min semi-structured GP-patient interview. Patients then choose one or more of the intervention modules proposed by the DSS to be self-implemented over the next 3 months. This process will be reformulated at 3, 6, and 9 months but without the GP–patient interview. Recruited patients of the GPs allocated to the control-group+CAU download another version of the e-predictD app, but the only intervention that they receive via the app is weekly brief psychoeducational messages (active-control group). The primary outcome is the cumulative incidence of major depression measured by the Composite International Diagnostic Interview at 6 and 12 months. Other outcomes include depressive symptoms (PHQ-9) and anxiety symptoms (GAD-7), depression risk (predictD risk algorithm), mental and physical quality of life (SF-12), and acceptability and satisfaction (‘e-Health Impact' questionnaire) with the intervention. Patients are evaluated at baseline and 3, 6, 9, and 12 months. An economic evaluation will also be performed (cost-effectiveness and cost-utility analysis) from two perspectives, societal and health systems.Trial registrationClinicalTrials.gov, identifier: NCT03990792

Family physicians' views on participating in prevention of major depression. The predictD-EVAL qualitative study

BACKGROUND: The predictD intervention, a multicomponent intervention delivered by family physicians (FPs), reduced the incidence of major depression by 21% versus the control group and was cost-effective. A qualitative methodology was proposed to identify the mechanisms of action of these complex interventions. PURPOSE: To seek the opinions of these FPs on the potential successful components of the predictD intervention for the primary prevention of depression in primary care and to identify areas for improvement. METHOD: Qualitative study with FPs who delivered the predictD intervention at 35 urban primary care centres in seven Spanish cities. Face-to-face semi-structured interviews adopting a phenomenological approach. The data was triangulated by three investigators using thematic analysis and respondent validation was carried out. RESULTS: Sixty-seven FPs were interviewed and they indicated strategies used to perform the predictD intervention, including specific communication skills such as empathy and the activation of patient resources. They perceived barriers such as lack of time and facilitators such as prior acquaintance with patients. FPs recognized the positive consequences of the intervention for FPs, patients and the doctor-patient relationship. They also identified strategies for future versions and implementations of the predictD intervention. CONCLUSIONS: The FPs who carried out the predictD intervention identified factors potentially associated with successful prevention using this program and others that could be improved. Their opinions about the predictD intervention will enable development of a more effective and acceptable version and its implementation in different primary health care settings

Effectiveness of a stepped-care programme of internet-based psychological interventions for healthcare workers with psychological distress: Study protocol for the RESPOND healthcare workers randomised controlled trial

The dataset that supports the findings of this study are archived in the Universidad Autónoma de Madrid data repository e‐cienciaDatos in https://doi.org/10.21950/HN1HNOBackground and aims: The coronavirus disease 2019 pandemic has challenged health services worldwide, with a worsening of healthcare workers’ mental health within initial pandemic hotspots. In early 2022, the Omicron variant is spreading rapidly around the world. This study explores the effectiveness and cost-effectiveness of a stepped-care programme of scalable, internet-based psychological interventions for distressed health workers on self-reported anxiety and depression symptoms. Methods: We present the study protocol for a multicentre (two sites), parallel-group (1:1 allocation ratio), analyst-blinded, superiority, randomised controlled trial. Healthcare workers with psychological distress will be allocated either to care as usual only or to care as usual plus a stepped-care programme that includes two scalable psychological interventions developed by the World Health Organization: A guided self-help stress management guide (Doing What Matters in Times of Stress) and a five-session cognitive behavioural intervention (Problem Management Plus). All participants will receive a single-session emotional support intervention, namely psychological first aid. We will include 212 participants. An intention-to-treat analysis using linear mixed models will be conducted to explore the programme's effect on anxiety and depression symptoms, as measured by the Patient Health Questionnaire – Anxiety and Depression Scale summary score at 21 weeks from baseline. Secondary outcomes include post-traumatic stress disorder symptoms, resilience, quality of life, cost impact and cost-effectiveness. Conclusions: This study is the first randomised trial that combines two World Health Organization psychological interventions tailored for health workers into one stepped-care programme. Results will inform occupational and mental health prevention, treatment, and recovery strategies. Registration details: ClinicalTrials.gov Identifier: NCT04980326The RESPOND project was funded under Horizon 2020 -the Framework Programme for Research and Innovation (2014– 2020) (grant number: 101016127), and the work of MF-N was supported by a postdoctoral fellowship of the ISCIII (CD20/ 00036

Reversed-phase high-performance liquid chromatography–fluorescence detection for the analysis of glutathione and its precursor γ-glutamyl cysteine in wines and model wines supplemented with oenological inactive dry yeast preparations

El pdf del artículo es la versión pre-print.A reversed-phase high-performance liquid chromatography-fluorescence detection methodology involving a pre-column derivatization procedure using 2,3-naphtalenedialdehyde in the presence of 5 and 0. 5 mM of dithiothreitol to determine total and reduced glutathione (GSH) and γ-glutamyl-cysteine (γ-glu-cys) in musts and wines has been set up and validated. The proposed method showed good linearity (R 2 >99% for reduced and total GSH, and R 2 >98% for γ-glu-cys) in synthetic wines, over a wide range of concentration (0-10 mg L -1). The limits of detection for reduced GSH in synthetic and real wines were almost the same (0. 13 and 0. 15 mg L -1, respectively) and slightly higher for γ-glu-cys (0. 24 mg L -1). The application of the method allowed knowing, for the first time, the amount of total and reduced GSH and γ-glu-cys released into synthetic wines by oenological preparations of commercial inactive dry yeast (IDY). In addition, the evolution of these three compounds during the winemaking and shelf life (0-9 months) of an industrially manufactured rosé wine supplemented with a GSH-enriched IDY showed that although GSH is effectively released from IDY, it is rapidly oxidized during alcoholic fermentation, contributing to the higher total GSH content determined in wines supplemented with GSH-enriched IDYs compared to control wines. © 2011 Springer Science+Business Media, LLC.IAO and JJRB acknowledge CAM and CSIC for their respective research grants. This work has been founded by PET2007-0134 project.Peer Reviewe

Preventing the onset of major depression based on the level and profile of risk of primary care attendees: protocol of a cluster randomised trial (the predictD-CCRT study)

BACKGROUND: The 'predictD algorithm' provides an estimate of the level and profile of risk of the onset of major depression in primary care attendees. This gives us the opportunity to develop interventions to prevent depression in a personalized way. We aim to evaluate the effectiveness, cost-effectiveness and cost-utility of a new intervention, personalized and implemented by family physicians (FPs), to prevent the onset of episodes of major depression. METHODS: This is a multicenter randomized controlled trial (RCT), with cluster assignment by health center and two parallel arms. Two interventions will be applied by FPs, usual care versus the new intervention predictD-CCRT. The latter has four components: a training workshop for FPs; communicating the level and profile of risk of depression; building up a tailored bio-psycho-family-social intervention by FPs to prevent depression; offering a booklet to prevent depression; and activating and empowering patients. We will recruit a systematic random sample of 3286 non-depressed adult patients (1643 in each trial arm), nested in 140 FPs and 70 health centers from 7 Spanish cities. All patients will be evaluated at baseline, 6, 12 and 18 months. The level and profile of risk of depression will be communicated to patients by the FPs in the intervention practices at baseline, 6 and 12 months. Our primary outcome will be the cumulative incidence of major depression (measured by CIDI each 6 months) over 18 months of follow-up. Secondary outcomes will be health-related quality of life (SF-12 and EuroQol), and measurements of cost-effectiveness and cost-utility. The inferences will be made at patient level. We shall undertake an intention-to-treat effectiveness analysis and will handle missing data using multiple imputations. We will perform multi-level logistic regressions and will adjust for the probability of the onset of major depression at 12 months measured at baseline as well as for unbalanced variables if appropriate. The economic evaluation will be approached from two perspectives, societal and health system. DISCUSSION: To our knowledge, this will be the first RCT of universal primary prevention for depression in adults and the first to test a personalized intervention implemented by FPs. We discuss possible biases as well as other limitations.Trial registration: ClinicalTrials.gov identifier: NCT01151982

Characterization of New Substrates Targeted By Yersinia Tyrosine Phosphatase YopH

YopH is an exceptionally active tyrosine phosphatase that is essential for virulence of Yersinia pestis, the bacterium causing plague. YopH breaks down signal transduction mechanisms in immune cells and inhibits the immune response. Only a few substrates for YopH have been characterized so far, for instance p130Cas and Fyb, but in view of YopH potency and the great number of proteins involved in signalling pathways it is quite likely that more proteins are substrates of this phosphatase. In this respect, we show here YopH interaction with several proteins not shown before, such as Gab1, Gab2, p85, and Vav and analyse the domains of YopH involved in these interactions. Furthermore, we show that Gab1, Gab2 and Vav are not dephosphorylated by YopH, in contrast to Fyb, Lck, or p85, which are readily dephosphorylated by the phosphatase. These data suggests that YopH might exert its actions by interacting with adaptors involved in signal transduction pathways, what allows the phosphatase to reach and dephosphorylate its susbstrates

Natural resistance to Meningococcal Disease related to CFH loci: Meta-analysis of genome-wide association studies

Meningococcal disease (MD) remains an important infectious cause of life threatening infection in both industrialized and resource poor countries. Genetic factors influence both occurrence and severity of presentation, but the genes responsible are largely unknown. We performed a genome-wide association study (GWAS) examining 5,440,063 SNPs in 422 Spanish MD patients and 910 controls. We then performed a meta-analysis of the Spanish GWAS with GWAS data from the United Kingdom (combined cohorts: 897 cases and 5,613 controls; 4,898,259 SNPs). The meta-analysis identified strong evidence of association ($P$-value≤5×10$^{−8}$) in 20 variants located at the $\textit{CFH}$ gene. SNP rs193053835 showed the most significant protective effect (Odds Ratio (OR)=0.62, 95% confidence interval (C.I.)=0.52–0.73; $P$-value=9.62×10$^{−9}$). Five other variants had been previously reported to be associated with susceptibility to MD, including the missense SNP rs1065489 (OR=0.64, 95% C.I.)=0.55–0.76, $\textit{P-value}$=3.25×10$^{−8}$). Theoretical predictions point to a functional effect of rs1065489, which may be directly responsible for protection against MD. Our study confirms the association of $\textit{CFH}$ with susceptibility to MD and strengthens the importance of this link in understanding pathogenesis of the disease.This study received support from the Instituto de Salud Carlos III (Proyecto de Investigación en Salud, Acción Estratégica en Salud: proyecto GePEM PI16/01478) (A.S.); Instituto Carlos III (Intensificación de la actividad investigadora) (A.V.); Consellería de Sanidade, Xunta de Galicia (RHI07/2-intensificación actividad investigadora, PS09749 and 10PXIB918184PR), Instituto de Salud Carlos III (Intensificación de la actividad investigadora 2007–2012, PI16/01569), Convenio de colaboración de investigación (Wyeth España-Fundación IDICHUS 2007–2011), Convenio de colaboración de investigación (Novartis España-Fundación IDICHUS 2010–2011), Fondo de Investigación Sanitaria (FIS; PI070069/PI1000540) del plan nacional de I+ D+ I and ‘fondos FEDER’ (F.M.T.). More information at: www. esigem.org. The UK cohort was established with support of the Meningitis Research Foundation (UK), who provide ongoing support, and the European Society for Paediatric Infectious Diseases supported the establishment of the international collaboration. This study makes use of data generated by the Wellcome Trust Case-Control Consortium 2. A full list of the investigators who contributed to the generation of the data is available from www. wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 085475. The research leading to these results has received funding from the European Union’s Seventh Framework Programme under EC-GA No. 279185 (EUCLIDS)