130 research outputs found

    Having a word with yourself:neural correlates of self-criticism and self-reassurance

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    Self-criticism is strongly correlated with a range of psychopathologies, such as depression, eating disorders and anxiety. In contrast, self-reassurance is inversely associated with such psychopathologies. Despite the importance of self-judgements and evaluations, little is known about the neurophysiology of these internal processes. The current study therefore used a novel fMRI task to investigate the neuronal correlates of self-criticism and self-reassurance. Participants were presented statements describing two types of scenario, with the instruction to either imagine being self-critical or self-reassuring in that situation. One scenario type focused on a personal setback, mistake or failure, which would elicit negative emotions, whilst the second was of a matched neutral event. Self-criticism was associated with activity in lateral prefrontal cortex (PFC) regions and dorsal anterior cingulate (dAC), therefore linking self-critical thinking to error processing and resolution, and also behavioural inhibition. Self-reassurance was associated with left temporal pole and insula activation, suggesting that efforts to be self-reassuring engage similar regions to expressing compassion and empathy towards others. Additionally, we found a dorsal/ventral PFC divide between an individual's tendency to be self-critical or self-reassuring. Using multiple regression analyses, dorsolateral PFC activity was positively correlated with high levels of self-criticism (assessed via self-report measure), suggesting greater error processing and behavioural inhibition in such individuals. Ventrolateral PFC activity was positively correlated with high self-reassurance. Our findings may have implications for the neural basis of a range of mood disorders that are characterised by a preoccupation with personal mistakes and failures, and a self-critical response to such events

    Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

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    Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council

    Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 study

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    Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside high-income countries, and alarmingly, the age-standardized rate of CVD has begun to rise in some locations where it was previously declining in high-income countries. There is an urgent need to focus on implementing existing cost-effective policies and interventions if the world is to meet the targets for Sustainable Development Goal 3 and achieve a 30% reduction in premature mortality due to noncommunicable diseases

    2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS guideline for the diagnosis and management of patients with stable ischemic heart disease

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    The recommendations listed in this document are, whenever possible, evidence based. An extensive evidence review was conducted as the document was compiled through December 2008. Repeated literature searches were performed by the guideline development staff and writing committee members as new issues were considered. New clinical trials published in peer-reviewed journals and articles through December 2011 were also reviewed and incorporated when relevant. Furthermore, because of the extended development time period for this guideline, peer review comments indicated that the sections focused on imaging technologies required additional updating, which occurred during 2011. Therefore, the evidence review for the imaging sections includes published literature through December 2011

    Computational Analysis Predicts Correlations among Amino Acids in SARS-CoV-2 Proteomes

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    Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious global challenge requiring urgent and permanent therapeutic solutions. These solutions can only be engineered if the patterns and rate of mutations of the virus can be elucidated. Predicting mutations and the structure of proteins based on these mutations have become necessary for early drug and vaccine design purposes in anticipation of future viral mutations. The amino acid composition (AAC) of proteomes and individual viral proteins provide avenues for exploitation since AACs have been previously used to predict structure, shape and evolutionary rates. Herein, the frequency of amino acid residues found in 1637 complete proteomes belonging to 11 SARS-CoV-2 variants/lineages were analyzed. Leucine is the most abundant amino acid residue in the SARS-CoV-2 with an average AAC of 9.658% while tryptophan had the least abundance of 1.11%. The AAC and ranking of lysine and glycine varied in the proteome. For some variants, glycine had higher frequency and AAC than lysine and vice versa in other variants. Tryptophan was also observed to be the most intolerant to mutation in the various proteomes for the variants used. A correlogram revealed a very strong correlation of 0.999992 between B.1.525 (Eta) and B.1.526 (Iota) variants. Furthermore, isoleucine and threonine were observed to have a very strong negative correlation of −0.912, while cysteine and isoleucine had a very strong positive correlation of 0.835 at p p < 0.05. Thus, AACs of SARS-CoV-2 variants can be predicted using probability and z-scores. AACs may be beneficial in classifying viral strains, predicting viral disease types, members of protein families, protein interactions and for diagnostic purposes. They may also be used as a feature along with other crucial factors in machine-learning based algorithms to predict viral mutations. These mutation-predicting algorithms may help in developing effective therapeutics and vaccines for SARS-CoV-2

    A Molecular Modeling Approach to Identify Potential Antileishmanial Compounds Against the Cell Division Cycle (cdc)-2-Related Kinase 12 (CRK12) Receptor of Leishmania donovani

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    The huge burden of leishmaniasis caused by the trypanosomatid protozoan parasite Leishmania is well known. This illness was included in the list of neglected tropical diseases targeted for elimination by the World Health Organization. However, the increasing evidence of resistance to existing antimonial drugs has made the eradication of the disease difficult to achieve, thus warranting the search for new drug targets. We report here studies that used computational methods to identify inhibitors of receptors from natural products. The cell division cycle-2-related kinase 12 (CRK12) receptor is a plausible drug target against Leishmania donovani. This study modelled the 3D molecular structure of the L. donovani CRK12 (LdCRK12) and screened for small molecules with potential inhibitory activity from African flora. An integrated library of 7722 African natural product-derived compounds and known inhibitors were screened against the LdCRK12 using AutoDock Vina after performing energy minimization with GROMACS 2018. Four natural products, namely sesamin (NANPDB1649), methyl ellagic acid (NANPDB1406), stylopine (NANPDB2581), and sennecicannabine (NANPDB6446) were found to be potential LdCRK12 inhibitory molecules. The molecular docking studies revealed two compounds NANPDB1406 and NANPDB2581 with binding affinities of −9.5 and −9.2 kcal/mol, respectively, against LdCRK12 which were higher than those of the known inhibitors and drugs, including GSK3186899, amphotericin B, miltefosine, and paromomycin. All the four compounds were predicted to have inhibitory constant (Ki) values ranging from 0.108 to 0.587 μM. NANPDB2581, NANPDB1649 and NANPDB1406 were also predicted as antileishmanial with Pa and Pi values of 0.415 and 0.043, 0.391 and 0.052, and 0.351 and 0.071, respectively. Molecular dynamics simulations coupled with molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) computations reinforced their good binding mechanisms. Most compounds were observed to bind in the ATP binding pocket of the kinase domain. Lys488 was predicted as a key residue critical for ligand binding in the ATP binding pocket of the LdCRK12. The molecules were pharmacologically profiled as druglike with inconsequential toxicity. The identified molecules have scaffolds that could form the backbone for fragment-based drug design of novel leishmanicides but warrant further studies to evaluate their therapeutic potential

    Structure-Based Discovery of Potential HPV E6 and EBNA1 Inhibitors: Implications for Cervical Cancer Treatment

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    Cervical cancer is the fourth most diagnosed cancer and the fourth leading cause of cancer death in women globally. Its onset and progression have been attributed to high-risk human papillomavirus (HPV) types, especially 16 and 18, while the Epstein–Barr virus (EBV) is believed to also significantly contribute to cervical cancer growth. The E6 protein associated with high-risk HPV strains, such as HPV16 and HPV18, is known for its role in promoting cervical cancer and other anogenital cancers. E6 proteins contribute to the malignant transformation of infected cells by targeting and degrading tumor suppressor proteins, especially p53. On the other hand, EBV nuclear antigen 1 (EBNA1) plays a crucial role in the maintenance and replication of the EBV genome in infected cells. EBNA1 is believed to increase HPV E6 and E7 levels, as well as c-MYC, and BIRC5 cellular genes in the HeLa cell line, implying that HPV/EBV co-infection accelerates cervical cancer onset and growth. Thus, the E6 and EBNA1 antigens of HPV and EBV, respectively, are attractive targets for cervical cancer immunotherapy. This study, therefore, virtually screened for potential drug candidates with good binding affinity to all three oncoviral proteins, HPV16 E6, HPV18 E6, and EBNA1. The compounds were further subjected to ADMET profiling, biological activity predictions, molecular dynamics (MD) simulations, and molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) calculations. A total of six compounds comprising ZINC000013380012, ZINC000070454124, ZINC000014588133, ZINC000085568136, ZINC000095909247, and ZINC000085597263 demonstrated very strong affinity (≤−60 kJ/mol) to the three oncoviral proteins (EBNA1, HPV16 E6, and HPV18 E6) after being subjected to docking, MD, and MM/PBSA. These compounds demonstrated relatively stronger binding than the controls used, inhibitors of EBNA1 (VK-1727) and HPV E6 (baicalein and gossypetin). Biological activity predictions also corroborated their antineoplastic, p53-enhancing, Pin1 inhibitory, and JAK2 inhibitory activities. Further experimental testing is required to validate the ability of the shortlisted compounds to silence the insidious effects of HPV E6 and EBNA1 proteins in cervical cancers
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