Targeted apoptosis in ovarian cancer cells through mitochondrial dysfunction in response to Sambucus nigra agglutinin

Ovarian carcinoma (OC) patients encounter the severe challenge of clinical management owing to lack of screening measures, chemoresistance and finally dearth of non-toxic therapeutics. Cancer cells deploy various defense strategies to sustain the tumor microenvironment, among which deregulated apoptosis remains a versatile promoter of cancer progression. Although recent research has focused on identifying agents capable of inducing apoptosis in cancer cells, yet molecules efficiently breaching their survival advantage are yet to be classified. Here we identify lectin, Sambucus nigra agglutinin (SNA) to exhibit selectivity towards identifying OC by virtue of its specific recognition of α-2, 6-linked sialic acids. Superficial binding of SNA to the OC cells confirm the hyper-sialylated status of the disease. Further, SNA activates the signaling pathways of AKT and ERK1/2, which eventually promotes de-phosphorylation of dynamin-related protein-1 (Drp-1). Upon its translocation to the mitochondrial fission loci Drp-1 mediates the central role of switch in the mitochondrial phenotype to attain fragmented morphology. We confirmed mitochondrial outer membrane permeabilization resulting in ROS generation and cytochrome-c release into the cytosol. SNA response resulted in an allied shift of the bioenergetics profile from Warburg phenotype to elevated mitochondrial oxidative phosphorylation, altogether highlighting the involvement of mitochondrial dysfunction in restraining cancer progression. Inability to replenish the SNA-induced energy crunch of the proliferating cancer cells on the event of perturbed respiratory outcome resulted in cell cycle arrest before G2/M phase. Our findings position SNA at a crucial juncture where it proves to be a promising candidate for impeding progression of OC. Altogether we unveil the novel aspect of identifying natural molecules harboring the inherent capability of targeting mitochondrial structural dynamics, to hold the future for developing non-toxic therapeutics for treating OC

Application of isothermal titration calorimetry in evaluation of protein–nanoparticle interactions

Nanoparticles (NPs) offer a number of advantages over small organic molecules for controlling protein behaviour inside the cell. Protein binding to the surface of NPs depends on their surface characteristics, composition and method of preparation (Mandal et al. in J Hazard Mater 248–249:238–245, 2013). It is important to understand the binding affinities, stoichiometries and thermodynamical parameters of NP–protein interactions in order to see which interaction will have toxic and hazardous consequences and thus to prevent it. On the other side, because proteins are on the brink of stability, they may experience interactions with some types of NPs that are strong enough to cause denaturation or significantly change their conformations with concomitant loss of their biological function. Structural changes in the protein may cause exposure of new antigenic sites, “cryptic” peptide epitopes, potentially triggering an immune response which can promote autoimmune disease (Treuel et al. in ACS Nano 8(1):503–513, 2014). Mechanistic details of protein structural changes at NP surface have still remained elusive. Understanding the formation and persistence of the protein corona is critical issue; however, there are no many analytical methods which could provide detailed information about the NP–protein interaction characteristics and about protein structural changes caused by interactions with nanoparticles. The article reviews recent studies in NP–protein interactions research and application of isothermal titration calorimetry (ITC) in this research. The study of protein structural changes upon adsorption on nanoparticle surface and application of ITC in these studies is emphasized. The data illustrate that ITC is a versatile tool for evaluation of interactions between NPs and proteins. When coupled with other analytical methods, it is important analytical tool for monitoring conformational changes in proteins

Digital IAPT: the effectiveness & cost-effectiveness of internet-delivered interventions for depression and anxiety disorders in the Improving Access to Psychological Therapies programme: study protocol for a randomised control trial

BACKGROUND: Depression and anxiety are common mental health disorders worldwide. The UK's Improving Access to Psychological Therapies (IAPT) programme is part of the National Health Service (NHS) designed to provide a stepped care approach to treating people with anxiety and depressive disorders. Cognitive Behavioural Therapy (CBT) is widely used, with computerised and internet-delivered cognitive behavioural therapy (cCBT and iCBT, respectively) being a suitable IAPT approved treatment alternative for step 2, low- intensity treatment. iCBT has accumulated a large empirical base for treating depression and anxiety disorders. However, the cost-effectiveness and impact of these interventions in the longer-term is not routinely assessed by IAPT services. The current study aims to evaluate the clinical and cost-effectiveness of internet-delivered interventions for symptoms of depression and anxiety disorders in IAPT. METHODS: The study is a parallel-groups, randomised controlled trial examining the effectiveness and cost-effectiveness of iCBT interventions for depression and anxiety disorders, against a waitlist control group. The iCBT treatments are of 8 weeks duration and will be supported by regular post-session feedback by Psychological Wellbeing Practitioners. Assessments will be conducted at baseline, during, and at the end of the 8-week treatment and at 3, 6, 9, and 12-month follow-up. A diagnostic interview will be employed at baseline and 3-month follow-up. Participants in the waitlist control group will complete measures at baseline and week 8, at which point they will receive access to the treatment. All adult users of the Berkshire NHS Trust IAPT Talking Therapies Step 2 services will be approached to participate and measured against set eligibility criteria. Primary outcome measures will assess anxiety and depressive symptoms using the GAD-7 and PHQ-9, respectively. Secondary outcome measures will allow for the evaluation of long-term outcomes, mediators and moderators of outcome, and cost-effectiveness of treatment. Analysis will be conducted on a per protocol and intention-to-treat basis. DISCUSSION: This study seeks to evaluate the immediate and longer-term impact, as well as the cost effectiveness of internet-delivered interventions for depression and anxiety. This study will contribute to the already established literature on internet-delivered interventions worldwide. The study has the potential to show how iCBT can enhance service provision, and the findings will likely be generalisable to other health services. TRIAL REGISTRATION: Current Controlled Trials ISRCTN ISRCTN91967124. DOI: https://doi.org/10.1186/ISRCTN91967124 . Web: http://www.isrctn.com/ISRCTN91967124 . Clinicaltrials.gov : NCT03188575. Trial registration date: June 8, 2017 (prospectively registered)

Category Theoretic Analysis of Hierarchical Protein Materials and Social Networks

Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a “concept web” or “semantic network” except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.Presidential Early Career Award for Scientists and Engineers (N000141010562)United States. Army Research Office. Multidisciplinary University Research Initiative (W911NF0910541)United States. Office of Naval Research (grant N000141010841)Massachusetts Institute of Technology. Dept. of MathematicsStudienstiftung des deutschen VolkesClark BarwickJacob Luri

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

BVT.2733, a Selective 11β-Hydroxysteroid Dehydrogenase Type 1 Inhibitor, Attenuates Obesity and Inflammation in Diet-Induced Obese Mice

BACKGROUND: Inhibition of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) is being pursued as a new therapeutic approach for the treatment of obesity and metabolic syndrome. Therefore, there is an urgent need to determine the effect of 11β-HSD1 inhibitor, which suppresses glucocorticoid action, on adipose tissue inflammation. The purpose of the present study was to examine the effect of BVT.2733, a selective 11β-HSD1 inhibitor, on expression of pro-inflammatory mediators and macrophage infiltration in adipose tissue in C57BL/6J mice. METHODOLOGY/PRINCIPAL FINDINGS: C57BL/6J mice were fed with a normal chow diet (NC) or high fat diet (HFD). HFD treated mice were then administrated with BVT.2733 (HFD+BVT) or vehicle (HFD) for four weeks. Mice receiving BVT.2733 treatment exhibited decreased body weight and enhanced glucose tolerance and insulin sensitivity compared to control mice. BVT.2733 also down-regulated the expression of inflammation-related genes including monocyte chemoattractant protein 1 (MCP-1), tumor necrosis factor alpha (TNF-α) and the number of infiltrated macrophages within the adipose tissue in vivo. Pharmacological inhibition of 11β-HSD1 and RNA interference against 11β-HSD1 reduced the mRNA levels of MCP-1 and interleukin-6 (IL-6) in cultured J774A.1 macrophages and 3T3-L1 preadipocyte in vitro. CONCLUSIONS/SIGNIFICANCE: These results suggest that BVT.2733 treatment could not only decrease body weight and improve metabolic homeostasis, but also suppress the inflammation of adipose tissue in diet-induced obese mice. 11β-HSD1 may be a very promising therapeutic target for obesity and associated disease

Is there an ideal way to initiate antiplatelet therapy with aspirin? A crossover study on healthy volunteers evaluating different dosing schemes with whole blood aggregometry

<p>Abstract</p> <p>Background</p> <p>Guidelines recommend an early initiation of aspirin treatment in patients with acute cerebral ischemia. Comparative studies on the best starting dose for initiating aspirin therapy to achieve a rapid antiplatelet effect do not exist. This study evaluated the platelet inhibitory effect in healthy volunteers by using three different aspirin loading doses to gain a model for initiating antiplatelet treatment in acute strokes patients.</p> <p>Methods</p> <p>Using whole blood aggregometry, this study with a prospective, uncontrolled, open, crossover design examined 12 healthy volunteers treated with three different aspirin loading doses: intravenous 500 mg aspirin, oral 500 mg aspirin, and a course of 200 mg aspirin on two subsequent days followed by a five-day course of 100 mg aspirin. Aspirin low response was defined as change of impedance exceeding 0 Ω after stimulation with arachidonic acid.</p> <p>Results</p> <p>Sufficient antiplatelet effectiveness was gained within 30 seconds when intravenous 500 mg aspirin was used. The mean time until antiplatelet effect was 74 minutes for 500 mg aspirin taken orally and 662 minutes (11.2 hours) for the dose scheme with 200 mg aspirin with a high inter- and intraindividual variability in those two regimes. Platelet aggregation returned to the baseline range during the wash-out phase within 4 days.</p> <p>Conclusion</p> <p>Our study reveals that the antiplatelet effect differs significantly between the three different aspirin starting dosages with a high inter- and intraindividual variability of antiplatelet response in our healthy volunteers. To ensure an early platelet inhibitory effect in acute stroke patients, it could be advantageous to initiate the therapy with an intravenous loading dose of 500 mg aspirin. However, clinical outcome studies must still define the best way to initiate antiplatelet treatment with aspirin.</p

The Information Coded in the Yeast Response Elements Accounts for Most of the Topological Properties of Its Transcriptional Regulation Network

The regulation of gene expression in a cell relies to a major extent on transcription factors, proteins which recognize and bind the DNA at specific binding sites (response elements) within promoter regions associated with each gene. We present an information theoretic approach to modeling transcriptional regulatory networks, in terms of a simple “sequence-matching” rule and the statistics of the occurrence of binding sequences of given specificity in random promoter regions. The crucial biological input is the distribution of the amount of information coded in these cognate response elements and the length distribution of the promoter regions. We provide an analysis of the transcriptional regulatory network of yeast Saccharomyces cerevisiae, which we extract from the available databases, with respect to the degree distributions, clustering coefficient, degree correlations, rich-club coefficient and the k-core structure. We find that these topological features are in remarkable agreement with those predicted by our model, on the basis of the amount of information coded in the interaction between the transcription factors and response elements