University of Lincoln

About: University of Lincoln is a education organization based out in Lincoln, Lincolnshire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 2341 authors who have published 7025 publications receiving 124797 citations.

Differences in facial expressions during positive anticipation and frustration in dogs awaiting a reward.

Abstract: Facial expressions are considered sensitive indicators of emotional states in humans and many animals. Identifying facial indicators of emotion is a major challenge and little systematic research has been done in non-primate species. In dogs, such research is important not only to address fundamental and applied scientific questions but also for practical reasons, since many problem behaviours are assumed to have an emotional basis, e.g. aggression based on frustration. Frustration responses can occur in superficially similar contexts as the emotional state of positive anticipation. For instance, the anticipated delivery of a food reward may induce the state of positive anticipation, but over time, if the food is not delivered, this will be replaced by frustration. We examined dogs’ facial expressions in contexts presumed to induce both positive anticipation and frustration, respectively, within a single controlled experimental setting. Using DogFACS, an anatomically-based method for coding facial expressions of dogs, we found that the “Ears adductor” action was more common in the positive condition and “Blink”, “Lips part”, “Jaw drop”, “Nose lick”, and “Ears flattener” were more common in the negative condition. This study demonstrates how differences in facial expression in emotionally ambiguous contexts may be used to help infer emotional states of different valence.

Abnormal T regulatory cells (Tregs: FOXP3+, CTLA-4+), myeloid-derived suppressor cells (MDSCs: monocytic, granulocytic) and polarised T helper cell profiles (Th1, Th2, Th17) in women with large and locally advanced breast cancers undergoing neoadjuvant chemotherapy (NAC) and surgery: failure of abolition of abnormal treg profile with treatment and correlation of treg levels with pathological response to NAC

Abstract: Host defences play a key role in tumour growth. Some of the benefits of chemotherapy may occur through modulation of these defences. The aim of this study was to define the status of regulatory cells in women with large and locally advanced breast cancers (LLABCs) undergoing neoadjuvant chemotherapy (NAC) and surgery. Bloods were collected from patients (n = 56) before, during and following NAC, and surgery. Controls (n = 10) were healthy, age-matched females donors (HFDs). Blood mononuclear cells (BMCs) were isolated and T regulatory cells (Tregs) (n = 31) determined. Absolute numbers (AbNs) of Tregs and myeloid-derived suppressor cells (MDSCs) were ascertained from whole blood (n = 25). Reverse transcriptase polymerase chain reaction analysis determined Treg mRNA (n = 16). In vitro production of Th1, Th2 and Th17 cytokines (n = 30), was documented. Patients were classified as clinical responders by magnetic resonance mammography after two cycles of NAC and as pathological responders using established criteria, following surgery. Patients with LLABCs had significantly increased circulating Tregs (≥ 6 fold AbN and percentage (%)) and MDSCs (≥ 1.5 fold AbN (p = 0.025)). Percentage of FOXP3+ Tregs in blood predicted the response of the LLABCs to subsequent NAC (p = 0.04). Post NAC blood Tregs (%) were significantly reduced in patients where tumours showed a good pathological response to NAC (p = 0.05). Blood MDSCs (granulocytic, monocytic) were significantly reduced in all patients, irrespective of the pathological tumour response to chemotherapy. NAC followed by surgery failed to restore blood Tregs to normal levels. MDSCs, however, were reduced to or below normal levels by NAC alone. Invitro Th1 profile (IL-1β, IL-2, INF-γ, TNF-α) was significantly reduced (p ≤ 0.009), whilst Th2 (IL-4, IL-5) was significantly enhanced (P ≤ 0.004). Th1 and Th2 (IL-5) were unaffected by NAC and surgery. IL-17A was significantly increased (p ≤ 0.023) but unaffected by chemotherapy and surgery. Women with LLABCs have abnormal blood regulatory cell levels (Tregs and MDSCs) and cytokine profiles (Th1, Th2, Th17). NAC followed by surgery failed to abolish the abnormal Treg and Th profiles. There was a significant correlation between the circulatory levels of Tregs and the pathological response of the breast cancers to NAC.

New ensemble machine learning method for classification and prediction on gene expression data.

Abstract: A reliable and precise classification of tumours is essential for successful treatment of cancer. Recent researches have confirmed the utility of ensemble machine learning algorithms for gene expression data analysis. In this paper, a new ensemble machine learning algorithm is proposed for classification and prediction on gene expression data. The algorithm is tested and compared with three popular adopted ensembles, i.e. bagging, boosting and arcing. The results show that the proposed algorithm greatly outperforms existing methods, achieving high accuracy over 12 gene expression datasets.

The interplay between stakeholders, resources and capabilities in climate change strategy: converting barriers into cooperation

Abstract: This article investigates how organizations deal with drivers and barriers to the adoption of low‐carbon operational (LCO) practices and, accordingly, we propose a framework for relationships with stakeholders to guide organizations in orchestrating stakeholders, resources and capabilities to meet the challenges and opportunities arising from climate change. Data was collected through interviews with experts working within companies participating in the Carbon Disclosure Program and the Brazilian GHG Protocol Program. Our findings show that the level of willingness of stakeholders influences how companies select mechanisms to deal with drivers and barriers to LCO practices. Our results, qualified by stakeholder relationships theory and the natural resource‐based view, introduce an analytical approach called ‘mechanisms of responses’ to understand how organizations deal with drivers and barriers in the context of climate change in order to guide companies to adopt LCO practices, strengthen co‐operation with stakeholders and develop the required organizational capabilities.