The evaluation of the delayed swollen breast in patients with a history of breast implants

Breast implants, whether placed for reconstructive or cosmetic purposes, are rarely lifetime devices. Rupture, resulting from compromised implant shell integrity, and capsular contracture caused by constriction of the specialized scar tissue that normally forms around breast implants, have long been recognized, and remain the leading causes of implant failure. It is apparent, however, that women with breast implants may also experience delayed breast swelling due to a range of etiologic factors. While a majority of delayed seromas associated with breast implants have a benign etiology, this presentation cannot be ignored without an adequate workup as malignancies such as breast implant associated anaplastic large cell lymphoma (BIA-ALCL), breast implant associated diffuse large B-cell lymphoma (BIA-DLBCL), and breast implant associated squamous cell carcinoma (BIA-SCC) can have a similar clinical presentation. Since these malignancies occur with sufficient frequency, and with sometimes lethal consequences, their existence must be recognized, and an appropriate diagnostic approach implemented. A multidisciplinary team that involves a plastic surgeon, radiologist, pathologist, and, as required, surgical and medical oncologists can expedite judicious care. Herein we review and further characterize conditions that can lead to delayed swelling around breast implants

Arbuscular mycorrhizal colonisation of roots of grass species differing in invasiveness

Recent research indicates that the soil microbial community, particularly arbuscular mycorrhizal fungi (AMF), can influence plant invasion in several ways. We tested if 1) invasive species are colonised by AMF to a lower degree than resident native species, and 2) AMF colonisation of native plants is lower in a community inhabited by an invasive species than in an uninvaded resident community. The two tests were run in semiarid temperate grasslands on grass (Poaceae) species, and the frequency and intensity of mycorrhizal colonisation, and the proportion of arbuscules and vesicles in plant roots have been measured. In the first test, grasses representing three classes of invasiveness were included: invasive species, resident species becoming abundant upon disturbance, and non-invasive native species. Each class contained one C3 and one C4 species. The AMF colonisation of the invasive Calamagrostis epigejos and Cynodon dactylon was consistently lower than that of the non-invasive native Chrysopogon gryllus and Bromus inermis, and contained fewer arbuscules than the post-disturbance dominant resident grasses Bothriochloa ischaemum and Brachypodium pinnatum. The C3 and C4 grasses behaved alike despite their displaced phenologies in these habitats. The second test compared AMF colonisation for sand grassland dominant grasses Festuca vaginata and Stipa borysthenica in stands invaded by either C. epigejos or C. dactylon, and in the uninvaded natural community. Resident grasses showed lower degree of AMF colonisation in the invaded stand compared to the uninvaded natural community with F. vaginata responding so to both invaders, while S. borysthenica responding to C. dactylon only. These results indicate that invasive grasses supposedly less reliant on AMF symbionts have the capacity of altering the soil mycorrhizal community in such a way that resident native species can establish a considerably reduced extent of the beneficial AMF associations, hence their growth, reproduction and ultimately abundance may decline. Accumulating evidence suggests that such indirect influences of invasive alien plants on resident native species mediated by AMF or other members of the soil biota is probably more the rule than the exception

Comprehensive review:Computational modelling of Schizophrenia

Computational modelling has been used to address: (1) the variety of symptoms observed in schizophrenia using abstract models of behavior (e.g. Bayesian models - top-down descriptive models of psychopathology); (2) the causes of these symptoms using biologically realistic models involving abnormal neuromodulation and/or receptor imbalance (e.g. connectionist and neural networks - bottom-up realistic models of neural processes). These different levels of analysis have been used to answer different questions (i.e. understanding behavioral vs. neurobiological anomalies) about the nature of the disorder. As such, these computational studies have mostly supported diverging hypotheses of schizophrenia's pathophysiology, resulting in a literature that is not always expanding coherently. Some of these hypotheses are however ripe for revision using novel empirical evidence.Here we present a review that first synthesizes the literature of computational modelling for schizophrenia and psychotic symptoms into categories supporting the dopamine, glutamate, GABA, dysconnection and Bayesian inference hypotheses respectively. Secondly, we compare model predictions against the accumulated empirical evidence and finally we identify specific hypotheses that have been left relatively under-investigated

Remote detection of invasive alien species

The spread of invasive alien species (IAS) is recognized as the most severe threat to biodiversity outside of climate change and anthropogenic habitat destruction. IAS negatively impact ecosystems, local economies, and residents. They are especially problematic because once established, they give rise to positive feedbacks, increasing the likelihood of further invasions and spread. The integration of remote sensing (RS) to the study of invasion, in addition to contributing to our understanding of invasion processes and impacts to biodiversity, has enabled managers to monitor invasions and predict the spread of IAS, thus supporting biodiversity conservation and management action. This chapter focuses on RS capabilities to detect and monitor invasive plant species across terrestrial, riparian, aquatic, and human-modified ecosystems. All of these environments have unique species assemblages and their own optimal methodology for effective detection and mapping, which we discuss in detail

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

Impact of inducible nitric oxide synthase (inos) expression on triple negative breast cancer outcome and activation of egfr and erk signaling pathways

Inflammation is implicated in triple negative breast cancer (TNBC) progression. TNBC carries a worse prognosis than other breast cancer subtypes, and with the clinical and molecular heterogeneity of TNBC, there is a lack of effective therapeutic targets available. Identification of molecular targets for TNBC subtypes is crucial towards personalized patient stratification. Inducible nitric oxide synthase (iNOS) has been shown to induce p53 mutation accumulation, basal-like gene signature enrichment and transactivation of the epidermal growth factor receptor (EGFR) via s-nitrosylation. Herein we report that iNOS is associated with disease recurrence, distant metastasis and decreased breast cancer specific survival in 209 cases of TNBC. Employing TNBC cell lines representing normal basal breast, and basal-like 1 and basal-like 2 tumors, we demonstrate that nitric oxide (NO) induces EGFR-dependent ERK phosphorylation in basal-like TNBC cell lines. Moreover NO mediated cell migration and cell invasion was found to be dependent on EGFR and ERK activation particularly in basal-like 2 TBNC cells. This occurred in conjunction with NF-.B activation and increased secretion of pro-inflammatory cytokines IL-8, IL-1 alpha and TNF-a. This provides substantial evidence for EGFR as a therapeutic target to be taken into consideration in the treatment of a specific subset of basal-like TNBC overexpressing iNOS