The microscopic features of heterogeneous ice nucleation may affect the macroscopic morphology of atmospheric ice crystals

It is surprisingly difficult to freeze water. Almost all ice that forms under “mild” conditions (temperatures > −40 °C) requires the presence of a nucleating agent – a solid particle that facilitates the freezing process – such as clay mineral dust, soot or bacteria. In a computer simulation, the presence of such ice nucleating agents does not necessarily alleviate the difficulties associated with forming ice on accessible timescales. Nevertheless, in this work we present results from molecular dynamics simulations in which we systematically compare homogeneous and heterogeneous ice nucleation, using the atmospherically important clay mineral kaolinite as our model ice nucleating agent. From our simulations, we do indeed find that kaolinite is an excellent ice nucleating agent but that contrary to conventional thought, non-basal faces of ice can nucleate at the basal face of kaolinite. We see that in the liquid phase, the kaolinite surface has a drastic effect on the density profile of water, with water forming a dense, tightly bound first contact layer. Monitoring the time evolution of the water density reveals that changes away from the interface may play an important role in the nucleation mechanism. The findings from this work suggest that heterogeneous ice nucleating agents may not only enhance the ice nucleation rate, but also alter the macroscopic structure of the ice crystals that form

Early start and stop of biologics: has the time come?

Despite considerable advances in the management of rheumatoid arthritis, results are still not satisfactory for all patients. The treatment goal in rheumatoid arthritis is remission, and there currently are numerous conventional and biological medications available to reach this aim. There are also different treatment strategies but with only limited comparative evidence about their efficacies. More patients now achieve remission while on treatment, but it remains elusive in the majority of patients. Treatment-free remission, the ultimate goal of therapy, is only achieved in very few patients; even when this happens, it is most likely due to the natural course of the disease rather than to any specific therapies. Modern treatment is based on the initiation of aggressive therapy as soon as the diagnosis is established, and on modifying or intensifying therapy guided by frequent assessment of disease activity. In this commentary we will discuss the current treatment paradigm as well as the possibility of an induction-maintenance regimen with biological disease-modifying antirheumatic drugs in early rheumatoid arthriti

IPSS-independent prognostic value of plasma CXCL10, IL-7 and IL-6 levels in myelodysplastic syndromes

Recent studies suggest a powerful prognostic value for plasma cytokine levels in primary myelofibrosis (interleukin (IL)-2R, IL-8, IL-12, IL-15 and C–X–C motif chemokine 10 (CXCL10)) and large-cell lymphoma (IL-2R, IL-8, IL-10, IL-12, CXCL9 and CXCL10). To examine the possibility of a similar phenomenon in myelodysplastic syndromes (MDS), we used multiplex enzyme-linked immunosorbent assay to measure 30 plasma cytokines in 78 patients with primary MDS. Compared with normal controls (n=35), the levels of 19 cytokines were significantly altered. Multivariable analysis identified increased levels of CXCL10 (P<0.01), IL-7 (P=0.02) and IL-6 (P=0.07) as predictors of shortened survival; the survival association remained significant when the Cox model was adjusted for the International Prognostic Scoring System, age, transfusion-need or thrombocytopenia. MDS patients with normal plasma levels of CXCL10, IL-7 and IL-6 lived significantly longer (median survival 76 months) than those with elevated levels of at least one of the three cytokines (median survival 25 months) (P<0.01). Increased levels of IL-6 were associated with inferior leukemia-free survival, independent of other prognostic factors (P=0.01). Comparison of plasma cytokines between MDS (n=78) and primary myelofibrosis (n=127) revealed a significantly different pattern of abnormalities. These observations reinforce the concept of distinct and prognostically relevant plasma cytokine signatures in hematological malignancies

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Anticonvulsant effects of aerial parts of Passiflora incarnata extract in mice: involvement of benzodiazepine and opioid receptors

<p>Abstract</p> <p>Background</p> <p>Passion flower (<it>Passiflora incarnata</it>) is used in traditional medicine of Europe and South America to treat anxiety, insomnia and seizure. Recently, it has shown antianxiety and sedative effects in human.</p> <p>Methods</p> <p>In this study, anticonvulsant effects of hydro- alcoholic extract of Passiflora, Pasipay, were examined by using pentylentetrazole model (PTZ) on mice. Pasipay, diazepam, and normal saline were injected intraperitoneally at the doses 0.4–0.05 mg/kg, 0.5–1 mg/kg and 10 ml/kg respectively 30 minutes before PTZ (90 mg/kg, i.p). The time taken before the onset of clonic convulsions, the duration of colonic convulsions, and the percentage of seizure and mortality protection were recorded. For investigating the mechanism of Pasipay, flumazenil (2 mg/kg, i.p) and naloxone (5 mg/kg, i.p) were also injected 5 minutes before Pasipay.</p> <p>Results</p> <p>An ED₅₀value of Pasipay in the PTZ model was 0.23 mg/kg (%95 CL: 0.156, 0.342). Pasipay at the dose of 0.4 mg/kg prolonged the onset time of seizure and decreased the duration of seizures compared to saline group (p < 0.001). At the dose of 0.4 mg/kg, seizure and mortality protection percent were 100%. Flumazenil and naloxone could suppress anticonvulsant effects of Pasipay.</p> <p>Conclusion</p> <p>It seems that Pasipay could be useful for treatment absence seizure and these effects may be related to effect of it on GABAergic and opioid systems. More studies are needed in order to investigate its exact mechanism.</p

Development of a clinical decision model for thyroid nodules

<p>Abstract</p> <p>Background</p> <p>Thyroid nodules represent a common problem brought to medical attention. Four to seven percent of the United States adult population (10–18 million people) has a palpable thyroid nodule, however the majority (>95%) of thyroid nodules are benign. While, fine needle aspiration remains the most cost effective and accurate diagnostic tool for thyroid nodules in current practice, over 20% of patients undergoing FNA of a thyroid nodule have indeterminate cytology (follicular neoplasm) with associated malignancy risk prevalence of 20–30%. These patients require thyroid lobectomy/isthmusectomy purely for the purpose of attaining a definitive diagnosis. Given that the majority (70–80%) of these patients have benign surgical pathology, thyroidectomy in these patients is conducted principally with diagnostic intent. Clinical models predictive of malignancy risk are needed to support treatment decisions in patients with thyroid nodules in order to reduce morbidity associated with unnecessary diagnostic surgery.</p> <p>Methods</p> <p>Data were analyzed from a completed prospective cohort trial conducted over a 4-year period involving 216 patients with thyroid nodules undergoing ultrasound (US), electrical impedance scanning (EIS) and fine needle aspiration cytology (FNA) prior to thyroidectomy. A Bayesian model was designed to predict malignancy in thyroid nodules based on multivariate dependence relationships between independent covariates. Ten-fold cross-validation was performed to estimate classifier error wherein the data set was randomized into ten separate and unique train and test sets consisting of a training set (90% of records) and a test set (10% of records). A receiver-operating-characteristics (ROC) curve of these predictions and area under the curve (AUC) were calculated to determine model robustness for predicting malignancy in thyroid nodules.</p> <p>Results</p> <p>Thyroid nodule size, FNA cytology, US and EIS characteristics were highly predictive of malignancy. Cross validation of the model created with Bayesian Network Analysis effectively predicted malignancy [AUC = 0.88 (95%CI: 0.82–0.94)] in thyroid nodules. The positive and negative predictive values of the model are 83% (95%CI: 76%–91%) and 79% (95%CI: 72%–86%), respectively.</p> <p>Conclusion</p> <p>An integrated predictive decision model using Bayesian inference incorporating readily obtainable thyroid nodule measures is clinically relevant, as it effectively predicts malignancy in thyroid nodules. This model warrants further validation testing in prospective clinical trials.</p