Likelihood of Extreme Early Flight of Myzus persicae (Hemiptera: Aphididae) Across the UK.

Myzus persicae (Sulzer, Hemiptera: Aphididae) is a major global crop pest; it is the primary aphid vector for many damaging viruses and has developed resistance to most insecticides. In temperate regions, the risk of widespread crop infection and yield loss is heightened following warm winters, which encourage rapid population growth and early flight. Estimates of the frequency and magnitude of warm winters are, therefore, helpful for understanding and managing this risk. However, it is difficult to quantify the statistical distribution of climate events, particularly extremes, because climate observations represent just a small sample of the possible climate variations in a region. The purpose of this study was to establish a large-scale relationship between temperature and M. persicae observations across the UK and apply this to a very large ensemble of climate model simulations, which better sample the variability in climate, to quantify the current likelihood of extreme early M. persicae flight across the UK. The timing of M. persicae flight was shown to be significantly related to January-February mean temperature, where a 1°C warmer/cooler temperature relates to about 12 d earlier/later flight. Climate model simulations predict 40% likelihood of experiencing a year with unprecedented early M. persicae flight during the next decade in the UK. Results from this method can help crop managers assess the long-term viability of crops and management practices across the UK and provide early warning information for targeting pest surveillance activities on the locations and timings at highest risk of early M. persicae flight.

How uncertain are climate model projections of water availability indicators across the Middle East?

The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961-1990 and 2021-2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between -5 and -25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model ProjectionsAtmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.

Effect of open-label lamotrigine as monotherapy and adjunctive therapy on the self-assessed cognitive function scores of patients with bipolar I disorder.

Cognitive deficits in patients with bipolar disorder are likely to impair occupational and social functioning. In a post hoc analysis of data from a prospective, open-label study of lamotrigine in 1175 patients 13 years or older with bipolar I disorder, changes in the self-rated cognitive function scores of patients receiving lamotrigine as monotherapy or as adjunctive therapy were evaluated. Lamotrigine was given for 12 weeks, with a target dosage of 200 mg/d. Cognitive function was assessed at baseline and week 12 with the self-rated Medical Outcomes Study Cognitive (MOS-Cog) Scale. Mean MOS-Cog scores improved significantly from baseline in the overall group (+8.4 +/- 22.55 points, P < 0.0001) and in subgroups of patients receiving and not receiving concomitant valproate, antidepressants, or antipsychotics. Patients receiving lamotrigine and not receiving concomitant antipsychotics, however, exhibited a small but significantly greater degree of improvement than patients who were receiving concomitant antipsychotics (adjusted mean difference = 4.05; 95% confidence interval, 1.30-6.81; P = 0.0039). Statistically significant improvement was seen in patient subgroups with a depressive (mean change from baseline, 8.8 +/- 21.97; P < 0.0001) or a manic (mean change from baseline, 7.5 +/- 22.62; P = 0.0007) index episode. Improvements in MOS-Cog scores significantly correlated with improvement in both depressive (correlation coefficient, -0.339; P < 0.0001) and manic (correlation coefficient, -0.151; P < 0.0001) symptoms. Overall, self-rated cognitive function scores improved during open-label lamotrigine therapy in patients with bipolar I disorder whether or not they were receiving concomitant valproate, antidepressants, or antipsychotics. Additional research is needed to explore the clinical relevance of these findings.

Is your depressed patient bipolar?

Accurate diagnosis of mood disorders is critical for treatment to be effective. Distinguishing between major depression and bipolar disorders, especially the depressed phase of a bipolar disorder, is essential, because they differ substantially in their genetics, clinical course, outcomes, prognosis, and treatment. In current practice, bipolar disorders, especially bipolar II disorder, are underdiagnosed. Misdiagnosing bipolar disorders deprives patients of timely and potentially lifesaving treatment, particularly considering the development of newer and possibly more effective medications for both depressive features and the maintenance treatment (prevention of recurrence/relapse). This article focuses specifically on how to recognize the identifying features suggestive of a bipolar disorder in patients who present with depressive symptoms or who have previously been diagnosed with major depression or dysthymia. This task is not especially time-consuming, and the interested primary care or family physician can easily perform this assessment. Tools to assist the physician in daily practice with the evaluation and recognition of bipolar disorders and bipolar depression are presented and discussed.