RNAi in the regulation of mammalian viral infections

Although RNA interference (RNAi) is known to play an important part in defense against viruses of invertebrates, its contribution to mammalian anti-viral defense has been a matter of dispute. This is surprising because all components of the RNAi machinery necessary for robust RNAi-mediated restriction of viruses are conserved in mammals, and the introduction of synthetic small interfering RNAs (siRNAs) into cells efficiently silences the replication of viruses that contain siRNA complementary sequences in those cells. Here, I discuss the reasons for the dispute, and review the evidence that RNAi is a part of the physiological defense of mammalian cells against viral infections

Inflammatory Cytokine Expression Is Associated with Chikungunya Virus Resolution and Symptom Severity

The Chikungunya virus infection zones have now quickly spread from Africa to parts of Asia, North America and Europe. Originally thought to trigger a disease of only mild symptoms, recently Chikungunya virus caused large-scale fatalities and widespread economic loss that was linked to recent virus genetic mutation and evolution. Due to the paucity of information on Chikungunya immunological progression, we investigated the serum levels of 13 cytokines/chemokines during the acute phase of Chikungunya disease and 6- and 12-month post-infection follow-up from patients of the Italian outbreak. We found that CXCL9/MIG, CCL2/MCP-1, IL-6 and CXCL10/IP-10 were significantly raised in the acute phase compared to follow-up samples. Furthermore, IL-1β, TNF-α, Il-12, IL-10, IFN-γ and IL-5 had low initial acute phase levels that significantly increased at later time points. Analysis of symptom severity showed association with CXCL9/MIG, CXCL10/IP-10 and IgG levels. These data give insight into Chikungunya disease establishment and subsequent convalescence, which is imperative to the treatment and containment of this quickly evolving and frequently re-emerging disease

Systemic α-synuclein injection triggers selective neuronal pathology as seen in patients with Parkinson’s disease

Abstract: Parkinson’s disease (PD) is an α-synucleinopathy characterized by the progressive loss of specific neuronal populations. Here, we develop a novel approach to transvascularly deliver proteins of complex quaternary structures, including α-synuclein preformed fibrils (pff). We show that a single systemic administration of α-synuclein pff triggers pathological transformation of endogenous α-synuclein in non-transgenic rats, which leads to neurodegeneration in discrete brain regions. Specifically, pff-exposed animals displayed a progressive deterioration in gastrointestinal and olfactory functions, which corresponded with the presence of cellular pathology in the central and enteric nervous systems. The α-synuclein pathology generated was both time dependent and region specific. Interestingly, the most significant neuropathological changes were observed in those brain regions affected in the early stages of PD. Our data therefore demonstrate for the first time that a single, transvascular administration of α-synuclein pff can lead to selective regional neuropathology resembling the premotor stage of idiopathic PD. Furthermore, this novel delivery approach could also be used to deliver a range of other pathogenic, as well as therapeutic, protein cargos transvascularly to the brain

The TOP-SCOPE Survey of Planck Galactic Cold Clumps: Survey Overview and Results of an Exemplar Source, PGCC G26.53+0.17

This is the final version. Available from American Astronomical Society via the DOI in this record.The low dust temperatures (<14 K) of Planck Galactic cold clumps (PGCCs) make them ideal targets to probe the initial conditions and very early phase of star formation. "TOP-SCOPE" is a joint survey program targeting ∼2000 PGCCs in J = 1-0 transitions of CO isotopologues and ∼1000 PGCCs in 850 μm continuum emission. The objective of the "TOP-SCOPE" survey and the joint surveys (SMT 10 m, KVN 21 m, and NRO 45 m) is to statistically study the initial conditions occurring during star formation and the evolution of molecular clouds, across a wide range of environments. The observations, data analysis, and example science cases for these surveys are introduced with an exemplar source, PGCC G26.53+0.17 (G26), which is a filamentary infrared dark cloud (IRDC). The total mass, length, and mean line mass (M/L) of the G26 filament are ∼6200 M, ∼12 pc, and ∼500 Mpc-1, respectively. Ten massive clumps, including eight starless ones, are found along the filament. The most massive clump as a whole may still be in global collapse, while its denser part seems to be undergoing expansion owing to outflow feedback. The fragmentation in the G26 filament from cloud scale to clump scale is in agreement with gravitational fragmentation of an isothermal, nonmagnetized, and turbulent supported cylinder. A bimodal behavior in dust emissivity spectral index (β) distribution is found in G26, suggesting grain growth along the filament. The G26 filament may be formed owing to large-scale compression flows evidenced by the temperature and velocity gradients across its natal cloud.German Research FoundationJoint Research Fund in AstronomyTop Talents Program of Yunnan ProvinceAcademy of FinlandMinistry of Education, Science, and TechnologyNational Research Foundation of KoreaChinese Academy of SciencesMinistry of Science and Technology of TaiwanEuropean Research Counci

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Forecasting of Currency Exchange Rate Using Artificial Neural Network: A Case Study of Solomon Island Dollar

The use of neural network models for currency exchange rate forecasting has received much attention in recent time. In this paper, we propose an exchange rate forecasting model based on artificial neural network. We tested our model on forecasting the exchange rate of Solomon Islands Dollar against some major trading currencies of the country such as, Australian Dollar, Great Britain Pound, Japanese yen, and Euro. We compared the performance of our model with that of the single exponential smoothing model; the double exponential smoothing with trend model; and Holt-Winter multiplicative and additive seasonal and multiple linear regression model. The performance of the models was measured using the error function, root mean square error (RMSE). The empirical result reveals that the proposed model is more efficient and accurate in forecasting currency exchange rate in comparison to the regression and time series models