Dengue: a continuing global threat.

Dengue fever and dengue haemorrhagic fever are important arthropod-borne viral diseases. Each year, there are ∼50 million dengue infections and ∼500,000 individuals are hospitalized with dengue haemorrhagic fever, mainly in Southeast Asia, the Pacific and the Americas. Illness is produced by any of the four dengue virus serotypes. A global strategy aimed at increasing the capacity for surveillance and outbreak response, changing behaviours and reducing the disease burden using integrated vector management in conjunction with early and accurate diagnosis has been advocated. Antiviral drugs and vaccines that are currently under development could also make an important contribution to dengue control in the future

Shading by Napier Grass Reduces Malaria Vector Larvae in Natural Habitats in Western Kenya Highlands

Increased human population in the Western Kenya highlands has led to reclamation of natural swamps resulting in the creation of habitats suitable for the breeding of Anopheles gambiae, the major malaria vector in the region. Here we report on a study to restore the reclaimed swamp and reverse its suitability as a habitat for malaria vectors. Napier grass-shaded and non-shaded water channels in reclaimed sites in Western Kenya highlands were studied for the presence and density of mosquito larvae, mosquito species composition, and daily variation in water temperature. Shading was associated with 75.5% and 88.4% (P < 0.0001) reduction in anopheline larvae densities and 78.1% and 88% (P < 0.0001) reduction in Anopheles gambiae sensu lato (s.l.) densities in two sites, respectively. Shading was associated with a 5.7°C, 5.0°C, and 4.7°C, and 1.6°C, 3.9°C, and 2.8°C (for maximum, minimum, and average temperatures, respectively) reduction (P < 0.0001) in water temperatures in the two locations, respectively. An. gambiae s.l. was the dominant species, constituting 83.2% and 73.1%, and 44.5% and 42.3%, of anophelines in non-shaded and shaded channels, respectively, in the two sites, respectively. An. gambiae sensu stricto (s.s.) constituted the majority (97.4%) of An. gambiae s.l., while the rest (2.6%) comprised of Anopheles arabiensis. Minimum water temperature decreased with increasing grass height (P = 0.0039 and P = 0.0415 for Lunyerere and Emutete sites, respectively). The results demonstrate how simple environmental strategies can have a strong impact on vector densities

Continuous low- to moderate-intensity exercise training is as effective as moderate- to high-intensity exercise training at lowering blood HbA1c in obese type 2 diabetes patients

Aims/hypothesis: Exercise represents an effective interventional strategy to improve glycaemic control in type 2 diabetes patients. However, the impact of exercise intensity on the benefits of exercise training remains to be established. In the present study, we compared the clinical benefits of 6 months of continuous low- to moderate-intensity exercise training with those of continuous moderate- to high-intensity exercise training, matched for energy expenditure, in obese type 2 diabetes patients. Methods: Fifty male obese type 2 diabetes patients (age 59∈±∈8 years, BMI 32∈± ∈4 kg/m2) participated in a 6 month continuous endurance-type exercise training programme. All participants performed three supervised exercise sessions per week, either 55 min at 50% of whole body peak oxygen uptake left(VO2peak) (low to moderate intensity) or 40 min at 75% of VO2peak (moderate to high intensity). Oral glucose tolerance, blood glycated haemoglobin, lipid profile, body composition, maximal workload capacity, whole body and skeletal muscle oxidative capacity and skeletal muscle fibre type composition were assessed before and after 2 and 6 months of intervention. Results: The entire 6 month intervention programme was completed by 37 participants. Continuous endurance-type exercise training reduced blood glycated haemoglobin levels, LDL-cholesterol concentrations, body weight and leg fat mass, and increased VO2peak, lean muscle mass and skeletal muscle cytochrome c oxidase and citrate synthase activity (p∈<∈0. 05). No differences were observed between the groups training at low to moderate or moderate to high intensity. Conclusions/interpretation: When matched for energy cost, prolonged continuous low- to moderate-intensity endurance-type exercise training is equally effective as continuous moderate- to high-intensity training in lowering blood glycated haemoglobin and increasing whole body and skeletal muscle oxidative capacity in obese type 2 diabetes patients. © 2009 Springer-Verlag

Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

Pure seminoma: A review and update

Pure seminoma is a rare pathology of the young adult, often discovered in the early stages. Its prognosis is generally excellent and many therapeutic options are available, especially in stage I tumors. High cure rates can be achieved in several ways: standard treatment with radiotherapy is challenged by surveillance and chemotherapy. Toxicity issues and the patients' preferences should be considered when management decisions are made. This paper describes firstly the management of primary seminoma and its nodal involvement and, secondly, the various therapeutic options according to stage

Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study.

BACKGROUND: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. METHODS: We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). FINDINGS: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. INTERPRETATION: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London

Key mechanisms governing resolution of lung inflammation

Innate immunity normally provides excellent defence against invading microorganisms. Acute inflammation is a form of innate immune defence and represents one of the primary responses to injury, infection and irritation, largely mediated by granulocyte effector cells such as neutrophils and eosinophils. Failure to remove an inflammatory stimulus (often resulting in failed resolution of inflammation) can lead to chronic inflammation resulting in tissue injury caused by high numbers of infiltrating activated granulocytes. Successful resolution of inflammation is dependent upon the removal of these cells. Under normal physiological conditions, apoptosis (programmed cell death) precedes phagocytic recognition and clearance of these cells by, for example, macrophages, dendritic and epithelial cells (a process known as efferocytosis). Inflammation contributes to immune defence within the respiratory mucosa (responsible for gas exchange) because lung epithelia are continuously exposed to a multiplicity of airborne pathogens, allergens and foreign particles. Failure to resolve inflammation within the respiratory mucosa is a major contributor of numerous lung diseases. This review will summarise the major mechanisms regulating lung inflammation, including key cellular interplays such as apoptotic cell clearance by alveolar macrophages and macrophage/neutrophil/epithelial cell interactions. The different acute and chronic inflammatory disease states caused by dysregulated/impaired resolution of lung inflammation will be discussed. Furthermore, the resolution of lung inflammation during neutrophil/eosinophil-dominant lung injury or enhanced resolution driven via pharmacological manipulation will also be considered

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.

Background: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.</p