Volatile Organic Compounds from Entomopathogenic and Nematophagous Fungi, Repel Banana Black Weevil (Cosmopolites sordidus)

Fungal Volatile Organic Compounds (VOCs) repel banana black weevil (BW), Cosmopolites sordidus (Germar, 1824), the key-pest of banana [Musa sp. (Linnaeus, 1753)]. The entomopathogens Beauveria bassiana (Bb1TS11) and Metarhizium robertsii (Mr4TS04) were isolated from banana plantation soils using an insect bait. Bb1TS11 and Mr4TS04 were pathogenic to BW adults. Bb1TS11, Bb203 (from infected palm weevils), Mr4TS04 and the nematophagous fungus Pochonia clamydosporia (Pc123), were tested for VOCs production. VOCs were identified by Gas Chromatography/Mass Spectrometry–Solid-Phase Micro Extraction (GC/MS-SPME). GC/MS-SPME identified a total of 97 VOCs in all strains tested. Seven VOCs (styrene, benzothiazole, camphor, borneol, 1,3-dimethoxy-benzene, 1-octen-3-ol and 3-cyclohepten-1-one) were selected for their abundance or previous record as insect repellents. BW-starved adults in the dark showed the highest mobility to banana corm in olfactometry bioassays. 3-cyclohepten-1-one (C7), produced by all fungal strains, is the best BW repellent (p < 0.05), followed by 1,3-dimethoxy-benzene (C5). The rest of the VOCs have a milder repellency to BW. Styrene (C1) and benzothiazole (C2) (known to repel palm weevil) block the attraction of banana corm and BW pheromone to BW adults in bioassays. Therefore, VOCs from biocontrol fungi can be used in future studies for the biomanagement of BW in the field.This research was funded by H2020 European Project Microbial Uptakes for Sustainable management of major bananA pests and diseases with project number 727624

Dispositivos de asistencia mecánica circulatoria

Un dispositivo de asistencia mecánica circulatoria o AMC, es una bomba con capacidad de dar soporte mecánico a un corazón en fallo cardiaco, facilitando el bombeo de la sangre desde las cavidades cardiacas hacia la circulación sistémica. Consideramos asistencia circulatoria a cualquier dispositivo o sistema utilizado para apoyar o sustituir la función cardiaca de forma temporal o, más raramente, permanente. Por norma general nos referimos a las asistencias ventriculares mecánicas y al corazón artificial total.  ABSTRACT A mechanical circulatory assist devices (MCADs) , is a pump capable of giving mechanical support to a heart in heart failure, facilitating the pumping of blood from the cardiac cavities to the systemic circulation. We consider circulatory assistance to any device or system used to support or replace cardiac function temporarily or, more rarely, permanently. As a general rule, we refer to mechanical ventricular assist and total artificial heart

Dispositivos de asistencia mecánica circulatoria

A mechanical circulatory assist devices (MCADs) , is a pump capable of giving mechanical support to a heart in heart failure, facilitating the pumping of blood from the cardiac cavities to the systemic circulation. We consider circulatory assistance to any device or system used to support or replace cardiac function temporarily or, more rarely, permanently. As a general rule, we refer to mechanical ventricular assist and total artificial heart.Un dispositivo de asistencia mecánica circulatoria o AMC, es una bomba con capacidad de dar soporte mecánico a un corazón en fallo cardiaco, facilitando el bombeo de la sangre desde las cavidades cardiacas hacia la circulación sistémica. Consideramos asistencia circulatoria a cualquier dispositivo o sistema utilizado para apoyar o sustituir la función cardiaca de forma temporal o, más raramente, permanente. Por norma general nos referimos a las asistencias ventriculares mecánicas y al corazón artificial total

Connected Insulin Pens and Caps : An Expert's Recommendation from the Area of Diabetes of the Spanish Endocrinology and Nutrition Society (SEEN)

Undoubtedly, technological advances have revolutionised diabetes management in recent years. The development of advanced closed hybrid loop insulin pumps or continuous glucose monitoring (CGM) systems, among others, have increased the quality of life and improved glycaemic control of people with diabetes. However, only some patients have access to such technology, and only some want to use it. CGM has become much more widespread, but in terms of insulin delivery, most people with type 1 diabetes (T1D) and almost all people with type 2 diabetes (T2D) on insulin therapy are treated with multiple-dose insulin injections (MDI) rather than an insulin pump. For these patients, using connected insulin pens or caps has shown benefits in reducing missed insulin injections and promoting correct administration over time. In addition, using these devices improves the quality of life and user satisfaction. The integration of insulin injection and CGM data facilitates both users and the healthcare team to analyse glucose control and implement appropriate therapeutic changes, reducing therapeutic inertia. This expert's recommendation reviews the characteristics of the devices marketed or in the process of being marketed and their available scientific evidence. Finally, it suggests the profile of users and professionals who would benefit most, the barriers to its generalisation and the changes in the care model that implementing these devices can bring with it

Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study.

BACKGROUND: With no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups. METHODS AND FINDINGS: We harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54-105 (mean = 72.7) years and without dementia at baseline. Studies had 2-15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E ε4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = -0.1, SE = 0.01), APOE*4 carriage (B = -0.31, SE = 0.11), depression (B = -0.11, SE = 0.06), diabetes (B = -0.23, SE = 0.10), current smoking (B = -0.20, SE = 0.08), and history of stroke (B = -0.22, SE = 0.09) were independently associated with poorer cognitive performance (p < 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p < 0.01 for both). Age (B = -0.07, SE = 0.01), APOE*4 carriage (B = -0.41, SE = 0.18), and diabetes (B = -0.18, SE = 0.10) were independently associated with faster cognitive decline (p < 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = -0.24, SE = 0.12), and between diabetes and cognitive decline (B = -0.66, SE = 0.27; p < 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife. CONCLUSIONS: These results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences

Correction: Lozano-Soria et al. Volatile Organic Compounds from Entomopathogenic and Nematophagous Fungi, Repel Banana Black Weevil (Cosmopolites sordidus). Insects 2020, 11, 509

Fungal Volatile Organic Compounds (VOCs) repel banana black weevil (BW), Cosmopolites sordidus (Germar, 1824), the key-pest of banana [Musa sp. (Linnaeus, 1753)]. The entomopathogens Beauveria bassiana (Bb1TS11) and Metarhizium robertsii (Mr4TS04) were isolated from banana plantation soils using an insect bait. Bb1TS11 and Mr4TS04 were pathogenic to BW adults. Bb1TS11, Bb203 (from infected palm weevils), Mr4TS04 and the nematophagous fungus Pochonia clamydosporia (Pc123), were tested for VOCs production. VOCs were identified by Gas Chromatography/Mass Spectrometry–Solid-Phase Micro Extraction (GC/MS-SPME). GC/MS-SPME identified a total of 97 VOCs in all strains tested. Seven VOCs (styrene, benzothiazole, camphor, borneol, 1,3-dimethoxy-benzene, 1-octen-3-ol and 3-cyclohepten-1-one) were selected for their abundance or previous record as insect repellents. In olfactometry bioassays, BW- starved adults in the dark showed the highest mobility to banana corm. 2-cyclohepten-1-one (C7), commercially available isomer of 3-cyclohepten-1-one, is the best BW repellent (p &lt; 0.05), followed by 1,3-dimethoxy-benzene (C5). The rest of the VOCs have a milder repellency to BW. Styrene (C1) and benzothiazole (C2) (known to repel palm weevil) block the attraction of banana corm and BW pheromone to BW adults in bioassays. Therefore, VOCs from biocontrol fungi can be used in future studies to biomanage BW in the field

Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study.

BackgroundWith no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups.Methods and findingsWe harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54-105 (mean = 72.7) years and without dementia at baseline. Studies had 2-15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E ε4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = -0.1, SE = 0.01), APOE*4 carriage (B = -0.31, SE = 0.11), depression (B = -0.11, SE = 0.06), diabetes (B = -0.23, SE = 0.10), current smoking (B = -0.20, SE = 0.08), and history of stroke (B = -0.22, SE = 0.09) were independently associated with poorer cognitive performance (p &lt; 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p &lt; 0.01 for both). Age (B = -0.07, SE = 0.01), APOE*4 carriage (B = -0.41, SE = 0.18), and diabetes (B = -0.18, SE = 0.10) were independently associated with faster cognitive decline (p &lt; 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = -0.24, SE = 0.12), and between diabetes and cognitive decline (B = -0.66, SE = 0.27; p &lt; 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife.ConclusionsThese results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences

Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study

Background With no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups. Methods and findings We harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54-105 (mean = 72.7) years and without dementia at baseline. Studies had 2-15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E epsilon 4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = -0.1, SE = 0.01), APOE*4 carriage (B = -0.31, SE = 0.11), depression (B = -0.11, SE = 0.06), diabetes (B = -0.23, SE = 0.10), current smoking (B = -0.20, SE = 0.08), and history of stroke (B = -0.22, SE = 0.09) were independently associated with poorer cognitive performance (p &lt; 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p &lt; 0.01 for both). Age (B = -0.07, SE = 0.01), APOE*4 carriage (B = -0.41, SE = 0.18), and diabetes (B = -0.18, SE = 0.10) were independently associated with faster cognitive decline (p &lt; 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = -0.24, SE = 0.12), and between diabetes and cognitive decline (B = -0.66, SE = 0.27; p &lt; 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife. Conclusions These results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences.Y