For various experimental applications, microbial cultures at defined, constant densities are highly advantageous over simple batch cultures. Due to high costs, however, devices for continuous culture at freely defined densities still experience limited use. We have developed a small-scale turbidostat for research purposes, which is manufactured from inexpensive components and 3D printed parts. A high degree of spatial system integration and a graphical user interface provide user-friendly operability. The used optical density feedback control allows for constant continuous culture at a wide range of densities and offers to vary culture volume and dilution rates without additional parametrization. Further, a recursive algorithm for on-line growth rate estimation has been implemented. The employed Kalman filtering approach based on a very general state model retains the flexibility of the used control type and can be easily adapted to other bioreactor designs. Within several minutes it can converge to robust, accurate growth rate estimates. This is particularly useful for directed evolution experiments or studies on metabolic challenges, as it allows direct monitoring of the population fitness.
For various experimental applications, microbial cultures at defined, constant densities are highly advantageous over simple batch cultures. Due to high costs, however, devices for continuous culture at freely defined densities still experience limited use. We have developed a small-scale turbidostat for research purposes, which is manufactured from inexpensive components and 3D printed parts. A high degree of spatial system integration and a graphical user interface provide user-friendly operability. The used optical density feedback control allows for constant continuous culture at a wide range of densities and offers to vary culture volume and dilution rates without additional parametrization. Further, a recursive algorithm for on-line growth rate estimation has been implemented. The employed Kalman filtering approach based on a very general state model retains the flexibility of the used control type and can be easily adapted to other bioreactor designs. Within several minutes it can converge to robust, accurate growth rate estimates. This is particularly useful for directed evolution experiments or studies on metabolic challenges, as it allows direct monitoring of the population fitness.
Dieser Beitrag beschäftigt sich mit der Frage, welche Relevanz arbeitsstatis-tische und -rechtliche Kategorisierungen im Zeitraum von 1880 bis 1992 für den Wandel der Deu-tungsmodelle des Geschlechts haben. Aus vergleichstheoretischer stellt die Durchsetzung desmodernen Konzepts der Erwerbsarbeit um 1900 im nationalen Kontext und dessen Veränderung aufglobaler Ebene ein spezifisches Ordnungsverfahren dar, das im Mittelpunkt dieses Aufsatzes steht.Auf der Grundlage von zwei Mikrostudien zur Klassifizierung und Reklassifizierung der „Mithel-fenden Familienangehörigen“ und des „Nachtarbeitsverbots“ wird zum einen die Globalisierung derErwerbsarbeit als Beobachtungsschema, zum anderen der Wandel des Deutungsmodells derGeschlechterdifferenz im Zuge transnationaler Vergleichsverfahren erforscht. In dem Beitrag wirddie Auffassung vertreten, dass der Vergleich einen Globalisierungsmechanismus in der Weltgesell-schaft darstellt.
Objective:
Brain-derived neurotrophic factor (BDNF) supports neurogenesis, angiogenesis, and promotes the survival of various cell types in the brain and the coronary system. Moreover, BDNF is associated with both coronary heart disease (CHD) and depression. The current study aims to investigate whether serum BDNF levels are associated with the course of depressive symptoms in CHD patients.
Methods:
At baseline, N = 225 CHD patients were enrolled while hospitalized. Of these, N = 190 (84%) could be followed up 6 months later. Depressive symptoms were assessed both at baseline and at the 6-months follow-up using the Patient Health Questionnaire (PHQ-9). Serum BDNF concentrations were measured using fluorometric Enzyme-linked immunosorbent assays (ELISA).
Results:
Logistic regression models showed that lower BDNF levels were associated with persistent depressive symptoms, even after adjustment for age, sex, smoking and potential medical confounders. The incidence of depressive symptoms was not related to lower BDNF levels. However, somatic comorbidity (as measured by the Charlson Comorbidity Index) was significantly associated with the incidence of depressive symptoms.
Conclusions:
Our findings suggest a role of BDNF in the link between CHD and depressive symptoms. Particularly, low serum BDNF levels could be considered as a valuable biomarker for the persistence of depressive symptoms among depressed CHD patients.
Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.