Seasonal variations of water and sediment quality parameters in endorheic reed pans on the Mpumalanga Highveld

The Mpumalanga Lakes District consists of approximately 320 pans, of which less than 3% are classified as reed pans. There is limited information available on reed pans and as a result they are at risk of various anthropogenic activities, for example mining and agriculture. Four reed pans were selected and assessed to determine seasonal trends of a variety of water and sediment quality parameters. The study took place over one seasonal cycle from 2008–2009; samples were collected seasonally to account for various hydrological extremes. Water samples were collected and their nutrient and chlorophyll a concentrations were determined, while various other water quality parameters were measured in situ. Sediment samples were analysed for physical and chemical properties, namely, grain size and organic carbon content. The seasonal changes in concentrations of As, Cr, Cu, Fe, Pb, Mn, Mo, Ni, Se, Sr, U and Zn were also analysed within the surface water and sediment. Increased nutrient concentrations within the water were evident during spring and summer at some of the sites, which influenced other water quality variables, e.g., dissolved oxygen and pH. Seasonal trends in metal concentrations were influenced by the prevailing environmental conditions (e.g., rainfall) experienced at the selected sites as well as physical and chemical properties (e.g., grain size and organic carbon content). This study showed distinct seasonal variability of water and sediment quality parameters in endorheic reed pans on the Mpumalanga Highveld. There is a need for further studies on all of the different types of pans in terms of their water and sediment quality. This type of information will allow for a sound and defensible scientific basis for the assessment of likely impacts (e.g., eutrophication), the evaluation of the significance of these impacts, and the design of remedial and preventative measures

Electrodeposited CuO thin film for wide linear range photoelectrochemical glucose sensing

Cupric oxide (CuO) has been used as a non-enzymatic glucose sensor for decades. However, there is a paucity of publications on bare CuO based photo electrochemical (PEC) glucose detection. In this study, a photo active CuO thin film was electrodeposited onto conductive glass and its band gap was tuned by etching in NH3 solution. A 6 W light-emitting diode (LED) bulb was used as the light source for PEC glucose oxidation. Various physical and electrochemical characterization techniques were used to study the PEC behavior of the CuO thin film electrode during glucose oxidation. The electrochemical oxidation of glucose was found to be an irreversible electron transfer process controlled by diffusion at the electrode surface under illumination and dark conditions. Electrochemical impedance spectroscopy (EIS) confirmed that the charge transfer resistance in the light decreases by several orders of magnitude. Good amperometric performance was obtained for the CuO film with a 4 s response time and negligible interference from other species present in human blood. The as prepared sensor exhibited a remarkable wide linear range up-to 29 mM

Automated cell tracking using StarDist and TrackMate [version 1; peer review: awaiting peer review]

The ability of cells to migrate is a fundamental physiological process involved in embryonic development, tissue homeostasis, immune surveillance, and wound healing. Therefore, the mechanisms governing cellular locomotion have been under intense scrutiny over the last 50 years. One of the main tools of this scrutiny is live-cell quantitative imaging, where researchers image cells over time to study their migration and quantitatively analyze their dynamics by tracking them using the recorded images. Despite the availability of computational tools, manual tracking remains widely used among researchers due to the difficulty setting up robust automated cell tracking and large-scale analysis. Here we provide a detailed analysis pipeline illustrating how the deep learning network StarDist can be combined with the popular tracking software TrackMate to perform 2D automated cell tracking and provide fully quantitative readouts. Our proposed protocol is compatible with both fluorescent and widefield images. It only requires freely available and open-source software (ZeroCostDL4Mic and Fiji), and does not require any coding knowledge from the users, making it a versatile and powerful tool for the field. We demonstrate this pipeline's usability by automatically tracking cancer cells and T cells using fluorescent and brightfield images. Importantly, we provide, as supplementary information, a detailed step-by-step protocol to allow researchers to implement it with their images

The role of neoadjuvant chemotherapy in the management of advanced ovarian cancer in geriatric patients

It is increasingly common for ovarian cancer to affect older women, with over half of all cases involving patients aged 65 years and older. Unfortunately, elderly patients with ovarian malignancy tend to be treated less aggressively than younger patients, with less extensive surgery and less intensive chemotherapy regimens. This is due to a variety of factors, such as overall medical fitness and the function of specific organs. Moreover, multiple morbidities are typical for geriatric patients and affect their eligibility for certain forms of cancer therapy as well as their treatment outcomes, which are commonly less satisfactory than in younger patients. Additionally, for fear of complications, treating physicians sometimes limit the extent of the necessary surgery, or adjust chemotherapy doses, even though such a course of management tends to be largely misguided. One available management option is neoadjuvant chemotherapy followed by a surgical treatment known as interval debulking surgery. This type of combination therapy is associated with fewer postoperative complications, thus increasing the patient's chances of receiving a full course of adjuvant treatment. The decision to begin treatment with neoadjuvant chemotherapy tends to restrict later surgical therapy; however, under certain circumstances, this therapy can be a valid therapeutic option and, in fact, facilitate surgery. Prior to initiating therapy in elderly patients, their eligibility for combination therapy must be evaluated and the geriatric assessment of their performance and condition must be considered during the course of interdisciplinary preoperative management

Health risk implications from simultaneous exposure to multiple environmental contaminants

Water quality has deteriorated in the upper Olifants River system, South Africa, as a result of land use activities which include mining, agriculture and industries. A health risk assessment was conducted from 2009 to 2011 in the catchment to determine the possible risks local communities face from various pollutants such as microbials, heavy metals and oestrogen in the river water and vegetation. Aluminium and manganese accumulated in plants and vanadium and aluminium concentrations found in selective water samples posed significant health risks when consumed. A quantitative microbial risk assessment revealed that the combined risk of infection ranged from 1 to 26 percent with the Norovirus posing the overall greatest health risk. The anticipated disability adjusted life years resulting from drinking untreated water from these sites are in the order of 10,000 times greater than what is considered acceptable. The oestradiol activity, caused by endocrine disrupting compounds in the water, measured above the trigger value of 0.7 ng L−1. Impoverished communities in the area, who partially depend on river water for potable and domestic use, are exposed to immune-compromising metals that increase their probability of infection from waterborne diseases caused by the excess microbial pathogens in the contaminated surface water.Olifants River Forumhttp://www.elsevier.com/locate/ecoenvhb201

Automated cell tracking using StarDist and TrackMate

The ability of cells to migrate is a fundamental physiological process involved in embryonic development, tissue homeostasis, immune surveillance, and wound healing. Therefore, the mechanisms governing cellular locomotion have been under intense scrutiny over the last 50 years. One of the main tools of this scrutiny is live-cell quantitative imaging, where researchers image cells over time to study their migration and quantitatively analyze their dynamics by tracking them using the recorded images. Despite the availability of computational tools, manual tracking remains widely used among researchers due to the difficulty setting up robust automated cell tracking and large-scale analysis. Here we provide a detailed analysis pipeline illustrating how the deep learning network StarDist can be combined with the popular tracking software TrackMate to perform 2D automated cell tracking and provide fully quantitative readouts. Our proposed protocol is compatible with both fluorescent and widefield images. It only requires freely available and open-source software (ZeroCostDL4Mic and Fiji), and does not require any coding knowledge from the users, making it a versatile and powerful tool for the field. We demonstrate this pipeline's usability by automatically tracking cancer cells and T cells using fluorescent and brightfield images. Importantly, we provide, as supplementary information, a detailed step-by-step protocol to allow researchers to implement it with their images. </div

An integrated assessment of nitrogen source, transformation and fate within an intensive dairy system to inform management change

From an environmental perspective optimised dairy systems, which follow current regulations, still have low nitrogen (N) use efficiency, high N surplus (kg N ha-1) and enable ad-hoc delivery of direct and indirect reactive N losses to water and the atmosphere. The objective of the present study was to divide an intensive dairy farm into N attenuation capacity areas based on this ad-hoc delivery. Historical and current spatial and temporal multi-level datasets (stable isotope and dissolved gas) were combined and interpreted. Results showed that the farm had four distinct attenuation areas: high N attenuation: characterised by ammonium-N (NH4+-N) below 0.23 mg NH4+-N l-1 and nitrate (NO3--N) below 5.65 mg NO3--N l-1 in surface, drainage and groundwater, located on imperfectly to moderately-well drained soils with high denitrification potential and low nitrous oxide (N2O) emissions (av. 0.0032 mg N2O-N l-1); moderate N attenuation: characterised by low NO3--N concentration in drainage water but high N2O production (0.0317 mg N2O-N l-1) and denitrification potential lower than group 1 (av. δ15N-NO3-: 16.4‰, av. δ18O-NO3-: 9.2‰), on well to moderately drained soils; low N attenuation—area 1: characterised by high NO3--N (av. 6.90 mg NO3--N l-1) in drainage water from well to moderately-well drained soils, with low denitrification potential (av. δ15N-NO3-: 9.5‰, av. δ18O-NO3-: 5.9‰) and high N2O emissions (0.0319 mg N2O l-1); and low N attenuation—area 2: characterised by high NH4+-N (av. 3.93 mg NH4+-N l-1 and high N2O emissions (av. 0.0521 mg N2O l-1) from well to imperfectly drained soil. N loads on site should be moved away from low attenuation areas and emissions to air and water should be assessed

Elevated aluminium concentration in acidified headwater streams lowers aquatic hyphomycete diversity and impairs leaf-litter breakdown.

Aquatic hyphomycetes play an essential role in the decomposition of allochthonous organic matter which is a fundamental process driving the functioning of forested headwater streams. We studied the effect of anthropogenic acidification on aquatic hyphomycetes associated with decaying leaves of Fagus sylvatica in six forested headwater streams (pH range, 4.3-7.1). Non-metric multidimensional scaling revealed marked differences in aquatic hyphomycete assemblages between acidified and reference streams. We found strong relationships between aquatic hyphomycete richness and mean Al concentration (r = -0.998, p < 0.0001) and mean pH (r = 0.962, p < 0.002), meaning that fungal diversity was severely depleted in acidified streams. By contrast, mean fungal biomass was not related to acidity. Leaf breakdown rate was drastically reduced under acidic conditions raising the issue of whether the functioning of headwater ecosystems could be impaired by a loss of aquatic hyphomycete species

Competitive interaction between two aquatic hyphomycete species and increase in leaf litter breakdown

Aquatic hyphomycete species produce large numbers of conidia which rapidly colonize the leaf litter that falls into rivers during autumn. Our objective was to understand how a species which produces many fewer conidia than another in laboratory conditions can nevertheless be codominant in a natural setting. In microcosm studies with two pioneer dominant species, Flagellospora curvula and Tetrachaetum elegans, inoculated on alder leaves, we first verified that the ratio of the conidium production of both species (6 to 7:1) was inverse to that of individual conidial masses (1:7) as previously described. Calculating the percentage of leaf mass loss that corresponds to 1 mg of conidial mass produced, the combination of the two species produced 2.9-fold more loss than the mean of each species. By contrast, the reproductive biomasses of F. curvula and T. elegans were 5.2- and 2.6-fold lower, respectively. As a result, the conidium production of F. curvula in the combination was only 3.2-fold that of T. elegans instead of 6- to 7-fold in pure culture. In a mixed culture of the two species, T. elegans conidia had a high germination potential (>90%) whereas the proportion of germinated F. curvula conidia was only 50%. Moreover, T. elegans reduced the area on which F. curvula could grow on poor and rich solid media. These results indicate that the dominance of F. curvula conidia in the river may be partly controlled by T. elegans and suggest that a negative interaction between microfungi may have a positive effect on the ecosystem functioning