Notes

MRI with sub-millisecond temporal solution on the decreased area regarding view.
Since Cajal's visualisations of the synaptic spine, this feature of the neuron has been of interest to neuroscientists and has been investigated usually in reference to degeneration or proliferation of dendrites and their neurons. Synaptic spine measurement often forms a critical element of any study investigating neuronal morphology. However, the way researchers have counted spines hasn't changed for almost a century. Some of the currently used legacy methods fail to accommodate obscured spines or factor-in visibility differences between histological stains.

Here we investigate the neuronal dendrite and its synaptic spines, and reveal that using confocal or bright-field technologies may in fact obfuscate spine counts. A mathematical model is developed for the distribution of synaptic spines within the rat, that should, by nature of the formula and the impartiality of probability quotients, be applied to estimate the number of synaptic spines across any length of dendrite that has protrusions within any species.

Using this estimation method, we show that, depending on the method of image capture, there are in fact more spines present than typically counted on lengths of dendrite, something that may have biased morphological studies in the past.

This new estimation method has been collapsed down into an easy-to-use free website. With input of only four fields, we provide the researcher with a more accurate estimation of the amount of spines on a length of dendrite. This was made possible by fluorescing a Golgi stain and comparing two-photon, bright-field and confocal images.

An easy web-based resource has been made available to use this new method for spine calculation. Using this method improves the validity of spine measurement and provides a means to review previously published work.
An easy web-based resource has been made available to use this new method for spine calculation. Using this method improves the validity of spine measurement and provides a means to review previously published work.Insights into chloride regulation in neurons have come slowly, but they are likely to be critical for our understanding of how the brain works. The reason is that the intracellular Cl- level ([Cl-]i) is the key determinant of synaptic inhibitory function, and this in turn dictates all manner of neuronal network function. The true impact on the network will only be apparent, however, if Cl- is measured at many locations at once (multiple neurons, and also across the subcellular compartments of single neurons), which realistically, can only be achieved using imaging. The development of genetically-encoded anion biosensors (GABs) brings the additional benefit that Cl- imaging may be done in identified cell-classes and hopefully in subcellular compartments. Here, we describe the historical background and motivation behind the development of these sensors and how they have been used so far. There are, however, still major limitations for their use, the most important being the fact that all GABs are sensitive to both pH and Cl-. Disambiguating the two signals has proved a major challenge, but there are potential solutions; notable among these is ClopHensor, which has now been developed for in vivo measurements of both ion species. We also speculate on how these biosensors may yet be improved, and how this could advance our understanding of Cl- regulation and its impact on brain function.Sulfamethoxazole (SMX), a typical sulfonamide antibiotic, is ubiquitous in secondary effluent and may pose undesirable effects on the aquatic ecosystem and human health. Constructed wetland (CW) is more and more applied in advanced sewage treatment, and the substrate plays an important role in removing pollutants. Manganese (Mn) ore has been widely concerned as a new type of substrate to remove pollutants in CW due to its high adsorption and redox properties. However, the removal mechanism of antibiotics by Mn ore CW is still unclear. In this study, Mn ore was selected as the substrate of a vertical flow constructed wetland (VFCW) while gravel substrate was selected as a control group, and the removal efficiencies of SMX in two VFCWs were investigated and compared. Experimental devices were layered as different regions, including anaerobic (0-32 cm), anoxic (32-64 cm) and aerobic (64-80 cm) zones, to examine the removal characteristics of SMX in different regions. And the removal mechanism of SMX was also expcould enhance SMX removal efficiency in anaerobic and aerobic zones by Mn redox process.As one of three top-priority eutrophic lakes in China, Dianchi Lake has received national attention due to its severe eutrophication in recent decades. Meteorological factors are the main factors driving the formation and persistence of algae blooms. In addition, meteorological variation-induced algal blooms usually have a hysteresis effect. However, there have been few quantitative studies on this hysteresis effect. In the present study, Landsat images were used to extract the dynamic characteristics of changes in algal blooms in Dianchi Lake from 1988 to 2020. The hysteresis effect of meteorological factors driving algal blooms was studied by employing the modified lag-correlation method. The results showed that the algal blooms in Dianchi Lake were most severe between 1998 and 2008. During the periods of algal blooms, the values of air temperature (AT) and precipitation (PP) were significantly higher, while those wind velocity (WV) and sunshine duration (SSD) were obviously lower, than the corresponding annual mean values. AT and PP were significantly positively correlated with algal bloom factors in both the formation and persistence stages of algal blooms, while SSD and WV both promoted their regression, but these effects were less significant in the persistence period than in the formation period. Moreover, rainfall led to a decrease in SSD and WV, indirectly contributing to algal blooms. Furthermore, AT, PP and SSD are the main factors impacting the duration of persistent blooms. The time periods during which each meteorological factor was most influential were as follows 1) AT - 25-30 days before the maximum bloom. Selleckchem GDC-0077 2) PP - within the first 10 days before the maximum bloom. 3) Both SSD and WV - 15-20 days before the maximum bloom. The results of this study support the prediction of algal blooms in Dianchi Lake.Gestation and lactation are critical and vulnerable stages for fetuses and newborns. During these periods, per-/polyfluoroalkyl substances (PFASs) accumulated in mothers can be transferred to newborns through placenta and/or breastfeeding, causing potential health risks. To investigate the pre- and postnatal PFAS exposure of newborns, we analyzed 21 emerging and legacy PFASs in 60 sets of matched maternal serum, cord serum, and breast milk samples. In serum, perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), and 62 chlorinated polyfluorinated ether sulfonates (62 Cl-PFESA) were the most predominant PFASs, while PFOA, PFOS and 62 fluorotelomer phosphate diester (62 diPAP) contributed most to breast milk. For most PFASs, the levels followed the order of maternal serum > cord serum > breast milk. The 62 Cl-PFESA was positively associated with birth weight and ponderal index (p less then 0.05). The breastfeeding transfer efficiencies (RBM, median 0.02-0.10) of most PFASs were 1-2 orders of magnitude lower than transplacental transfer efficiencies (RCM, median 0.40-1.45), except for perfluorobutanesulfonic acid (PFBS) showing high transfer efficiency both through placenta (median at 0.89) and breastfeeding (median at 0.86). The one-month postnatal exposure to PFASs via breastfeeding was much higher than prenatal exposure in utero. This study enhances the understanding of transplacental and breastfeeding transfer of PFASs and provides assessments of prenatal and postnatal exposure of newborns to emerging and legacy PFASs.Tetracycline is a common antibiotic and is often carelessly released into the natural environment, thus constantly posing potential threats to the environment. Currently, due to lack of effective methods to remove it from the environmental water system, researchers are still exploring new ways to deal with tetracycline. In this work, we employed atmospheric-pressure non-thermal plasma (NTP) to treat tetracycline in water and investigated the involved degradation mechanism. The enhanced degradation efficiency was acquired and investigated, and the degradation mechanism by the plasma-generated active species were explored. The tetracycline degradation pathways via especially the interactions with plasma-generated hydroxyl radical and ozone were examined by virtue of UV spectroscopy, three-dimensional fluorescence spectroscopy, high performance liquid chromatography-mass spectrometry (HPLC-MS), together with the assistance of theoretical simulations. Moreover, the toxicological evaluation of NTP treatment of tetracycline was also provided, which confirmed that the biological toxicity of tetracycline degradation products was negligible. Therefore, this work provides not only the effective way of treating antibiotics by engineered plasma technology, but also the insights into the mechanisms of degradation of antibiotics by NTP.Potentially Toxic Elements (PTEs) are contaminants with high toxicity and complex geochemical behaviour and, therefore, high PTEs contents in soil may affect ecosystems and/or human health. However, before addressing the measurement of soil pollution, it is necessary to understand what is meant by pollution-free soil. Often, this background, or pollution baseline, is undefined or only partially known. Since the concentration of chemical elements is compositional, as the attributes vary together, here we present a novel approach to build compositional indicators based on Compositional Data (CoDa) principles. The steps of this new methodology are 1) Exploratory data analysis through variation matrix, biplots or CoDa dendrograms; 2) Selection of geological background in terms of a trimmed subsample that can be assumed as non-pollutant; 3) Computing the spread Aitchison distance from each sample point to the trimmed sample; 4) Performing a compositional balance able to predict the Aitchison distance computed in step 3.Identifying a compositional balance, including pollutant and non-pollutant elements, with sparsity and simplicity as properties, is crucial for the construction of a Compositional Pollution Indicator (CI). Here we explored a database of 150 soil samples and 37 chemical elements from the contaminated region of Langreo, Northwestern Spain. There were obtained three Cis the first two using elements obtained through CoDa analysis, and the third one selecting a list of pollutants and non-pollutants based on expert knowledge and previous studies. The three indicators went through a Stochastic Sequential Gaussian simulation. The results of the 100 computed simulations are summarized through mean image maps and probability maps of exceeding a given threshold, thus allowing characterization of the spatial distribution and variability of the CIs. A better understanding of the trends of relative enrichment and PTEs fate is discussed.
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