Dynamic development of community behaviour in the direction of technology policymaking

It is predicted that these will be further implemented in EC-LFAs as high-performance transducers. Considering the low cost of point-of-care devices, it becomes even more important to also identify strategies that efficiently integrate nanomaterials into EC-LFAs in a high-throughput manner while maintaining their favorable analytical performance. Graphical abstract.In the Amazon, the leaching from soil left unprotected by deforestation increases the entry of iron, among other elements, in aquatic ecosystems, which can cause cyanobacterial blooms. This study aimed to investigate the physiological response of a strain of Microcystis panniformis to iron variation. The strain was isolated from a reservoir located in the Western Amazon and produces microcystin-LR. After a period of iron deprivation, the cultures were submitted to three conditions control (223 μgFe.L-1), treatment with 23 μgFe.L-1, and absence of iron. At regular intervals for eight days, the cell density, levels of chlorophyll a and microcystins were determined. On the second and fourth day, transcription of genes responsive to iron limitation was quantified. Starting on the fourth day of the experiment, the different iron concentrations affected growth, and on the eighth day in the iron-free condition cell density was 90% lower than in control. Chlorophyll cell quota in 23 μgFe.L-1 and control presented similar values, while without iron the cells became chlorotic as of the fourth day Toxin concentration in cells grow in 0 μgFe.L-1 in relation to the control. Higher transcription levels of the feo and fut genes were observed in the 0 μgFe.L-1 and 23 μgFe.L-1 treatments, indicating that the cells were activating high-affinity capture systems to reestablish an adequate concentration of intracellular iron. The increasing deforestation in the Jamari River Basin (Amazon region), can contribute to the occurrence of toxic cyanobacterial blooms due to the greater entrance of iron in water bodies.
The aim of the present study was to characterize the pharmacokinetics of irinotecan and its four main metabolites (SN-38, SN-38G, APC and NPC) in metastatic colorectal cancer patients treated with FOLFIRI and FOLFIRINOX regimens and to quantify and explain the inter-individual pharmacokinetic variability in this context.
A multicenter study including 109 metastatic colorectal cancer patients treated with FOLFIRI or FOLFIRINOX regimen, associated or not with a monoclonal antibody, was conducted. Trichostatin A in vitro Concentrations of irinotecan and its four main metabolites were measured in 506 blood samples during the first cycle of treatment. Collected data were analyzed using the population approach. First, fixed and random effects models were selected using statistical and graphical methods; second, the impact of covariates on pharmacokinetic parameters was evaluated to explain the inter-individual variability in pharmacokinetic parameters.
A seven-compartment model best described the pharmacokinetics of irinotecan and its four main metabolites. First-order rates were assigned to distribution, elimination, and metabolism processes, except for the transformation of irinotecan to NPC which was nonlinear. Addition of a direct conversion of NPC into SN-38 significantly improved the model. Co-administration of oxaliplatin significantly modified the distribution of SN-38.
To our knowledge, the present model is the first to allow a simultaneous description of irinotecan pharmacokinetics and of its four main metabolites. Moreover, a direct conversion of NPC into SN-38 had never been described before in a population pharmacokinetic model of irinotecan. The model will be useful to develop pharmacokinetic-pharmacodynamic models relating SN-38 concentrations to efficacy and digestive toxicities.
ClinicalTrials.gov identifier NCT00559676.
ClinicalTrials.gov identifier NCT00559676.In many low and middle-income countries, solid waste management (SWM) systems remain weak and lack standardization. Moreover, these systems fail to account for citizen's insight on the proposed solid waste initiatives. This study aims to identify the main determinants of SWM practices in a low-middle income country while accounting for citizens' perceived knowledge, attitudes, structural barriers, and willingness to pay for different services. Three communities were thus selected with varying socioeconomic factors and where different SWM practices were adopted. A cross-sectional study based on an interviewer-administered questionnaire was conducted across the three areas. Our results showed that increased knowledge and awareness of proper SWM did not correlate with people's attitudes nor with their adoption of positive waste management practices, such as reusing, reducing, recycling, and sorting of waste. Nevertheless, the results showed that the presence of an effective SWM system in a community positively influenced people's attitudes. Structural determinants, including the lack of appropriate facilities and adequate infrastructure, weak public knowledge on sorting, recycling, and composting, as well as the absence of guiding policies, appeared to be core barriers hindering the adoption of sustainable waste management practices across the three communities. The results of this study highlight the importance of establishing integrated SWM systems in developing countries, as they appear to trigger positive behaviors by the serviced citizens.
One sub-MAGIC population was genotyped using SLAF-seq, and QTLs and candidate genes for agronomic traits were identified in Upland cotton. The agronomic traits of Upland cotton have serious impacts on cotton production, as well as economic benefits. To discover the genetic basis of important agronomic traits in Upland cotton, a subset MAGIC (multi-parent advanced generation inter-cross) population containing 372 lines (SMLs) was selected from an 8-way MAGIC population with 960 lines. The 372 lines and 8 parents were phenotyped in six environments and deeply genotyped by SLAF-seq with 60,495 polymorphic SNPs. The genetic diversity indexes of all SNPs were 0.324 and 0.362 for the parents and MAGIC lines, respectively. The LD decay distance of the SMLs was 600kb (r
 = 0.1). Genome-wide association mapping was performed using 60,495 SNPs and the phenotypic data of the SMLs, and 177 SNPs were identified to be significantly associated with 9 stable agronomic traits in multiple environments. The identified SNPs were divided into 117 QTLs (quantitative trait loci) by LD decay distance, explaining 5.