Moreover, reduction of MCM loading at specific origins of replication led to a delay in their replication during S phase. In contrast, overexpression of MCM had no effects on cell cycle progression, relative MCM levels at origins, or replication timing, suggesting that, under optimal growth conditions, cellular MCM levels are not limiting for MCM loading. Our results support a model in which the loading capacity of origins is the primary determinant of MCM stoichiometry in wild-type cells, but that stoichiometry is controlled by origins’ ability to recruit ORC and compete for MCM when MCM becomes limiting.Burkholderia pseudomallei is a soil-dwelling organism present throughout the tropics. It is the causative agent of melioidosis, a disease that is believed to kill 89,000 people per year. It is naturally resistant to many antibiotics, requiring at least two weeks of intravenous treatment with ceftazidime, imipenem or meropenem followed by 6 months of orally delivered co-trimoxazole. This places a large treatment burden on the predominantly middle-income nations where the majority of disease occurs. We have established a high-throughput assay for compounds that could be used as a co-therapy to potentiate the effect of ceftazidime, using the related non-pathogenic bacterium Burkholderia thailandensis as a surrogate. Optimization of the assay gave a Z’ factor of 0.68. We screened a library of 61,250 compounds and identified 29 compounds with a pIC50 (-log10(IC50)) greater than five. Detailed investigation allowed us to down select to six “best in class” compounds, which included the licensed drug chloroxine. Co-treatment of B. thailandensis with ceftazidime and chloroxine reduced culturable cell numbers by two orders of magnitude over 48 hours, compared to treatment with ceftazidime alone. Hit expansion around chloroxine was performed using commercially available compounds. Minor modifications to the structure abolished activity, suggesting that chloroxine likely acts against a specific target. Finally, an initial study demonstrates the utility of chloroxine to act as a co-therapy to potentiate the effect of ceftazidime against B. pseudomallei. This approach successfully identified potential co-therapies for a recalcitrant Gram-negative bacterial species. Our assay could be used more widely to aid in chemotherapy to treat infections caused by these bacteria.Emergence of resistance to artemisinin and partner drugs in the Greater Mekong Subregion has made elimination of malaria from this region a global priority; it also complicates its achievement. Novel drug strategies such as triple artemisinin combination therapies (ACTs) and chemoprophylaxis have been proposed to help limit resistance and accelerate elimination. The objective of this study was to better understand the potential impacts of triple ACTs and chemoprophylaxis, using a mathematical model parameterized using data from Cambodia. We used a simple compartmental model to predict trends in malaria incidence and resistance in Cambodia from 2020-2025 assuming no changes in transmission since 2018. We assessed three scenarios a status quo scenario with artesunate-mefloquine (ASMQ) as treatment; a triple ACT scenario with dihydroartemisinin-piperaquine (DP) plus mefloquine (MQ) as treatment; and a chemoprophylaxis scenario with ASMQ as treatment plus DP as chemoprophylaxis. We predicted MQ resistance to incrby monitoring for drug resistance.Sequential behaviour is often compositional and organised across multiple time scales a set of individual elements developing on short time scales (motifs) are combined to form longer functional sequences (syntax). 4-Aminobutyric price Such organisation leads to a natural hierarchy that can be used advantageously for learning, since the motifs and the syntax can be acquired independently. Despite mounting experimental evidence for hierarchical structures in neuroscience, models for temporal learning based on neuronal networks have mostly focused on serial methods. Here, we introduce a network model of spiking neurons with a hierarchical organisation aimed at sequence learning on multiple time scales. Using biophysically motivated neuron dynamics and local plasticity rules, the model can learn motifs and syntax independently. Furthermore, the model can relearn sequences efficiently and store multiple sequences. Compared to serial learning, the hierarchical model displays faster learning, more flexible relearning, increased capacity, and higher robustness to perturbations. The hierarchical model redistributes the variability it achieves high motif fidelity at the cost of higher variability in the between-motif timings.Published analysis of genetic material from field-collected tsetse (Glossina spp, primarily from the Palpalis group) has been used to predict that the distance (δ) dispersed per generation increases as effective population densities (De) decrease, displaying negative density-dependent dispersal (NDDD). Using the published data we show this result is an artefact arising primarily from errors in estimates of S, the area occupied by a subpopulation, and thereby in De. The errors arise from the assumption that S can be estimated as the area ([Formula see text]) regarded as being covered by traps. We use modelling to show that such errors result in anomalously high correlations between [Formula see text] and [Formula see text] and the appearance of NDDD, with a slope of -0.5 for the regressions of log([Formula see text]) on log([Formula see text]), even in simulations where we specifically assume density-independent dispersal (DID). A complementary mathematical analysis confirms our findings. Modelling of field results shows, similarly, that the false signal of NDDD can be produced by varying trap deployment patterns. Errors in the estimates of δ in the published analysis were magnified because variation in estimates of S were greater than for all other variables measured, and accounted for the greatest proportion of variation in [Formula see text]. Errors in census population estimates result from an erroneous understanding of the relationship between trap placement and expected tsetse catch, exacerbated through failure to adjust for variations in trapping intensity, trap performance, and in capture probabilities between geographical situations and between tsetse species. Claims of support in the literature for NDDD are spurious. There is no suggested explanation for how NDDD might have evolved. We reject the NDDD hypothesis and caution that the idea should not be allowed to influence policy on tsetse and trypanosomiasis control.