Cell Penetrating Peptides (CPPs) are promising anticancer and antimicrobial drugs. We recently reported that a peptide derived from the human mitochondrial/ER membrane-anchored NEET protein, Nutrient Autophagy Factor 1 (NAF-1; NAF-144-67), selectively permeates and kills human metastatic epithelial breast cancer cells (MDA-MB-231), but not control epithelial cells. As cancer cells alter their phenotype during growth and metastasis, we tested whether NAF-144–67 would also be efficient in killing other human epithelial breast cancer cells that may have a different phenotype. Here we report that NAF-144–67 is efficient in killing BT-549, Hs 578T, MDA-MB-436, and MDA-MB-453 breast cancer cells, but that MDA-MB-157 cells are resistant to it. Upon closer examination, we found that MDA-MB-157 cells display a high content of intracellular vesicles and cellular protrusions, compared to MDA-MB-231 cells, that could protect them from NAF-144–67. Inhibiting the formation of intracellular vesicles and dynamics of cellular protrusions of MDA-MB-157 cells, using a protein translation inhibitor (the antibiotic Cycloheximide), rendered these cells highly susceptible to NAF-144–67, suggesting that under certain conditions, the killing effect of CPPs could be augmented when they are applied in combination with an antibiotic or chemotherapy agent. These findings could prove important for the treatment of metastatic cancers with CPPs and/or treatment combinations that include CPPs.
The emergence of antibiotic tolerance (prolonged survival against exposure) in natural bacterial populations is a major concern. Since it has been studied primarily in isogenic populations, we do not yet understand how ecological interactions in a diverse community impact the evolution of tolerance. To address this, we studied the evolutionary dynamics of a synthetic bacterial community composed of two interacting strains. In this community, an antibiotic-resistant strain protected the other, susceptible strain by degrading the antibiotic ampicillin in the medium. Surprisingly, we found that in the presence of antibiotics, the susceptible strain evolved tolerance. Tolerance was typified by an increase in survival as well as an accompanying decrease in the growth rate, highlighting a trade-off between the two. A simple mathematical model explained that the observed decrease in the death rate, even when coupled with a decreased growth rate, is beneficial in a community with weak protective interactions. In the presence of strong interactions, the model predicted that the trade-off would instead be detrimental, and tolerance would not emerge, which we experimentally verified. By whole genome sequencing the evolved tolerant isolates, we identified two genetic hot spots which accumulated mutations in parallel lines, suggesting their association with tolerance. Our work highlights that ecological interactions can promote antibiotic tolerance in bacterial communities, which has remained understudied.
OBJECTIVES: To investigate the comparative antiseizure activity of the individual enantiomers of fenfluramine and its major active primary metabolite norfenfluramine in rodent seizure models, and its relationship with the pharmacokinetics of these compounds in plasma and brain.
METHODS: The antiseizure potency of d,l-fenfluramine (racemic fenfluramine) was compared with the respective potencies of its individual enantiomers and the individual enantiomers of norfenfluramine using the maximal electroshock (MES) test in rats and mice, and the 6-Hz 44 mA test in mice. Minimal motor impairment was assessed simultaneously. The time course of seizure protection in rats was compared with the concentration profiles of d-fenfluramine, l-fenfluramine, and their primary active metabolites in plasma and brain.
RESULTS: All compounds tested were active against MES-induced seizures in rats and mice after acute (single-dose) administration, but no activity against 6-Hz seizures was found even at doses up to 30 mg/kg. Estimates of median effective doses (ED ) in the rat-MES test were obtained for all compounds except for d-norfenfluramine, which caused dose-limiting neurotoxicity. Racemic fenfluramine had approximately the same antiseizure potency as its individual enantiomers. Both d- and l-fenfluramine were absorbed and distributed rapidly to the brain, suggesting that seizure protection at early time points (≤2 h) was related mainly to the parent compound. Concentrations of all enantiomers in brain tissue were >15-fold higher than those in plasma.
SIGNIFICANCE: Although there are differences in antiseizure activity and pharmacokinetics among the enantiomers of fenfluramine and norfenfluramine, all compounds tested are effective in protecting against MES-induced seizures in rodents. In light of the evidence linking the d-enantiomers to cardiovascular and metabolic adverse effects, these data suggest that l-fenfluramine and l-norfenfluramine are potentially attractive candidates for a chiral switch approach leading to development of a novel, enantiomerically-pure antiseizure medication.
Matrix metalloproteinase-9 (MMP-9) is an endopeptidase that remodels the extracellular matrix. MMP-9 has been implicated in several diseases including neurodegeneration, arthritis, cardiovascular diseases, fibrosis and several types of cancer, resulting in a high demand for MMP-9 inhibitors for therapeutic purposes. For such drug design efforts, large amounts of MMP-9 are required. Yet, the catalytic domain of MMP-9 (MMP-9Cat) is an intrinsically unstable enzyme that tends to auto-cleave within minutes, making it difficult to use in drug design experiments and other biophysical studies. We set our goal to design MMP-9Cat variant that is active but stable to auto-cleavage. For this purpose, we first identified potential auto-cleavage sites on MMP-9Cat using mass spectroscopy and then eliminated the auto-cleavage site by predicting mutations that minimize auto-cleavage potential without reducing enzyme stability. Four computationally designed MMP-9Cat variants were experimentally constructed and evaluated for auto-cleavage and enzyme activity. Our best variant, Des2, with 2 mutations, was as active as the wild-type enzyme but did not exhibit auto-cleavage after 7 days of incubation at 37°C. This MMP-9Cat variant, with an identical with MMP-9Cat WT active site, is an ideal candidate for drug design experiments targeting MMP-9 and enzyme crystallization experiments. The developed strategy for MMP-9CAT stabilization could be applied to redesign other proteases to improve their stability for various biotechnological applications.
Adapting to new environments is a hallmark of animal and human cognition, and Reinforcement Learning (RL) models provide a powerful and general framework for studying such adaptation. A fundamental learning component identified by RL models is that in the absence of direct supervision, when learning is driven by trial-and-error, exploration is essential. The necessary ingredients of effective exploration have been studied extensively in machine learning. However, the relevance of some of these principles to humans’ exploration is still unknown. An important reason for this gap is the dominance of the Multi-Armed Bandit tasks in human exploration studies. In these tasks, the exploration component per se is simple, because local measures of uncertainty, most notably visit-counters, are sufficient to effectively direct exploration. By contrast, in more complex environments, actions have long-term exploratory consequences that should be accounted for when measuring their associated uncertainties. Here, we use a novel experimental task that goes beyond the bandit task to study human exploration. We show that when local measures of uncertainty are insufficient, humans use exploration strategies that propagate uncertainties over states and actions. Moreover, we show that the long-term exploration consequences are temporally-discounted, similar to the temporal discounting of rewards in standard RL tasks. Additionally, we show that human exploration is largely uncertainty-driven. Finally, we find that humans exhibit signatures of temporally-extended learning, rather than local, 1-step update rules which are commonly assumed in RL models. All these aspects of human exploration are well-captured by a computational model in which agents learn an exploration “value-function”, analogous to the standard (reward-based) value-function in RL.
This research provides evidence regarding the causal effect of group conformity on task performance in stable and variable environments. Drawing on studies in cultural evolution, social learning, and social psychology, we experimentally tested the hypotheses that conformity improves group performance in a stable environment (H1), and decreases performance (by hindering adaptability) in a temporally variable environment (H2). We compare the performance of individuals, low conformity groups, and high conformity groups within a four-arm randomized lab-experiment (N=240). High conformity was manipulated by rewarding agreement with the group’s majority, and imposing a cost on disagreement. The monetary implications of conformity impaired performance in a variable environment, but did not have a significant effect on performance in the stable environment. Intra-group individual-level analyses provide insights into the mechanisms that account for the group-level results, by showing that lower conformity in groups facilitates efficient adaptability in the use of social information.
Nitrogen heterocycles play a vital role in pharmaceuticals and natural products, with the six-membered aromatic and aliphatic architectures being commonly used. While synthetic methods for aromatic N-heterocycles are well-established, the synthesis of their aliphatic functionalized analogues, particularly piperidine derivatives, poses a significant challenge. In that regard, we propose a stepwise dearomative functionalization reaction for the construction of highly decorated piperidine derivatives with diverse functional handles. We also discuss challenges related to site-selectivity, regio- and diastereoselectivity, and provide insights into the reaction mechanism through mechanistic studies and density functional theory computations.
This study tested the role of perceived social support as a moderating factor in the mediation of COVID-19-related concerns in the association between continuous traumatic stress (CTS) and depression. The study participants were 499 college students who responded to an anonymous online questionnaire. Measures included the assessment of prior continuous exposure to threats of terrorism, COVID-19-related distress, perceived social support and depressive symptoms. The results demonstrated that COVID-19-related concerns mediated the relationship between continuous exposure to threats of terrorism and depression symptoms, and that perceived social support moderated the association between COVID-19-related concerns and depression. The implications of the study highlight the role of prior exposure to traumatic stress as a risk factor for depression and the role of social support as a protective factor. These results point to the need to develop accessible and non-stigmatic mental health services for populations exposed to other types of continuous traumatic stress.
The soil seed bank is a major component of plant communities. However, long-term analyses of the dynamics of the seed bank and the ensuing vegetation are rare. Here, we studied the dynamics in plant communities with high dominance of annuals in Mediterranean, semiarid, and arid ecosystems for nine consecutive years. For annuals, we hypothesized that the density of the seed bank would be more stable than the density of the standing herbaceous vegetation. Moreover, we predicted that differences in temporal variability between the seed bank and the vegetation would increase with aridity, where year-to-year rainfall variability is higher. We found that the temporal variability at the population level (assessed as the standard deviation of the loge-transformed density) of the nine dominant annuals in each site did not differ between the seed bank and the ensuing vegetation in any of the sites. For the total density of annuals, patterns depended on aridity. In the Mediterranean site, the temporal variability was similar in the seed bank and the vegetation (0.40 vs. 0.40). Still, in the semiarid and arid sites, variability in the seed bank was lower than in the vegetation (0.49 vs. 1.01 and 0.63 vs. 1.38, respectively). This difference between the population-level patterns and the total density of annuals can be related to the lower population synchrony in their seed bank. In contrast, for the herbaceous perennials (all species combined), the seed bank variability was higher than in the vegetation. Overall, our results highlight the role of the seed bank in buffering the annual vegetation density with increasing climatic uncertainty typical in aridity gradients. This role is crucial under the increasing uncertainty imposed by climatic change in the region.
Aluminum nanocrystals are emerging as a promising alternative to silver and gold for various applications ranging from plasmonic functionalities to photocatalysis and as energetic materials. Such nanocrystals often exhibit an inherent surface oxidation layer, as aluminum is highly reactive. Its controlled removal is challenging but required, as it can hinder the properties of the encaged metal. Herein, two wet-chemical colloidal approaches toward the surface coating of Al nanocrystals, which afford control over the surface chemistry of the nanocrystals and the oxide thickness, are presented. The first approach utilizes oleic acid as a surface ligand by its addition toward the end of the Al nanocrystals synthesis, and the second approach is the post-synthesis treatment of Al nanocrystals with NOBF4, in a "wet" colloidal-based approach, which is found to etch and fluorinate the surface oxides. As surface chemistry is an important handle for controlling materials' properties, this research paves a path for manipulating Al nanocrystals while promoting their utilization in diverse applications.
nd as energetic materials. Such nanocrystals often exhibit an inherent surface oxidation layer, as aluminum is highly reactive. Its controlled removal is challenging but required, as it can hinder the properties of the encaged metal. Herein, two wet-chemical colloidal approaches toward the surface coating of Al nanocrystals, which afford control over the surface chemistry of the nanocrystals and the oxide thickness, are presented. The first approach utilizes oleic acid as a surface ligand by its addition toward the end of the Al nanocrystals synthesis, and the second approach is the post-synthesis treatment of Al nanocrystals with NOBF4, in a "wet" colloidal-based approach, which is found to etch and fluorinate the surface oxides. As surface chemistry is an important handle for controlling materials' properties, this research paves a path for manipulating Al nanocrystals while promoting their utilization in diverse applications.