Chemoproteomics Identifies State-Dependent and Proteoform-Selective Caspase-2 Inhibitors.

Caspases are a highly conserved family of cysteine-aspartyl proteases known for their essential roles in regulating apoptosis, inflammation, cell differentiation, and proliferation. Complementary to genetic approaches, small-molecule probes have emerged as useful tools for modulating caspase activity. However, due to the high sequence and structure homology of all 12 human caspases, achieving selectivity remains a central challenge for caspase-directed small-molecule inhibitor development efforts. Here, using mass spectrometry-based chemoproteomics, we first identify a highly reactive noncatalytic cysteine that is unique to caspase-2. By combining both gel-based activity-based protein profiling (ABPP) and a tobacco etch virus (TEV) protease activation assay, we then identify covalent lead compounds that react preferentially with this cysteine and afford a complete blockade of caspase-2 activity. Inhibitory activity is restricted to the zymogen or precursor form of monomeric caspase-2. Focused analogue synthesis combined with chemoproteomic target engagement analysis in cellular lysates and in cells yielded both pan-caspase-reactive molecules and caspase-2 selective lead compounds together with a structurally matched inactive control. Application of this focused set of tool compounds to stratify the functions of the zymogen and partially processed (p32) forms of caspase-2 provide evidence to support that caspase-2-mediated response to DNA damage is largely driven by the partially processed p32 form of the enzyme. More broadly, our study highlights future opportunities for the development of proteoform-selective caspase inhibitors that target nonconserved and noncatalytic cysteine residues.

Chemoproteomics identifies proteoform-selective caspase-2 inhibitors.

Caspases are a highly conserved family of cysteine-aspartyl proteases known for their essential roles in regulating apoptosis, inflammation, cell differentiation, and proliferation. Complementary to genetic approaches, small-molecule probes have emerged as useful tools for modulating caspase activity. However, due to the high sequence and structure homology of all twelve human caspases, achieving selectivity remains a central challenge for caspase-directed small-molecule inhibitor development efforts. Here, using mass spectrometry-based chemoproteomics, we first identify a highly reactive non-catalytic cysteine that is unique to caspase-2. By combining both gel-based activity-based protein profiling (ABPP) and a tobacco etch virus (TEV) protease activation assay, we then identify covalent lead compounds that react preferentially with this cysteine and afford a complete blockade of caspase-2 activity. Inhibitory activity is restricted to the zymogen or precursor form of monomeric caspase-2. Focused analogue synthesis combined with chemoproteomic target engagement analysis in cellular lysates and in cells yielded both pan-caspase reactive molecules and caspase-2 selective lead compounds together with a structurally matched inactive control. Application of this focused set of tool compounds to stratify caspase contributions to initiation of intrinsic apoptosis, supports compensatory caspase-9 activity in the context of caspase-2 inactivation. More broadly, our study highlights future opportunities for the development of proteoform-selective caspase inhibitors that target non-conserved and non-catalytic cysteine residues.

The effects of random and seasonal environmental fluctuations on optimal harvesting and stocking.

We analyze the harvesting and stocking of a population that is affected by random and seasonal environmental fluctuations. The main novelty comes from having three layers of environmental fluctuations. The first layer is due to the environment switching at random times between different environmental states. This is similar to having sudden environmental changes or catastrophes. The second layer is due to seasonal variation, where there is a significant change in the dynamics between seasons. Finally, the third layer is due to the constant presence of environmental stochasticity-between the seasonal or random regime switches, the species is affected by fluctuations which can be modelled by white noise. This framework is more realistic because it can capture both significant random and deterministic environmental shifts as well as small and frequent fluctuations in abiotic factors. Our framework also allows for the price or cost of harvesting to change deterministically and stochastically, something that is more realistic from an economic point of view. The combined effects of seasonal and random fluctuations make it impossible to find the optimal harvesting-stocking strategy analytically. We get around this roadblock by developing rigorous numerical approximations and proving that they converge to the optimal harvesting-stocking strategy. We apply our methods to multiple population models and explore how prices, or costs, and environmental fluctuations influence the optimal harvesting-stocking strategy. We show that in many situations the optimal way of harvesting and stocking is not of threshold type.

Harvesting and seeding of stochastic populations: analysis and numerical approximation.

We study an ecosystem of interacting species that are influenced by random environmental fluctuations. At any point in time, we can either harvest or seed (repopulate) species. Harvesting brings an economic gain while seeding incurs a cost. The problem is to find the optimal harvesting-seeding strategy that maximizes the expected total income from harvesting minus the cost one has to pay for the seeding of various species. In Hening et al. (J Math Biol 79(2):533-570, 2019b) we considered this problem when one has absolute control of the population (infinite harvesting and seeding rates are possible). In many cases, these approximations do not make biological sense and one must consider what happens when one, or both, of the seeding and harvesting rates are bounded. The focus of this paper is the analysis of these three novel settings: bounded seeding and infinite harvesting, bounded seeding and bounded harvesting, and infinite seeding and bounded harvesting. Even one dimensional harvesting problems can be hard to tackle. Once one looks at an ecosystem with more than one species analytical results usually become intractable. In order to gain information regarding the qualitative behavior of the system we develop rigorous numerical approximation methods. This is done by approximating the continuous time dynamics by Markov chains and then showing that the approximations converge to the correct optimal strategy as the mesh size goes to zero. By implementing these numerical approximations, we are able to gain qualitative information about how to best harvest and seed species in specific key examples. We are able to show through numerical experiments that in the single species setting the optimal seeding-harvesting strategy is always of threshold type. This means there are thresholds [Formula: see text] such that: (1) if the population size is 'low', so that it lies in [Formula: see text], there is seeding using the maximal seeding rate; (2) if the population size 'moderate', so that it lies in [Formula: see text], there is no harvesting or seeding; (3) if the population size is 'high', so that it lies in the interval [Formula: see text], there is harvesting using the maximal harvesting rate. Once we have a system with at least two species, numerical experiments show that constant threshold strategies are not optimal anymore. Suppose there are two competing species and we are only allowed to harvest or seed species 1. The optimal strategy of seeding and harvesting will involve lower and upper thresholds [Formula: see text] which depend on the density [Formula: see text] of species 2.

Correction: An Unusual Finding of a Ladybug on Screening Colonoscopy.

[This corrects the article DOI: 10.14309/crj.0000000000000174.].

Harvesting of interacting stochastic populations.

We analyze the optimal harvesting problem for an ecosystem of species that experience environmental stochasticity. Our work generalizes the current literature significantly by taking into account non-linear interactions between species, state-dependent prices, and species seeding. The key generalization is making it possible to not only harvest, but also 'seed' individuals into the ecosystem. This is motivated by how fisheries and certain endangered species are controlled. The harvesting problem becomes finding the optimal harvesting-seeding strategy that maximizes the expected total income from the harvest minus the lost income from the species seeding. Our analysis shows that new phenomena emerge due to the possibility of species seeding. It is well-known that multidimensional harvesting problems are very hard to tackle. We are able to make progress, by characterizing the value function as a viscosity solution of the associated Hamilton-Jacobi-Bellman equations. Moreover, we provide a verification theorem, which tells us that if a function has certain properties, then it will be the value function. This allows us to show heuristically, as was shown by Lungu and Øksendal (Bernoulli 7(3):527-539, 2001), that it is almost surely never optimal to harvest or seed from more than one population at a time. It is usually impossible to find closed-form solutions for the optimal harvesting-seeding strategy. In order to by-pass this obstacle we approximate the continuous-time systems by Markov chains. We show that the optimal harvesting-seeding strategies of the Markov chain approximations converge to the correct optimal harvesting strategy. This is used to provide numerical approximations to the optimal harvesting-seeding strategies and is a first step towards a full understanding of the intricacies of how one should harvest and seed interacting species. In particular, we look at three examples: one species modeled by a Verhulst-Pearl diffusion, two competing species and a two-species predator-prey system.

Pattern and frequency of use of complementary and alternative medicine among patients with epilepsy in the midwestern United States.

Complementary and alternative medicine (CAM) is recognized to be commonly used by patients, yet there have been few studies regarding the scope of CAM use by patients with epilepsy. This study assessed usage and perceptions of CAM by patients with epilepsy in the midwest of the United States. A 25-item survey was administered to adult patients with epilepsy, and data were collected from 228 patients. The survey collected demographics, specific CAM usage, adverse effects of CAM therapy, and perceptions of the effectiveness of CAM. Thirty-nine percent reported using CAM; 25% reported using CAM specifically for their epilepsy. Prayer/spirituality was the most commonly used form of CAM (46%), followed by "mega" vitamins (25%), chiropractic care (24%), and stress management (16%). CAM use is common among midwestern patients with epilepsy, although the pattern of use may be slightly different than in other regions of the United States and elsewhere.

Assessing measurement properties of two single-item general health measures.

BACKGROUND: Multi-item health status measures can be lengthy, expensive, and burdensome to collect. Single-item measures may be an alternative. We compared measurement properties of two single-item, general self-rated health (GSRH) questions to assess how well they captured information in a validated, multi-item instrument. METHODS: We administered a general health survey (SF-12V) that included "standard" and "comparative" forms of a GSRH. We repeated the survey two weeks later to the same 75 medically stable outpatients to test for GSRH reproducibility, reliability, and validity using SF-12V Physical Functioning and Emotional Health subscales as a reference. RESULTS: At each survey administration, the two GSRH questions demonstrated good alternate forms reliability (first administration: r = 0.74, p < 0.001; second administration: r = 0.74, p < 0.001) and good reproducibility ("standard": ICC 0.69; "comparative": ICC 0.85). Both GSRH items correlated with physical functioning ("standard": r = 0.66; "comparative": r = 0.56) and emotional health measures ("standard": r = 0.65; "comparative": r = 0.59). Mean subscale measures associated with responses in each GSRH category were significantly different (ANOVA, p < 0.001), indicating strong discriminant scale performance. CONCLUSIONS: Our single-item, GSRH questions demonstrated good reproducibility, reliability, and strong concurrent and discriminant scale performance with an established health status measure.