Transdiagnostic failure to adapt interoceptive precision estimates across affective, substance use, and eating disorders: A replication and extension of previous results.

Recent Bayesian theories of interoception suggest that perception of bodily states rests upon a precision-weighted integration of afferent signals and prior beliefs. In a previous study, we fit a computational model of perception to behavior on a heartbeat tapping task to test whether aberrant precision-weighting could explain misestimation of cardiac states in psychopathology. We found that, during an interoceptive perturbation designed to amplify afferent signal precision (inspiratory breath-holding), healthy individuals increased the precision-weighting assigned to ascending cardiac signals (relative to resting conditions), while individuals with anxiety, depression, substance use disorders, and/or eating disorders did not. In this pre-registered study, we aimed to replicate and extend our prior findings in a new transdiagnostic patient sample (N = 285) similar to the one in the original study. As expected, patients in this new sample were also unable to adjust beliefs about the precision of cardiac signals - preventing the ability to accurately perceive changes in their cardiac state. Follow-up analyses combining samples from the previous and current study (N = 719) also afforded power to identify group differences between narrower diagnostic categories, and to examine predictive accuracy when logistic regression models were trained on one sample and tested on the other. With this confirmatory evidence in place, future studies should examine the utility of interceptive precision measures in predicting treatment outcomes and test whether these computational mechanisms might represent novel therapeutic targets.

Transdiagnostic failure to adapt interoceptive precision estimates across affective, substance use, and eating disorders: A replication study.

Recent computational theories of interoception suggest that perception of bodily states rests upon an expected reliability- or precision-weighted integration of afferent signals and prior beliefs. The computational psychiatry framework further suggests that aberrant precision-weighting may lead to misestimation of bodily states, potentially hindering effective visceral regulation and promoting psychopathology. In a previous study, we fit a Bayesian computational model of perception to behavior on a heartbeat tapping task to test whether aberrant precision-weighting was associated with misestimation of bodily states. We found that, during an interoceptive perturbation designed to amplify afferent signal precision (inspiratory breath-holding), healthy individuals increased the precision-weighting assigned to ascending cardiac signals (relative to resting conditions), while individuals with symptoms of anxiety, depression, substance use disorders, and/or eating disorders did not. A second study also replicated the pattern observed in healthy participants. In this pre-registered study, we aimed to replicate our prior findings in a new transdiagnostic patient sample (N=285) similar to the one in the original study. These new results successfully replicated those found in our previous study, indicating that, transdiagnostically, patients were unable to adjust beliefs about the reliability of interoceptive signals - preventing the ability to accurately perceive changes in their bodily state. Follow-up analyses combining samples from the previous and current study (N=719) also afforded the power to identify group differences within narrower diagnostic groups and to examine predictive accuracy when logistic regression models were trained on one sample and tested on the other. Given the increased confidence in the generalizability of these effects, future studies should examine the utility of interceptive precision measures in predicting treatment outcomes or identify whether these computational mechanisms might represent novel therapeutic targets for improving visceral regulation.

Active learning impairments in substance use disorders when resolving the explore-exploit dilemma: A replication and extension of previous computational modeling results.

BACKGROUND: Substance use disorders (SUDs) represent a major public health risk. Yet, our understanding of the mechanisms that maintain these disorders remains incomplete. In a recent computational modeling study, we found initial evidence that SUDs are associated with slower learning rates from negative outcomes and less value-sensitive choice (low "action precision"), which could help explain continued substance use despite harmful consequences. METHODS: Here we aimed to replicate and extend these results in a pre-registered study with a new sample of 168 individuals with SUDs and 99 healthy comparisons (HCs). We performed the same computational modeling and group comparisons as in our prior report (doi: 10.1016/j.drugalcdep.2020.108208) to confirm previously observed effects. After completing all pre-registered replication analyses, we then combined the previous and current datasets (N = 468) to assess whether differences were transdiagnostic or driven by specific disorders. RESULTS: Replicating prior results, SUDs showed slower learning rates for negative outcomes in both Bayesian and frequentist analyses (partial η2=.02). Previously observed differences in action precision were not confirmed. Learning rates for positive outcomes were also similar between groups. Logistic regressions including all computational parameters as predictors in the combined datasets could differentiate several specific disorders from HCs, but could not differentiate most disorders from each other. CONCLUSIONS: These results provide robust evidence that individuals with SUDs adjust behavior more slowly in the face of negative outcomes than HCs. They also suggest this effect is common across several different SUDs. Future research should examine its neural basis and whether learning rates could represent a new treatment target or moderator of treatment outcome.

Active learning impairments in substance use disorders when resolving the explore-exploit dilemma: A replication and extension of previous computational modeling results.

Background: Substance use disorders (SUDs) represent a major public health risk. Yet, our understanding of the mechanisms that maintain these disorders remains incomplete. In a recent computational modeling study, we found initial evidence that SUDs are associated with slower learning rates from negative outcomes and less value-sensitive choice (low "action precision"), which could help explain continued substance use despite harmful consequences. Methods: Here we aimed to replicate and extend these results in a pre-registered study with a new sample of 168 individuals with SUDs and 99 healthy comparisons (HCs). We performed the same computational modeling and group comparisons as in our prior report (doi: 10.1016/j.drugalcdep.2020.108208) to confirm previously observed effects. After completing all pre-registered replication analyses, we then combined the previous and current datasets (N = 468) to assess whether differences were transdiagnostic or driven by specific disorders. Results: Replicating prior results, SUDs showed slower learning rates for negative outcomes in both Bayesian and frequentist analyses (η 2 =.02). Previously observed differences in action precision were not confirmed. Logistic regressions including all computational parameters as predictors in the combined datasets could differentiate several specific disorders from HCs, but could not differentiate most disorders from each other. Conclusions: These results provide robust evidence that individuals with SUDs have more difficulty adjusting behavior in the face of negative outcomes than HCs. They also suggest this effect is common across several different SUDs. Future research should examine its neural basis and whether learning rates could represent a new treatment target or moderator of treatment outcome.

Handheld instrument for wound-conformal delivery of skin precursor sheets improves healing in full-thickness burns.

The current standard of care for patients with severe large-area burns consists of autologous skin grafting or acellular dermal substitutes. While emerging options to accelerate wound healing involve treatment with allogeneic or autologous cells, delivering cells to clinically relevant wound topologies, orientations, and sizes remains a challenge. Here, we report the one-step in situ formation of cell-containing biomaterial sheets using a handheld instrument that accommodates the topography of the wound. In an approach that maintained cell viability and proliferation, we demonstrated conformal delivery to surfaces that were inclined up to 45° with respect to the horizontal. In porcine pre-clinical models of full-thickness burn, we delivered mesenchymal stem/stromal cell-containing fibrin sheets directly to the wound bed, improving re-epithelialization, dermal cell repopulation, and neovascularization, indicating that this device could be introduced in a clinical setting improving dermal and epidermal regeneration.

Handheld skin printer: in situ formation of planar biomaterials and tissues.

We present a handheld skin printer that enables the in situ formation of biomaterial and skin tissue sheets of different homogeneous and architected compositions. When manually positioned above a target surface, the compact instrument (weight <0.8 kg) conformally deposits a biomaterial or tissue sheet from a microfluidic cartridge. Consistent sheet formation is achieved by coordinating the flow rates at which bioink and cross-linker solution are delivered, with the speed at which a pair of rollers actively translate the cartridge along the surface. We demonstrate compatibility with dermal and epidermal cells embedded in ionically cross-linkable biomaterials (e.g., alginate), and enzymatically cross-linkable proteins (e.g., fibrin), as well as their mixtures with collagen type I and hyaluronic acid. Upon rapid crosslinking, biomaterial and skin cell-laden sheets of consistent thickness, width and composition were obtained. Sheets deposited onto horizontal, agarose-coated surfaces were used for physical and in vitro characterization. Proof-of-principle demonstrations for the in situ formation of biomaterial sheets in murine and porcine excisional wound models illustrate the capacity of depositing onto inclined and compliant wound surfaces that are subject to respiratory motion. We expect the presented work will enable the in situ delivery of a wide range of different cells, biomaterials, and tissue adhesives, as well as the in situ fabrication of spatially organized biomaterials, tissues, and biohybrid structures.

3D shape evolution of microparticles and 3D enabled applications using non-uniform UV flow lithography (NUFL).

The generation of microparticles with non-spherical morphologies has generated extensive interest because of their enhanced physical properties that can increase their performance in a wide variety of clinical and industrial applications. A flow lithographic technique based on stop flow lithography (SFL) recently showed the ability to fabricate particles with 3D shapes via manipulation of the UV intensity profile in a simple 2D microfluidic channel. Here, we further explore this flow lithographic method, called non-uniform flow lithography (NUFL), to investigate the 3D-shape tuning ability for the generation of 3D magnetic microparticles and their potential applications. We characterize the morphological microparticle shape change through variation of polymerization objective, UV intensity, and solution opacity. We also couple the particles' intrinsic anisotropic magnetic properties with an external magnetic field to create chains of bullet- and bell-shaped particles and a valve-like micromachine. In addition, in contrast to other complex and multi-step methodologies, NUFL shows a simple route for the facile creation of 3D microstructure platforms such as microneedles with fully modifiable tip morphology. This method presents intriguing possibilities for growing research within 3D microstructure assembly, micromachine systems and minimally invasive medical interventions.

Microfluidic conformal coating of non-spherical magnetic particles.

We present the conformal coating of non-spherical magnetic particles in a co-laminar flow microfluidic system. Whereas in the previous reports spherical particles had been coated with thin films that formed spheres around the particles; in this article, we show the coating of non-spherical particles with coating layers that are approximately uniform in thickness. The novelty of our work is that while liquid-liquid interfacial tension tends to minimize the surface area of interfaces-for example, to form spherical droplets that encapsulate spherical particles-in our experiments, the thin film that coats non-spherical particles has a non-minimal interfacial area. We first make bullet-shaped magnetic microparticles using a stop-flow lithography method that was previously demonstrated. We then suspend the bullet-shaped microparticles in an aqueous solution and flow the particle suspension with a co-flow of a non-aqueous mixture. A magnetic field gradient from a permanent magnet pulls the microparticles in the transverse direction to the fluid flow, until the particles reach the interface between the immiscible fluids. We observe that upon crossing the oil-water interface, the microparticles become coated by a thin film of the aqueous fluid. When we increase the two-fluid interfacial tension by reducing surfactant concentration, we observe that the particles become trapped at the interface, and we use this observation to extract an approximate magnetic susceptibility of the manufactured non-spherical microparticles. Finally, using fluorescence imaging, we confirm the uniformity of the thin film coating along the entire curved surface of the bullet-shaped particles. To the best of our knowledge, this is the first demonstration of conformal coating of non-spherical particles using microfluidics.

One-step two-dimensional microfluidics-based synthesis of three-dimensional particles.

Synthesis of three-dimensional anisotropic microparticles using a simple one-step microfluidic-based method is described. The method exploits the nonuniformity of the polymerizing UV light, UV absorption by opaque nanoparticles in the precursor solution, and discontinuous photomask patterns to make magnetic and non-magnetic microparticles in a twodimensional microchannel. Numerical simulations of monomer conversion in the microfluidic channel are performed to predict the manufactured particle shape.