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The cap-pushing response (CPR) is a new free-flying technique used to study learning and memory in honey bees. Bees fly to a target where they push a cap to reveal a hidden food source. When combined with traditional odor and color targets, the CPR technique opens the door to additional choice preference tests in honey bees. To facilitate the use of the CPR technique, three experiments were conducted. Experiment 1 investigates the impact of extended training on the CPR response and its role in extinction. Experiment 2 explores the role of CPR in overshadowing, and Experiment 3 explores the effects of electric shock punishment on the CPR technique. (PsycInfo Database Record (c) 2023 APA, all rights reserved) 

The cap pushing response (CPR) is a free flying technique where honey bees are trained to fly to a target where they push a cap to reveal a hidden food source. In this paper, we report the results of three studies. First, we provide information on three techniques used to shape the CPR. Second, we provide preliminary data suggesting that honey bees can learn the CPR through observing a previously shaped bee. Finally, we provide data on the ability of a honey bee to recall the CPR response. In addition to the three studies, we also continue to advocate for the use of Observation Orientated Modeling (OOM) for comparative investigations. 

Coral reef soundscapes are increasingly studied for their ecological uses by invertebrates and fishes, for monitoring habitat quality, and to investigate effects of anthropogenic noise pollution. Few examinations of aquatic soundscapes have reported particle motion levels and variability, despite their relevance to invertebrates and fishes. In this study, ambient particle acceleration was quantified from orthogonal hydrophone arrays over several months at four coral reef sites, which varied in benthic habitat and fish communities. Time-averaged particle acceleration magnitudes were similar across axes, within 3 dB. Temporal trends of particle acceleration corresponded with those of sound pressure, and the strength of diel trends in both metrics significantly correlated with percent coral cover. Higher magnitude particle accelerations diverged further from pressure values, potentially representing sounds recorded in the near field. Particle acceleration levels were also reported for boat and example fish sounds. Comparisons with particle acceleration derived audiograms suggest the greatest capacity of invertebrates and fishes to detect soundscape components below 100 Hz, and poorer detectability of soundscapes by invertebrates compared to fishes. Based on these results, research foci are discussed for which reporting of particle motion is essential, versus those for which sound pressure may suffice. 

Abstract Harmful algal blooms produce potent neurotoxins that accumulate in seafood and are hazardous to human health. Developmental exposure to the harmful algal bloom toxin, domoic acid (DomA), has behavioral consequences well into adulthood, but the cellular and molecular mechanisms of DomA developmental neurotoxicity are largely unknown. To assess these, we exposed zebrafish embryos to DomA during the previously identified window of susceptibility and used the well-known startle response circuit as a tool to identify specific neuronal components that are targeted by exposure to DomA. Exposure to DomA reduced startle responsiveness to both auditory/vibrational and electrical stimuli, and even at the highest stimulus intensities tested, led to a dramatic reduction of one type of startle (short latency c-starts). Furthermore, DomA-exposed larvae had altered kinematics for both types of startle responses tested, exhibiting shallower bend angles and slower maximal angular velocities. Using vital dye staining, immunolabelling, and live imaging of transgenic lines, we determined that while the sensory inputs were intact, the reticulospinal neurons required for short latency c-starts were absent in most DomA-exposed larvae. Furthermore, axon tracing revealed that DomA-treated larvae also showed significantly reduced primary motor neuron axon collaterals. Overall, these results show that developmental exposure to DomA targets large reticulospinal neurons and motor neuron axon collaterals, resulting in measurable deficits in startle behavior. They further provide a framework for using the startle response circuit to identify specific neural populations disrupted by toxins or toxicants and to link these disruptions to functional consequences for neural circuit function and behavior. 

A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures. 

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol⁻¹at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases.