We have developed a miniature telemetry system that captures neural, EMG, and acceleration signals from a freely moving insect and transmits the data wirelessly to a remote digital receiver. The system is based on a custom low-power integrated circuit that amplifies and digitizes four biopotential signals as well as three acceleration signals from an off-chip MEMS accelerometer, and transmits this information over a wireless 920-MHz telemetry link. The unit weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts.

Electrons, because of their strong interaction with matter, produce high-resolution diffraction patterns from tiny 3D crystals only a few hundred nanometers thick in a frozen-hydrated state. This discovery offers the prospect of facile structure determination of complex biological macromolecules, which cannot be coaxed to form crystals large enough for conventional crystallography or cannot easily be produced in sufficient quantities. Two potential obstacles stand in the way. The first is a phenomenon known as dynamical scattering, in which multiple scattering events scramble the recorded electron diffraction intensities so that they are no longer informative of the crystallized molecule. The second obstacle is the lack of a proven means of de novo phase determination, as is required if the molecule crystallized is insufficiently similar to one that has been previously determined. We show with four structures of the amyloid core of the Sup35 prion protein that, if the diffraction resolution is high enough, sufficiently accurate phases can be obtained by direct methods with the cryo-EM method microelectron diffraction (MicroED), just as in X-ray diffraction. The success of these four experiments dispels the concern that dynamical scattering is an obstacle to ab initio phasing by MicroED and suggests that structures of novel macromolecules can also be determined by direct methods.

BACKGROUND: Female sexual receptivity offers an excellent model for complex behavioral decisions. The female must parse her own reproductive state, the external environment, and male sensory cues to decide whether to copulate. In the fly Drosophila melanogaster, virgin female receptivity has received relatively little attention, and its neural circuitry and individual behavioral components remain unmapped. Using a genome-wide neuronal RNAi screen, we identify a subpopulation of neurons responsible for pausing, a novel behavioral aspect of virgin female receptivity characterized in this study.

RESULTS: We show that Abdominal-B (Abd-B), a homeobox transcription factor, is required in developing neurons for high levels of virgin female receptivity. Silencing adult Abd-B neurons significantly decreased receptivity. We characterize two components of receptivity that are elicited in sexually mature females by male courtship: pausing and vaginal plate opening. Silencing Abd-B neurons decreased pausing but did not affect vaginal plate opening, demonstrating that these two components of female sexual behavior are functionally separable. Synthetic activation of Abd-B neurons increased pausing, but male courtship song alone was not sufficient to elicit this behavior.

CONCLUSIONS: Our results provide an entry point to the neural circuit controlling virgin female receptivity. The female integrates multiple sensory cues from the male to execute discrete motor programs prior to copulation. Abd-B neurons control pausing, a key aspect of female sexual receptivity, in response to male courtship.

Down syndrome (DS) is a genetic disorder that causes cognitive impairment. The staggering effects associated with an extra copy of human chromosome 21 (HSA21) complicates mechanistic understanding of DS pathophysiology. We examined the neuron-astrocyte interplay in a fully recapitulated HSA21 trisomy cellular model differentiated from DS-patient-derived induced pluripotent stem cells (iPSCs). By combining calcium imaging with genetic approaches, we discovered the functional defects of DS astroglia and their effects on neuronal excitability. Compared with control isogenic astroglia, DS astroglia exhibited more-frequent spontaneous calcium fluctuations, which reduced the excitability of co-cultured neurons. Furthermore, suppressed neuronal activity could be rescued by abolishing astrocytic spontaneous calcium activity either chemically by blocking adenosine-mediated signaling or genetically by knockdown of inositol triphosphate (IP3) receptors or S100B, a calcium binding protein coded on HSA21. Our results suggest a mechanism by which DS alters the function of astrocytes, which subsequently disturbs neuronal excitability.

Amyloid fibrils characterize a diverse group of human diseases that includes Alzheimer’s disease, Creutzfeldt-Jakob and type II diabetes. Alzheimer’s amyloid fibrils consist of amyloid-beta (Abeta) peptide and occur in a range of structurally different fibril morphologies. The structural characteristics of 12 single Abeta(1-40) amyloid fibrils, all formed under the same solution conditions, were determined by electron cryo-microscopy and three-dimensional reconstruction. The majority of analyzed fibrils form a range of morphologies that show almost continuously altering structural properties. The observed fibril polymorphism implies that amyloid formation can lead, for the same polypeptide sequence, to many different patterns of inter- or intra-residue interactions. This property differs significantly from native, monomeric protein folding reactions that produce, for one protein sequence, only one ordered conformation and only one set of inter-residue interactions.

Disrupted-in-Schizophrenia-1 (DISC1) is a genetic susceptibility locus for major mental illness, including schizophrenia and depression. The Disc1 protein was recently shown to interact with the Wnt signaling protein, DIX domain containing 1 (Dixdc1). Both proteins participate in neural progenitor proliferation dependent on Wnt signaling, and in neural migration independently of Wnt signaling. Interestingly, their effect on neural progenitor proliferation is additive. By analogy to Disc1, mutations in Dixdc1 may lead to abnormal behavior in mice, and to schizophrenia or depression in humans. To explore this hypothesis further, we generated mice mutant at the Dixdc1 locus and analyzed their behavior. Dixdc1(-/-) mice had normal prepulse inhibition, but displayed decreased spontaneous locomotor activity, abnormal behavior in the elevated plus maze and deficits in startle reactivity. Our results suggest that Dixdc1(-/-) mice will be a useful tool to elucidate molecular pathophysiology involving Disc1 in major mental illnesses.

In tandem ring-closing metathesis of alkynyl silaketals containing two different tethered olefins, the gem-dimethyl group showed the expected Thorpe-Ingold effect, thereby giving good level of group selectivity. Unexpectedly, however, the corresponding gem-diphenyl group did not show any Thorpe-Ingold effect for the ring closure reaction.

Circulating tumor cells (CTCs) are critical biomarkers for predicting therapy response and survival in breast cancer patients. Multicellular CTC clusters exhibit enhanced metastatic potential, yet their detection and characterization are constrained by low frequency in blood samples and reliance on labor-intensive manual analysis. Advancing these methods could significantly improve prognostic evaluation and therapeutic strategies.Leveraging FDA-approved CellSearch technology and single-cell sequencing, we analyzed 2, 853 blood specimens, longitudinally collected from 1358 patients with advanced cancer (breast, prostate, etc) and other diseases. Integrating machine learning and deep learning tools, we developed a novel CTCpose platform to automate detection and analysis of CTCs, immune cells, and their interactions. Using artificial intelligence (AI)-driven image analysis, we extracted over 270 cellular and nuclear features including intensity, morphometry, fourier shape, gradient/edge, and haralick of cytokeratin, CD45, and DAPI expression patterns, enabling precise characterization of CTCs, white blood cells (WBCs), CTC clusters, and their interactions with immune cells (WBCs).The CTCpose platform enabled automated identification of CTCs, WBCs, homotypic CTC clusters, heterogenous CTC-WBC clusters, and immune cell clusters, providing comprehensive insights into cell morphology, biomarker expression, and spatial organization. These features correlated with patient survival, disease progression, and treatment response. Our findings highlight the clinical significance of CTC-immune cell interactions and dynamic alterations of CTCs (singles and clusters) and underscore their potential in stratifying patients into distinct risk categories.This study demonstrates the transformative potential of deep learning in overcoming limitations of traditional CTC detection methods and integrating imaging data with large cohorts of patient data. By automating and enhancing the analysis of CTC-immune cell interactions, we present a robust framework for developing predictive models with direct clinical relevance. This work opens avenues for personalized treatment strategies, underscoring the impact of AI in advancing precision oncology.Yuanfei Sun, Joshua R. Squires, Andrew Hoffmann, Youbin Zhang, Allegra Minor, Anmol Singh, David Scholten, Chengsheng Mao, Yuan Luo, Deyu Fang, William J. Gradishar, Massimo Cristofanilli, Carsen Stringer, Huiping Liu. Deep learning enables automated detection of circulating tumor cell-immune cell interactions with prognostic insights in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2420.

Spatial multiomic profiling has been transforming the understanding of local tumor ecosystems. Yet, the spatial analyses of tumor-immune interactions at systemic levels, such as in liquid biopsies, are challenging. Within the last 10 years, we have longitudinally collected nearly 3,000 patient blood samples for multiplexing imaging of circulating tumor cells (CTCs) and their interactions with white blood cells (WBCs). Multicellular CTC clusters exhibit enhanced metastatic potential. The detection of CTCs and characterization of tumor immune ecosystems are constrained by (1) low frequency of CTCs in blood samples; (2) specific lineages of immune cells are not recognized by limited channels of current imaging methods, (3) reliance on labor-intensive manual analysis slows down the discovery of biomarkers for predicting therapy response and survival in cancer patients. We hypothesize that an AI-powered platform will accelerate the lineage and spatial characterization of tumor immune ecosystems for prognostic evaluations.

Medial frontal cortical areas are thought to play a critical role in the brain's ability to flexibly deploy strategies that are effective in complex settings. Still, the specific circuit computations that underpin this foundational aspect of intelligence remain unclear. Here, by examining neural ensemble activity in rats that sample different strategies in a self-guided search for latent task structure, we demonstrate a robust tracking of individual strategy prevalence in the anterior cingulate cortex (ACC), especially in an area homologous to primate area 32D. Prevalence encoding in the ACC is wide-scale, independent of reward delivery, and persists through a substantial ensemble reorganization that tags ACC representations with contextual content. Our findings argue that ACC ensemble dynamics is structured by a summary statistic of recent behavioral choices, raising the possibility that ACC plays a role in estimating - through statistical learning - which actions promote the occurrence of events in the environment.