University of Wisconsin System

Individual animal identification is crucial for dairy cattle management, regulatory compliance, and enhancing food security. Although computer vision systems (CVS) have been proposed for noninvasive animal recognition, limited research has explored their capability to identify the same individual across various life phases and in open-set scenarios. This study evaluated the efficacy of Siamese neural networks (SNN) for identifying individual dairy cattle throughout extensive periods of growth and physiological change. The primary objectives were to (1) leverage a semi-supervised approach to compile and augment datasets, (2) investigate the effects of temporal growth on SNN-based identification model performance, and (3) evaluate open-set inference capabilities in real-world applications. We collected and processed 2,397,338 infrared and depth images from 106 Holstein heifers spanning from birth to first lactation (average 803 d of age). Images underwent comprehensive preprocessing including semantic segmentation via U-Net architecture, binary classification of mask quality, and image augmentation. The SNN architecture utilized a ResNet-50 backbone with L2-normalized 128-dimensional embedding vectors and was trained using categorical cross-entropy and triplet loss functions. Our best-performing model, integrating data from preweaning through 12-mo phases, achieved an accuracy of 0.946, mean average precision of 0.964, and an F1-score of 0.939 when identifying lactating animals in closed-set evaluation using 15 support images. In open-set inference under real-world farm conditions with unknown animals present, the model maintained F1-scores exceeding 0.80 across all growth phases. Infrared imaging consistently outperformed depth imaging for longitudinal identification. These findings demonstrate the feasibility of CVS for noninvasive cattle traceability across different growth phases and environmental conditions, with further research needed to validate performance in diverse commercial settings and across multiple herds.

Severe rhinovirus (RV)/enterovirus (EV) respiratory infections in pediatric patients increased in the US during 2022-2023. This study aimed to characterize RV/EV genetic diversity among hospitalized children in Wisconsin and describe demographic and clinical factors of patients by RV/EV type. During September 2022-April 2023, five Wisconsin pediatric hospitals submitted five RV/EV-positive specimens weekly to CDC. Viral typing was performed using partial viral protein (VP) 4/VP2 (RV) and VP1 (EV) sequencing. Wisconsin Department of Health Services abstracted demographic, comorbid condition, and hospitalization course information from patient medical records. Ninety-six patients were included in this investigation. RV-C (n = 40, 42%) and RV-A (n = 31, 32%) were the most frequently detected species, with 46 RV and 5 EV types identified. The median age was 2.5 (IQR: 0.7-5.5) years. Seventy-one (74%) children had at least one comorbid condition. Asthma was more common among children with RV-C infections (n = 12, 30%) compared with other RVs (n = 3, 9%) (p = 0.02). RV-A and RV-C were important contributors to severe pediatric respiratory infection in Wisconsin. Molecular typing showed virus divergence typically observed during season-long investigations. Year-round molecular characterization is needed to better understand the contribution of RV/EV types to severe pediatric respiratory illness.

Bulk tissue rhythms arise from the coordination of thousands of individual cellular oscillations. Bulk rhythm amplitude differences may reflect changes in the amplitude of the underlying cellular oscillators or changes in their temporal coherence. To resolve this fundamental ambiguity, we developed ORPHEUS ( O scillatory R hythm P hase H eterogeneity E stimated U sing S tatistical-moments), an analytical method that quantifies cellular desynchrony by leveraging the unique 12hr rhythmic signature it imparts on intercellular expression variance. After validating ORPHEUS in silico and on data from the mouse suprachiasmatic nucleus (SCN), we applied it to data from the mouse liver and human brain to uncover disease- and pathway-related differences in intercellular synchrony. In both tissues, we found that circadian synchrony is higher in cells and samples with higher MTORC activity. Most critically, we observed a dramatic loss of cellular synchrony in excitatory neurons from subjects with Alzheimer's Disease (AD) dementia. By decoupling the influence of cellular amplitude and synchrony, ORPHEUS introduces a new, interpretable tool for analyzing circadian coordination in time-course single-cell data.

ABSTRACT Following the evolution of internal fertilisation, the female reproductive tract became the site of reproductive interactions. However, our understanding of the evolution of female reproductive tract function, including postmating responses critical for reproductive success, are taxonomically limited. Traumatic insemination in the common bedbug ( Cimex lectularius ) presents an unusual scenario under which postmating responses unfold. Bedbugs have evolved a novel organ, the mesospermalege, that is the site of initial ejaculate × female interactions. As the female reproductive tract does not take receipt of the ejaculate until several hours after mating, bedbugs provide a unique opportunity to explore the evolution of a novel reproductive organ that decouples postmating female responses involved in mating and transfer of the ejaculate from sperm storage, ovulation, and oviposition. Here we show that the mesospermalege has a gene expression profile consistent with functions of ejaculate processing and immune response normally found in the lower reproductive tract of other insect species. In parallel, the postmating response in the lower female reproductive tract is delayed, coinciding with movement of sperm through the female, clearly showing that the postmating response has evolved in response to sperm receipt rather than being an innate function of the tissue. Notably, we also found expression of male seminal fluid genes in the mesospermalege, indicating that intersexual molecular dynamics influence the evolution of reproductive tissues. Our results provide insights into the evolution of novel reproductive traits and female postmating physiology in a global pest with an unusual reproductive biology. SIGNIFICANCE Reproduction poses one of the most persistent challenges faced by animals whereby females undergo a series of physiological changes after mating. The independent origin of a reproductive organ in bedbugs (called the mesospermalege) which has evolved to alleviate the costs of traumatic insemination presents a unique case to study the evolution of a novel trait and postmating physiology. Using transcriptomics, we show that many genes normally expressed in the female reproductive tract are instead expressed in the mesospermalege. The reproductive tract also shows a delayed postmating transcriptional response coinciding with sperm entry into the reproductive tract. Our results provide insights into the evolution of reproductive traits and female postmating physiology in a global pest with an unusual reproductive biology.

Studies of multiple mantle exposures indicate that a fundamental shift occurs in polymineralic peridotites at ~850° C. At these temperatures, there is a shift from dislocation creep (plus or minus dislocation accommodated grain boundary sliding) to reaction-facilitated grain-size sensitive creep. This reaction results in a fine-grained matrix produced by neocrystallization. The fine-grained shear zones that formed by dislocation creep dynamic recrystallization create increased grain-boundary surface area that localize the reaction-enhanced deformation. Because the grains are formed by reaction, grain boundary pinning of the different mineral phases occurs. Moreover, these fine-grain sizes are preserved during exhumation, because of the grain boundary pinning. Thus, the fine-grain size – once it has been formed by reaction-facilitated deformation – continues to exist even if there is a change in temperature. This rheological behavior is not typically shown in deformation strength profiles, because monophase olivine does not show these effects. Yet, the lithospheric mantle is polyphase, and we have observed evidence for reaction-facilitated deformation that occurred below ~850° C. Once grain size reduction has occurred in a polyphase material, it is not expected to grow large grain sizes again, due to the role of grain boundary pinning. Thus, once formed, a reaction-facilitated shear zone with smaller grain size relative to the surrounding mantle rocks would remain a lithospheric “scar”. The fine-grain shear zones would preferentially reactivate because the zone can deform by grain-size sensitive creep at lower stress conditions that the surrounding mantle material can deform by dislocation creep. This interpretation could explain the common reactivation of transform faults, and perhaps even extensional faults, in orogenic belts. Reactivation of transform faults in the mantle may explain: 1) the Neoproterozoic transform faults of the eastern and western United States, which are reactivated by Pennsylvanian and Cretaceous deformation, respectively; and 2) the modern San Andreas System reactivating a Cretaceous – Paleogene proto San Andreas Fault.

As part of the celebration of 25 years of interactive open access publishing at the EGU, the Co-Chief Editors of Biogeosciences invite the community to an interactive PICO presentation reflecting on the journal’s development, its scientific diversity, and its continuing role in advancing integrative Earth system science.Founded in 2004, Biogeosciences is an open access EGU journal grounded in a transparent, community-driven peer-review process. The journal publishes research that brings together biological, chemical, and physical perspectives to improve understanding of Earth system functioning across terrestrial, freshwater, coastal, oceanic, and atmospheric environments. Key themes include biogeochemical cycles, ecosystem dynamics, microbial processes, land–ocean–atmosphere linkages, and Earth system feedbacks, drawing on approaches such as field and laboratory studies, numerical modelling, remote sensing, and data-integrative analyses. Biogeosciences publishes Research Articles, Letters, Reviews and Syntheses, Ideas and Perspectives, Technical Notes, and Comments, and actively supports community-driven Special Issues that foster scientific exchange across disciplines.The PICO session will offer an opportunity to learn more about the Biogeosciences editorial workflow, including how interdisciplinary scope and scientific significance are evaluated and how authors and reviewers engage during the open public discussion phase on EGUsphere.We warmly welcome researchers at all career stages who are interested in transparent, interdisciplinary, and not-for-profit publishing to join the conversation, share ideas, ask questions, and celebrate Biogeosciences as part of the EGU’s interactive open access community.

Two new species of Ficus sect. Pharmacosycea subsect. Bergianae from Ecuador are described herein. The first, Ficus montalvoana, occurs at Andean elevations and, among other diagnostic characters such as velutinous leaves, exhibits a peduncle and receptacle significantly smaller than those of its related congener, Ficus dulciaria. The second species, Ficus penafieliae, occurs in western Ecuador and is distinguished by its glabrous leaves and geminate, sessile syconia, which are relatively small compared to those of its related congener, F. crassivenosa. Both species honor two renowned Ecuadorian researchers.

Abstract Cognitive Flexibility (CF) is the ability to switch between tasks, even under conditions when the need to switch is not explicitly cued. While the prefrontal cortex and its interaction with subcortical regions are considered central to CF, a key question remains: what are the underlying computational mechanisms that implement the switch from one task to another? In particular, does the switch rely on 1) learning processes in which synaptic changes directly alter action execution choice, or 2) neural state processes that estimate a belief state from which actions can be chosen? Bartolo and Averbeck (2020) argue for the neural state change hypothesis, proposing a Bayesian belief state estimation model, and ruling out Reinforcement Learning as an approach to modeling CF tasks because of its reliance on synaptic changes to implement the switch. We propose instead a Reinforcement Learning-based Deep Recurrent Q-Learning (DRQL) model that simultaneously learns to update a belief state representation based on prior action outcomes, and an action preference representation based on this belief state. This model is presented with a repeated-trial, force-choice probability switching task (PST) in which actions are rewarded stochastically, and the reward probabilites switch between blocks of trials. Although the model is not explicitly cued to the task type, probability of reward, or time of switch, following training, the model performs the PST in the absence of synaptic changes. We show that the trained model produces behavior consistent with non-human primates performing a similar task, and that it develops a belief state representation that captures key information about the current state of the task. Significance Statement The proposed DRQL model learns to perform the PST, even when reward probabilities vary across different blocks of trials. Behaviorally, the trained model requires different amounts of time to commit to a task switch, depending on the uncertainty of the reward information, with quicker switches for more certain outcomes. The learned belief state and other computed measures may give insight into the neural mechanisms underlying task switching in the primate brain. In contrast with other approaches, the DRQL model presents a more biologically tractable solution to CF, as it is easily adapted to other forms of the PST task, including altering the number of possible actions and the rules for providing rewards.

Abstract Soybean cyst nematode (SCN, Heterodera glycines ) causes significant soybean yield losses. The Rhg1 locus is a major contributor to SCN resistance and contains three genes that mediate this trait including Rhg1-GmAAT ( Glyma.18G022400), which encodes putative amino acid transporter AAT Rhg1 . The molecular function of AAT Rhg1 in SCN resistance is not understood. In this study, rhg1-b soybean lines with Rhg1-GmAAT silencing demonstrated that Rhg1-GmAAT can contribute resistance against HG 0 SCN and also against problematic HG 2.5.7 populations that partially overcome rhg1-b -mediated resistance. An AAT Rhg1 Y268L mutant complemented SCN resistance in Rhg1-GmAAT -silenced plants while an AAT Rhg1 D122A mutant did not. Overexpression of Rhg1-GmAAT was not sufficient to enhance SCN resistance, suggesting that AAT Rhg1 requires coordinated activity with other proteins or pathways. Confocal microscopy demonstrated that AAT Rhg1 localizes to the tonoplast in soybean root cells. Amino acid, transcriptomic and metabolomic profiles were determined for SCN-infected root segments 3 days after SCN inoculation. In Rhg1-GmAAT -silenced plants relative to fully resistant (non-silenced) rhg1-b plants, levels of leucine, isoleucine, and tyrosine were significantly elevated. Rhg1-GmAAT silencing reduced SCN-responsive transcript abundances for multiple processes, significantly including genes for MAPK signaling, ethylene responses and starch and sucrose metabolism. The most common identified metabolomic changes were in amino acid derivatives, shikimate/phenylpropanoid/isoflavonoid compounds, terpenoids, and especially fatty acids. These findings can guide further investigation into the mechanisms by which AAT Rhg1 contributes to SCN resistance.