bluuebunny/crossref_metadata_2025 huggingface dataset:
A modular model of immune response as a computational platform to investigate a pathogenesis of infection disease
Authors: Miroshnichenko Maxim , Kolpakov Fedor Anatolyevich , Akberdin Ilya Rinatovich
Published: October 2024

The COVID-19 pandemic significantly transformed the field of mathematical modeling in immunology. International collaboration among numerous research groups yielded a substantial amount of experimental data, which greatly facilitated model validation and led to the development of new mathematical models. The aim of the study is an improvement of system understanding of the immune response to SARS-CoV-2 infection based on the development of a modular mathematical model which provides a foundation for further research on host-pathogen interactions. We utilized the open-source BioUML platform to develop a model using ordinary, delay and stochastic differential equations. The model was validated using experimental data from middle-aged individuals with moderate COVID-19 progression, including measurements of viral load, antibodies, CD4+ and CD8+ T cells, and interleukin-6 levels. Parameter optimization and sensitivity analysis were conducted to refine the model`s accuracy. The model effectively reproduces moderate, severe, and critical COVID-19 progressions, consistent with experimental observations. We investigated the efficiency and contributions of innate and adaptive immunity in response to SARS-CoV-2 infection and assessed immune system behavior during co-infection with HIV and organ transplantation. Additionally, we studied therapy methods, such as interferon administration. The developed model can be employed as a framework for simulating other infectious diseases taking into account follow-up immune response.
When Attention Hurts: The Effect Of rTMS On Neural Correlates Of Time Perception
Authors: Contò Federica , Ellena Giulia , Tosi Michele , Peatfield Nicholas A. , Battelli Lorella
Published: October 2024

The parietal lobe plays a crucial role in the attentional networks that help shape our perception, including our perception of time. Based on neuropsychological and neurophysiological evidence, a “when” pathway including the right parietal lobe has been proposed as the critical cortical site for the discrimination of objects across time. When an oddball stimulus is presented in a stream of identical standard stimuli, it is perceived as lasting longer, even when its actual duration is shorter. While attentional capture seems to play a major role in this subjective expansion of time the cortical mechanisms responsible for this effect remain unclear. We therefore set to investigate the direct role of parietal brain areas in time perception using combined repetitive transcranial magnetic stimulation (rTMS) and electroencephalogram (EEG). We measured the perceived duration of an oddball stimulus in each participant before and after inhibitory 1-Hz rTMS stimulation at one of three scalp locations: the right intraparietal sulcus (rIPS), the right inferior parietal lobe (rIPL), or the occipital cortex as a control. EEG was recorded throughout. Stimulation over the rIPL caused a more veridical experience of times subjective expansion towards the oddball, while rTMS over the rIPS and the occipital cortex had no effect. These data provide theoretically challenging notions to the concept of the cortexes role within time perception and the mechanisms involved.
Spontaneous emergence and drifting of sequential neural activity in recurrent networks
Authors: Shao Shuai , Riquelme Juan Luis , Gjorgjieva Julijana
Published: October 2024

Repeating sequences of neural activity exist across diverse brain regions of different animals and are thought to underlie diverse computations. However, their emergence and evolution in the presence of ongoing synaptic plasticity remain poorly understood. To gain mechanistic insights into this process, we modeled how biologically-inspired rules of activity-dependent synaptic plasticity in recurrent circuits interact to produce connectivity structures that support sequential neuronal activity. Even under unstructured inputs, our recurrent networks developed strong unidirectional connections, resulting in spontaneous repeating spiking sequences. During ongoing plasticity these sequences repeated despite turnover of individual synaptic connections, a process reminiscent of synaptic drift. The turnover process occurred over different timescales, with certain connectivity types and motif structures leading to sequences with different volatility. Structured inputs could reinforce or retrain the resulting connectivity structures underlying sequences, enabling stable but still flexible encoding of inputs. Our model unveils the interplay between synaptic plasticity and sequential activity in recurrent networks, providing insights into how brains implement reliable but flexible computations.
A rich conformational palette underlies human CaV2.1-channel availability
Authors: Wang Kaiqian , Nilsson Michelle , Angelini Marina , Olcese Riccardo , Elinder Fredrik , Pantazis Antonios
Published: October 2024

Depolarization-evoked opening of CaV2.1 (P/Q-type) Ca2+-channels triggers neurotransmitter release, while voltage-dependent inactivation (VDI) limits channel availability to open, contributing to synaptic plasticity. The mechanism of CaV2.1 response to voltage is unclear. Using voltage-clamp fluorometry and kinetic modeling, we optically tracked and physically characterized the structural dynamics of the four CaV2.1 voltage-sensor domains (VSDs). VSD-I seems to directly drive opening and convert between two modes of function, associated with VDI. VSD-II is apparently voltage-insensitive. VSD-III and VSD-IV sense more negative voltages and undergo voltage-dependent conversion uncorrelated with VDI. Auxiliary β-subunits regulate VSD-I-to-pore coupling and VSD conversion kinetics. CaV2.1 VSDs are differentially sensitive to voltage changes brief and long-lived. Specifically the voltage-dependent conformational changes of VSD-I are linked to synaptic release and plasticity.
Refined Myocardium Segmentation from CT Using a Hybrid-Fusion Transformer
Authors: Qin Shihua , Xing Fangxu , Cho Jihoon , Park Jinah , Liu Xiaofeng , Rouhollahi Amir , Farhat Elias J. Bou , Javadikasgari Hoda , Sabe Ashraf , Nezami Farhad R. , Woo Jonghye , Aganj Iman
Published: October 2024

Accurate segmentation of the left ventricle (LV) in cardiac CT images is crucial for assessing ventricular function and diagnosing cardiovascular diseases. Common semi-automatic segmentation often includes unwanted structures, such as papil-lary muscles, due to low contrast between the LV wall and surrounding tissues. In this study, we address this issue by proposing a two-input-channel method within a Hybrid-Fusion Transformer deep-learning framework. Our method refines coarse LV masks by incorporating both the CT images and the semi-automatic rough masks as input channels, effectively removing papillary muscles. Using a small number of manually refined labels, we evaluated the method through leave-one-out cross-validation. The results demonstrate an average Dice similarity coefficient of 95.2%, outperforming models that use only CT images or rough masks. This approach reduces the need for extensive manual labeling while maintaining high segmentation accuracy and stability, making it suitable for clinical applications.
Microfluidic Formation of Ultrathin, Handleable Collagen Sheets Exhibiting Toe-heel Tensile Behavior
Authors: Zhang Yuming , Malladi Shashi , Wang Bangan , Chaikof Elliot L. , Günther Axel
Published: October 2024

The extracellular matrix (ECM) of cardiovascular tissues displays a non-linear, strain-dependent elastic modulus, attributed to the hierarchical organization of collagen. At low loads, these tissues exhibit compliance, permitting contraction or dilation, while at high loads, they stiffen considerably, increasing their mechanical strength by at least tenfold. Although collagen gels are widely used in 3D cell culture, tissue engineering, and biofabrication, current engineering techniques fail to replicate this hierarchical organization at the microscale. As a result, they lack both the non-linear tensile behavior and the physiologically relevant strength of native tissues. To address this limitation, we present templated collagen sheets that are 1.8 microns thin and 10 mm wide that demonstrate non-linear tensile behavior. Collagen sheets are obtained from an acidic collagen solution via a microfluidic flow focusing process, incorporating and subsequently removing emulsified oil droplets (mean diameters 2.1 microns and 5.0 microns, volume concentration 2.25%). Templated collagen sheets exhibit a two-fold increase in fibril alignment dispersion compared with non-templated ones. When assessed along their length, the Young’s modulus of templated sheets increases 62-fold at 90% failure strain, closely matching the properties of native load-bearing tissues. We anticipate that these ultrathin templated collagen sheets will have broad applications as a substrate material for the bottom-up fabrication of load-bearing biomaterials and tissue structures for in vitro applications and implantation.
Cortex-wide spatiotemporal motifs of theta oscillations are coupled to freely moving behavior
Authors: Sattler Nicholas J , Wehr Michael
Published: October 2024

Multisensory information is combined across the cortex and assimilated into the continuous production of ongoing behavior. In the hippocampus, theta oscillations (4-12 Hz) radiate as large-scale traveling waves, and serve as a scaffold for neuronal ensembles of multisensory information involved in memory and movement-related processing. An extension of such an encoding framework across the neocortex could similarly serve to bind disparate multisensory signals into ongoing, coherent, phase-coded processes. Whether the neocortex exhibits unique large-scale traveling waves distinct from that of the hippocampus however, remains unknown. Here, using cortex-wide electrocorticography in freely moving mice, we find that theta oscillations are organized into bilaterally-symmetric spatiotemporal “modes” that span virtually the entire neocortex. The dominant mode (Mode 1) is a divergent traveling wave that originates from retrosplenial cortex and whose amplitude correlates with mouse speed. Secondary modes are asynchronous spiral waves centered over primary somatosensory cortex (Modes 2 & 3), which become prominent during rapid drops in amplitude and synchrony (null spikes) and which underlie a phase reset of Mode 1. These structured cortex-wide traveling waves may provide a scaffold for large-scale phase-coding that allows the binding of multisensory information across all the regions of the cortex.

Bulleted list of key results

Cortical theta oscillations are organized into bilaterally-symmetric spatiotemporal modes that span the neocortex.

The dominant mode appears as a divergent traveling wave that originates in retrosplenial cortex and is correlated with mouse speed.

Secondary modes are asynchronous spiral waves centered over somatosensory cortex.

Secondary modes become prominent during transient drops in synchrony that underlie a phase reset of the dominant mode.

We hypothesize that spiral waves may provide a mechanism to exert large-scale phase separability, and assimilate information into ongoing multisensory processing across the neocortex.
Simultaneous observation of Pol II and potato spindle tuber viroid RNA in the nucleus by combining immunofluorescence and RNA in situ hybridization
Authors: Ma Junfei , Wang Yunhan , Folimonova Svetlana Y. , Liu Bin , Wang Ying
Published: October 2024

RNA comprises a versatile group of biomolecules that play diverse roles in a wide range of biological processes. From synthesis to degradation, RNAs interact with cognate proteins that assist in processes such as transcription, splicing, modification, trafficking, and the execution of their functions. While numerous valuable techniques exist to study RNA-protein interactions, observing RNAs and their associated proteins simultaneously within cells remains a challenge, despite its potential to provide deeper insights into RNA-protein interactions. In this study, we adapted a modified immunofluorescence (IF) assay combined with RNA fluorescence in situ hybridization (FISH) to successfully visualize the colocalization of potato spindle tuber viroid with RNA polymerase II in the nucleus. This new method that combines IF and FISH will facilitate future studies on RNA and protein colocalization in various plant systems.
Effects of systemic oxytocin and beta-3 receptor agonist (CL 316243) treatment on body weight and adiposity in male diet-induced obese rats
Authors: Slattery Jared D. , Rambousek June R. , Tsui Edison , Honeycutt Mackenzie K. , Goldberg Matvey , Graham James L. , Wietecha Tomasz A. , Wolden-Hanson Tami , Williams Amber L. , O’Brien Kevin D. , Havel Peter J. , Blevins James E.
Published: October 2024

Previous studies have implicated hindbrain oxytocin (OT) receptors in the control of food intake and brown adipose tissue (BAT) thermogenesis. We recently demonstrated that hindbrain [fourth ventricle (4V)] administration of oxytocin (OT) could be used as an adjunct to drugs that directly target beta-3 adrenergic receptors (β3-AR) to elicit weight loss in diet-induced obese (DIO) rodents. What remains unclear is whether systemic OT can be used as an adjunct with the β3-AR agonist, CL 316243, to increase BAT thermogenesis and elicit weight loss in DIO rats. We hypothesized that systemic OT and β3-AR agonist (CL 316243) treatment would produce an additive effect to reduce body weight and adiposity in DIO rats by decreasing food intake and stimulating BAT thermogenesis. To test this hypothesis, we determined the effects of systemic (subcutaneous) infusions of OT (50 nmol/day) or vehicle (VEH) when combined with daily systemic (intraperitoneal) injections of CL 316243 (0.5 mg/kg) or VEH on body weight, adiposity, food intake and brown adipose tissue temperature (TIBAT). OT and CL 316243 monotherapy decreased body weight by 8.0±0.9% (P<0.05) and 8.6±0.6% (P<0.05), respectively, but OT in combination with CL 316243 produced more substantial weight loss (14.9±1.0%;P<0.05) compared to either treatment alone. These effects were associated with decreased adiposity, energy intake and elevated TIBATduring the treatment period. The findings from the current study suggest that the effects of systemic OT and CL 316243 to elicit weight loss are additive and appear to be driven primarily by OT-elicited changes in food intake and CL 316243-elicited increases in BAT thermogenesis.
LPS-induced delirium-like behavior and microglial activation in mice correlate with bispectral electroencephalography (BSEEG)
Authors: Nishiguchi Tsuyoshi , Yamanishi Kyosuke , Gorantla Nipun , Shimura Akiyoshi , Seki Tomoteru , Ishii Takaya , Aoyama Bun , Malicoat Johnny R. , Phuong Nathan James , Dye Nicole Jade , Yamanashi Takehiko , Iwata Masaaki , Shinozaki Gen
Published: October 2024

Delirium is a multifactorial medical condition characterized by impairment across various mental functions and is one of the greatest risk factors for prolonged hospitalization, morbidity, and mortality. Research focused on delirium has proven to be challenging due to a lack of objective measures for diagnosing patients, and few laboratory models have been validated. Our recent studies report the efficacy of bispectral electroencephalography (BSEEG) in diagnosing delirium in patients and predicting patient outcomes. We applied BSEEG to validate a lipopolysaccharide (LPS)-induced mouse model of delirium. Moreover, we investigated the relationship between BSEEG score, delirium-like behaviors, and microglia activation in hippocampal dentate gyrus and cortex regions in young and aged mice. There was a significant correlation between BSEEG score and impairment of attention in young mice. Additionally, there was a significant correlation between BSEEG score and microglial activation in hippocampal dentate gyrus and cortex regions in young and aged mice. We have successfully validated the BSEEG method by showing its associations with a level of behavioral change and microglial activation in an LPS-induced mouse model of delirium. In addition, the BSEEG method was able to sensitively capture an LPS-induced delirium-like condition that behavioral tests could not capture because of a hypoactive state.
Diagnostic Efficacy of Various Imaging Modalities Across Different Stages of Prostate Cancer: A Network Meta-Analysis of Diagnostic Studies
Authors: Shi Chengdong , Yu Kai , Hu Yu , Wang Yuantao , Bu Fan , Lu Ji , Wang Weigang
Published: October 2024

Purpose

To assess the diagnostic performance of various imaging modalities in detecting and monitoring prostate cancer across different disease stages using diagnostic test accuracy (DTA) and network meta-analysis (NMA).

Methods

A systematic literature review was conducted to identify studies evaluating mpMRI, PSMA PET/CT, MRE, MRSI, BS, CT, PET, and other tracers for prostate cancer detection. Data on sensitivity, specificity, PPV, NPV, and detection rate were extracted and analyzed using NMA.

Result

Across 123 studies involving 9,371 patients, 68Ga-P16-093 PET/CT and 68Ga-PSMA-617 PET/CT showed high diagnostic accuracy in early-phase prostate cancer. For lymph node metastasis, 68Ga-PSMA-11 PET/MRI was the most sensitive. 18F-DCFPyL PET/CT had the highest specificity and PPV, while 18F-PSMA-1007 PET/CT had the highest NPV. In bone metastasis, 18F-PSMA-1007 PET/MRI excelled in sensitivity and NPV, while 18F-Fluciclovine PET/CT had the highest specificity and PPV. For biochemical recurrence, 18F-PSMA-1007 PET/CT had the highest lesion detection rate, and for different radiotracers, 18F-PSMA-1007 had the highest detection rate.

Conclusion

This network meta-analysis comprehensively evaluated the diagnostic efficacy of various imaging modalities for prostate cancer across different stages. Our findings underscore the strengths and limitations of each imaging technique in detecting and staging prostate cancer.
Distinct gene regulatory networks govern hematopoietic and leukemia stem cells
Authors: Zhang Boyang , Murison Alex , Varesi Angelica , Takayama Naoya , Jin Liqing , Mbong Nathan , Schoof Erwin M. , Xie Stephanie , Mitchell Amanda , Etchin Julia , Look A. Thomas , Lupien Mathieu , Minden Mark D. , Wang Jean C.Y. , Zandstra Peter W. , Wagenblast Elvin , Dick John E. , Ng Stanley W.K.
Published: October 2024

The underlying gene regulatory networks (GRN) that govern leukemia stem cells (LSC) in acute myeloid leukemia (AML) and hematopoietic stem cells (HSC) are not well understood. Here, we identified GRNs by integrating gene expression (GE) and chromatin accessibility data derived from functionally defined cell populations enriched for HSC and LSC. We analyzed n=32 LSC+ and n=32 LSC-cell fractions from n=22 AML patients, along with n=7 stem and n=10 progenitor enriched cell populations sorted from human umbilical cord blood (hUCB), producing a database of n≈17,000 transcription factor (TF) regulatory interactions for hUCB-HSPC and AML. We developed an iterative algorithm that associates the degree of chromatin openness with TF binding preferences, and the GE of candidate TF and target genes within 100kb upstream of transcription start sites. A putative regulatory structure was found to be enriched in HSC-enriched cell populations, comprising TF-target gene interactions between ETS1, EGR1, RUNX2, and ZNF683 oriented in a self-reinforcing configuration. A regulatory loop comprising FOXK1 and MEIS1, rather than the 4-factor HSC subnetwork, was detected in the LSC-specific GRN. The core HSC and LSC TF networks were extended using protein-protein interaction (PPI) data to determine connectivity with interacting genes whose expression strongly associated with LSC/HSC frequency estimates, producing a database of n=103,516 PPI target pathways. The effect of perturbing genes along the identified pathways on functional HSC and LSC frequency was predicted based on statistical regression analyses. To validate GRN predictions, we used pharmacologic and CRISPR targeting, in addition to re-examining published functional data associated with several network nodes that were predicted to impact stemness. Notably, we found that inhibition of CDK6 in AML samples markedly reduced LSC numbers as assessed in de novo serial xenotransplantation studies (fold change ≈ 10), as predicted by the LSC GRN model. Additionally, in-house CRISPR-based knockdown of ETS1 resulted in a significant decrease in HSC quiescence-associated microRNA-126 expression, and increased HSC frequency. Taken together, our models provide a comprehensive view of the underlying regulatory structures governing functional human HSC and LSC. This approach has translational potential as it can be used as a high-throughput in-silico screening tool for the systematic identification of gene targets for LSC elimination and HSC expansion.
Activation of the endoplasmic reticulum stress regulator IRE1α compromises pulmonary host defenses
Authors: Sharma Amit , Heffernan Linda M. , Hoang Ky , Jeyaseelan Samithamby , Beavers William N. , Abuaita Basel H.
Published: October 2024

The endoplasmic reticulum (ER) stress sensor inositol-requiring enzyme 1-α (IRE1α) is associated with lung infections where innate immune cells are drivers for progression and resolution of inflammation. Yet, the role of IRE1α in pulmonary innate immune host defense during acute respiratory infection remains unexplored. Here, we found that activation of IRE1α in infected lungs compromises immunity against methicillin-resistantStaphylococcus aureus(MRSA)-induced primary and secondary pneumonia. Moreover, activation of IRE1α in MRSA-infected lungs and alveolar macrophages (AMs) leads to exacerbated production of inflammatory mediators followed by cell death. Ablation of myeloid IRE1α or global IRE1α inhibition confers protection against MRSA-induced pneumonia with improves survival, bacterial clearance, cytokine reduction, and lung injury. In addition, loss of myeloid IRE1α protects mice against MRSA-induced secondary to influenza pneumonia by promoting AM survival. Thus, activation of IRE1α is detrimental to pneumonia and therefore, it shows potential as a target to control excessive unresolved lung inflammation.
Model-Based Reinforcement Learning for Ultrasound-Driven Autonomous Microrobots
Authors: Medany Mahmoud , Piglia Lorenzo , Achenbach Liam , Mukkavilli S. Karthik , Ahmed Daniel
Published: October 2024

AI has catalyzed transformative advancements across multiple sectors, from medical diagnostics to autonomous vehicles, enhancing precision and efficiency. As it ventures into microrobotics, AI offer innovative solutions to the formidable challenge of controlling and manipulating microrobots, which typically operate within imprecise, remotely actuated systems—a task often too complex for human operators. We implement state-of-the-art model-based reinforcement learning for autonomous control of an ultrasound-driven microrobot learning from recurrent imagined environments. Our non-invasive, AI-controlled microrobot offers precise propulsion, which efficiently learns from images in data-scarce environments. Transitioning from a pre-trained simulation environment, we achieve sample-efficient collision avoidance and channel navigation, reaching a 90% success rate in target navigation across various channels within an hour of fine-tuning. Moreover, our model initially successfully generalized in 50% of tasks in new environments, improving to over 90% with 30 minutes of further training. Furthermore, we have showcased real-time manipulation of microrobots within complex vasculatures and across stationary and physiological flows, underscoring AI’s potential to revolutionize microrobotics in biomedical applications, potentially transforming medical procedures.
Allo-Allo: Data-efficient prediction of allosteric sites
Authors: Dong Tianze , Kan Christopher , Devkota Kapil , Singh Rohit
Published: October 2024

Allostery, a fundamental structural mechanism where ligand binding at a protein site affects protein function at another site, plays a crucial role in key drug-target proteins like GPCRs. Unfortunately, existing methods for predicting allosteric sites have limited performance– they are particularly constrained by scarce ground-truth experimental data. We introduce Allo-Allo, a data-efficient, sequence-based method that predicts allosteric sites by leveraging protein language models (PLMs). Honing in on ESM-2 attention heads that capture allosteric residue associations, Allo-Allo achieves a 67% higher AUPRC than state-of-the-art methods. Our innovative, data-efficient pipeline not only outperforms alternate, commonly-used PLM-based prediction architectures but also generalizes well. Notably, mutations in Allo-Allo-predicted sites show significant association with elevated disease risk scores from AlphaMissense, highlighting its translational potential. Beyond Allo-Allo’s biological and translational applicability, its architecture presents a powerful framework for other data-scarce problems in protein analysis.
Integrating cold hardiness and deacclimation resistance demonstrates a conserved response to chilling accumulation in grapevines
Authors: Londo Jason P , Kovaleski Al P
Published: October 2024

To survive the harsh conditions of winter, woody perennial species such as grapevine have adapted to use environmental cues to trigger physiological changes to induce dormancy, acquire cold hardiness, and measure the length of winter to properly time spring budbreak. Human induced climate change disrupts these cues by prolonging warm temperatures in fall, reducing the depth and consistency of midwinter, and triggering early budbreak through false spring events. We evaluated variation in dormant bud cold hardiness and chilling hour requirements of 31 different grapevine varieties over 3 years. Differential thermal analysis was used to track changes in cold hardiness and deacclimation resistance was assessed throughout the season to track dormancy progression. Results demonstrate wide variation in maximum deacclimation rate (1.03 – 2.87 °C/day) among varieties under forcing conditions. Absolute maximum rates of deacclimation show signatures of species-level responses to forcing temperatures. When integrated with variation in cold hardiness, these rates revealed a relationship between winter cold hardiness, changes in deacclimation rate and budbreak phenology. Standardizing rates among varieties as deacclimation potential demonstrated a conserved response to chilling exposure among varieties that alters our interpretation of the concept of high and low chill varieties and chilling requirement in grapevine.
Biomechanical and Compositional Changes in the Murine Uterus with Age
Authors: Domingo Mari J.E. , Vanoven Triniti N. , De Vita Raffaella , Florian Rodriguez Maria E. , Miller Kristin S. , Pence Isaac J.
Published: October 2024

The uterus is a hollow, fibromuscular organ involved in physiologic processes such as menstruation and pregnancy. The content and organization of extracellular matrix constituents such as fibrillar collagen dictates passive (non-contractile) biomechanical tissue function; however, how extracellular matrix composition and biomechanical function change with age in the uterus remains unknown. This study utilizes Raman spectroscopy coupled with biaxial inflation testing to investigate changes in the murine uterus with age (2-3 months, 4-6 months, 10-12 months, and 20-24 months). Linear and toe moduli significantly decreased with reproductive aging (2 to 12 months); however, moduli increased in the oldest age group (20-24 months). The optical signature of combined elastin and collagen content was significantly higher in the oldest group (20-24 month), while the glycogen contribution was the highest in the 2-3 month murine uterus. The presented workflow couples biaxial inflation testing and Raman spectroscopy, representing a critical first step to correlating biomechanics and optical signatures in the aging uterus with the potential for clinical translation. Further, this study may provide critical compositional and structure-function information regarding age-related uterine disorders.
Standardizing Phenotypic Algorithms for the Classification of Degenerative Rotator Cuff Tear from Electronic Health Record Systems
Authors: Herzberg S , Garduno-Rapp NE , Ong H , Gangreddi S , Chandrashekar A , Wei W , LeClere L , Wen W , Hartmann K , Jain N , Giri A
Published: October 2024

Background

Degenerative rotator cuff tears (DCTs) are the leading cause of shoulder pain, affecting 30% to 50% of individuals over 50. Current phenotyping strategies for DCT rely on heterogeneous combinations of procedural and diagnostic codes, leading to concerns about misclassification. We aimed to create universal phenotypic algorithms to classify DCT status across EHR systems.

Methods

Using Vanderbilt University Medical Center’s de-identified EHR system, we developed and validated two sets of algorithms—one requiring imaging verification and one without imaging verification—to identify DCT cases and controls. The algorithms used combinations of ICD and CPT codes, as well as natural language processing (NLP), to increase diagnostic certainty. Manual chart reviews by trained personnel blinded to case-control determinations were conducted to compute positive (PPV) and negative predictive values (NPV).

Results

The algorithm development process resulted in five phenotypes with an overall predictive value of 94.5%. By approach: 1) code only cases that required imaging confirmation (PPV = 89%), 2) code only cases that did not require imaging verification (PPV = 92%), 3) NLP-based cases that did not require imaging verification (PPV = 89%), 4) code-based controls that were confirmed by imaging (NPV = 90%), and 5) code and NLP-based controls that did not require imaging verification (NPV = 100%). External validation demonstrated 94% sensitivity and 75% specificity for the code-only algorithms. The addition of NLP increased the number of identified cases without compromising predictive values.

Conclusions

These algorithms represent an improvement over current phenotyping strategies and allows for EHR studies of unprecedented size
Early zygotic engineering promotes targeted large transgene integration and direct production of fully transgenic animals
Authors: Gupta Khusali , Xu Ping , Gallant Judith , Yoon Yeonsoo , Rivera-Pérez Jaime A. , Lawrence Jeanne B.
Published: October 2024

Genetic engineering has become increasingly feasible with the advent of site-specific nucleases. This technology is highly effective for the generation of small mutations, however targeted insertion of large sequences to generate transgenic animals remains challenging, time consuming, and laborious. Following several failed attempts using the same reagents, we identified a protocol that achieved very high targeted integration of a 3.2 kb transgene into a single locus of a humanized mouse model of Down syndrome. Moreover, we demonstrate in multiple ways that this procedure directly generates numerous non-mosaic founder animals, which bred true to generate all transgenic progeny.In vitrofertilization of oocytes was followed by AAV-mediated delivery of donor sequence and electroporation of Cas9 ribonucleoprotein, all parameters designed to promoteearlyzygoticengineering (EZE). This strategy can obviate the need to breed mosaic animals for germline transmission and can enable engineering of difficult to breed animals. While efforts to improve genome engineering focus on reagents and delivery techniques, findings here suggest a narrow window of time in the early fertilized oocyte, likely before genome replication, is key to achieve both high integration efficiency and one-step generation of non-mosaic, engineered mice.
Stem water content is crucial to support fruit tree functioning during heatwaves in a Mediterranean climate
Authors: Rez Laura , Missik Justine E. , Bohrer Gil , Mau Yair
Published: October 2024

Droughts are expected to intensify in the Mediterranean region due to climate change, yet the effect of these highly variable events on local trees is unknown. To study the particular effect of heatwaves in orchards, where soil-drought can be mitigated by irrigation, we propose a heatwave definition that focuses on atmospheric stress and its consequences, by relating the intensity of high VPD events to losses in tree stem-water storage (StWS). We found that the sensitivity and resilience of StWS to heatwaves is species-specific, and varies among species with different water-management strategies (e.g., isohydric orange and anisohydric mango trees,p< 10−3). Navel orange trees were sensitive to heatwaves starting at the 80th percentile of VPD in early spring, and once irrigation began, despite the harsh Mediterranean summer temperatures, StWC increased to 0.57 g cm−3, slightly greater than the StWC of the earlier wet season (approximately 0.55 g cm−3). Oppositely, there was a net reduction in StWC in Shelly mango trees from 0.75 to 0.69 g cm−3between the two seasons, as sensitivity to heatwaves increased from the 90th to the 80th percentile in spring and summer, respectively. By first quantifying heatwaves and relating this new variable to changes in StWS, we were able to describe the sensitivity of each species according to the rarity of the heatwave events by VPD percentile, and their resilience to heatwaves over seasons based on the corresponding net changes in StWC. Though the experiment in this study was performed in a Mediterranean climate, hotter-droughts are rising globally and the framework developed here for quantifying and measuring the effect of heatwaves can be broadly applied across geographic locations.
Novel AI-powered computational method using tensor decomposition for identification of common optimal bin sizes when integrating multiple Hi-C datasets
Authors: Taguchi Y-H , Turki Turki
Published: October 2024

Identifying the optimal bin sizes (or resolutions) for the integration of multiple Hi-C datasets is a challenge due to the fact that bin sizes must be common over multiple datasets. By contrast, the dependence of quality upon bin sizes can vary from dataset to dataset. Moreover, common structures should not be sought in bin sizes smaller than the optimal bin sizes, below which common structure cannot be the primary structure any more even after increasing the number of mapped short reads per bin. In this case, there are no common structures at finer resolutions, suggesting that individual Hi-C datasets may have to be analyzed separately in the bin sizes smaller than the optimal one. Thus, quality assessments of individual datasets have a limited ability to determine the best bin size for all datasets. In this study, we propose a novel application of tensor decomposition (TD) based unsupervised feature extraction (FE) to choose the optimal bin sizes for the integration of multiple Hi-C datasets. TD-based unsupervised FE exhibit phase transition-like phenomena through which the smallest possible bin size (or the highest resolution) can be automatically estimated empirically, without the need to manually set a threshold value for the integration of multiple Hi-C datasets, retrieved from GEO with GEO ID, GSE260760 and GSE255264. To our knowledge, ours is the first one that can optimize bin sizes over multiple Hi-C profiles without any tunable parameters.
Separating biological variance from noise by applying EM algorithm to modified General Linear Model
Authors: Lee Tien-Wen
Published: October 2024

Introduction

The General Linear Model (GLM) has been widely used in research, where error term has been treated as noise. However, compelling evidence suggests that in biological systems, the target variables may possess their innate variances.

Methods

A modified GLM was proposed to explicitly model biological variance and non-biological noise. Employing the Expectation and Maximization (EM) scheme can distinguish biological variance from noise, termed EMSEV (EM for Separating Variances). The performance of EMSEV was evaluated by varying noise levels, dimensions of the design matrix, and covariance structures of the target variables.

Results

The deviation between EMSEV outputs and the pre-defined distribution parameters increased with noise level. With a proper initial guess, when the noise magnitude and the variance of the target variables were similar, there were deviations of 3% and 10–16% in the estimated mean and covariance of the target variables, respectively, along with a 1.7% deviation in noise estimation.

Conclusion

EMSEV appears promising for distinguishing signal variance from noise in biological systems. The potential applications and implications in biological science and statistical inference are discussed.
Serotonergic neurons in the dorsal raphe regulate visual attention
Authors: Lehnert Jonas , Cha Kuwook , Forestell Julia , Yang Kerry , Ma Xinyue , Britt Jonathan , Khadra Anmar , Cook Erik P. , Krishnaswamy Arjun
Published: October 2024

Visual attention enhances the neural representation of salient stimuli within the visual cortex. It is generally thought that this enhancement is driven by glutamatergic feedback from frontal cortical areas. Here we report the unexpected observation that dorsal raphe (DR) derived serotonin (5HT) controls visual attention. We developed a behavioral model that captured the way mice allocated attention to cued and uncued visual locations and features. Simultaneous photometry showed reduced DR activity when mice deployed attention to the cued locations and features, whereas high DR activity was observed when mice were less attentive. Optogenetic excitation of DR-5HT neurons impaired attention to the cue and degraded behavioral performance, while optogenetic suppression improved attention and performance. A genetically encoded sensor of 5HT release showed reduced 5HT levels in visual cortex when mice attend and detect stimuli. These results demonstrate that DR-5HT neurons are members of the brain’s attentional circuit and suggest that 5HT is a novel biological carrier of visual attention.
UBE3A reinstatement restores behavior and proteome in an Angelman Syndrome mouse model of Imprinting Defects
Authors: Milazzo Claudia , Narayanan Ramanathan , Badillo Solveig , Wang Silvia , Almand Rosaisela , Mientjes Edwin , Chamberlain Stormy , Kremer Thomas , Elgersma Ype
Published: October 2024

Angelman Syndrome (AS) is a severe neurodevelopmental disorder wionly symptomatic treatment currently available. Besides mutations within theUBE3Agene, AS is caused by deletions, imprinting center defects (mICD) or uniparental disomy of chromosome 15 (UPD). Current mouse models areUbe3a-centric and do not address expression changes of other 15q11-q13 genes on AS pathophysiology. Here, we studied a mouse line that harbors a mutation affecting the AS-PWS imprinting center, hence modeling mICD/UPD AS subtypes. mICD mice showed significant reduction in UBE3A protein, bi-allelic expression ofUbe3a-ATSandMkrn3-Snord115gene cluster, leading to robust AS behavioral deficits and proteome alterations similar toUbe3aKOmice. Genetic UBE3A overexpression in mICD mice, mimicking therapeutic strategies that effectively activate the biallelic silencedUbe3agene, resulted in a complete rescue of all behavioral and proteome alterations. Subsequently, treatment with an antisense oligonucleotide (ASO) to directly activate the biallelic silencedUbe3agene in mICD mice also resulted in efficient reinstatement of UBE3A, alongside a partial rescue of behavioral phenotypes. Taken together, these findings demonstrate that UBE3A loss is the primary factor underlying AS phenotypes in the mICD/UPD mouse model, and also corroborate that UBE3A reinstatement is an attractive therapeutic strategy for mICD/UPD AS individuals.
Fluid Flow Impacts Endothelial-Monocyte Interactions in a Model of Vascular Inflammatory Fibrosis
Authors: Linares Isabelle , Chen Kaihua , Saffren Ava , Mansouri Mehran , Abhyankar Vinay V. , Miller Benjamin L. , Begolo Stefano , Awad Hani A. , McGrath James L.
Published: October 2024

The aberrant vascular response associated with tendon injury results in circulating immune cell infiltration and a chronic inflammatory feedback loop leading to poor healing outcomes. Studying this dysregulated tendon repair response in human pathophysiology has been historically challenging due to the reliance on animal models. To address this, our group developed the human tendon-on-a-chip (hToC) to model cellular interactions in the injured tendon microenvironment; however, this model lacked the key element of physiological flow in the vascular compartment. Here, we leveraged the modularity of our platform to create a fluidic hToC that enables the study of circulating immune cell and vascular crosstalk in a tendon injury model. Under physiological shear stress consistent with postcapillary venules, we found a significant increase in the endothelial leukocyte activation marker intercellular adhesion molecule 1 (ICAM-1), as well as enhanced adhesion and transmigration of circulating monocytes across the endothelial barrier. The addition of tissue macrophages to the tendon compartment further increased the degree of circulating monocyte infiltration into the tissue matrix. Our findings demonstrate the importance of adding physiological flow to the human tendon-on-a-chip, and more generally, the significance of flow for modeling immune cell interactions in tissue inflammation and disease.
Effects of Host-Tree Foliage on Polymorphism in an Insect Pathogen
Authors: Freedman Ari S. , Huang Amy , Dixon Katherine , Polivka Carlos , Dwyer Greg
Published: October 2024

The theory of host-pathogen interactions has successfully shown that persistent pathogen virulence may be explained through tradeoffs between different pathogen fitness components, but classical theory cannot explain pathogen coexistence. More recent theory invokes both tradeoffs and environmental heterogeneity, but resembles classical theory in focusing on a limited range of possible tradeoffs, and therefore has seen few applications. To better understand the usefulness of tradeoff theory for explaining pathogen coexistence in nature, we measured components of pathogen fitness in two distantly related morphotypes of a baculovirus that infects larvae of the Douglas-fir tussock moth (Orgyia pseudotsugata). We show that the two morphotypes vary in multiple components of fitness, including the probability of infection given exposure to the pathogen, the incubation time of the pathogen, variability in the incubation time of the pathogen, and the detectability of the pathogen. Moreover, because the baculovirus is transmitted when host larvae accidentally consume infectious virus particles while feeding on foliage of the insect’s host trees, the strength and direction of the differences in fitness components of the two morphotypes depends on the host-tree species on which host larvae consume the virus. Through simulations of a model parameterized using our experimental data, we demonstrate how several varying fitness components can work in concert to promote strain coexistence, particularly highlighting the role of variability in incubation time. Our results suggest that the two morphotypes may coexist because of variation in forest tree-species composition, providing important empirical evidence that tradeoffs and environmental heterogeneity can together modulate pathogen competition.
Impact of ligand binding on VEGFR1, VEGFR2, and NRP1 localization in human endothelial cells
Authors: Sarabipour Sarvenaz , Kinghorn Karina , Quigley Kaitlyn M , Kovacs-Kasa Anita , Annex Brian H , Bautch Victoria L , Mac Gabhann Feilim
Published: October 2024

The vascular endothelial growth factor receptors (VEGFRs) bind to cognate ligands to facilitate signaling pathways critical for angiogenesis, the growth of new capillaries from existing vasculature. Intracellular trafficking regulates the availability of receptors on the cell surface to bind ligands, which regulate activation, and the movement of activated receptors between the surface and intracellular pools, where they can initiate different signaling pathways. Using experimental data and computational modeling, we recently demonstrated and quantified the differential trafficking of three VEGF receptors, VEGFR1, VEGFR2, and coreceptor Neuropilin-1 (NRP1). Here, we expand that approach to quantify how the binding of different VEGF ligands alters the trafficking of these VEGF receptors and demonstrate the consequences of receptor localization and ligand binding on the localization and dynamics of signal initiation complexes. We include simulations of four different splice isoforms of VEGF-A and PLGF, each of which binds to different combinations of the VEGF receptors, and we use new experimental data for two of these ligands to parameterize and validate our model. We show that VEGFR2 trafficking is altered in response to ligand binding, but that trafficking of VEGFR1 is not; we also show that the altered trafficking can be explained by a single mechanistic process, increased internalization of the VEGFR2 receptor when bound to ligand; other processes are unaffected. We further show that even though the canonical view of receptor tyrosine kinases is of activation on the cell surface, most of the ligand-receptor complexes for both VEGFR1 and VEGFR2 are intracellular. We also explore the competition between the receptors for ligand binding, the so-called ‘decoy effect’, and show that whilein vitroon the cell surface minimal such effect would be observed, inside the cell the effect can be substantial and may influence signaling. We term this location dependence the ‘reservoir effect’ as the size of the local ligand reservoir (large outside the cell, small inside the cell) plays an integral role in the receptor-receptor competition. These results expand our understanding of receptor-ligand trafficking dynamics and are critical for the design of therapeutic agents to regulate ligand availability to VEGFR1 and hence VEGF receptor signaling in angiogenesis.
The contribution of coding variants to the heritability of multiple cancer types using UK Biobank whole-exome sequencing data
Authors: Wilcox Naomi , Tyrer Jonathan P. , Dennis Joe , Yang Xin , Perry John R. B. , Gardner Eugene J. , Easton Douglas F.
Published: October 2024

Genome-wide association studies have been highly successful at identifying common variants associated with cancer, however, they do not explain all the inherited risk of cancer. Family-based studies, targeted sequencing and, more recently, exome-wide association studies have identified rare coding variants in some genes associated with cancer risk, but the overall contribution of these variants to the heritability of cancer is less clear. Here we describe a method to estimate the genome-wide contribution of rare coding variants to heritability that fits models to the burden effect sizes using an empirical Bayesian approach. We apply this method to the burden of protein-truncating variants in over 15,000 genes for 11 cancers in UK Biobank, using whole-exome sequencing data on over 400,000 individuals. We extend the method to consider the overlap of genes contributing to pairs of cancers. We found ovarian cancer to have the greatest proportion of heritability attributable to protein-truncating variants in genes (46%). The joint cancer models highlight significant clustering of cancer types, including a near complete overlap in susceptibility genes for breast, ovarian, prostate and pancreatic cancer. Our results provide insights into the contribution of rare coding variants to the heritability of cancer and identify additional genes with strong evidence of susceptibility to multiple cancer types.