Auditory cortical regions show resting-state functional connectivity with the default mode-like network in echolocating bats.

Echolocating bats are among the most social and vocal of all mammals. These animals are ideal subjects for functional MRI (fMRI) studies of auditory social communication given their relatively hypertrophic limbic and auditory neural structures and their reduced ability to hear MRI gradient noise. Yet, no resting-state networks relevant to social cognition (e.g., default mode-like networks or DMLNs) have been identified in bats since there are few, if any, fMRI studies in the chiropteran order. Here, we acquired fMRI data at 7 Tesla from nine lightly anesthetized pale spear-nosed bats (Phyllostomus discolor). We applied independent components analysis (ICA) to reveal resting-state networks and measured neural activity elicited by noise ripples (on: 10 ms; off: 10 ms) that span this species' ultrasonic hearing range (20 to 130 kHz). Resting-state networks pervaded auditory, parietal, and occipital cortices, along with the hippocampus, cerebellum, basal ganglia, and auditory brainstem. Two midline networks formed an apparent DMLN. Additionally, we found four predominantly auditory/parietal cortical networks, of which two were left-lateralized and two right-lateralized. Regions within four auditory/parietal cortical networks are known to respond to social calls. Along with the auditory brainstem, regions within these four cortical networks responded to ultrasonic noise ripples. Iterative analyses revealed consistent, significant functional connectivity between the left, but not right, auditory/parietal cortical networks and DMLN nodes, especially the anterior-most cingulate cortex. Thus, a resting-state network implicated in social cognition displays more distributed functional connectivity across left, relative to right, hemispheric cortical substrates of audition and communication in this highly social and vocal species.

KRAGEN: a knowledge graph-enhanced RAG framework for biomedical problem solving using large language models.

MOTIVATION: Answering and solving complex problems using a large language model (LLM) given a certain domain such as biomedicine is a challenging task that requires both factual consistency and logic, and LLMs often suffer from some major limitations, such as hallucinating false or irrelevant information, or being influenced by noisy data. These issues can compromise the trustworthiness, accuracy, and compliance of LLM-generated text and insights. RESULTS: Knowledge Retrieval Augmented Generation ENgine (KRAGEN) is a new tool that combines knowledge graphs, Retrieval Augmented Generation (RAG), and advanced prompting techniques to solve complex problems with natural language. KRAGEN converts knowledge graphs into a vector database and uses RAG to retrieve relevant facts from it. KRAGEN uses advanced prompting techniques: namely graph-of-thoughts (GoT), to dynamically break down a complex problem into smaller subproblems, and proceeds to solve each subproblem by using the relevant knowledge through the RAG framework, which limits the hallucinations, and finally, consolidates the subproblems and provides a solution. KRAGEN's graph visualization allows the user to interact with and evaluate the quality of the solution's GoT structure and logic. AVAILABILITY AND IMPLEMENTATION: KRAGEN is deployed by running its custom Docker containers. KRAGEN is available as open-source from GitHub at: https://github.com/EpistasisLab/KRAGEN.

Subthreshold firing in Mott nanodevices.

Resistive switching, a phenomenon in which the resistance of a device can be modified by applying an electric field1-5, is at the core of emerging technologies such as neuromorphic computing and resistive memories6-9. Among the different types of resistive switching, threshold firing10-14 is one of the most promising, as it may enable the implementation of artificial spiking neurons7,13,14. Threshold firing is observed in Mott insulators featuring an insulator-to-metal transition15,16, which can be triggered by applying an external voltage: the material becomes conducting ('fires') if a threshold voltage is exceeded7,10-12. The dynamics of this induced transition have been thoroughly studied, and its underlying mechanism and characteristic time are well documented10,12,17,18. By contrast, there is little knowledge regarding the opposite transition: the process by which the system returns to the insulating state after the voltage is removed. Here we show that Mott nanodevices retain a memory of previous resistive switching events long after the insulating resistance has recovered. We demonstrate that, although the device returns to its insulating state within 50 to 150 nanoseconds, it is possible to re-trigger the insulator-to-metal transition by using subthreshold voltages for a much longer time (up to several milliseconds). We find that the intrinsic metastability of first-order phase transitions is the origin of this phenomenon, and so it is potentially present in all Mott systems. This effect constitutes a new type of volatile memory in Mott-based devices, with potential applications in resistive memories, solid-state frequency discriminators and neuromorphic circuits.

Activation of PDGF pathway links LMNA mutation to dilated cardiomyopathy.

Lamin A/C (LMNA) is one of the most frequently mutated genes associated with dilated cardiomyopathy (DCM). DCM related to mutations in LMNA is a common inherited cardiomyopathy that is associated with systolic dysfunction and cardiac arrhythmias. Here we modelled the LMNA-related DCM in vitro using patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). Electrophysiological studies showed that the mutant iPSC-CMs displayed aberrant calcium homeostasis that led to arrhythmias at the single-cell level. Mechanistically, we show that the platelet-derived growth factor (PDGF) signalling pathway is activated in mutant iPSC-CMs compared to isogenic control iPSC-CMs. Conversely, pharmacological and molecular inhibition of the PDGF signalling pathway ameliorated the arrhythmic phenotypes of mutant iPSC-CMs in vitro. Taken together, our findings suggest that the activation of the PDGF pathway contributes to the pathogenesis of LMNA-related DCM and point to PDGF receptor-ß (PDGFRB) as a potential therapeutic target.

Who are we missing? Language exclusivity of patient-reported outcomes in atrial fibrillation clinical trials.

INTRODUCTION: Patient-reported outcomes (PROs) are increasingly used to evaluate quality of life (QoL) in Atrial Fibrillation (AF) patients, providing crucial insights in clinical trials. This study examines the frequency of PRO use in AF trials and the linguistic accessibility of AF-specific PROs. BACKGROUND: As the United States becomes more multilingual, ensuring PROs are available in various languages is vital. The number of people speaking a language other than English at home has tripled from 23.1 million in 1980 to 67.8 million in 2019. This diversity necessitates the availability of PROs in multiple languages for inclusive clinical assessments. METHODS: We queried ClinicalTrials.gov for all US interventional AF trials up to November 28, 2023, reviewing each for PRO usage as primary or secondary outcomes. We identified the five most common AF-specific and generic PROs, extracting their available translations and original languages from published sources. RESULTS: Of 233 identified trials, 191 had associated publications, with 180 (94.2%) conducted solely in English. Only one trial (0.4%) used an AF-specific PRO as a primary outcome, compared to four (1.7%) with a generic PRO. Ten trials (4.3%) used AF-specific PROs as secondary endpoints, versus 22 (9.4%) using generic PROs. AF-specific PROs had significantly fewer translations than generic PROs (11.2 vs. 148.8; p < .001). The AF Effect on Quality-of-Life (AFEQT) was available in 24 languages, with limited translations in commonly spoken US languages like Arabic and Asian languages. CONCLUSION: The limited availability of AF-specific PRO translations highlights a barrier to inclusive AF clinical trials. Expanding translations for AF-specific PROs is crucial for equitable QoL assessments.

Fast spin-echo approach for accelerated B1 gradient-based MRI.

PURPOSE: To expand on the previously developed B 1 + $$ {\mathrm{B}}_1^{+} $$ -encoding technique, frequency-modulated Rabi-encoded echoes (FREE), to perform accelerated image acquisition by collecting multiple lines of k-space in an echo train. METHODS: FREE uses adiabatic full-passage pulses and a spatially varying RF field to encode unique spatial information without the use of traditional B0 gradients. The original implementation relied on acquiring single lines of k-space, leading to long acquisitions. In this work, an acceleration scheme is presented in which multiple echoes are acquired in a single shot, analogous to conventional fast spin-echo sequences. Theoretical analysis and computer simulations investigated the feasibility of this approach and presented a framework to analyze important imaging parameters of FREE-based sequences. Experimentally, the multi-echo approach was compared with conventional phase-encoded images of the human visual cortex using a simple surface transceiver coil. Finally, different contrasts demonstrated the clinical versatility of the new accelerated sequence. RESULTS: Images were acquired with an acceleration factor of 3.9, compared with the previous implementation of FREE, without exceeding specific absorption rate limits. Different contrasts can easily be acquired without major modifications, including inversion recovery-type images. CONCLUSION: FREE initially illustrated the feasibility of performing slice-selective 2D imaging of the human brain without the need for a B0 gradient along the y-direction. The multi-echo version maintains the advantages that B 1 + $$ {\mathrm{B}}_1^{+} $$ encoding provides but represents an important step toward improving the clinical feasibility of such sequences. Additional acceleration and more advanced reconstruction techniques could further improve the clinical viability of FREE-based techniques.

Correcting image distortions from a nonlinear B 1 + $$ {\boldsymbol{B}}_{\mathbf{1}}

PURPOSE: To correct image distortions that result from nonlinear spatial variation in the transmit RF field amplitude ( B 1 + $$ {B}_1^{+} $$ ) when performing spatial encoding with the method called frequency-modulated Rabi encoded echoes (FREE). THEORY AND METHODS: An algorithm developed to correct image distortion resulting from the use of nonlinear static field (B0 ) gradients in standard MRI is adapted herein to correct image distortion arising from a nonlinear B 1 + $$ {B}_1^{+} $$ -gradient field in FREE. From a B 1 + $$ {B}_1^{+} $$ -map, the algorithm performs linear interpolation and intensity scaling to correct the image. The quality of the distortion correction is evaluated in 1.5T images of a grid phantom and human occipital lobe. RESULTS: An expanded theoretical description of FREE revealed the symmetry between this B 1 + $$ {B}_1^{+} $$ -gradient field spatial-encoding and standard B0 -gradient field spatial-encoding. The adapted distortion-correction algorithm substantially reduced image distortions arising in the spatial dimension that was encoded by the nonlinear B 1 + $$ {B}_1^{+} $$ gradient of a circular surface coil. CONCLUSION: Image processing based on straightforward linear interpolation and intensity scaling, as previously applied in conventional MRI, can effectively reduce distortions in FREE images acquired with nonlinear B 1 + $$ {B}_1^{+} $$ -gradient fields.

Ambient circulation surrounding an ablation catheter tip affects ablation lesion characteristics.

INTRODUCTION: The association between ambient circulating environments (CEs) and ablation lesions has been largely underexplored. METHODS: Viable bovine myocardium was placed in a saline bath in an ex vivo endocardial model. Radiofrequency (RF) ablation was performed using three different ablation catheters: 3.5 mm open irrigated (OI), 4, and 8 mm. Variable flow rates of surrounding bath fluids were applied to simulate standard flow, high flow, and no flow. For in vivo epicardial ablation, 24 rats underwent a single OI ablation and performed with circulating saline (30 ml/min; n = 12), versus those immersed in saline without circulation (n = 12). RESULTS: High flow reduced ablation lesion volumes for all three catheters. In no-flow endocardial CE, both 4 mm and OI catheters produced smaller lesions compared with standard flow. However, the 8 mm catheter produced the largest lesions in a no-flow CE. Ablation performed in an in vivo model with CE resulted in smaller lesions compared with ablation performed in a no-flow environment. No statistically significant differences in steam pops were found among the groups. CONCLUSION: A higher endocardial CE flow can decrease RF effectiveness. Cardiac tissue subjected to no endocardial CE flow may also limit RF for 4 mm catheters, but not for OI catheters; these findings may have implications for RF ablation safety and efficacy, especially in the epicardial space without circulating fluid or in the endocardium under varying flow conditions.

Atrial fibrillation ablation outcome prediction with a machine learning fusion framework incorporating cardiac computed tomography.

BACKGROUND: Structural changes in the left atrium (LA) modestly predict outcomes in patients undergoing catheter ablation for atrial fibrillation (AF). Machine learning (ML) is a promising approach to personalize AF management strategies and improve predictive risk models after catheter ablation by integrating atrial geometry from cardiac computed tomography (CT) scans and patient-specific clinical data. We hypothesized that ML approaches based on a patient's specific data can identify responders to AF ablation. METHODS: Consecutive patients undergoing AF ablation, who had preprocedural CT scans, demographics, and 1-year follow-up data, were included in the study for a retrospective analysis. The inputs of models were CT-derived morphological features from left atrial segmentation (including the shape, volume of the LA, LA appendage, and pulmonary vein ostia) along with deep features learned directly from raw CT images, and clinical data. These were merged intelligently in a framework to learn their individual importance and produce the optimal classification. RESULTS: Three hundred twenty-one patients (64.2 ± 10.6 years, 69% male, 40% paroxysmal AF) were analyzed. Post 10-fold nested cross-validation, the model trained to intelligently merge and learn appropriate weights for clinical, morphological, and imaging data (AUC 0.821) outperformed those trained solely on clinical data (AUC 0.626), morphological (AUC 0.659), or imaging data (AUC 0.764). CONCLUSION: Our ML approach provides an end-to-end automated technique to predict AF ablation outcomes using deep learning from CT images, derived structural properties of LA, augmented by incorporation of clinical data in a merged ML framework. This can help develop personalized strategies for patient selection in invasive management of AF.

Impact of additional genetic abnormalities at diagnosis of chronic myeloid leukemia for first-line imatinib-treated patients receiving proactive treatment intervention.

The BCR::ABL1 gene fusion initiates chronic myeloid leukemia (CML); however, evidence has accumulated from studies of highly selected cohorts that variants in other cancer-related genes are associated with treatment failure. Nevertheless, the true incidence and impact of additional genetic abnormalities (AGA) at diagnosis of chronic phase (CP)-CML is unknown. We sought to determine whether AGA at diagnosis in a consecutive imatinib-treated cohort of 210 patients enrolled in the TIDEL-II trial influenced outcome despite a highly proactive treatment intervention strategy. Survival outcomes including overall survival, progression-free survival, failure-free survival, and BCR::ABL1 kinase domain mutation acquisition were evaluated. Molecular outcomes were measured at a central laboratory and included major molecular response (MMR, BCR::ABL1 ≤0.1%IS), MR4 (BCR::ABL1 ≤0.01%IS), and MR4.5 (BCR::ABL1 ≤0.0032%IS). AGA included variants in known cancer genes and novel rearrangements involving the formation of the Philadelphia chromosome. Clinical outcomes and molecular response were assessed based on the patient's genetic profile and other baseline factors. AGA were identified in 31% of patients. Potentially pathogenic variants in cancer-related genes were detected in 16% of patients at diagnosis (including gene fusions and deletions) and structural rearrangements involving the Philadelphia chromosome (Ph-associated rearrangements) were detected in 18%. Multivariable analysis demonstrated that the combined genetic abnormalities plus the EUTOS long-term survival clinical risk score were independent predictors of lower molecular response rates and higher treatment failure. Despite a highly proactive treatment intervention strategy, first-line imatinib-treated patients with AGA had poorer response rates. These data provide evidence for the incorporation of genomically-based risk assessment for CML.