Another Lonely-ish Night

Dr. Shourik Dutta is an anesthesiology resident. He shared a story of an experience when he was on call. Excerpt: Another Lonely-ish Night “Replaying the last hour over and over again, my chest starts to get tight. Carrying my big red bag, I marched up and into the room, only to find something that would finally drowned out the sound of my little red pager. My eyes take in an entropic group and an array of monitors, brought together by cacophony. Pulse Check!

Transcription factor interactions explain the context-dependent activity of CRX binding sites

The effects of transcription factor binding sites (TFBSs) on the activity of a cis-regulatory element (CRE) depend on the local sequence context. In rod photoreceptors, binding sites for the transcription factor (TF) Cone-rod homeobox (CRX) occur in both enhancers and silencers, but the sequence context that determines whether CRX binding sites contribute to activation or repression of transcription is not understood. To investigate the context-dependent activity of CRX sites, we fit neural network-based models to the activities of synthetic CREs composed of photoreceptor TFBSs. The models revealed that CRX binding sites consistently make positive, independent contributions to CRE activity, while negative homotypic interactions between sites cause CREs composed of multiple CRX sites to function as silencers. The effects of negative homotypic interactions can be overcome by the presence of other TFBSs that either interact cooperatively with CRX sites or make independent positive contributions to activity. The context-dependent activity of CRX sites is thus determined by the balance between positive heterotypic interactions, independent contributions of TFBSs, and negative homotypic interactions. Our findings explain observed patterns of activity among genomic CRX-bound enhancers and silencers, and suggest that enhancers may require diverse TFBSs to overcome negative homotypic interactions between TFBSs

The impact of patterns in linkage disequilibrium and sequencing quality on the imprint of balancing selection

Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima\u27s D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions

Understanding the nebulisation of antibiotics: The key role of lung microdialysis studies

BACKGROUND: Nebulisation of antibiotics is a promising treatment for ventilator-associated pneumonia (VAP) caused by multidrug-resistant organisms. Ensuring effective antibiotic concentrations at the site of infection in the interstitial space fluid is crucial for clinical outcomes. Current assessment methods, such as epithelial lining fluid and tissue homogenates, have limitations in providing longitudinal pharmacokinetic data. MAIN BODY: Lung microdialysis, an invasive research technique predominantly used in animals, involves inserting probes into lung parenchyma to measure antibiotic concentrations in interstitial space fluid. Lung microdialysis offers unique advantages, such as continuous sampling, regional assessment of antibiotic lung concentrations and avoidance of bronchial contamination. However, it also has inherent limitations including the cost of probes and assay development, the need for probe calibration and limited applicability to certain antibiotics. As a research tool in VAP, lung microdialysis necessitates specialist techniques and resource-intensive experimental designs involving large animals undergoing prolonged mechanical ventilation. However, its potential impact on advancing our understanding of nebulised antibiotics for VAP is substantial. The technique may enable the investigation of various factors influencing antibiotic lung pharmacokinetics, including drug types, delivery devices, ventilator settings, interfaces and disease conditions. Combining in vivo pharmacokinetics with in vitro pharmacodynamic simulations can become feasible, providing insights to inform nebulised antibiotic dose optimisation regimens. Specifically, it may aid in understanding and optimising the nebulisation of polymyxins, effective against multidrug-resistant Gram-negative bacteria. Furthermore, lung microdialysis holds promise in exploring novel nebulisation therapies, including repurposed antibiotic formulations, bacteriophages and immunomodulators. The technique\u27s potential to monitor dynamic biochemical changes in pneumonia, such as cytokines, metabolites and inflammation/infection markers, opens avenues for developing theranostic tools tailored to critically ill patients with VAP. CONCLUSION: In summary, lung microdialysis can be a potential transformative tool, offering real-time insights into nebulised antibiotic pharmacokinetics. Its potential to inform optimal dosing regimen development based on precise target site concentrations and contribute to development of theranostic tools positions it as key player in advancing treatment strategies for VAP caused by multidrug-resistant organisms. The establishment of international research networks, exemplified by LUMINA (lung microdialysis applied to nebulised antibiotics), signifies a proactive step towards addressing complexities and promoting multicentre experimental studies in the future

Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods

BACKGROUND: Intracranial electrodes are typically localized from post-implantation CT artifacts. Automatic algorithms localizing low signal-to-noise ratio artifacts and high-density electrode arrays are missing. Additionally, implantation of grids/strips introduces brain deformations, resulting in registration errors when fusing post-implantation CT and pre-implantation MR images. Brain-shift compensation methods project electrode coordinates to cortex, but either fail to produce smooth solutions or do not account for brain deformations. NEW METHODS: We first introduce GridFit, a model-based fitting approach that simultaneously localizes all electrodes\u27 CT artifacts in grids, strips, or depth arrays. Second, we present CEPA, a brain-shift compensation algorithm combining orthogonal-based projections, spring-mesh models, and spatial regularization constraints. RESULTS: We tested GridFit on ∼6000 simulated scenarios. The localization of CT artifacts showed robust performance under difficult scenarios, such as noise, overlaps, and high-density implants (\u3c1 mm errors). Validation with data from 20 challenging patients showed 99% accurate localization of the electrodes (3160/3192). We tested CEPA brain-shift compensation with data from 15 patients. Projections accounted for simple mechanical deformation principles with \u3c 0.4 mm errors. The inter-electrode distances smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. COMPARISON WITH EXISTING METHODS: GridFit succeeded in difficult scenarios that challenged available methods and outperformed visual localization by preserving the inter-electrode distance. CEPA registration errors were smaller than those obtained for well-established alternatives. Additionally, modeling resting-state high-frequency activity in five patients further supported CEPA. CONCLUSION: GridFit and CEPA are versatile tools for registering intracranial electrode coordinates, providing highly accurate results even in the most challenging implantation scenarios. The methods are implemented in the iElectrodes open-source toolbox

Dopamine-mediated interactions between short- and long-term memory dynamics

In dynamic environments, animals make behavioural decisions on the basis of the innate valences of sensory cues and information learnt about these cues across multiple timescale

Neural mechanisms of face familiarity and learning in the human amygdala and hippocampus

Recognizing familiar faces and learning new faces play an important role in social cognition. However, the underlying neural computational mechanisms remain unclear. Here, we record from single neurons in the human amygdala and hippocampus and find a greater neuronal representational distance between pairs of familiar faces than unfamiliar faces, suggesting that neural representations for familiar faces are more distinct. Representational distance increases with exposures to the same identity, suggesting that neural face representations are sharpened with learning and familiarization. Furthermore, representational distance is positively correlated with visual dissimilarity between faces, and exposure to visually similar faces increases representational distance, thus sharpening neural representations. Finally, we construct a computational model that demonstrates an increase in the representational distance of artificial units with training. Together, our results suggest that the neuronal population geometry, quantified by the representational distance, encodes face familiarity, similarity, and learning, forming the basis of face recognition and memory

Causal relationships between pain, medical treatments, and knee osteoarthritis: A graphical causal model to guide analyses

OBJECTIVE: Randomized controlled trials (RCTs) are a gold standard for estimating the benefits of clinical interventions, but their decision-making utility can be limited by relatively short follow-up time. Longer-term follow-up of RCT participants is essential to support treatment decisions. However, as time from randomization accrues, loss to follow-up and competing events can introduce biases and require covariate adjustment even for intention-to-treat effects. We describe a process for synthesizing expert knowledge and apply this to long-term follow-up of an RCT of treatments for meniscal tears in patients with knee osteoarthritis (OA). METHODS: We identified 2 post-randomization events likely to impact accurate assessment of pain outcomes beyond 5 years in trial participants: loss to follow-up and total knee replacement (TKR). We conducted literature searches for covariates related to pain and TKR in individuals with knee OA and combined these with expert input. We synthesized the evidence into graphical models. RESULTS: We identified 94 potential covariates potentially related to pain and/or TKR among individuals with knee OA. Of these, 46 were identified in the literature review and 48 by expert panelists. We determined that adjustment for 50 covariates may be required to estimate the long-term effects of knee OA treatments on pain. CONCLUSION: We present a process for combining literature reviews with expert input to synthesize existing knowledge and improve covariate selection. We apply this process to the long-term follow-up of a randomized trial and show that expert input provides additional information not obtainable from literature reviews alone

Multiomics profiling of mouse polycystic kidney disease progression at a single-cell resolution

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease and causes significant morbidity, ultimately leading to kidney failure. PKD pathogenesis is characterized by complex and dynamic alterations in multiple cell types during disease progression, hampering a deeper understanding of disease mechanism and the development of therapeutic approaches. Here, we generate a single-nucleus multimodal atlas of an orthologous mouse PKD model at early, mid, and late timepoints, consisting of 125,434 single-nucleus transcriptomic and epigenetic multiomes. We catalog differentially expressed genes and activated epigenetic regions in each cell type during PKD progression, characterizing cell-type-specific responses t

Tract-based analyses of white matter in schizophrenia, bipolar disorder, aging, and dementia using high spatial and directional resolution diffusion imaging: A pilot study

INTRODUCTION: Structural brain connectivity abnormalities have been associated with several psychiatric disorders. Schizophrenia (SCZ) is a chronic disabling disorder associated with accelerated aging and increased risk of dementia, though brain findings in the disorder have rarely been directly compared to those that occur with aging. METHODS: We used an automated approach to reconstruct key white matter tracts and assessed tract integrity in five participant groups. We acquired one-hour-long high-directional diffusion MRI data from young control (CON, n =28), bipolar disorder (BPD, n =21), and SCZ (n =22) participants aged 18-30, and healthy elderly (ELD, n =15) and dementia (DEM, n =9) participants. Volume, fractional (FA), radial diffusivity (RD) and axial diffusivity (AD) of seven key white matter tracts (anterior thalamic radiation, ATR; dorsal and ventral cingulum bundle, CBD and CBV; corticospinal tract, CST; and the three superior longitudinal fasciculi: SLF-1, SLF-2 and SLF-3) were analyzed with TRACULA. Group comparisons in tract metrics were performed using multivariate and univariate analyses. Clinical relationships of tract metrics with recent and chronic symptoms were assessed in SCZ and BPD participants. RESULTS: A MANOVA showed group differences in FA (λ=0.5; p=0.0002) and RD (λ=0.35; p\u3c0.0001) across the seven tracts, but no significant differences in tract AD and volume. Post-hoc analyses indicated lower tract FA and higher RD in ELD and DEM groups compared to CON, BPD and SCZ groups. Lower FA and higher RD in SCZ compared to CON did not meet statistical significance. In SCZ participants, a significant negative correlation was found between chronic psychosis severity and FA in the SLF-1 (r= -0.45; p=0.035), SLF-2 (r= -0.49; p=0.02) and SLF-3 (r= -0.44; p=0.042). DISCUSSION: Our results indicate impaired white matter tract integrity in elderly populations consistent with myelin damage. Impaired tract integrity in SCZ is most prominent in patients with advanced illness