Asymmetric paralog evolution between the "cryptic" gene Bmp16 and its well-studied sister genes Bmp2 and Bmp4

Hyperglycemia selectively increases cerebral non-oxidative glucose consumption without affecting blood flow

Multiple studies have shown that hyperglycemia increases the cerebral metabolic rate of glucose (CMRglc) in subcortical white matter. This observation remains unexplained. Using positron emission tomography (PET) and euinsulinaemic glucose clamps, we found, for the first time, that acute hyperglycemia increases non-oxidative CMRglc (i.e., aerobic glycolysis (AG)) in subcortical white mater as well as in medial temporal lobe structures, cerebellum and brainstem, all areas with low euglycemic CMRglc. Surprisingly, hyperglycemia did not change regional cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO 2 ), or the blood-oxygen-level-dependent (BOLD) response. Regional gene expression data reveal that brain regions where CMRglc increased have greater expression of hexokinase 2 ( HK2 ). Simulations of glucose transport revealed that, unlike hexokinase 1, HK2 is not saturated at euglycemia, thus accommodating increased AG during hyperglycemia.

Complementary cognitive roles for D2-MSNs and D1-MSNs during interval timing

The role of striatal pathways in cognitive processing is unclear. We studied dorsomedial striatal cognitive processing during interval timing, an elementary cognitive task that requires mice to estimate intervals of several seconds and involves working memory for temporal rules as well as attention to the passage of time. We harnessed optogenetic tagging to record from striatal D2-dopamine receptor-expressing medium spiny neurons (D2-MSNs) in the indirect pathway and from D1-dopamine receptor-expressing MSNs (D1-MSNs) in the direct pathway. We found that D2-MSNs and D1-MSNs exhibited distinct dynamics over temporal intervals as quantified by principal component analyses and trial-by-trial generalized linear models. MSN recordings helped construct and constrain a four-parameter drift-diffusion computational model. This model predicted that disrupting either D2-MSNs or D1-MSNs would increase interval timing response times and alter MSN firing. In line with this prediction, we found that optogenetic inhibition or pharmacological disruption of either D2-MSNs or D1-MSNs increased interval timing response times. Pharmacologically disrupting D2-MSNs or D1-MSNs also changed MSN dynamics and degraded trial-by-trial temporal decoding. Together, our findings demonstrate that D2-MSNs and D1-MSNs make complementary contributions to interval timing despite opposing dynamics, implying that striatal direct and indirect pathways work together to shape temporal control of action. These data provide novel insight into basal ganglia cognitive operations beyond movement and have implications for human striatal diseases and therapies targeting striatal pathways.

Human Pluripotent Stem Cell-Derived Astrocyte Functionality Compares Favorably with Primary Rat Astrocytes

Astrocytes are essential for the formation and maintenance of neural networks. However, a major technical challenge for investigating astrocyte function and disease-related pathophysiology has been the limited ability to obtain functional human astrocytes. Despite recent advances in human pluripotent stem cell (hPSC) techniques, primary rodent astrocytes remain the gold standard in coculture with human neurons. We demonstrate that a combination of leukemia inhibitory factor (LIF) and bone morphogenetic protein-4 (BMP4) directs hPSC-derived neural precursor cells to a highly pure population of astroglia in 28 d. Using single-cell RNA sequencing, we confirm the astroglial identity of these cells and highlight profound transcriptional adaptations in cocultured hPSC-derived astrocytes and neurons, consistent with their further maturation. In coculture with human neurons, multielectrode array recordings revealed robust network activity of human neurons in a coculture with hPSC-derived or rat astrocytes [3.63 ± 0.44 min-1 (hPSC-derived), 2.86 ± 0.64 min-1 (rat); p = 0.19]. In comparison, we found increased spike frequency within network bursts of human neurons cocultured with hPSC-derived astrocytes [56.31 ± 8.56 Hz (hPSC-derived), 24.77 ± 4.04 Hz (rat); p < 0.01], and whole-cell patch-clamp recordings revealed an increase of postsynaptic currents [2.76 ± 0.39 Hz (hPSC-derived), 1.07 ± 0.14 Hz (rat); p < 0.001], consistent with a corresponding increase in synapse density [14.90 ± 1.27/100 μm2 (hPSC-derived), 8.39 ± 0.63/100 μm2 (rat); p < 0.001]. Taken together, we show that hPSC-derived astrocytes compare favorably with rat astrocytes in supporting human neural network activity and maturation, providing a fully human platform for investigating astrocyte function and neuronal-glial interactions.

Prior Negative Experience Biases Activity of Medial Amygdala during Interstrain Social Engagement in Male Rats

Social recognition is an essential part of social function and often promotes specific social behaviors based on prior experience. Social and defensive behaviors in particular often emerge with prior experiences of familiarity or novelty/stress, respectively. This is also commonly seen in rodents toward same-strain and interstrain conspecifics. Medial amygdala (MeA) activity guides social choice based on age and sex recognition and is sensitive to social experiences. However, little is known about whether the MeA exhibits differential responses based on strain or how this is impacted by experience. Social stress impacts posterior MeA (MeAp) function and can shift measures of social engagement. However, it is unclear how stress impacts MeAp activity and contributes to altered social behavior. The primary goal of this study in adult male Sprague Dawley rats was to determine whether prior stress experience with a different-strain (Long-Evans) rat impacts MeAp responses to same-strain and different-strain conspecifics in parallel with a change in behavior using in vivo fiber photometry. We found that MeAp activity was uniformly activated during social contact with a novel same-strain rat during a three-chamber social preference test following control handling but became biased toward a novel different-strain rat following social stress. Socially stressed rats also showed initially heightened social interaction with novel same-strain rats but showed social avoidance and fragmented social behavior with novel different-strain rats relative to controls. These results indicate that heightened MeAp activity may guide social responses to novel, threatening, rather than non-threatening, social stimuli after stress.

Automated identification of fleck lesions in Stargardt disease using deep learning enhances lesion detection sensitivity and enables morphometric analysis of flecks

PURPOSE

To classify fleck lesions and assess artificial intelligence (AI) in identifying flecks in Stargardt disease (STGD).

METHODS

A retrospective study of 170 eyes from 85 consecutive patients with confirmed STGD. Fundus autofluorescence images were extracted, and flecks were manually outlined. A deep learning model was trained, and a hold-out testing subset was used to compare with manually identified flecks and for graders to assess. Flecks were clustered using K-means clustering.

RESULTS

Of the 85 subjects, 45 were female, and the median age was 37 years (IQR 25-59). A subset of subjects (n=41) had clearly identifiable fleck lesions, and an AI was successfully trained to identify these lesions (average Dice score of 0.53, n=18). The AI segmentation had smaller (0.018 compared with 0.034 mm2, p<0.001) but more numerous flecks (75.5 per retina compared with 40.0, p<0.001), but the total size of flecks was not different. The AI model had higher sensitivity to detect flecks but resulted in more false positives. There were two clusters of flecks based on morphology: broadly, one cluster of small round flecks and another of large amorphous flecks. The per cent frequency of small round flecks negatively correlated with subject age (r=-0.31, p<0.005).

CONCLUSIONS

AI-based detection of flecks shows greater sensitivity than human graders but with a higher false-positive rate. With further optimisation to address current shortcomings, this approach could be used to prescreen subjects for clinical research. The feasibility and utility of quantifying fleck morphology in conjunction with AI-based segmentation as a biomarker of progression require further study.

Gut Microbiota and DTI Microstructural Brain Alterations in Rodents Due to Morphine Self-Administration

The opioid epidemic is an evolving health crisis in need of interventions that target all domains of maladaptive changes due to chronic use and abuse. Opioids are known for their effects on the opioid and dopaminergic systems, in addition to neurocircuitry changes that mediate changes in behavior; however, new research lines are looking at complementary changes in the brain and gut. The gut-brain axis (GBA) is a bidirectional signaling process that permits feedback between the brain and gut and is altered in subjects with opioid use disorders. In this work, we determine longitudinal, non-invasive, and in-vivo complementary changes in the brain and gut in rodents trained to self-administer morphine for two weeks using MRI and 16S rDNA analysis of fecal matter. We assess the changes occurring during both an acute phase (early in the self-administration process, after two days of self-administration) and a chronic phase (late in the self-administration process, after two weeks of self-administration), with all measurements benchmarked against baseline (naïve, non-drug state). Rats were surgically implanted with an intravenous jugular catheter for self-administration of morphine. Rats were allowed to choose between an active lever, which delivers a single infusion of morphine (0.4 mg/kg/infusion), or an inactive lever, which had no consequence upon pressing. Animals were scanned in a 7T MRI scanner three times (baseline, acute, and chronic), and before scanning, fecal matter was collected from each rat. After the last scan session, a subset of animals was euthanized, and brains were preserved for immunohistochemistry analysis. We found early changes in gut microbiota diversity and specific abundance as early as the acute phase that persisted into the chronic phase. In MRI, we identified alterations in diffusivity indices both within subjects and between groups, showing a main effect in the striatum, thalamus, and somatosensory cortex. Finally, immunohistochemistry analyses revealed increased neuroinflammatory markers in the thalamus of rats exposed to morphine. Overall, we demonstrate that morphine self-administration shapes the brain and gut microbiota. In conclusion, gut changes precede the anatomical effects observed in MRI features, with neuroinflammation emerging as a crucial link mediating communication between the gut and the brain. This highlights neuroinflammation as a potential target in addressing the impacts of opioid use.

Thermotherapy has Sexually Dimorphic Responses in APP/PS1 Mice

A thermoregulatory decline occurs with age due to changes in muscle mass, vasoconstriction, and metabolism that lowers core body temperature (Tc). Although lower Tc is a biomarker of successful aging, we have previously shown this worsens cognitive performance in the APP/PS1 mouse model of Alzheimer's disease (AD) [1]. We hypothesized that elevating Tc with thermotherapy would improve metabolism and cognition in APP/PS1 mice. From 6-12 months of age, male and female APP/PS1 and C57BL/6 mice were chronically housed at 23 or 30°C. At 12 months of age, mice were assayed for insulin sensitivity, glucose tolerance, and spatial cognition. Plasma, hippocampal, and peripheral (adipose, hepatic, and skeletal muscle) samples were procured postmortem and tissue-specific markers of amyloid accumulation, metabolism, and inflammation were assayed. Chronic 30°C exposure increased Tc in all groups except female APP/PS1 mice. All mice receiving thermotherapy had either improved glucose tolerance or insulin sensitivity, but the underlying processes responsible for these effects varied across sexes. In males, glucose regulation was influenced predominantly by hormonal signaling in plasma and skeletal muscle glucose transporter 4 expression, whereas in females, this was modulated at the tissue level. Thermotherapy improved spatial navigation in male C57BL/6 and APP/PS1 mice, with the later attributed to reduced hippocampal soluble amyloid-β (Aβ) 42 . Female APP/PS1 mice exhibited worse spatial memory recall after chronic thermotherapy. Together, the data highlights the metabolic benefits of passive thermotherapy, but future studies are needed to determine therapeutic benefits for those with AD.

The progression of neurovascular features and chemokine signatures of the intervertebral disc with degeneration

Inflammatory cytokine production and de novo neurovascularization have been identified in painful, degenerated intervertebral discs (IVDs). However, the temporal trajectories of these key pathoanatomical features, including the cascade of inflammatory chemokines and neo- vessel and neurite infiltration, and their associations with IVD degeneration, remain relatively unknown. Investigating this process in the caudal mouse IVD enables the opportunity to study the tissue-specific response without confounding inflammatory signaling from neighboring structures. Thus this study aims to define the progression of chemokine production and neurovascular invasion during the IVD degeneration initiated by injury in the caudal spine 3-month-old C57BL6/J mice. Forty-nine IVD-secreted chemokines and matrix metalloproteinases (MMPs) was measured using multiplex ELISA, and the intradiscal infiltrating vessels (endomucin) and nerves (protein-gene-product 9.5) was quantified in the tissue volume using immunohistochemistry. Injury provoked the increase secretion of IL6, CCL2, CCL12, CCL17, CCL20, CCL21, CCL22, CXCL2 and MMP2 proteins. The centrality and structure of inflammatory networks in IVDs evolved over the 12 post-injury weeks, highlighting distinct responses between the acute and chronic phases. Neurites propagated rapidly within 2-weeks post-injury and remained relatively constant until 12-weeks. Vascular vessel length was observed to peak at 4-weeks post-injury and it regressed by 12-weeks. These findings identified the temporal flux of inflammatory chemokines and pain-associated pathoanatomy in a model of IVD degeneration using the mouse caudal spine.

Coxsackievirus B infection invokes unique cell-type specific responses in primary human pancreatic islets

Coxsackievirus B (CVB) infection has long been considered an environmental factor precipitating Type 1 diabetes (T1D), an autoimmune disease marked by loss of insulin-producing β cells within pancreatic islets. Previous studies have shown CVB infection negatively impacts islet function and viability but do not report on how virus infection individually affects the multiple cell types present in human primary islets. Therefore, we hypothesized that the various islet cell populations have unique transcriptional responses to CVB infection. Here, we performed single-cell RNA sequencing on human cadaveric islets treated with either CVB or poly(I:C), a viral mimic, for 24 and 48 hours. Our global analysis reveals CVB differentially induces dynamic transcriptional changes associated with multiple cell processes and functions over time whereas poly(I:C) promotes an immune response that progressively increases with treatment duration. At the single-cell resolution, we find CVB infects all islet cell types at similar rates yet induces unique cell-type specific transcriptional responses with β, α, and ductal cells having the strongest response. Sequencing and functional data suggest that CVB negatively impacts mitochondrial respiration and morphology in distinct ways in β and α cells, while also promoting the generation of reactive oxygen species. We also observe an increase in the expression of the long-noncoding RNA MIR7-3HG in β cells with high viral titers and reveal its knockdown reduces gene expression of viral proteins as well as apoptosis in stem cell-derived islets. Together, these findings demonstrate a cell-specific transcriptional, temporal, and functional response to CVB infection and provide new insights into the relationship between CVB infection and T1D.

Robust deep learning estimation of cortical bone porosity from MR T1-weighted images for individualized transcranial focused ultrasound planning

Objective

Transcranial focused ultrasound (tFUS) is an emerging neuromodulation approach that has been demonstrated in animals but is difficult to translate to humans because of acoustic attenuation and scattering in the skull. Optimal dose delivery requires subject-specific skull porosity estimates which has traditionally been done using CT. We propose a deep learning (DL) estimation of skull porosity from T1-weighted MRI images which removes the need for radiation-inducing CT scans.

Approach

We evaluate the impact of different DL approaches, including network architecture, input size and dimensionality, multichannel inputs, data augmentation, and loss functions. We also propose back-propagation in the mask (BIM), a method whereby only voxels inside the skull mask contribute to training. We evaluate the robustness of the best model to input image noise and MRI acquisition parameters and propagate porosity estimation errors in thousands of beam propagation scenarios.

Main results

Our best performing model is a cGAN with a ResNet-9 generator with 3D 64×64×64 inputs trained with L1 and L2 losses. The model achieved a mean absolute error of 6.9% in the test set, compared to 9.5% with the pseudo-CT of Izquierdo et al. (38% improvement) and 9.4% with the generic pixel-to-pixel image translation cGAN pix2pix (36% improvement). Acoustic dose distributions in the thalamus were more accurate with our approach than with the pseudo-CT approach of both Burgos et al. and Izquierdo et al, resulting in near-optimal treatment planning and dose estimation at all frequencies compared to CT (reference).

Significance

Our DL approach porosity estimates with ~7% error, is robust to input image noise and MRI acquisition parameters (sequence, coils, field strength) and yields near-optimal treatment planning and dose estimates for both central (thalamus) and lateral brain targets (amygdala) in the 200-1000 kHz frequency range.

Poly(allylamine)-tripolyphosphate polymeric nanoparticle as an NLRP3-dependent systemic adjuvant for the vaccine development

Nanotechnology plays a crucial role in vaccine development and provides the opportunity to design functional nanoparticles (Np) of different compositions, sizes, charges and surface properties for biomedical applications. The present study aims to evaluate a complex coacervate-like Np composed of poly(allylamine hydrochloride) (PAH) and tripolyphosphate (Tpp) as a safe vehicle and adjuvant for systemic vaccines. We investigated the activation of different antigen-presenting cells (APCs) with Np-PAH and its adjuvanticity in Balbc/c and different KO mice that were intraperitoneally immunized with Np-OVA. We found that Np-PAH increased the expression of CD86 and MHCII and promoted the production and secretion of interleukin-1β (IL-1β) and IL-18 through the inflammasome NLRP3 when macrophages and dendritic cells were co-incubated with LPS and Np-PAH. We evidenced an unconventional IL-1β release through the autophagosome pathway. The inhibition of autophagy with 3-methyladenine reduced the LPS/Np-PAH-induced IL-1β secretion. Additionally, our findings showed that the systemic administration of mice with Np-OVA triggered a significant induction of serum OVA-specific IgG and IgG2a, an increased secretion of IFN-γ by spleen cells, and high frequencies of LT CD4 + IFN-γ + and LT CD8 + IFN-γ + . In conclusion, our findings show that PAH-based Np promoted the inflammasome activation of innate cells with Th1-dependent adjuvant properties, making them valuable for formulating of novel preventive or therapeutic vaccines for infectious and non-infectious diseases.

Adiposity, fat-free mass and incident heart failure in 500 000 individuals

BACKGROUND AND AIMS

The independent role of body fat distribution and fat-free mass in heart failure (HF) risk is unclear. We investigated the role of different body composition compartments in risk of HF.

METHODS

Present analyses include 428 087 participants (mean age 55.9 years, 44% male) from the UK Biobank. Associations of long-term average levels of body composition measures with incident HF were determined using adjusted Cox proportional hazards regression models.

RESULTS

Over a median follow-up of 13.8 years, there were 10 455 first-ever incident HF events. Overall, HF risk was more strongly associated with central adiposity (waist circumference (WC) adjusted for body mass index (BMI); HR 1.38, 95% CI 1.32 to 1.45) than general adiposity (BMI adjusted for WC; HR 1.22, 95% CI 1.16 to 1.27). Although dual X-ray absorptiometry-derived body fat remained positively related to HF after adjustment for fat-free mass (HR 1.37, 95% CI 1.18 to 1.59), the association of fat-free mass with HF was substantially attenuated by fat mass (HR 1.12, 95% CI 1.01 to 1.26) while visceral fat (VAT) remained associated with HF independent of subcutaneous fat (HR 1.20, 95% CI 1.09 to 1.33). In analyses of HF subtypes, HF with preserved ejection fraction was independently associated with all fat measures (eg, VAT: HR 1.23, 95% CI 1.12 to 1.35; body fat: HR 1.36, 95% CI 1.17 to 1.57) while HF with reduced ejection fraction was not independently associated with fat measures (eg, VAT: HR 1.29, 95% CI 0.98 to 1.68; body fat: HR 1.29, 95% CI 0.80 to 2.07).

CONCLUSIONS

This large-scale study shows that excess adiposity and fat mass are associated with higher HF risk while the association of fat-free mass with HF could be explained largely by its correlation with fat mass. The study also describes the independent relevance of body fat distribution to HF subtypes, suggesting different mechanisms may be driving their aetiopathogenesis.

Deep-learning-based prediction of glaucoma conversion in normotensive glaucoma suspects

BACKGROUND/AIMS

To assess the performance of deep-learning (DL) models for prediction of conversion to normal-tension glaucoma (NTG) in normotensive glaucoma suspect (GS) patients.

METHODS

Datasets of 12 458 GS eyes were reviewed. Two hundred and ten eyes (105 eyes showing NTG conversion and 105 without conversion), followed up for a minimum of 7 years during which intraocular pressure (IOP) was lower than 21 mm Hg, were included. The features of two fundus images (optic disc photography and red-free retinal nerve fibre layer (RNFL) photography) were extracted by convolutional auto encoder. The extracted features as well as 15 clinical features including age, sex, IOP, spherical equivalent, central corneal thickness, axial length, average circumpapillary RNFL thickness, systolic/diastolic blood pressure and body mass index were used to predict NTG conversion. Prediction was performed using three machine-learning classifiers (ie, XGBoost, Random Forest, Gradient Boosting) with different feature combinations.

RESULTS

All three algorithms achieved high diagnostic accuracy for NTG conversion prediction. The AUCs ranged from 0.987 (95% CI 0.978 to 1.000; Random Forest trained with both fundus images and clinical features) and 0.994 (95% CI 0.984 to 1.000; XGBoost trained with both fundus images and clinical features). XGBoost showed the best prediction performance for time to NTG conversion (mean squared error, 2.24). The top three important clinical features for time-to-conversion prediction were baseline IOP, diastolic blood pressure and average circumpapillary RNFL thickness.

CONCLUSION

DL models, trained with both fundus images and clinical data, showed the potential to predict whether and when normotensive GS patients will show conversion to NTG.

Long-Read Structural and Epigenetic Profiling of a Kidney Tumor-Matched Sample with Nanopore Sequencing and Optical Genome Mapping

Carcinogenesis often involves significant alterations in the cancer genome architecture, marked by large structural and copy number variations (SVs and CNVs) that are difficult to capture with short-read sequencing. Traditionally, cytogenetic techniques are applied to detect such aberrations, but they are limited in resolution and do not cover features smaller than several hundred kilobases. Optical genome mapping and nanopore sequencing are attractive technologies that bridge this resolution gap and offer enhanced performance for cytogenetic applications. These methods profile native, individual DNA molecules, thus capturing epigenetic information. We applied both techniques to characterize a clear cell renal cell carcinoma (ccRCC) tumor's structural and copy number landscape, highlighting the relative strengths of each method in the context of variant size and average read length. Additionally, we assessed their utility for methylome and hydroxymethylome profiling, emphasizing differences in epigenetic analysis applicability.

The Capicua C1 Domain is Required for Full Activity of the CIC::DUX4 Fusion Oncoprotein

Rearrangements between genes can yield neomorphic fusions that drive oncogenesis. Fusion oncogenes are made up of fractional segments of the partner genes that comprise them, with each partner potentially contributing some of its own function to the nascent fusion oncoprotein. Clinically, fusion oncoproteins driving one diagnostic entity are typically clustered into a single molecular subset and are often treated a similar fashion. However, knowledge of where specific fusion breakpoints occur in partner genes, and the resulting retention of functional domains in the fusion, is an important determinant of fusion oncoprotein activity and may differ between patients. This study investigates this phenomena through the example of CIC::DUX4, a fusion between the transcriptional repressor capicua (CIC) and the double homeobox 4 gene (DUX4), which drives an aggressive subset of undifferentiated round cell sarcoma. Using a harmonized dataset of over 100 patient fusion breakpoints from the literature, we show that most bona fide CIC::DUX4 fusions retain the C1 domain, which is known to contribute to DNA binding by wild type CIC. Mechanistically, deletion or mutation of the C1 domain reduces, but does not eliminate, activation of CIC target genes by CIC::DUX4. We also find that expression of C1-deleted CIC::DUX4 is capable of exerting intermediate transformation-related phenotypes compared with those imparted by full-length CIC::DUX4, but was not sufficient for tumorigenesis in a subcutaneous mouse model. In summary, our results suggest a supercharging role for the C1 domain in the activity of CIC::DUX4.

Comprehensive multimodal and multiomic profiling reveals epigenetic and transcriptional reprogramming in lung tumors

Epigenomic mechanisms are critically involved in mediation of genetic and environmental factors that underlie cancer development. Histone modifications represent highly informative epigenomic marks that reveal activation and repression of gene activities and dysregulation of transcriptional control due to tumorigenesis. Here, we present a comprehensive epigenomic and transcriptomic mapping of 18 tumor and 20 non-neoplastic tissues from non-small cell lung adenocarcinoma patients. Our profiling covers 5 histone marks including activating (H3K4me3, H3K4me1, and H3K27ac) and repressive (H3K27me3 and H3K9me3) marks and the transcriptome using only 20 mg of tissue per sample, enabled by low-input omic technologies. Using advanced integrative bioinformatic analysis, we uncovered cancer-driving signaling cascade networks, changes in 3D genome modularity, and differential expression and functionalities of transcription factors and noncoding RNAs. Many of these identified genes and regulatory molecules showed no significant change in their expression or a single epigenomic modality, emphasizing the power of integrative multimodal and multiomic analysis using patient samples.

Transfer learning predicts species-specific drug interactions in emerging pathogens

Machine learning (ML) algorithms are necessary to efficiently identify potent drug combinations within a large candidate space to combat drug resistance. However, existing ML approaches cannot be applied to emerging and under-studied pathogens with limited training data. To address this, we developed a transfer learning and crowdsourcing framework (TACTIC) to train ML models on data from multiple bacteria. TACTIC was built using 2,965 drug interactions from 12 bacterial strains and outperformed traditional ML models in predicting drug interaction outcomes for species that lack training data. Top TACTIC model features revealed genetic and metabolic factors that influence cross-species and species-specific drug interaction outcomes. Upon analyzing ~600,000 predicted drug interactions across 9 metabolic environments and 18 bacterial strains, we identified a small set of drug interactions that are selectively synergistic against Gram-negative (e.g., A. baumannii) and non-tuberculous mycobacteria (NTM) pathogens. We experimentally validated synergistic drug combinations containing clarithromycin, ampicillin, and mecillinam against M. abscessus, an emerging pathogen with growing levels of antibiotic resistance. Lastly, we leveraged TACTIC to propose selectively synergistic drug combinations to treat bacterial eye infections (endophthalmitis).

Sitetack: A Deep Learning Model that Improves PTM Prediction by Using Known PTMs

Post-translational modifications (PTMs) increase the diversity of the proteome and are vital to organismal life and therapeutic strategies. Deep learning has been used to predict PTM locations. Still, limitations in datasets and their analyses compromise success. Here we evaluate the use of known PTM sites in prediction via sequence-based deep learning algorithms. Specifically, PTM locations were encoded as a separate amino acid before sequences were encoded via word embedding and passed into a convolutional neural network that predicts the probability of a modification at a given site. Without labeling known PTMs, our model is on par with others. With labeling, however, we improved significantly upon extant models. Moreover, knowing PTM locations can increase the predictability of a different PTM. Our findings highlight the importance of PTMs for the installation of additional PTMs. We anticipate that including known PTM locations will enhance the performance of other proteomic machine learning algorithms.

The balance between intrinsic and ecological fitness defines new regimes in eco-evolutionary population dynamics

Selection upon intrinsic fitness differences is one of the most basic mechanisms of evolution, fundamental to all biology. Equally, within macroscopic populations and microscopic environments, ecological interactions influence evolution. Direct experimental evidence of ecological selection between microscopic agents continues to grow. Whilst eco-evolutionary dynamics describes how interactions influence population fitness and composition, we build a model that allows ecological aspects of these interactions to fall on a spectrum independent of the intrinsic fitness of the population. With our mathematical framework, we show how ecological interactions between mutating populations modify the estimated evolutionary trajectories expected from monoculture fitnesses alone. We derive and validate analytical stationary solutions to our partial differential equations that depend on intrinsic and ecological terms, and mutation rates. We determine cases in which these interactions modify evolution in such ways as to, for example, maintain or invert existing monoculture fitness differences. This work discusses the importance of understanding ecological and intrinsic selection effects to avoid misleading conclusions from experiments and defines new ways to assess this balance from experimental results. Using published experimental data, we also show evidence that real microbiological systems can span intrinsic fitness dominant and ecological-effect dominant regimes and that ecological contributions can change with an environment to exaggerate or counteract the composite populations' intrinsic fitness differences.

Neurochemical Predictors of Generalized Learning Induced by Brain Stimulation and Training

Methods of cognitive enhancement for humans are most impactful when they generalize across tasks. However, the extent to which such "transfer" is possible via interventions is widely debated. In addition, the contribution of excitatory and inhibitory processes to such transfer is unknown. Here, in a large-scale neuroimaging individual differences study with humans (both sexes), we paired multitasking training and noninvasive brain stimulation (transcranial direct current stimulation, tDCS) over multiple days and assessed performance across a range of paradigms. In addition, we varied tDCS dosage (1.0 and 2.0 mA), electrode montage (left or right prefrontal regions), and training task (multitasking vs a control task) and assessed GABA and glutamate concentrations via ultrahigh field 7T magnetic resonance spectroscopy. Generalized benefits were observed in spatial attention, indexed by visual search performance, when multitasking training was combined with 1.0 mA stimulation targeting either the left or right prefrontal cortex (PFC). This transfer effect persisted for ∼30 d post intervention. Critically, the transferred benefits associated with right prefrontal tDCS were predicted by pretraining concentrations of glutamate in the PFC. Thus, the effects of this combined stimulation and training protocol appear to be linked predominantly to excitatory brain processes.

Decoding the Best Automated Segmentation Tools for Vascular White Matter Hyperintensities in the Aging Brain: A Clinician's Guide to Precision and Purpose

Cerebrovascular damage from small vessel disease (SVD) occurs in healthy and pathological aging. SVD markers, such as white matter hyperintensities (WMH), are commonly found in individuals over 60 and increase in prevalence with age. WMHs are detectable on standard MRI by adhering to the STRIVE criteria. Currently, visual assessment scales are used in clinical and research scenarios but is time-consuming and has rater variability, limiting its practicality. Addressing this issue, our study aimed to determine the most precise WMH segmentation software, offering insights into methodology and usability to balance clinical precision with practical application. This study employed a dataset comprising T1, FLAIR, and DWI images from 300 cognitively healthy older adults. WMHs in this cohort were evaluated using four automated neuroimaging tools: Lesion Prediction Algorithm (LPA) and Lesion Growth Algorithm (LGA) from Lesion Segmentation Tool (LST), Sequence Adaptive Multimodal Segmentation (SAMSEG), and Brain Intensity Abnormalities Classification Algorithm (BIANCA). Additionally, clinicians manually segmented WMHs in a subsample of 45 participants to establish a gold standard. The study assessed correlations with the Fazekas scale, algorithm performance, and the influence of WMH volume on reliability. Results indicated that supervised algorithms were superior, particularly in detecting small WMHs, and can improve their consistency when used in parallel with unsupervised tools. The research also proposed a biomarker for moderate vascular damage, derived from the top 95th percentile of WMH volume in healthy individuals aged 50 to 60. This biomarker effectively differentiated subgroups within the cohort, correlating with variations in brain structure and behavior.

Pooled screening for CAR function identifies novel IL13Rα2-targeted CARs for treatment of glioblastoma

Chimeric antigen receptor therapies have demonstrated potent efficacy in treating B cell malignancies, but have yet to meaningfully translate to solid tumors. Here, we utilize our pooled screening platform, CARPOOL, to expedite the discovery of CARs with anti-tumor functions necessary for solid tumor efficacy. We performed selections in primary human T cells expressing a library of 1.3×10 6 3 rd generation CARs targeting IL13Rα2, a cancer testis antigen commonly expressed in glioblastoma. Selections were performed for cytotoxicity, proliferation, memory formation, and persistence upon repeated antigen challenge. Each enriched CAR robustly produced the phenotype for which it was selected, and one enriched CAR triggered potent cytotoxicity and long-term proliferation upon in vitro tumor rechallenge. It also showed significantly improved persistence and comparable antigen-specific tumor control in a microphysiological human in vitro model and a xenograft model of human glioblastoma. Taken together, this work demonstrates the utility of extending CARPOOL to diseases beyond hematological malignancies and represents the largest exploration of signaling combinations in human primary cells to date.

Analysis of Amblyomma americanum microRNAs in response to Ehrlichia chaffeensis infection and their potential role in vectorial capacity

Background

MicroRNAs (miRNAs) represent a subset of small noncoding RNAs and carry tremendous potential for regulating gene expression at the post-transcriptional level. They play pivotal roles in distinct cellular mechanisms including inhibition of bacterial, parasitic, and viral infections via immune response pathways. Intriguingly, pathogens have developed strategies to manipulate the host's miRNA profile, fostering environments conducive to successful infection. Therefore, changes in an arthropod host's miRNA profile in response to pathogen invasion could be critical in understanding host-pathogen dynamics. Additionally, this area of study could provide insights into discovering new targets for disease control and prevention. The main objective of the present study is to investigate the functional role of differentially expressed miRNAs upon Ehrlichia chaffeensis, a tick-borne pathogen, infection in tick vector, Amblyomma americanum.

Methods

Small RNA libraries from uninfected and E. chaffeensis-infected Am. americanum midgut and salivary gland tissues were prepared using the Illumina Truseq kit. Small RNA sequencing data was analyzed using miRDeep2 and sRNAtoolbox to identify novel and known miRNAs. The differentially expressed miRNAs were validated using a quantitative PCR assay. Furthermore, a miRNA inhibitor approach was used to determine the functional role of selected miRNA candidates.

Results

The sequencing of small RNA libraries generated >147 million raw reads in all four libraries and identified a total of >250 miRNAs across the four libraries. We identified 23 and 14 differentially expressed miRNAs in salivary glands, and midgut tissues infected with E. chaffeensis, respectively. Three differentially expressed miRNAs (miR-87, miR-750, and miR-275) were further characterized to determine their roles in pathogen infection. Inhibition of target miRNAs significantly decreased the E. chaffeensis load in tick tissues, which warrants more in-depth mechanistic studies.

Conclusions

The current study identified known and novel miRNAs and suggests that interfering with these miRNAs may impact the vectorial capacity of ticks to harbor Ehrlichia. This study identified several new miRNAs for future analysis of their functions in tick biology and tick-pathogen interaction studies.

Transcranial Blood-Brain Barrier Opening in Alzheimer's Disease Patients Using a Portable Focused Ultrasound System with Real-Time 2-D Cavitation Mapping

Background

Focused ultrasound (FUS) in combination with microbubbles has recently shown great promise in facilitating blood-brain barrier (BBB) opening for drug delivery and immunotherapy in Alzheimer's disease (AD). However, it is currently limited to systems integrated within the MRI suites or requiring post-surgical implants, thus restricting its widespread clinical adoption. In this pilot study, we investigate the clinical safety and feasibility of a portable, non-invasive neuronavigation-guided FUS (NgFUS) system with integrated real-time 2-D microbubble cavitation mapping.

Methods

A phase 1 clinical study with mild to moderate AD patients (N=6) underwent a single session of microbubble-mediated NgFUS to induce transient BBB opening (BBBO). Microbubble activity under FUS was monitored with real-time 2-D cavitation maps and dosing to ensure the efficacy and safety of the NgFUS treatment. Post-operative MRI was used for BBB opening and closure confirmation as well as safety assessment. Changes in AD biomarker levels in both blood serum and extracellular vesicles (EVs) were evaluated, while changes in amyloid-beta (Aβ) load in the brain were assessed through 18F-Florbetapir PET.

Results

BBBO was achieved in 5 out of 6 subjects with an average volume of 983±626 mm3 following FUS at the right frontal lobe both in white and gray matter regions. The outpatient treatment was completed within 34.8±10.7 min. Cavitation dose significantly correlated with the BBBO volume (R 2>0.9, N=4), demonstrating the portable NgFUS system's capability of predicting opening volumes. The cavitation maps co-localized closely with the BBBO location, representing the first report of real-time transcranial 2-D cavitation mapping in the human brain. Larger opening volumes correlated with increased levels of AD biomarkers, including Aβ42 (R 2=0.74), Tau (R 2=0.95), and P-Tau181 (R 2=0.86), assayed in serum-derived EVs sampled 3 days after FUS (N=5). From PET scans, subjects showed a lower Aβ load increase in the treated frontal lobe region compared to the contralateral region. Reduction in asymmetry standardized uptake value ratios (SUVR) correlated with the cavitation dose (R 2>0.9, N=3). Clinical changes in the mini-mental state examination over 6 months were within the expected range of cognitive decline with no additional changes observed as a result of FUS.

Conclusion

We showed the safety and feasibility of this cost-effective and time-efficient portable NgFUS treatment for BBBO in AD patients with the first demonstration of real-time 2-D cavitation mapping. The cavitation dose correlated with BBBO volume, a slowed increase in pathology, and serum detection of AD proteins. Our study highlights the potential for accessible FUS treatment in AD, with or without drug delivery.

Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions

T-cells recognize antigens and induce specialized gene expression programs (GEPs) enabling functions including proliferation, cytotoxicity, and cytokine production. Traditionally, different classes of helper T-cells express mutually exclusive responses - for example, Th1, Th2, and Th17 programs. However, new single-cell RNA sequencing (scRNA-Seq) experiments have revealed a continuum of T-cell states without discrete clusters corresponding to these subsets, implying the need for new analytical frameworks. Here, we advance the characterization of T-cells with T-CellAnnoTator (TCAT), a pipeline that simultaneously quantifies pre-defined GEPs capturing activation states and cellular subsets. From 1,700,000 T-cells from 700 individuals across 38 tissues and five diverse disease contexts, we discover 46 reproducible GEPs reflecting the known core functions of T-cells including proliferation, cytotoxicity, exhaustion, and T helper effector states. We experimentally characterize several novel activation programs and apply TCAT to describe T-cell activation and exhaustion in Covid-19 and cancer, providing insight into T-cell function in these diseases.

Baseline functional connectivity predicts who will benefit from neuromodulation: evidence from primary progressive aphasia

Background

Identifying the characteristics of individuals who demonstrate response to an intervention allows us to predict who is most likely to benefit from certain interventions. Prediction is challenging in rare and heterogeneous diseases, such as primary progressive aphasia (PPA), that have varying clinical manifestations. We aimed to determine the characteristics of those who will benefit most from transcranial direct current stimulation (tDCS) of the left inferior frontal gyrus (IFG) using a novel heterogeneity and group identification analysis.

Methods

We compared the predictive ability of demographic and clinical patient characteristics (e.g., PPA variant and disease progression, baseline language performance) vs. functional connectivity alone (from resting-state fMRI) in the same cohort.

Results

Functional connectivity alone had the highest predictive value for outcomes, explaining 62% and 75% of tDCS effect of variance in generalization (semantic fluency) and in the trained outcome of the clinical trial (written naming), contrasted with <15% predicted by clinical characteristics, including baseline language performance. Patients with higher baseline functional connectivity between the left IFG (opercularis and triangularis), and between the middle temporal pole and posterior superior temporal gyrus, were most likely to benefit from tDCS.

Conclusions

We show the importance of a baseline 7-minute functional connectivity scan in predicting tDCS outcomes, and point towards a precision medicine approach in neuromodulation studies. The study has important implications for clinical trials and practice, providing a statistical method that addresses heterogeneity in patient populations and allowing accurate prediction and enrollment of those who will most likely benefit from specific interventions.

Enhancing Prosthetic Vision by Upgrade of a Subretinal Photovoltaic Implant in situ

In patients with atrophic age-related macular degeneration, subretinal photovoltaic implant (PRIMA) provided visual acuity up to 20/440, matching its 100μm pixels size. Next-generation implants with smaller pixels should significantly improve the acuity. This study in rats evaluates removal of a subretinal implant, replacement with a newer device, and the resulting grating acuity in-vivo. Six weeks after the initial implantation with planar and 3-dimensional devices, the retina was re-detached, and the devices were successfully removed. Histology demonstrated a preserved inner nuclear layer. Re-implantation of new devices into the same location demonstrated retinal re-attachment to a new implant. New devices with 22μm pixels increased the grating acuity from the 100μm capability of PRIMA implants to 28μm, reaching the limit of natural resolution in rats. Reimplanted devices exhibited the same stimulation threshold as for the first implantation of the same implants in a control group. This study demonstrates the feasibility of safely upgrading the subretinal photovoltaic implants to improve prosthetic visual acuity.

Simultaneous cortical, subcortical, and brainstem mapping of sensory activation

Non-painful tactile sensory stimuli are processed in the cortex, subcortex, and brainstem. Recent functional magnetic resonance imaging (fMRI) studies have highlighted the value of whole-brain, systems-level investigation for examining pain processing. However, whole-brain fMRI studies are uncommon, in part due to challenges with signal to noise when studying the brainstem. Furthermore, the differentiation of small sensory brainstem structures such as the cuneate and gracile nuclei necessitates high resolution imaging. To address this gap in systems-level sensory investigation, we employed a whole-brain, multi-echo fMRI acquisition at 3T with multi-echo independent component analysis (ME-ICA) denoising and brainstem-specific modeling to enable detection of activation across the entire sensory system. In healthy participants, we examined patterns of activity in response to non-painful brushing of the right hand, left hand, and right foot, and found the expected lateralization, with distinct cortical and subcortical responses for upper and lower limb stimulation. At the brainstem level, we were able to differentiate the small, adjacent cuneate and gracile nuclei, corresponding to hand and foot stimulation respectively. Our findings demonstrate that simultaneous cortical, subcortical, and brainstem mapping at 3T could be a key tool to understand the sensory system in both healthy individuals and clinical cohorts with sensory deficits.

RummaGEO: Automatic Mining of Human and Mouse Gene Sets from GEO

The Gene Expression Omnibus (GEO) is a major open biomedical research repository for transcriptomics and other omics datasets. It currently contains millions of gene expression samples from tens of thousands of studies collected by many biomedical research laboratories from around the world. While users of the GEO repository can search the metadata describing studies for locating relevant datasets, there are currently no methods or resources that facilitate global search of GEO at the data level. To address this shortcoming, we developed RummaGEO, a webserver application that enables gene expression signature search of a large collection of human and mouse RNA-seq studies deposited into GEO. To develop the search engine, we performed offline automatic identification of sample conditions from the uniformly aligned GEO studies available from ARCHS4. We then computed differential expression signatures to extract gene sets from these studies. In total, RummaGEO currently contains 135,264 human and 158,062 mouse gene sets extracted from 23,395 GEO studies. Next, we analyzed the contents of the RummaGEO database to identify statistical patterns and perform various global analyses. The contents of the RummaGEO database are provided as a web-server search engine with signature search, PubMed search, and metadata search functionalities. Overall, RummaGEO provides an unprecedented resource for the biomedical research community enabling hypothesis generation for many future studies. The RummaGEO search engine is available from: https://rummageo.com/.

Remembering what we imagine: the role of event schemas in shaping how imagined autobiographical events are recalled

Much like recalling autobiographical memories, constructing imagined autobiographical events depends on episodic memory processes. The ability to imagine events contributes to several future-oriented behaviors (e.g., decision-making, problem solving), which relies, in part, on the ability to remember the imagined events. A factor affecting the memorability of such events is their adherence to event schemas-conceptualizations of how events generally unfold. In the current study, we examined how two aspects of event schemas-event expectancy and familiarity-affect the ability to recall imagined events. Participants first imagined and described in detail autobiographical events that either aligned with or deviated from an event, expected to occur in a context (e.g., a kitchen) that was either familiar or unfamiliar. This resulted in imaginations ranging from maximally schema-congruent (expected events in a familiar context) to maximally novel (unexpected events in an unfamiliar context). Twenty-four hours later, participants recalled these imagined events. Recollections were scored for the number of reinstated details from the imaginations and the number of newly added details. We found greater reinstatement of details for both the maximally congruent and maximally novel events, while maximally novel events were recalled more precisely than other events (i.e., fewer added details). Our results indicate a complementary benefit to remembering schematic and novel imagined events, which may guide equally important but distinct future-oriented behaviors.

Small extracellular vesicles promote stiffness-mediated metastasis

Tissue stiffness is a critical prognostic factor in breast cancer and is associated with metastatic progression. Here we show an alternative and complementary hypothesis of tumor progression whereby physiological matrix stiffness affects the quantity and protein cargo of small EVs produced by cancer cells, which in turn drive their metastasis. Primary patient breast tissue produces significantly more EVs from stiff tumor tissue than soft tumor adjacent tissue. EVs released by cancer cells on matrices that model human breast tumors (25 kPa; stiff EVs) feature increased adhesion molecule presentation (ITGα 2 β 1 , ITGα 6 β 4 , ITGα 6 β 1 , CD44) compared to EVs from softer normal tissue (0.5 kPa; soft EVs), which facilitates their binding to extracellular matrix (ECM) protein collagen IV, and a 3-fold increase in homing ability to distant organs in mice. In a zebrafish xenograft model, stiff EVs aid cancer cell dissemination through enhanced chemotaxis. Moreover, normal, resident lung fibroblasts treated with stiff and soft EVs change their gene expression profiles to adopt a cancer associated fibroblast (CAF) phenotype. These findings show that EV quantity, cargo, and function depend heavily on the mechanical properties of the extracellular microenvironment.

Evaluation of Treatment of Methicillin-Resistant Staphylococcus aureus Biofilms with Intermittent Electrochemically-Generated H2O2 or HOCl

Chronic wound infections can be difficult to treat and may lead to impaired healing and worsened patient outcomes. Novel treatment strategies are needed. This study evaluated effects of intermittently produced H2O2 and HOCl, generated via an electrochemical bandage (e-bandage), against methicillin-resistant Staphylococcus aureus biofilms in an agar membrane biofilm model. By changing the working electrode potential, the e-bandage generated either HOCl (1.5 VAg/AgCl) or H2O2 (-0.6 VAg/AgCl). The degree of biocidal activity of intermittent treatment with HOCl and H2O2 correlated with HOCl treatment time; HOCl treatment durations of 0, 1.5, 3, 4.5, and 6 hours (with the rest of the 6 hour total treatment time devoted to H2O2 generation) resulted in mean biofilm reductions of 1.36±0.2, 2.22±0.16, 3.46±0.38, 4.63±0.74 and 7.66±0.5 log CFU/cm2, respectively vs. non-polarized controls, respectively. However, application of H2O2 immediately after HOCl treatment was detrimental to biofilm removal. For example, 3-hours HOCl treatment followed by 3-hours H2O2 resulted in a 1.90±0.84 log CFU/cm2 lower mean biofilm reduction than 3-hours HOCl treatment followed by 3-hours non-polarization. HOCl generated over 3-hours exhibited biocidal activity for at least 7.5-hours after e-bandage operation ceased; 3-hours of HOCl generation followed by 7.5-hours of non-polarization resulted in a biofilm cell reduction of 7.92±0.12 log CFU/cm2 vs. non polarized controls. Finally, intermittent treatment with HOCl (i.e., interspersed with periods of e-bandage non-polarization) for various intervals showed similar effects (approximately 6 log CFU/cm2 reduction vs. non-polarized control) to continuous treatment with HOCl for 3-hours, followed by 3-hours of non-polarization. These findings suggest that timing and sequencing of HOCl and H2O2 treatments are crucial for maximizing biofilm control.

The 24-Hour Time Course of Integrated Molecular Responses to Resistance Exercise in Human Skeletal Muscle Implicates MYC as a Hypertrophic Regulator That is Sufficient for Growth

Molecular control of recovery after exercise in muscle is temporally dynamic. A time course of biopsies around resistance exercise (RE) combined with -omics is necessary to better comprehend the molecular contributions of skeletal muscle adaptation in humans. Vastus lateralis biopsies before and 30 minutes, 3-, 8-, and 24-hours after acute RE were collected. A time-point matched biopsy-only group was also included. RNA-sequencing defined the transcriptome while DNA methylomics and computational approaches complemented these data. The post-RE time course revealed: 1) DNA methylome responses at 30 minutes corresponded to upregulated genes at 3 hours, 2) a burst of translation- and transcription-initiation factor-coding transcripts occurred between 3 and 8 hours, 3) global gene expression peaked at 8 hours, 4) ribosome-related genes dominated the mRNA landscape between 8 and 24 hours, 5) methylation-regulated MYC was a highly influential transcription factor throughout the 24-hour recovery and played a primary role in ribosome-related mRNA levels between 8 and 24 hours. The influence of MYC in human muscle adaptation was strengthened by transcriptome information from acute MYC overexpression in mouse muscle. To test whether MYC was sufficient for hypertrophy, we generated a muscle fiber-specific doxycycline inducible model of pulsatile MYC induction. Periodic 48-hour pulses of MYC over 4 weeks resulted in higher muscle mass and fiber size in the soleus of adult female mice. Collectively, we present a temporally resolved resource for understanding molecular adaptations to RE in muscle and reveal MYC as a regulator of RE-induced mRNA levels and hypertrophy.

The sodium-proton exchangers sNHE and NHE1 control plasma membrane hyperpolarization in mouse sperm

Sperm capacitation, crucial for fertilization, occurs in the female reproductive tract and can be replicated in vitro using a medium rich in bicarbonate, calcium, and albumin. These components trigger the cAMP-PKA signaling cascade, proposed to promote hyperpolarization of the mouse sperm plasma membrane through activation of SLO3 K+ channel. Hyperpolarization is a hallmark of capacitation: proper membrane hyperpolarization renders higher in vitro fertilizing ability, while Slo3 KO mice are infertile. However, the precise regulation of SLO3 opening remains elusive. Our study challenges the involvement of PKA in this event and reveals the role of Na+/H+ exchangers. During capacitation, calcium increase through CatSper channels activates NHE1, while cAMP directly stimulates the sperm-specific NHE, collectively promoting the alkalinization threshold needed for SLO3 opening. Hyperpolarization then feeds back Na+/H+ activity. Our work is supported by pharmacology, and a plethora of KO mouse models, and proposes a novel pathway leading to hyperpolarization.

Spatial visualization of A-to-I Editing in cells using Endonuclease V Immunostaining Assay (EndoVIA)

Adenosine-to-Inosine (A-to-I) editing is one of the most widespread post-transcriptional RNA modifications and is catalyzed by adenosine deaminases acting on RNA (ADARs). Varying across tissue types, A-to-I editing is essential for numerous biological functions and dysregulation leads to autoimmune and neurological disorders, as well as cancer. Recent evidence has also revealed a link between RNA localization and A-to-I editing, yet understanding of the mechanisms underlying this relationship and its biological impact remains limited. Current methods rely primarily on in vitro characterization of extracted RNA that ultimately erases subcellular localization and cell-to-cell heterogeneity. To address these challenges, we have repurposed Endonuclease V (EndoV), a magnesium dependent ribonuclease that cleaves inosine bases in edited RNA, to selectively bind and detect A-to-I edited RNA in cells. The work herein introduces Endonuclease V Immunostaining Assay (EndoVIA), a workflow that provides spatial visualization of edited transcripts, enables rapid quantification of overall inosine abundance, and maps the landscape of A-to-I editing within the transcriptome at the nanoscopic level.

Differentiating stages of functional vision loss from glaucoma using the Disc Damage Likelihood Scale and cup:disc ratio

BACKGROUND

Glaucoma staging is critical for treatment planning but has rarely been tested in severe/end-stage disease. We compared the performance of the Disc Damage Likelihood Scale (DDLS) and cup:disc ratio (CDR) using a functional glaucoma staging system (GSS) as the reference standard.

METHODS

Post hoc analysis of a randomised controlled trial at the Eye Department of Kilimanjaro Christian Medical Centre, Tanzania. Eligible participants (aged ≥18 years) with open-angle glaucoma, intraocular pressure (IOP) of >21 mm Hg, were randomised to timolol 0.5% eye drops or selective laser trabeculoplasty. Fundoscopy established vertical and horizontal CDRs and DDLS. Visual acuity and static visual fields were graded (GSS). The study used area under the receiver operating characteristic (AROC) curves and Spearman's rank correlation coefficients to compare staging systems. Logistic regression with generalised estimating equations determined risk factors of functional severe/end-stage glaucoma.

RESULTS

382 eyes (201 participants) were evaluated; 195 (51%) had severe or end-stage glaucoma; mean IOP was 26.7 (SD 6.9) mm Hg. DDLS yielded an AROC of 0.90 (95% CI 0.87 to 0.93), vertical cup:disc ratio (vCDR) of 0.88 (95% CI 0.85 to 0.91, p=0.048) for identifying severe/end-stage disease. Correlation coefficients comparing GSS to DDLS and vCDRs were 0.73 and 0.71, respectively. Advanced structural stages, vision impairment, higher IOP and less financial resources were risk factors of functional severe/end-stage glaucoma.

CONCLUSION

This study indicates that both structural staging systems can differentiate severe/end-stage glaucoma from less severe disease, with a moderate advantage of DDLS over CDR. Clinical examination of the optic disc plays an important role in addition to functional assessment when managing severe/end-stage glaucoma.

Cocaine sensitization in male rats requires activation of estrogen receptors

Gonadal steroids play a modulatory role in cocaine use disorders, and are responsible for many sex differences observed in the behavioral response to cocaine. In females, it is well established that estradiol enhances the behavioral response to cocaine. In males, we have recently shown that testosterone enhances sensitization to cocaine but its mechanism of action remains to be elucidated. The current study investigated the contribution of DHT, a non-aromatizable androgen, and of estradiol, in regulating cocaine-induced sensitization in male rats. Gonadectomized (GDX) male rats treated with estradiol sensitized to repeated cocaine administration, while GDX rats treated with DHT did not, implicating estradiol in cocaine sensitization. Furthermore, intact male rats treated with the antiestrogen ICI 182,780 did not show sensitization to repeated cocaine. This study demonstrates the pivotal role of estradiol in cocaine-induced neuroplasticity and neuroadaptations in the rodent brain.

Greater reliance on model-free learning in adolescent anorexia nervosa: An examination of dual-system reinforcement learning

Alterations in learning and decision-making systems are thought to contribute to core features of anorexia nervosa (AN), a psychiatric disorder characterized by persistent dietary restriction and weight loss. Instrumental learning theory identifies a dual-system of habit and goal-directed decision-making, linked to model-free and model-based reinforcement learning algorithms. Difficulty arbitrating between these systems, resulting in an over-reliance on one strategy over the other, has been implicated in compulsivity and extreme goal pursuit, both of which are observed in AN. Characterizing alterations in model-free and model-based systems, and their neural correlates, in AN may clarify mechanisms contributing to symptom heterogeneity (e.g., binge/purge symptoms). This study tested whether adolescents with restricting AN (AN-R; n = 36) and binge/purge AN (AN-BP; n = 20) differentially utilized model-based and model-free learning systems compared to a healthy control group (HC; n = 28) during a Markov two-step decision-making task under conditions of reward and punishment. Associations between model-free and model-based learning and resting-state functional connectivity between neural regions of interest, including orbitofrontal cortex (OFC), nucleus accumbens (NAcc), putamen, and sensory motor cortex (SMC) were examined. AN-R showed higher utilization of model-free learning compared to HC for reward, but attenuated model-free and model-based learning for punishment. In AN-R only, higher model-based learning was associated with stronger OFC-to-left NAcc functional connectivity, regions linked to goal-directed behavior. Greater utilization of model-free learning for reward in AN-R may differentiate this group, particularly during adolescence, and facilitate dietary restriction by prioritizing habitual control in rewarding contexts.

DNA-Diffusion: Leveraging Generative Models for Controlling Chromatin Accessibility and Gene Expression via Synthetic Regulatory Elements

The challenge of systematically modifying and optimizing regulatory elements for precise gene expression control is central to modern genomics and synthetic biology. Advancements in generative AI have paved the way for designing synthetic sequences with the aim of safely and accurately modulating gene expression. We leverage diffusion models to design context-specific DNA regulatory sequences, which hold significant potential toward enabling novel therapeutic applications requiring precise modulation of gene expression. Our framework uses a cell type-specific diffusion model to generate synthetic 200 bp regulatory elements based on chromatin accessibility across different cell types. We evaluate the generated sequences based on key metrics to ensure they retain properties of endogenous sequences: transcription factor binding site composition, potential for cell type-specific chromatin accessibility, and capacity for sequences generated by DNA diffusion to activate gene expression in different cell contexts using state-of-the-art prediction models. Our results demonstrate the ability to robustly generate DNA sequences with cell type-specific regulatory potential. DNA-Diffusion paves the way for revolutionizing a regulatory modulation approach to mammalian synthetic biology and precision gene therapy.

A Modular Implementation to Handle and Benchmark Drift Correction for High-Density Extracellular Recordings

High-density neural devices are now offering the possibility to record from neuronal populations in vivo at unprecedented scale. However, the mechanical drifts often observed in these recordings are currently a major issue for "spike sorting," an essential analysis step to identify the activity of single neurons from extracellular signals. Although several strategies have been proposed to compensate for such drifts, the lack of proper benchmarks makes it hard to assess the quality and effectiveness of motion correction. In this paper, we present a benchmark study to precisely and quantitatively evaluate the performance of several state-of-the-art motion correction algorithms introduced in the literature. Using simulated recordings with induced drifts, we dissect the origins of the errors performed while applying a motion correction algorithm as a preprocessing step in the spike sorting pipeline. We show how important it is to properly estimate the positions of the neurons from extracellular traces in order to correctly estimate the probe motion, compare several interpolation procedures, and highlight what are the current limits for motion correction approaches.

BDNF signaling requires Matrix Metalloproteinase-9 during structural synaptic plasticity

Synaptic plasticity underlies learning and memory processes as well as contributes, in its aberrant form, to neuropsychiatric disorders. One of its major forms is structural long-term potentiation (sLTP), an activity-dependent growth of dendritic spines that harbor excitatory synapses. The process depends on the release of brain-derived neurotrophic factor (BDNF), and activation of its receptor, TrkB. Matrix metalloproteinase-9 (MMP-9), an extracellular protease is essential for many forms of neuronal plasticity engaged in physiological as well as pathological processes. Here, we utilized two-photon microscopy and two-photon glutamate uncaging to demonstrate that MMP-9 activity is essential for sLTP and is rapidly (~seconds) released from dendritic spines in response to synaptic stimulation. Moreover, we show that either chemical or genetic inhibition of MMP-9 impairs TrkB activation, as measured by fluorescence lifetime imaging microscopy of FRET sensor. Furthermore, we provide evidence for a cell-free cleavage of proBDNF into mature BDNF by MMP-9. Our findings point to the autocrine mechanism of action of MMP-9 through BDNF maturation and TrkB activation during sLTP.

Whole-Genome Sequencing Analysis Reveals New Susceptibility Loci and Structural Variants Associated with Progressive Supranuclear Palsy

Background

Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs).

Method

In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed.

Results

Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73×10-3) in PSP.

Conclusions

Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.

Short-chain fatty acids propionate and butyrate control growth and differentiation linked to cellular metabolism

The short-chain fatty acids (SCFA) propionate and butyrate are produced in large amounts by microbial metabolism and have been identified as unique acyl lysine histone marks. In order to better understand the function of these modifications we used ChIP-seq to map the genome-wide location of four short-chain acyl histone marks H3K18pr/bu and H4K12pr/bu in treated and untreated colorectal cancer (CRC) and normal cells, as well as in mouse intestines in vivo . We correlate these marks with open chromatin regions along with gene expression to access the function of the target regions. Our data demonstrate that propionate and butyrate act as promoters of growth, differentiation as well as ion transport. We propose a mechanism involving direct modification of specific genomic regions, resulting in increased chromatin accessibility, and in case of butyrate, opposing effects on the proliferation of normal versus CRC cells.

Influence of combat boot types on in-shoe forces and perceived comfort during unloaded and loaded walking

INTRODUCTION

Combat boots are essential protective gear for military personnel. The purposes of the present study were to examine (1) the influence of combat boot type on ground reaction force (GRF) variables and perceived comfort during unloaded and loaded walking and (2) the relationship between comfort and biomechanical measurements.

METHODS

Four types of combat boots with different physical features (eg, mass, thickness) and mechanical properties (eg, cushioning, rigidity) were compared across 61 male participants with experience in military marching while carrying heavy loads. In each boot type, participants completed a 10-m walk under an unloaded and a 20-kg loaded conditions at their preferred speeds. Peak force and loading rate during walking were measured using the loadsol wireless in-shoe sensor system. Comfort level was assessed using a 7-point Likert scale. Difference between loaded and unloaded walking, and across boot types were statistically compared. Correlation analyses were performed between comfort and GRF variables.

RESULTS

On average across all boot types, participants walked 2.1% slower when carrying 20-kg loads while experiencing 24.3% higher peak force and 20.8% higher loading rate. Boot D was perceived as most comfortable, followed by boots C, B and A (χ2(2)=115.4, p<0.001). Participants walked slightly faster (p=0.022, ηp 2 = 0.052) and displayed higher loading rates (p<0.001, ηp 2=0.194) in the two more comfortable boots (C and D) than the less comfortable boots (A and B). No significant correlations were found between perceived comfort and any GRF variables.

CONCLUSIONS

Combat boot features can influence perceived comfort ratings substantially during walking, whereas biomechanical differences among boot types are more subtle regardless of load conditions. The lack of relationship between comfort and force variables suggests that both subjective and objective measurements should be considered for comprehensive evaluation of combat boots.

CHOIR improves significance-based detection of cell types and states from single-cell data

Clustering is a critical step in the analysis of single-cell data, as it enables the discovery and characterization of putative cell types and states. However, most popular clustering tools do not subject clustering results to statistical inference testing, leading to risks of overclustering or underclustering data and often resulting in ineffective identification of cell types with widely differing prevalence. To address these challenges, we present CHOIR (clustering hierarchy optimization by iterative random forests), which applies a framework of random forest classifiers and permutation tests across a hierarchical clustering tree to statistically determine which clusters represent distinct populations. We demonstrate the enhanced performance of CHOIR through extensive benchmarking against 14 existing clustering methods across 100 simulated and 4 real single-cell RNA-seq, ATAC-seq, spatial transcriptomic, and multi-omic datasets. CHOIR can be applied to any single-cell data type and provides a flexible, scalable, and robust solution to the important challenge of identifying biologically relevant cell groupings within heterogeneous single-cell data.

Microbiome-induced Increases and Decreases in Bone Tissue Strength can be Initiated After Skeletal Maturity

Recent studies in mice have indicated that the gut microbiome can regulate bone tissue strength. However, prior work involved modifications to the gut microbiome in growing animals and it is unclear if the same changes in the microbiome, applied later in life, would change matrix strength. Here we changed the composition of the gut microbiome before and/or after skeletal maturity (16 weeks of age) using oral antibiotics (ampicillin + neomycin). Male and female mice (n=143 total, n=12-17/group/sex) were allocated into five study groups:1) Unaltered, 2) Continuous (dosing 4-24 weeks of age), 3) Delayed (dosing only 16-24 weeks of age), 4) Initial (dosing 4-16 weeks of age, suspended at 16 weeks), and 5) Reconstituted (dosing from 4-16 weeks following by fecal microbiota transplant from Unaltered donors). Animals were euthanized at 24 weeks of age. In males, bone matrix strength in the femur was 25-35% less than expected from geometry in mice from the Continuous (p= 0.001), Delayed (p= 0.005), and Initial (p=0.040) groups as compared to Unaltered. Reconstitution of the gut microbiota, however, led to a bone matrix strength similar to Unaltered animals (p=0.929). In females, microbiome-induced changes in bone matrix strength followed the same trend as males but were not significantly different, demonstrating sex-related differences in the response of bone matrix to the gut microbiota. Minor differences in chemical composition of bone matrix were observed (Raman spectroscopy). Our findings indicate that microbiome-induced impairment of bone matrix in males can be initiated and/or reversed after skeletal maturity. The portion of the femoral cortical bone formed after skeletal maturity (16 weeks) is small; however, this suggests that microbiome-induced changes in bone matrix occur without osteoblast/osteoclast turnover using an, as of yet unidentified mechanism. These findings add to evidence that the mechanical properties of bone matrix can be altered in the adult skeleton.

Growth in early infancy drives optimal brain functional connectivity which predicts cognitive flexibility in later childhood

Functional brain network organization, measured by functional connectivity (FC), reflects key neurodevelopmental processes for healthy development. Early exposure to adversity, e.g. undernutrition, affects neurodevelopment, observable via disrupted FC, and leads to poorer outcomes from preschool age onward. We assessed longitudinally the impact of early growth trajectories on developmental FC in a rural Gambian population from age 5 to 24 months. To investigate how these early trajectories relate to later childhood outcomes, we assessed cognitive flexibility at 3-5 years. We observed that early physical growth before the fifth month of life drove optimal developmental trajectories of FC that in turn predicted cognitive flexibility at pre-school age. In contrast to previously studied developmental populations, this Gambian sample exhibited long-range interhemispheric FC that decreased with age. Our results highlight the measurable effects that poor growth in early infancy has on brain development and the subsequent impact on pre-school age cognitive development, underscoring the need for early life interventions throughout global settings of adversity.

Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery

Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.

Survey of liver pathologists to assess attitudes towards digital pathology and artificial intelligence

AIMS

A survey of members of the UK Liver Pathology Group (UKLPG) was conducted, comprising consultant histopathologists from across the UK who report liver specimens and participate in the UK National Liver Pathology External Quality Assurance scheme. The aim of this study was to understand attitudes and priorities of liver pathologists towards digital pathology and artificial intelligence (AI).

METHODS

The survey was distributed to all full consultant members of the UKLPG via email. This comprised 50 questions, with 48 multiple choice questions and 2 free-text questions at the end, covering a range of topics and concepts pertaining to the use of digital pathology and AI in liver disease.

RESULTS

Forty-two consultant histopathologists completed the survey, representing 36% of fully registered members of the UKLPG (42/116). Questions examining digital pathology showed respondents agreed with the utility of digital pathology for primary diagnosis 83% (34/41), second opinions 90% (37/41), research 85% (35/41) and training and education 95% (39/41). Fatty liver diseases were an area of demand for AI tools with 80% in agreement (33/41), followed by neoplastic liver diseases with 59% in agreement (24/41). Participants were concerned about AI development without pathologist involvement 73% (30/41), however, 63% (26/41) disagreed when asked whether AI would replace pathologists.

CONCLUSIONS

This study outlines current interest, priorities for research and concerns around digital pathology and AI for liver pathologists. The majority of UK liver pathologists are in favour of the application of digital pathology and AI in clinical practice, research and education.

The role of mitochondria in sex- and age-specific gene expression in a species without sex chromosomes

Mitochondria perform an array of functions, many of which involve interactions with gene products encoded by the nucleus. These mitochondrial functions, particularly those involving energy production, can be expected to differ between sexes and across ages. Here we measured mitochondrial effects on sex- and age-specific gene expression in parental and reciprocal F1 hybrids between allopatric populations of Tigriopus californicus with over 20% mitochondrial DNA divergence. Because the species lacks sex chromosomes, sex-biased mitochondrial effects are not confounded by the effects of sex chromosomes. Using single-individual RNA sequencing, sex differences were found to explain more than 80% of the variance in gene expression. Males had higher expression of mitochondrial genes and mitochondrially targeted proteins (MTPs) involved in oxidative phosphorylation (OXPHOS), while females had elevated expression of non-OXPHOS MTPs, indicating strongly sex-dimorphic energy metabolism at the whole organism level. Comparison of reciprocal F1 hybrids allowed insights into the nature of mito-nuclear interactions, showing both mitochondrial effects on nuclear expression, as well as nuclear effects on mitochondrial expression. Across both sexes, increases in mitochondrial expression with age were associated with longer life. Network analyses identified nuclear components of strong mito-nuclear interactions, and found them to be sexually dimorphic. These results highlight the profound impact of mitochondria and mito-nuclear interactions on sex- and age-specific gene expression.