bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of intestinal epithelial cell responses toCryptosporidiumhighlights the temporal effects of IFN-γ on parasite restriction
Authors: Pardy Ryan D. , Walzer Katelyn A. , Wallbank Bethan A. , Byerly Jessica H. , O’Dea Keenan M. , Cohn Ian S. , Haskins Breanne E. , Roncaioli Justin L. , Smith Eleanor J. , Buenconsejo Gracyn Y. , Striepen Boris , Hunter Christopher A. 
Published: November 2023

ABSTRACTThe production of IFN-γ is crucial for control of multiple enteric infections, but its impact on intestinal epithelial cells (IEC) is not well understood.Cryptosporidiumparasites exclusively infect epithelial cells and the ability of interferons to activate the transcription factor STAT1 in IEC is required for parasite clearance. The use of single cell RNA sequencing to profile IEC during infection revealed induction of IFN-γ-dependent gene signatures that was comparable between uninfected and infected cells, and IEC expression of the IFN-γ receptor was required for parasite control. Unexpectedly, treatment ofIfng−/−mice with IFN-γ demonstrated the IEC response to this cytokine correlates with a delayed reduction in parasite burden but did not affect parasite development. These data sets provide insight into the impact of IFN-γ on IEC and suggest a model in which IFN-γ-mediated bystander activation of uninfected enterocytes is important for control ofCryptosporidium.AUTHOR SUMMARYThe cytokine interferon-gamma (IFN-γ) plays an important role in the control of intracellular infections by a wide variety of bacteria, viruses and parasites. While the impact of IFN-γ on immune cells has been a major research focus, how it impacts intestinal epithelial cells remains poorly understood.Cryptosporidiumparasites are an important cause of morbidity in a variety of epidemiological settings and exclusively infect intestinal epithelial cells (IEC). Recent advances in the ability to genetically modify and studyCryptosporidiumin wild-type hosts provides a useful model to investigate IEC-intrinsic mechanisms of pathogen control. In this study, single cell RNA-sequencing was used to analyze the IEC response to infection and IFN-γ signalling. We demonstrate broad changes in the epithelial compartment during infection that include the induction of an IEC population with robust induction of IFN-γ-stimulated genes. In addition, we show that infected IEC remain responsive to IFN-γ signalling, and that this cytokine causes a delayed reduction in parasite burden that correlates with the kinetics of IEC responsiveness to IFN-γ stimulation. Together, our work uncovers howCryptosporidiuminfection impacts the IEC compartment and helps define the relationship between the kinetics of IFN-γ responsiveness and pathogen control in IEC.
YAP localization mediates mechanical adaptation of human cancer cells during extravasationin vivo
Authors: So Woong Young , Wong Claudia S. , Azubuike Udochi F. , Paul Colin D. , Sangsari Paniz Rezvan , Gordon Patricia B. , Gong Hyeyeon , Maity Tapan K. , Lim Perry , Yang Zhilin , Haryanto Christian A. , Batchelor Eric , Jenkins Lisa M. , Morgan Nicole Y. , Tanner Kandice 
Published: November 2023

AbstractBiophysical profiling of primary tumors has revealed that individual tumor cells fall along a highly heterogeneous continuum of mechanical phenotypes. One idea is that a subset of tumor cells is “softer” to facilitate detachment and escape from the primary site, a step required to initiate metastasis. However, it has also been postulated that cells must be able to deform and generate sufficient force to exit into distant sites. Here, we aimed to dissect the mechanical changes that occur during extravasation and organ colonization. Using multiplexed methods of intravital microscopy and optical tweezer based active microrheology, we obtained longitudinal images and mechanical profiles of cells during organ colonizationin vivo. We determined that cells were softer, more liquid like upon exit of the vasculature but stiffened and became more solid like once in the new organ microenvironment. We also determined that a YAP mediated mechanogenotype influenced the global dissemination in our in vivo and in vitro models and that reducing mechanical heterogeneity could reduce extravasation. Moreover, our high throughput analysis of mechanical phenotypes of patient samples revealed that this mechanics was in part regulated by the external hydrodynamic forces that the cancer cells experienced within capillary mimetics. Our findings indicate that disseminated cancer cells can keep mutating with a continuum landscape of mechano-phenotypes, governed by the YAP-mediated mechanosensing of hydrodynamic flow.
mzrtsim: Raw Data Simulation for Reproducible Gas/Liquid Chromatography–Mass Spectrometry Based Non-targeted Metabolomics Data Analysis
Authors: Yu Miao , Philip Vivek 
Published: November 2023

AbstractReproducibility of data analysis is pivotal in the context of non-targeted metabolomics based on mass spectrometry coupled with chromatography. While various algorithms have been proposed for feature or peak extraction, their validation often revolves around a limited set of known compounds or standards. While data simulation is widely used in other omics studies, simulation are focused on the feature level, neglecting uncertainties inherent in the feature or peak extraction process for metabolomics mass spectrometry data. In this technique note, we introduce a R package called ‘mzrtsim’ to simulate gas/liquid chromatography full scan raw data in the mzML format. Unlike simulations solely based on virtual features, our approach leverages experimental spectral data from the MassBank of North America (MoNA) and the human metabolome database (HMDB). We developed algorithms to simulate chromatographic peaks, accounting for the tailing factor. The results of our study demonstrate the potential of this tool for comparing established metabolomics software (e.g., XCMS, mzMine, and OpenMS) against a ground truth. We found that the investigated software introduced false positive peaks and/or loss compounds with less peaks. They also showed different sensitivity to tailing and leading peaks and we also found setting appropriate intensity cutoffs will not lose information for the following statistical analysis. This R package is free and available online (https://github.com/yufree/mzrtsim).TOC
Tumor cell-derived spermidine promotes a pro-tumorigenic immune microenvironment in glioblastoma via CD8+ T cell inhibition
Authors: Kay Kristen E. , Lee Juyeun , Hong Ellen S. , Beilis Julia , Dayal Sahil , Wesley Emily , Mitchell Sofia , Wang Sabrina Z. , Silver Daniel J. , Volovetz Josephine , Johnson Sadie , McGraw Mary , Grabowski Matthew M. , Lu Tianyao , Freytag Lutz , Narayana Vinod , Freytag Saskia , Best Sarah A. , Whittle James R. , Wang Zeneng , Reizes Ofer , Yu Jennifer S. , Hazen Stanley L. , Brown J. Mark , Bayik Defne , Lathia Justin D. 
Published: November 2023

AbstractThe glioblastoma microenvironment is enriched in immunosuppressive factors that potently interfere with the function of cytotoxic T lymphocytes. Cancer cells can directly impact the immune system, but the mechanisms driving these interactions are not completely clear. Here we demonstrate that the polyamine metabolite spermidine is elevated in the glioblastoma tumor microenvironment. Exogenous administration of spermidine drives tumor aggressiveness in an immune-dependent manner in pre-clinical mouse models via reduction of CD8+ T cell frequency and phenotype. Knockdown of ornithine decarboxylase, the rate-limiting enzyme in spermidine synthesis, did not impact cancer cell growth in vitro but did result in extended survival. Furthermore, glioblastoma patients with a more favorable outcome had a significant reduction in spermidine compared to patients with a poor prognosis. Our results demonstrate that spermidine functions as a cancer cell-derived metabolite that drives tumor progression by reducing CD8+T cell number and function.
Functional Test of a Naturally Occurred Tumor Modifier Gene Provides Insights to Melanoma Development
Authors: Garcia-Olazabal Mateo , Adolfi Mateus Contar , Wilde Brigitta , Hufnagel Anita , Paudel Rupesh , Lu Yuan , Meierjohann Svenja , Rosenthal Gil G. , Schartl Manfred 
Published: November 2023

AbstractOccurrence of degenerative interactions is thought to serve as a mechanism underlying hybrid unfitness. However, the molecular mechanisms underpinning the genetic interaction and how they contribute to overall hybrid incompatibilities are limited to only a handful of examples. A vertebrate model organism,Xiphophorus, is used to study hybrid dysfunction and it has been shown from this model that diseases, such as melanoma, can occur in certain interspecies hybrids. Melanoma development is due to hybrid inheritance of an oncogene,xmrk, and loss of a co-evolved tumor modifier. It was recently found thatadgre5, a G protein-coupled receptor involved in cell adhesion, is a tumor regulator gene in naturally hybridizingXiphophorusspeciesX. birchmanniandX. malinche. We hypothesized that one of the two parental alleles ofadgre5is involved in regulation of cell proliferation, migration and melanomagenesis. Accordingly, we assessed the function ofadgre5alleles from each parental species of the melanoma-bearing hybrids usingin vitrocell proliferation and migration assays. In addition, we expressed eachadgre5allele with thexmrkoncogene in transgenic medaka. We found that cells transfected with theX. birchmanni adgre5exhibited decreased proliferation and migration compared to those with theX. malincheallele. Moreover,X. birchmanniallele ofadgre5completely inhibited melanoma development inxmrktransgenic medaka, whileX. malinche adgre5expression did not exhibit melanoma suppressive activity in medaka. These findings showed thatadgre5is a natural melanoma suppressor and provide new insight in melanoma etiology.
Population analyses reveal heterogenous encoding in the medial prefrontal cortex during naturalistic foraging
Authors: Jeong Ji Hoon , Choi June-Seek 
Published: November 2023

AbstractForaging in the wild requires coordinated switching of critical functions, including goal-oriented navigation and context-appropriate action selection. Nevertheless, few studies have examined how different functions are represented in the brain during naturalistic foraging. To address this question, we recorded multiple single-unit activities from the medial prefrontal cortex (mPFC) of rats seeking a sucrose reward in the presence of an unpredictable attack posed by a robotic predator (Lobsterbot). Simultaneously recorded ensemble activities from neurons were analyzed in reference to various behavioral indices as the animal moved freely across the foraging area (F) between the nest (N) and the goal (E) area. An artificial neural network, trained with simultaneously recorded neural activity, estimated the rat’s current distance from the Lobsterbot. The accuracy of distance estimation was the highest in the middle F-zone in which the dominant behavior was active navigation. The spatial encoding persisted in the N-zone when non-navigational behaviors such as grooming, rearing, and sniffing were excluded. In contrast, the accuracy decreased as the animal approached the E-zone, when the activity of the same neuronal ensembles was more correlated with events related to dynamic decision-making between food procurement and Lobsterbot evasion. A population-wide analysis confirmed highly heterogeneous encoding by the region. To further assess the decision-related activity in the E-zone, a naïve Bayesian classifier was trained to predict the success and failure of avoidance behavior. The classifier predicted the avoidance outcome as much as 6 s before the head withdrawal. In addition, two sub-populations of recorded units with distinct temporal dynamics contributed differently to the prediction. These findings suggest that an overlapping population of mPFC neurons may switch between two heterogenous modes, encoding relevant locations for goal-directed navigation or an imminent situational challenge.
Implantable nanophotonic neural probes for integrated patterned photostimulation and electrophysiology recording
Authors: Chen Fu Der , Chameh Homeira Moradi , Movahed Mandana , Wahn Hannes , Mu Xin , Ding Peisheng , Xue Tianyuan , Straguzzi John N. , Roszko David A. , Sharma Ankita , Govdeli Alperen , Jung Youngho , Chua Hongyao , Luo Xianshu , Lo Patrick G. Q. , Valiante Taufik A. , Sacher Wesley D. , Poon Joyce K. S. 
Published: November 2023

AbstractOptogenetics has transformed neuroscience by allowing precise manipulation of neural circuits with light [1–5]. However, a central difficulty has been to deliver spatially shaped light and record deep within the brain without causing damage or significant heating. Current approaches form the light beam in free space and record the neural activity using fluorescence imaging or separately inserted electrodes [6–9], but attenuation limits optical penetration to around 1 mm of the brain surface [10]. Here, we overcome this challenge with foundry-fabricated implantable silicon neural probes that combine microelectrodes for electrophysiology recordings with nanophotonic circuits that emit light with engineered beam profiles and minimal thermal impact. Our experiments reveal that planar light sheets, emitted by our neural probes, excited more neurons and induced greater firing rate fatigue in layers V and VI of the motor and somatosensory cortex of Thy1-ChR2 mice at lower output intensities than low divergence beams. In the hippocampus of an epilepsy mouse model, we induced seizures, a network-wide response, with light sheets without exceeding the∼1◦C limit for thermally induced electrophysiological responses [11–13]. These findings show that optical spatial profiles can be tailored for optogenetic stimulation paradigms and that the probes can photostimulate and record neural activity at single or population levels while minimizing thermal damage to brain tissue. The neural probes, made in a commercial silicon photonics foundry on 200-mm silicon wafers, demonstrate the manufacturability of the technology. The prospect of monolithically integrating additional well-established silicon photonics devices, such as wavelength and polarization multiplexers, temperature sensors, and optical power monitors, into the probes holds the potential of realizing more versatile, implantable tools for multimodal brain activity mapping.
Parietal alpha stimulation causally enhances attentional information coding in evoked and oscillatory activity
Authors: Lu Runhao , Michael Elizabeth , Scrivener Catriona L. , Jackson Jade B. , Duncan John , Woolgar Alexandra 
Published: November 2023

AbstractSelective attention is a fundamental cognitive mechanism that allows people to prioritise task-relevant information while ignoring irrelevant information. Previous research has suggested key roles of parietal evoked potentials and alpha oscillatory responses in spatial attention tasks. However, the informational content of these signals is less clear, and their causal effects on the coding of multiple task elements are yet unresolved. Here, we used concurrent TMS-EEG to causally manipulate parietal alpha power and evoked potentials and investigate their roles in coding multiple task features (where to attend,what to attend to, andvisual stimulus) in a selective attention task. First, using EEG-only data, we found that evoked potentials coded all three types of task-relevant information with distinct temporal dynamics, and alpha oscillations carried information regarding both where to attend and what to attend to. Then, we applied rhythmic-TMS (rTMS) at individual alpha frequency over the right intraparietal sulcus (IPS), while concurrently measuring EEG. Compared with control arrhythmic-TMS, alpha rTMS increased alpha power and inter-trial phase coherence and yielded more negative posterior-contralateral evoked potentials. Moreover, alpha rTMS causally and specifically improved multivariate decoding of the information aboutwhere to attend(but notwhat to attend toorfeature information) during task performance, with decoding improvements predicting changes in behavioural performance. These findings illuminate the dynamics with which the complementary aspects of a selective attention task are encoded in evoked and oscillatory brain activity. Moreover, they reveal a specific and causal role of IPS-controlled evoked and oscillatory activity in carrying behaviour-driving information about where to focus attention.
A yeast two-hybrid system to obtain triple-helical ligands from combinatorial random peptide libraries
Authors: Masuda Ryo , Thant Khine Phyu Phyu , Kawahara Kazuki , Oki Hiroya , Kadonosono Tetsuya , Kobayashi Yuji , Koide Takaki 
Published: November 2023

AbstractMany bioactive proteins interact with collagen, recognizing amino acid sequences displayed on the triple helix. We report here a selection strategy to obtain triple-helical peptides that interact with the proteins from a combinatorial random library constructed in yeast cells. This system enables us to select them using the standard two-hybrid protocol, detecting interactions between triple-helical peptides and target proteins fused to the GAL4-activating and binding domains, respectively. The library was constructed having triple-helical peptides with a “host-guest” design in which host helix-stabilizing regions flanked guest random sequences. Using this system, we selected peptides that bind to pigment epithelium-derived factor (PEDF), a collagen-binding protein that shows anti-angiogenic and neurotrophic activities, from the libraries. Two-step selections from the total random library and subsequently from the second focused library yielded new PEDF-binding sequences that exhibited a comparable affinity to or more potent than that of the native PEDF-binding sequence in collagen. The obtained sequences also contained a variant of the PEDF-binding motif that did not match the known motif identified from the native collagen sequences. This combinatorial library system allows the chemical space of triple-helical peptides to be screened more widely than that found in native collagen, thus increasing the expectation of obtaining more specific and high-affinity peptides.
Acquired temozolomide resistance instructs patterns of glioblastoma behavior in gelatin hydrogels
Authors: Kriuchkovskaia Victoria , Eames Ela K. , Riggins Rebecca B. , Harley Brendan A.C. 
Published: November 2023

AbstractAcquired drug resistance in glioblastoma (GBM) presents a major clinical challenge and is a key factor contributing to abysmal prognosis, with less than 15 months median overall survival. Aggressive chemotherapy with the frontline therapeutic, temozolomide (TMZ), ultimately fails to kill residual highly invasive tumor cells after surgical resection and radiotherapy. Here, we report a three-dimensional (3D) engineered model of acquired TMZ resistance using two isogenically-matched sets of GBM cell lines encapsulated in gelatin methacrylol hydrogels. We benchmark response of TMZ-resistant vs. TMZ-sensitive GBM cell lines within the gelatin-based extracellular matrix platform and further validate drug response at physiologically relevant TMZ concentrations. We show changes in drug sensitivity, cell invasion, and matrix-remodeling cytokine production as the result of acquired TMZ resistance. This platform lays the foundation for future investigations targeting key elements of the GBM tumor microenvironment to combat GBM’s devastating impact by advancing our understanding of GBM progression and treatment response to guide the development of novel treatment strategies.TeaserA hydrogel model to investigate the impact of acquired drug resistance on functional response in glioblastoma.
Cortical acetylcholine dynamics are predicted by cholinergic axon activity and behavior state
Authors: Neyhart Erin , Zhou Na , Munn Brandon R. , Law Robert G. , Smith Cameron , Mridha Zakir H. , Blanco Francisco A. , Li Guochuan , Li Yulong , McGinley Matthew J. , Shine James M. , Reimer Jacob 
Published: November 2023

AbstractEven under spontaneous conditions and in the absence of changing environmental demands, awake animals alternate between increased or decreased periods of alertness. These changes in brain state can occur rapidly, on a timescale of seconds, and neuromodulators such as acetylcholine (ACh) are thought to play an important role in driving these spontaneous state transitions. Here, we perform the first simultaneous imaging of ACh sensors and GCaMP-expressing axonsin vivo, to examine the spatiotemporal properties of cortical ACh activity and release during spontaneous changes in behavioral state. We observed a high correlation between simultaneously recorded basal forebrain axon activity and neuromodulator sensor fluorescence around periods of locomotion and pupil dilation. Consistent with volume transmission of ACh, increases in axon activity were accompanied by increases in local ACh levels that fell off with the distance from the nearest axon. GRAB-ACh fluorescence could be accurately predicted from axonal activity alone, providing the first validation that neuromodulator axon activity is a reliable proxy for nearby neuromodulator levels. Deconvolution of fluorescence traces allowed us to account for the kinetics of the GRAB-ACh sensor and emphasized the rapid clearance of ACh for smaller transients outside of running periods. Finally, we trained a predictive model of ACh fluctuations from the combination of pupil size and running speed; this model performed better than using either variable alone, and generalized well to unseen data. Overall, these results contribute to a growing understanding of the precise timing and spatial characteristics of cortical ACh during fast brain state transitions.
Flow-field inference from neural data using deep recurrent networks
Authors: Kim Timothy Doyeon , Luo Thomas Zhihao , Can Tankut , Krishnamurthy Kamesh , Pillow Jonathan W. , Brody Carlos D. 
Published: November 2023

AbstractComputations involved in processes such as decision-making, working memory, and motor control are thought to emerge from the dynamics governing the collective activity of neurons in large populations. But the estimation of these dynamics remains a significant challenge. Here we introduce Flow-field Inference from Neural Data using deep Recurrent networks (FINDR), an unsupervised deep learning method that can infer low-dimensional nonlinear stochastic dynamics underlying neural population activity. Using population spike train data from frontal brain regions of rats performing an auditory decision-making task, we demonstrate that FINDR outperforms existing methods in capturing the heterogeneous responses of individual neurons. We further show that FINDR can discover interpretable low-dimensional dynamics when it is trained to disentangle task-relevant and irrelevant components of the neural population activity. Importantly, the low-dimensional nature of the learned dynamics allows for explicit visualization of flow fields and attractor structures. We suggest FINDR as a powerful method for revealing the low-dimensional task-relevant dynamics of neural populations and their associated computations.