bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pilot MRI study of carbon monoxide (CO) against ischemic stroke in mice: blood brain barrier integrity and metabolic pattern
Authors: Oliveira Sara R. , Castelhano João , Sereno José , Petrella Lorena , Castelo-Branco Miguel , Vieira Helena L. A. , Duarte Carlos B. 
Published: November 2022

ABSTRACTAlthough stroke is the main cause of brain damage worldwide, stroke therapies are based on blood reperfusion and do not target cerebral parenchyma. Ischemic stroke (representing 87% of all strokes) causes cerebral damage due to oxygen and tissue energy depletion, which lead to acidosis, inflammation, excitotoxicity and oxidative stress. Carbon monoxide (CO) is an endogenous gasotransmitter produced by heme oxygenase cleavage of the heme group. CO promotes cytoprotection by limiting inflammation and preventing cell death in several tissues including the brain. Previous studies have demonstrated the protective role of CO in the mouse ischemic stroke model, middle cerebral artery occlusion (MCAo) by histological analysis when CO is when applied before ischemia. Herein, there are two main novelties. First CO is administrated following stroke, which better mimics its potential future use as therapeutic drug. Secondly, imaging techniques were used to elucidate the effect of this gasotransmitter at the metabolic, vascular and anatomic levels.The putative neuroprotective effects of CO following MCAo were assessed by 3 i.p. injections of the CO-releasing molecule CORM-A1 (3 mg/kg), administered 6, 24 and 48h after reperfusion. Magnetic Resonance Imaging was performed 1 day and 7 days after reperfusion using T2-weighted, diffusion weighted images, proton spectroscopy (1H-MRS) and perfusion (dynamic contrast enhanced images).1H-MRS also allowed the comparison between metabolite signatures at day 1 versus 7 day following MCAo. Furthermore, CORM-A1 limited the loss of blood-brain barrier (BBB) integrity as it reduced the edema formation. Furthermore, the CO donor minimized the metabolite load loss at an early stage after MCAo, both in striatum and cortex.In conclusion and based on MRI analysis, CO has a protective role in the recovery from stroke injury, mainly by acting on BBB integrity and brain metabolism.
Central extended amygdala neurons in the development of activity-based anorexia
Authors: Schnapp Wesley Ilana , Kim JungMin , Wang Yong , Timilsena Sayujya , Fang Caohui , Cai Haijiang 
Published: November 2022

ABSTRACTAnorexia nervosa (AN) is a serious psychiatric disease characterized by restricted eating, fear of gaining weight, as well as excessive exercise, and also is often comorbid with emotional disorders such as anxiety and depression. However, the etiology of AN is unknown and the neural mechanism that leads to AN remains to be determined. Here, we show that a specific subpopulation of neurons, marked by the expression of protein kinase C-delta (PKC-δ), in two nuclei of the central extended amygdala (EAc)— central nucleus (CeA) and oval region of bed nucleus of stria terminalis (ovBNST)—regulates development of activity-based anorexia (ABA), the current best animal model of AN. Specifically, simultaneous dual ablation of CeAPKC-δand ovBNSTPKC-δneurons prevents the key phenotypes of ABA: increases in wheel activity, decreases in food intake, and life-threatening body weight loss. However, ablating PKC-δ neurons in CeA or ovBNST alone is not sufficient to prevent ABA. Correspondingly, activation of PKC-δ neurons in one type of nuclei continues to suppress food intake even when PKC-δ neurons in the other nuclei are silenced. Consistent with their role in suppressing food intake when activated, these PKC-δ neurons show increased activity with ABA development. Together, our study illuminates how neurons in the amygdala regulate ABA development and supports the complex and heterogenous etiology of AN.
Evolution shapes metabolic function and niche-specific antimicrobial targets in pathobionts
Authors: Glass Emma M. , Dillard Lillian R. , Kolling Glynis L. , Warren Andrew S. , Papin Jason A. 
Published: November 2022

AbstractTreatment of infections with traditional antimicrobials has become difficult due to the growing antimicrobial resistance crisis, necessitating the development of innovative approaches for deeply understanding pathogen function. Here, we generated a collection of genome-scale metabolic network reconstructions to gain insight into evolutionary drivers of metabolic function. We determined physiological location is a major driver of evolution of metabolic function. We observed that stomach-associated pathobionts had the most unique metabolic phenotypes and identified three essential genes unique to stomach pathobionts across diverse phylogenetic relationships. We demonstrate that inhibition of one such gene,thyX, inhibited growth of stomach- specific pathobionts exclusively, indicating possible physiological niche-specific targeting. This pioneering approach is the first step to using unique metabolic signatures to inform targeted antimicrobial therapies.One sentence summaryA data-driven approach to drug target discovery through metabolic signatures of diverse pathogens conserved across body-sites.
Direct Cortical Inputs to Hippocampal Area CA1 Transmit Complementary Signals for Goal-directed Navigation
Authors: Bowler John C , Losonczy Attila 
Published: November 2022

SummaryThe entorhinal cortex (EC) is central to the brain’s navigation system. Its subregions are conventionally thought to compute dichotomous representations for spatial processing: medial entorhinal cortex (MEC) provides a global spatial map, while lateral entorhinal cortex (LEC) encodes specific sensory details of experience. While local recordings of EC circuits have amassed a vast catalogue of specialized cell types that could support navigation computations in the brain, we have little direct evidence for how these signals are actually transmitted outside of the EC to its primary downstream reader, the hippocampus, which itself is critical for the formation of spatial and episodic memories. Here we exploitin vivosub-cellular imaging to directly record from EC axon terminals as they locally innervate hippocampal area CA1, while mice performed navigational and spatial learning tasks in virtual reality. We find both distinct and overlapping representations of task, location, and context in both MEC and LEC axons. While MEC transmitted a highly location- and context-specific code, LEC inputs were strongly biased by ongoing navigational goals and reward. Surprisingly, the position of the animal could be accurately decoded from either entorhinal subregion. Our results challenge prevailing dogma on the routing of spatial and non-spatial information from the cortex to the hippocampus, indicating that cortical interactions upstream of the hippocampus are critical for combining these processing streams to support navigation and memory.
More hot air: measuring the paradox of European ecology conferences
Authors: Smith Graham C , Begeman Lineke , Coles Alexia , Gilot-Fromont Emmanuelle , López-Olvera Jorge R , Vale Ana , Vogler Barbara R , Kuiken Thijs 
Published: November 2022

AbstractAs scientists we cause an above average carbon footprint for work-related travel. International conferences are a common way for us to meet and discuss, and we do not address the environmental costs of these meetings. Knowing the costs might help us to reduce them. Here we estimated the carbon footprint of the last five physical conferences of the European Wildlife Disease Association (EWDA). We obtained the number of participants from each country for those conferences, and along with assumed travel options, commuting, accommodation, meals and printing, estimated the carbon emissions for each conference. The estimate ranged from 155 to 1205 tons CO2per conference, or 0.7 to 2.4 tons per person. The outlying upper value was due to one joint global conference of the EWDA and the American mother association (WDA), which takes place every eight years. The geocentre was calculated for both the country of origin of the average conference attendants and for the society membership. The former was located in Luxembourg, and the latter near Dusseldorf, Germany, just approximately 170 km to the north. This represents the shortest total distance attendees would travel. Air transport to the conference country was the major source of CO2emissions (87-97%), and the average distance flown per person increased from 1000 km (2010) to over 2000 km (2018), since later conferences were generally further from the geocentre. The biggest reduction in carbon emissions (up to 100 tons CO2) could therefore be achieved by decreasing air travel. This could be brought about by reducing the overall travel distance to the conference, i.e. a conference location near the membership geocentre, or – by a lesser amount – by encouraging travel to the conference by train or bus, i.e. conference location near good public travel hubs, and by promoting virtual attendance. Minor but yet substantial savings could be made elsewhere (2-6 tons CO2), including providing accommodation in greener hotels located closer to the conference venue and offering vegan/local food as the default option.
Neuroelectrophysiology-Compatible Electrolytic Lesioning
Authors: Bray Iliana E. , Clarke Stephen E. , Casey Kerriann , Nuyujukian Paul ,   the Brain Interfacing Laboratory
Published: November 2022

AbstractLesion studies have historically been instrumental for establishing causal connections between brain and behavior. They stand to provide additional insight if integrated with multielectrode techniques common in systems neuroscience. Here we present and test a platform for creating electrolytic lesions through chronically implanted, intracortical multielectrode probes without compromising the ability to acquire neuroelectrophysiology. A custom-built current source provides stable current and allows for controlled, repeatable lesions in awake-behaving animals. Performance of this novel lesioning technique was validated using histology fromex vivoandin vivotesting, current and voltage traces from the device, and measurements of spiking activity before and after lesioning. This electrolytic lesioning method avoids disruptive procedures, provides millimeter precision over the extent and submillimeter precision over the location of the injury, and permits electrophysiological recording of single-unit activity from the remaining neuronal population after lesioning. This technique can be used in many areas of cortex, in several species, and theoretically with any multielectrode probe. The low-cost, external lesioning device can also easily be adopted into an existing electrophysiology recording setup. This technique is expected to enable future causal investigations of the recorded neuronal population’s role in neuronal circuit function, while simultaneously providing new insight into local reorganization after neuron loss.
Default But Not Rest: Topological Discrimination Defines the Default Mode Network
Authors: Wang Bo , Zhou Tiangang , He Sheng , Chen Lin 
Published: November 2022

AbstractThe default mode network (DMN), a set of transmodal cortical regions, has historically been argued to serve the internal functions of brain. The discovery of this network highlighted the brain’s intrinsic operations. The DMN generally decreases its activity during tasks and increases its activity during relaxed non-task states. It is important to investigate the nature of the DMN in order to understand the human brain in health and disease. In the current study, we discovered a task-related cortical network we called the Topological Discrimination Network (TDN), which was consistently revealed by contrasting activations from topological discrimination tasks with local geometric discrimination tasks. The TDN and the DMN consist of essentially the same group of brain regions and the fMRI response of topological discrimination in those regions exhibited consistent temporal dynamics with resting state. The robustness of the TDN is supported by multiple experiments performed at different field strengths (3T and 7T MRI scanner) as well as different types of signals measured (BOLD and CBF). The collective results suggest that the process of topological discrimination could almost be considered as a functional “default mode” of our brain. The TDN, like the DMN, could define the functional baseline of brain, with the advantage of functional consistency across participants and experimental sessions.
COVID Seq as Laboratory Developed Test (LDT) for diagnosis of SARS-CoV-2 Variants of Concern (VOC)
Authors: Carpenter Rob E. , Tamrakar Vaibhav K. , Almas Sadia , Brown Emily , Sharma Rahul 
Published: November 2022

ABSTRACTRapid classification and detection of SARS-CoV-2 variants have been critical in comprehending the virus’s transmission dynamics. Clinical manifestation of the infection is influenced by comorbidities such as age, immune status, diabetes, and the infecting variant. Thus, clinical management may differ for new variants. For example, some monoclonal antibody treatments are variant-specific. Yet, an FDA-approved test for detecting the SARS-CoV-2 variant is unavailable. A laboratory-developed test (LDT) remains a viable option for reporting the infecting variant for clinical intervention or epidemiological purposes. Accordingly, we have validated the Illumina COVID-Seq assay as an LDT according to the guidelines prescribed by the College of American Pathologists (CAP) and Clinical Laboratory Improvement Amendments (CLIA). The limit of detection (LOD) of this test is Ct<30 (∼15 viral copies) and >200X genomic coverage, and the test is 100% specific in the detection of existing variants. The test demonstrated 100% precision in inter-day, intra-day, and intra-laboratory reproducibility studies. It is also 100% accurate, defined by reference strain testing and split sample testing with other CLIA laboratories. Advanta Genetics LDT COVID Seq has been reviewed by CAP inspectors and is under review by FDA for Emergency Use Authorization.
Preliminary Study on the Diagnostic Value of Ultrasonic Shear Wave Dispersion for High-risk Esophageal Gastric Varices in Cirrhosis
Authors: Wang Jiayin , Zhou Hongyu , Li Tinghong , Liu Chuan , Zhao Lei , Xu Baiguo , Yin Weili , Wang Fang , Liang Jing , Jing Xiang , Xiang Huiling 
Published: November 2022

AbstractObjectiveTo explore the clinical value of two-dimensional ultrasonic shear wave elastography (SWE) and shear wave dispersion (SWD) in the diagnosis of high-risk esophageal gastric varices with cirrhosis.MethodsA total of 123 people were included, which were divided into the high-risk esophageal gastric varices (high-risk EGV) group (n =60) and low-risk esophageal gastric varices (low-risk EGV) group (n =63). Both shear wave elastography (SWE) and SWD were adopted to examine each patient’s liver synchronously with the Doppler ultrasonic instrument.ResultsIn total patients, the results of SWD and SWE of the high-risk EGV group were significantly higher than low-risk EGV group respectively. According to SWD examination, the area under the curve (AUC) of high-risk EGV was 0.709(95%CI:0.616-0.802), the optimal cutoff value was 14.35 m/s/kHz, the sensitivity and specificity was 81.7% and 57.1%, the AUC of high-risk EGV in patients with compensated cirrhosis was 0.786(95%CI:0.656-0.916), the optimal cutoff value was 14.35 m/s/kHz, the sensitivity and specificity was 86.4% and 61.1%, while the AUC of high-risk EGV in patients with decompensated cirrhosis was 0.637(95%CI: 0.494-0.780). According to SWE, the AUC of high-risk EGV in all patients, patients with compensated cirrhosis, and patients with decompensated cirrhosis was 0.606(95%CI: 0.506-0.706), 0.596(95%CI: 0.449-0.743), and 0.579(95%CI: 0.434-0.725), respectively, indicating limited diagnostic value.ConclusionSWD predicted the existence of high-risk EGV in patients with compensated cirrhosis non-invasively and provided a supplementary method to determine whether high-risk EGV exists or not in patients, while SWE had limited diagnostic value.
The Eating Disorders Genetics Initiative (EDGI) United Kingdom
Authors: Monssen Dina , Davies Helena L , Bristow Shannon , Kakar Saakshi , Curzons Susannah C B , Davies Molly R , Ahmad Zain , Bradley John R , Bright Steven , Coleman Jonathan R I , Glen Kiran , Hotopf Matthew , Kelly Emily J , Kuile Abigail R Ter , Malouf Chelsea Mika , Kalsi Gursharan , Kingston Nathalie , McAtarsney-Kovacs Monika , Mundy Jessica , Peel Alicia J , Palmos Alish B , Rogers Henry C , Skelton Megan , Adey Brett N , Lee Sang Hyuck , Virgo Hope , Quinn Tom , Price Tom , Zvrskovec Johan , Eley Thalia C , Treasure Janet , Hübel Christopher , Breen Gerome 
Published: November 2022

AbstractObjectiveThe Eating Disorders Genetics Initiative United Kingdom (EDGI UK), part of the National Institute for Health and Care Research (NIHR) Mental Health BioResource, aims to deepen our understanding of the environmental and genetic aetiology of eating disorders. EDGI UK launched in February 2020 and is partnered with the UK eating disorders charity, Beat. There are multiple EDGI branches worldwide.MethodEDGI UK recruits via media and clinical services. Anyone living in England, at least 16 years old, with a lifetime probable or clinical eating disorder is eligible to sign up online:edgiuk.org. Participants complete online questionnaires, donate a saliva sample for genetic analysis, and consent to medical record linkage and recontact for future studies.ResultsAs of September 2022, EDGI UK has recruited 8,397 survey participants: 98% female, 93% white, 97.7% cisgender, 67% heterosexual, and 52% have a university degree. Half (51.7%) of participants have returned their saliva kit. The most common diagnoses are anorexia nervosa (42.7%), atypical anorexia nervosa (31.4%), bulimia nervosa (33.2%), binge-eating disorder (14.6%), and purging disorder (33.5%).ConclusionEDGI UK is the largest UK eating disorders study but needs to increase its diversity, and efforts are underway to do so. It also offers a unique opportunity to accelerate eating disorder research, and collaboration between researchers and participants with lived experience, with unparalleled sample size.
Comparing Models of Information Transfer in the Structural Brain Network and Their Relationship to Functional Connectivity: Diffusion Versus Shortest Path Routing
Authors: Neudorf Josh , Kress Shaylyn , Borowsky Ron 
Published: November 2022

AbstractThe relationship between structural and functional connectivity in the human brain is a core question in network neuroscience, and a topic of paramount importance to our ability to meaningfully describe and predict functional outcomes. Graph theory has been used to produce measures based on the structural connectivity network that are related to functional connectivity. These measures are commonly based on either the shortest path routing model or the diffusion model, which carry distinct assumptions about how information is transferred through the network. Unlike shortest path routing, which assumes the most efficient path is always known, the diffusion model makes no such assumption, and lets information diffuse in parallel based on the number of connections to other regions. Past research has also developed hybrid measures that use concepts from both models, which have better predicted the functional connectivity from structural connectivity than shortest path length alone. We examined the extent to which each of these models can account for the structure-function relationship of interest using graph theory measures that are exclusively based on each model. This analysis was performed on multiple parcellations of the Human Connectome Project using multiple approaches, which all converged on the same finding. We found that the diffusion model accounts for much more variance in functional connectivity than the shortest path routing model, suggesting that the diffusion model is better suited to describing the structure-function relationship in the human brain at the macroscale.
Immediate reuse of patch-clamp pipettes with sonification
Authors: Jehasse Kevin , Wetz Sophie , Neumann-Raizel Peter , Kampa Björn M. 
Published: November 2022

AbstractThe patch-clamp technique has revolutionized neurophysiology by allowing to study single neuronal excitability, synaptic connectivity, morphology, and the transcriptomic profile. However, the throughput in recordings is limited because of the manual replacement of patch-pipettes after each attempt which are often also unsuccessful. This has been overcome by automated cleaning the tips in detergent solutions, allowing to reuse the pipette for further recordings. Here, we developed a novel method of automated cleaning by sonicating the tips within the bath solution wherein the cells are placed, reducing the risk of contaminating the bath solution or internal solution of the recording pipette by any detergent and avoiding the necessity of a separate chamber for cleaning. We showed that the patch-pipettes can be used consecutively at least 10 times and that the cleaning process does not negatively impact neither the brain slices nor other patched neurons. This method, combined with automated patch-clamp, highly improves the throughput for single and especially multiple recordings.
CelltypeR: A flow cytometry pipeline to annotate, characterize and isolate single cells from brain organoids
Authors: Thomas Rhalena A. , Sirois Julien , Li Shuming , Gestin Alexandre , Deyab Ghislaine , Piscopo Valerio E. , Lépine Paula , Mathur Meghna , Chen Carol X.Q. , Soubannier Vincent , Goldsmith Taylor M. , Fawaz Lama , Durcan Thomas M. , Fon Edward A. 
Published: November 2022

AbstractMotivated by the growing number of single cell RNA sequencing datasets (scRNAseq) revealing the cellular heterogeneity in complex tissues, particularly in brain and induced pluripotent stem cell (iPSC)-derived brain models, we developed a high-throughput, standardized approach for reproducibly characterizing cell types in complex neuronal tissues based on protein expression levels. Our approach combines a flow cytometry (FC) antibody panel targeting brain cells with a computational pipeline called CelltypeR, with functions for aligning and transforming datasets, optimizing unsupervised clustering, annotating and quantifying cell types, and statistical comparisons. We applied this workflow to human iPSC-derived midbrain organoids and identified the expected brain cell types, including neurons, astrocytes, radial glia, and oligodendrocytes. Defining gates based on the expression levels of our protein markers, we performed Fluorescence-Activated Cell Sorting of astrocytes, radial glia, and neurons, cell types were then confirmed by scRNAseq. Among the sorted neurons, we identified three subgroups of dopamine (DA) neurons; one reminiscent of substantia nigra DA neurons, the cell type most vulnerable in Parkinson’s disease. Finally, we use our workflow to track cell types across a time course of organoid differentiation. Overall, our adaptable analysis framework provides a generalizable method for reproducibly identifying cell types across FC datasets.