bluuebunny/crossref_metadata_2025 huggingface dataset:
Landscape, complexity and regulation of a filamentous fungal transcriptome
Authors: Lu Ping , Chen Daipeng , Qi Zhaomei , Wang Haoming , Chen Yitong , Wang Qinhu , Jiang Cong , Liu Huiquan , Xu Jin-Rong
Published: November 2021

Alternative splicing (AS) and alternative polyadenylation (APA) of pre-mRNAs contribute greatly to transcriptome complexity and gene expression regulation in higher eukaryotes. Their biological impact in filamentous fungi, however, has been poorly studied. Here we combine PacBio Isoform Sequencing and strand-specific RNA-Seq of multiple tissues together with mutant characterization to reveal the landscape, complexity and regulation of AS and APA in the filamentous plant pathogenic fungusFusarium graminearum. We updated the reference genome and generated a comprehensive annotation comprising 51,617 transcript isoforms from 17,189 genes. Majority of the transcripts represent novel isoforms, including 2,998 undiscovered protein-coding genes. In total, 42.7% of multi-exonic genes and 64.8% of genes have AS and APA isoforms, respectively, suggesting AS and APA increase previously unrecognized transcriptome complexity in fungi. Nonsense-mediated mRNA decay factor FgUPF1 may not degrade AS transcripts with premature-stop codons but regulate ribosome biogenesis. Distal polyadenylation sites have a strong signal but proximal polyadenylation isoforms are high expressed. The core 3’-end processing factors FgRNA15, FgHRP1, and FgFIP1 play important roles in promoting proximal polyadenylation site usage and also intron splicing. Genome-wide increase in the abundance of transcripts with retained introns and long 3’-UTRs and downregulation of the spliceosomal and 3’-end processing factors are found in older tissues and quiescent conidia, indicating that intron retention and 3’-UTR lengthening may be a transcriptional signature of aging and dormancy in fungi. Overall, our study generates a comprehensive full-length transcript annotation forF. graminearumand provides new insights into the complexity and regulation of transcriptome in filamentous fungi.
Frontline Healthcare workers suffering from psychosomatic disorders during COVID-19 (a pandemic) – A Systematic review
Authors: Joshi Rhythm , Agarwal Nidhi.B. , Bhurani Dinesh , Khan Mohd Ashif
Published: November 2021

Purpose

The emergence of SARS CoV-2, has imposed high pressure on the healthcare system worldwide. As a consequence, frontline healthcare workers were impacted widely. The aim of this systematic review is to examine the impact of COVID-19 on mental status of FHW during pandemic.

Methods

Databases such as PubMed, Scopus, google scholar were searched extensively from the date of inception till April 2021. All cross-sectional studies published in English assessing the mental condition and well-being of frontline caregivers during COVID-19 were included in the study. The quality assessment was done by Newcastle Ottawa scale.

Results

Ten thousand eight hundred sixty-nine articles were found. After conscientious literature search, total 78 articles were included satisfying the objective of the review. The highest and lowest values for the rates of depression, anxiety and insomnia was found to be 99.51% & 6.07%, 85.7% & 73.6%, and 5.3% & 11.4%, respectively.

Conclusion

It has been found that FHW were psychologically impacted by the pandemic. This could be due to lack of resources such as PPE, organizational support, inefficient relevant knowledge regarding the novel virus, its extremely indelible transmission rates, fear of contamination, stigmatization, and/or due to prevalence of ignorance by government and health policy makers.

Prospero registration no-CRD42021244612
Neural assemblies uncovered by generative modeling explain whole-brain activity statistics and reflect structural connectivity
Authors: van der Plas Thijs L. , Tubiana Jérôme , Le Goc Guillaume , Migault Geoffrey , Kunst Michael , Baier Herwig , Bormuth Volker , Englitz Bernhard , Debrégeas Georges
Published: November 2021

Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here we recorded the activity from ~ 40,000 neurons simultaneously in zebrafish larvae, and show that a data-driven generative model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine (cRBM), unveils ~ 200 neural assemblies, which compose neurophysiological circuits and whose various com-binations form successive brain states. We then performed in silico perturbation experiments to determine the interregional functional connectivity, which is conserved across individual animals and correlates well with structural connectivity. Our results showcase how cRBMs can capture the coarse-grained organization of the zebrafish brain. Notably, this generative model can readily be deployed to parse neural data obtained by other large-scale recording techniques.
Unsupervised integration of single-cell multi-omics datasets with disparities in cell-type representation
Authors: Demetci Pinar , Santorella Rebecca , Sandstede Björn , Singh Ritambhara
Published: November 2021

Integrated analysis of multi-omics data allows the study of how different molecular views in the genome interact to regulate cellular processes; however, with a few exceptions, applying multiple sequencing assays on the same single cell is not possible. While recent unsupervised algorithms align single-cell multi-omic datasets, these methods have been primarily benchmarked on co-assay experiments rather than the more common single-cell experiments taken from separately sampled cell populations. Therefore, most existing methods perform subpar alignments on such datasets. Here, we improve our previous work Single Cell alignment using Optimal Transport (SCOT) by using unbalanced optimal transport to handle disproportionate cell-type representation and differing sample sizes across single-cell measurements. We show that our proposed method, SCOTv2, consistently yields quality alignments on five real-world single-cell datasets with varying cell-type proportions and is computationally tractable. Additionally, we extend SCOTv2 to integrate multiple (M ≥ 2) single-cell measurements and present a self-tuning heuristic process to select hyperparameters in the absence of any orthogonal correspondence information.

Available at:http://rsinghlab.github.io/SCOT.
From shallow to deep: exploiting feature-based classifiers for domain adaptation in semantic segmentation
Authors: Matskevych Alex , Wolny Adrian , Pape Constantin , Kreshuk Anna
Published: November 2021

The remarkable performance of Convolutional Neural Networks on image segmentation tasks comes at the cost of a large amount of pixelwise annotated images that have to be segmented for training. In contrast, feature-based learning methods, such as the Random Forest, require little training data, but never reach the segmentation accuracy of CNNs. This work bridges the two approaches in a transfer learning setting. We show that a CNN can be trained to correct the errors of the Random Forest in the source domain and then be applied to correct such errors in the target domain without retraining, as the domain shift between the Random Forest predictions is much smaller than between the raw data. By leveraging a few brushstrokes as annotations in the target domain, the method can deliver segmentations that are sufficiently accurate to act as pseudo-labels for target-domain CNN training. We demonstrate the performance of the method on several datasets with the challenging tasks of mitochondria, membrane and nuclear segmentation. It yields excellent performance compared to microscopy domain adaptation baselines, especially when a significant domain shift is involved.
The Role of Extended Range of Interactions in the Dynamics of Interacting Molecular Motors
Authors: Spaulding Cade , Teimouri Hamid , Narasimhan S.L. , Kolomeisky Anatoly B.
Published: November 2021

Motor proteins, also known as biological molecular motors, play important roles in various intracellular processes. Experimental investigations suggest that molecular motors interact with each other during the cellular transport, but the nature of such interactions remains not well understood. Stimulated by these observations, we present a theoretical study aimed to understand the effect of the range of interactions on dynamics of interacting molecular motors. For this purpose, we develop a new version of the totally asymmetric simple exclusion processes in which nearest-neighbor as well as the next nearest-neighbor interactions are taken into account in a thermodynamically consistent way. A theoretical framework based on a cluster mean-field approximation, which partially takes correlations into account, is developed to evaluate the stationary properties of the system. It is found that fundamental current-density relations in the system strongly depend on the strength and the sign of interactions, as well as on the range of interactions. For repulsive interactions stronger than some critical value, increasing the range of interactions leads to a change from unimodal to trimodal dependence in the flux-density fundamental diagram. Theoretical calculations are tested with extensive Monte Carlo computer simulations. Although in most ranges of parameters excellent agreement between theoretical predictions and computer simulations is observed, there are situations when the cluster mean-field approach fails to describe properly the dynamics in the system. Theoretical arguments to explain these observations are presented. Our theoretical analysis clarifies the microscopic picture of how the range of interactions influences the dynamics of interacting molecular motors.
Recurrent exon-deleting activating mutations in AHR act as drivers of urinary tract cancer
Authors: Vlaar Judith M. , Borgman Anouska , Kalkhoven Eric , Westland Denise , Besselink Nicolle , Shale Charles , Faltas Bishoy M. , Priestley Peter , Kuijk Ewart , Cuppen Edwin
Published: November 2021

Bladder cancer has a high recurrence rate and low survival of advanced stage patients. Few genetic drivers of bladder cancer have thus far been identified. We performed in-depth structural variant analysis on whole-genome sequencing data of 206 metastasized urinary tract cancers. In ~10% of the patients, we identified recurrent in-frame deletions of exons 8 and 9 in the aryl hydrocarbon receptor gene (AHRΔe8-9), which codes for a ligand-activated transcription factor. Pan-cancer analyses show that AHRΔe8-9 is highly specific to urinary tract cancer and mutually exclusive with other bladder cancer drivers. In AHRΔe8-9 the ligand-binding domain is disrupted and we show that this results in ligand-independent AHR-pathway activation. In bladder organoids, AHRΔe8-9 induces a transformed phenotype that is characterized by upregulation of AHR target genes, downregulation of differentiation markers and upregulation of genes associated with stemness and urothelial cancer. Furthermore, AHRΔe8-9 expression results in anchorage independent growth of bladder organoids, indicating tumorigenic potential. DNA-binding deficient AHRΔe8-9 fails to induce transformation, suggesting a role for AHR target genes in the acquisition of the oncogenic phenotype. In conclusion, we show that AHRΔe8-9 is a novel driver of urinary tract cancer and that the AHR pathway could be an interesting therapeutic target.
Immune escape mutations selected by neutralizing antibodies in natural HIV-1 infection can alter coreceptor usage repertoire of the transmitted/founder virus
Authors: Marichannegowda Manukumar Honnayakanahalli , Song Hongshuo
Published: November 2021

The ability of HIV-1 to evade neutralizing antibodies (NAbs) in vivo is well demonstrated, but the impact of NAb escape mutations on HIV-1 phenotype other than immune escape itself has rarely been studied. Here, we show that immune escape mutations selected by V3-glycan specific NAbs in vivo can alter the coreceptor usage repertoire of the transmitted/founder (T/F) HIV-1. In a participant developed V3-glycan NAb response, naturally selected mutations at the V3 N301 and N332 glycan sites abrogated CCR8 usage while conferred APJ usage on the cognate T/F strain. Mutations at the N301 glycan also impaired CCR3 usage and partially compromised the efficiency in using CCR5, which could be fully restored by a single escape mutation at the N332 glycan site. Our study demonstrates the link between NAb escape and coreceptor usage alteration in natural HIV-1 infection and indicates that NAb response could drive virus entry tropism evolution in vivo.
Predicting efficiency of writing short sequences into the genome using prime editing
Authors: Koeppel Jonas , Peets Elin Madli , Weller Juliane , Pallaseni Ananth , Liberante Fabio , Parts Leopold
Published: November 2021

Short sequences can be precisely written into a selected genomic target using prime editing. This ability facilitates protein tagging, correction of pathogenic deletions, and many other exciting applications. However, it remains unclear what types of sequences prime editors can easily insert, and how to choose optimal reagents for a desired outcome. To characterize features that influence insertion efficiency, we designed a library of 2,666 sequences up to 69 nt in length and measured the frequency of their insertion into four genomic sites in three human cell lines, using different prime editor systems. We discover that insertion sequence length, nucleotide composition and secondary structure all affect insertion rates, and that mismatch repair proficiency is a strong determinant for the shortest insertions. Combining the sequence and repair features into a machine learning model, we can predict insertion frequency for new sequences with R = 0.69. The tools we provide allow users to choose optimal constructs for DNA insertion using prime editing.
Resonant Learning in Scale-free Networks
Authors: Goldman Samuel , Aldana Maximino , Cluzel Philippe
Published: November 2021

Over the last decades, analyses of the connectivity of large biological and artificial networks have identified a common scale-free topology, where few of the network elements, called hubs, control many other network elements. In monitoring the dynamics of networks’ hubs, recent experiments have revealed that they can show behaviors oscillating between ‘on’ and ‘off’ states of activation. Prompted by these observations, we ask whether the existence of oscillatory hubs states could contribute to the emergence of specific network dynamical behaviors. Here, we use Boolean threshold networks with scale-free architecture as representative models to demonstrate how periodic activation of the network hub can provide a network-level advantage in learning specific new dynamical behaviors. First, we find that hub oscillations with distinct periods can induce robust and distinct attractors whose lengths depend upon the hub oscillation period. Second, we determine that a given network can exhibit series of different attractors when we sequentially change the period of hub pulses. Using rounds of evolution and selection, these different attractors could independently learn distinct target functions. We term this network-based learning strategy resonant learning, as the emergence of new learned dynamical behaviors depends on the choice of the period of the hub oscillations. Finally, we find that resonant learning leads to convergence towards target behaviors over an order of magnitude faster than standard learning procedures. While it is already known that modular network architecture contributes to learning separate tasks, our results reveal an alternative design principle based on forced oscillations of the network hub.

SIGNIFICANCE

Large networks of interconnected components such as genes or machines can coordinate complex behavioral dyamics. One outstanding question has been to identify the design principles that allow networks to learn new behaviors. Here, in simulating learning cycles, we randomly modify the interactions between components and select networks that exhibit a desired behavior. Surprisingly, we find that networks can learn new behaviors faster when the state of the most connected network component is forced to oscillate during learning. Remarkably, using distinct periods of oscillations allows a given network to learn distinct behaviors. While it is known that modular network architecture contributes to learning separate tasks, our results reveal an alternative design principle for which modules are not needed.
Cell type identification in spatial transcriptomics data can be improved by leveraging cell-type-informative paired tissue images using a Bayesian probabilistic model
Authors: Zubair Asif , Chapple Richard H. , Natarajan Sivaraman , Wright William C. , Pan Min , Lee Hyeong-Min , Tillman Heather , Easton John , Geeleher Paul
Published: November 2021

Spatial transcriptomics technologies have recently emerged as a powerful tool for measuring spatially resolved gene expression directly in tissues sections, revealing cell types and their dysfunction in unprecedented detail. However, spatial transcriptomics technologies are limited in their ability to separate transcriptionally similar cell types and can suffer further difficulties identifying cell types in slide regions where transcript capture is low. Here, we describe a conceptually novel methodology that can computationally integrate spatial transcriptomics data with cell-type-informative paired tissue images, obtained from, for example, the reverse side of the same tissue section, to improve inferences of tissue cell type composition in spatial transcriptomics data. The underlying statistical approach is generalizable to any spatial transcriptomics protocol where informative paired tissue images can be obtained. We demonstrate a use case leveraging cell-type-specific immunofluorescence markers obtained on mouse brain tissue sections and a use case for leveraging the output of AI annotated H&E tissue images, which we used to markedly improve the identification of clinically relevant immune cell infiltration in breast cancer tissue. Thus, combining spatial transcriptomics data with paired tissue images has the potential to improve the identification of cell types and hence to improve the applications of spatial transcriptomics that rely on accurate cell type identification.
Alterations in the Antioxidant Metabolites in Cotton Leaf Curl Disease Infected and Healthy Cotton Leaves
Authors: Rehman Atiq Ur , Zia Muhammad Anjum , Mubin Muhammad , Shahid Muhammad
Published: November 2021

The upland cotton (Gossypium hirsutum) belongs to the family Malvaceae and cultivated since ancient times in warmer parts of the world. Pakistan is the 4th largest cotton producing country and prominent cotton yarn exporter of the world. Cotton is the major source of natural fiber and significantly contributes to the economy of Pakistan. There are many factors (biotic and abiotic) affecting the cotton yield in Pakistan. The cotton leaf curl disease (CLCuD) is one of the biotic factors and endemic in the most cotton growing areas of the country. The antioxidant enzymes and antioxidant biochemical metabolites play important role during stress. The present study was planned to compare the antioxidant enzymes and metabolites from healthy and CLCuD infected cotton leaves. Antioxidant enzymes activities including catalase, peroxidase and peroxidase were measured through different antioxidant assays and different antioxidant metabolites were also determined. During stress condition antioxidant metabolites serve as signal for the activation of antioxidant enzymes. Present study revealed that antioxidant enzymes were significantly higher in the infected cotton leaves as compared to the healthy cotton leaves. While the amount of antioxidant metabolites like total phenolic contents (TPC) and total flavonoid contents (TFC) were higher in healthy cotton leaves as compared to the infected leaves.
Integrative Properties of the Pe1 Neuron, a Unique Mushroom Body Output Neuron
Authors: Rybak Jürgen , Menzel Randolf
Published: November 2021

A mushroom body extrinsic neuron, the Pe1 neuron, connects the peduncle of the mushroom body (MB) with two areas of the protocerebrum in the honeybee brain, the lateral protocerebral lobe (LPL) and the ring neuropil around the α-lobe. Each side of the bee brain contains only one Pe1 neuron. Using a combination of intracellular recording and neuroanatomical techniques we analyzed its properties of integrative processing of the different sensory modalities. The Pe1 neuron responds to visual, mechanosensory, and olfactory stimuli. The responses are broadly tuned, consisting of a sustained increase of spike frequency to the onset and offset of light flashes, to horizontal and vertical movements of extended objects, to mechanical stimuli applied to the antennae or mouth parts, and to all olfactory stimuli tested (29 chemicals). These multisensory properties are reflected in its dendritic organization. Serial reconstructions of intracellularly stained Pe1 neurons using confocal microscopy reveal that the Pe1 neuron arborizes throughout all layers of MB peduncle with finger-like, vertically oriented dendrites. The peduncle of the MB is formed by the axons of Kenyon cells, whose dendritic inputs are organized in modality-specific subcompartments of the calyx region. The peduncular arborization indicates that the Pe1 neuron receives input from Kenyon cells of all calycal subcompartments. Because the Pe1 neuron changes its odor responses transiently as a consequence of olfactory learning, we hypothesize that the multimodal response properties might have a role in memory consolidation and help to establish contextual references in the long-term trace.
The Organization of Extrinsic Neurons and Their Implications in the Functional Roles of the Mushroom Bodies inDrosophila melanogasterMeigen
Authors: Ito Kei , Suzuki Kazumi , Estes Patricia , Ramaswami Mani , Yamamoto Daisuke , Strausfeld Nicholas J.
Published: November 2021

Although the importance of theDrosophilamushroom body in olfactory learning and memory has been stressed, virtually nothing is known about the brain regions to which it is connected. Using Golgi and GAL4–UAS techniques, we performed the first systematic attempt to reveal the anatomy of its extrinsic neurons. A novel presynaptic reporter construct, UAS-neuronal synaptobrevin–green fluorescent protein(n-syb–GFP), was used to reveal the direction of information in the GAL4-labeled neurons. Our results showed that the main target of the output neurons from the mushroom body lobes is the anterior part of the inferior medial, superior medial, and superior lateral protocerebrum. The lobes also receive afferents from these neuropils. The lack of major output projections directly to the deutocerebrum’s premotor pathways discourages the view that the role of the mushroom body may be that of an immediate modifier of behavior. Our data, as well as a critical evaluation of the literature, suggest that the mushroom body may not by itself be a “center” for learning and memory, but that it can equally be considered as a preprocessor of olfactory signals en route to “higher” protocerebral regions.
Immunocytochemical Mapping of an RDL-Like GABA Receptor Subunit and of GABA in Brain Structures Related to Learning and Memory in the Cricket Acheta domesticus
Authors: Strambi Colette , Cayre Myriam , Sattelle David B. , Augier Roger , Charpin Pierre , Strambi Alain
Published: November 2021

The distribution of putative RDL-like GABA receptors and of γ-aminobutyric acid (GABA) in the brain of the adult house cricket Acheta domesticus was studied using specific antisera. Special attention was given to brain structures known to be related to learning and memory. The main immunostaining for the RDL-like GABA receptor was observed in mushroom bodies, in particular the upper part of mushroom body peduncle and the two arms of the posterior calyx. Weaker immunostaining was detected in the distal part of the peduncle and in the α and β lobes. The dorso- and ventrolateral protocerebrum neuropils appeared rich in RDL-like GABA receptors. Staining was also detected in the glomeruli of the antennal lobe, as well as in the ellipsoid body of the central complex. Many neurons clustered in groups exhibit GABA-like immunoreactivity. Tracts that were strongly immunostained innervated both the calyces and the lobes of mushroom bodies. The glomeruli of the antennal lobe, the ellipsoid body, as well as neuropils of the dorso- and ventrolateral protocerebrum were also rich in GABA-like immuno- reactivity. The data demonstrated a good correlation between the distribution of the GABA-like and of the RDL-like GABA receptor immunoreactivity. The prominent distribution of RDL-like GABA receptor subunits, in particular areas of mushroom bodies and antennal lobes, underlines the importance of inhibitory signals in information processing in these major integrative centers of the insect brain.
NMDA Receptor Antagonism in the Lateral/Basolateral but Not Central Nucleus of the Amygdala Prevents the Induction of Facilitated Learning in Response to Stress
Authors: Shors Tracey J. , Mathew Pramod R.
Published: November 2021

Exposure to an acute stressful event facilitates classical eye-blink conditioning in the male rat. The facilitation persists for days after the stressor and its induction is prevented by antagonism of the N-methyl-d-aspartate (NMDA) type of glutamate receptor. To determine whether NMDA receptor antagonists prevent the facilitated conditioning by activity in the amygdala, a competitive antagonist, AP5, was injected bilaterally into the lateral/basolateral versus central nuclei of the amygdala. Local injection of d,l-2-amino-5-phosphonovaleric acid (AP5) into the lateral/basolateral nucleus before stressor exposure prevented the facilitated learning 24 hr later, whereas antagonism in the central nucleus before stressor exposure did not. To determine when the necessary activation occurs, AP5 was injected into the lateral/basolateral nucleus before versus after exposure to the acute stressful event. Blockade of NMDA receptors before but not after stressor exposure prevented the facilitated acquisition of the conditioning in response to stress. These results suggest that exposure to a stressful event transiently activates NMDA receptors in basolateral/lateral nuclei of the amygdala and thereby induces a persistent enhancement of associative learning.
Higher Seizure Susceptibility and Enhanced Tyrosine Phosphorylation of N-Methyl-d-Aspartate Receptor Subunit 2B in fyn Transgenic Mice
Authors: Kojima Nobuhiko , Ishibashi Hidetoshi , Obata Kunihiko , Kandel Eric R.
Published: November 2021

Earlier work has suggested that Fyn tyrosine kinase plays an important role in synaptic plasticity. To understand the downstream targets of Fyn signaling cascade in neurons, we generated transgenic mice expressing either a constitutively activated form of Fyn or native Fyn in neurons of the forebrain. Transgenic mice expressing mutant Fyn exhibited higher seizure activity and were prone to sudden death. Mice overexpressing native Fyn did not show such an obvious epileptic phenotype, but they exhibited accelerated kindling in response to once-daily stimulation of the amygdala. Tyrosine phosphorylation of at least three proteins was enhanced in the forebrains of both native and mutant fyn transgenic mice; tyrosine phosphorylation of these three proteins was reduced infyn knockout mice, suggesting that they are substrates of Fyn. One of these proteins was identified as the subunit 2B (NR2B) of theN-methyl-d-aspartate (NMDA) receptor. Administration of MK-801, a noncompetitive NMDA receptor antagonist, retarded kindling in mice overexpressing native Fyn, as well as wild-type mice, suggests that the accelerated kindling in mice overexpressing Fyn is also mediated by the NMDA receptor activity. Our results thus suggest that tyrosine phosphorylation by Fyn might be involved in regulation of the susceptibility of kindling, one form of the NMDA receptor-mediated neuronal plasticity.
On the Respective Roles of Nitric Oxide and Carbon Monoxide in Long-Term Potentiation in the Hippocampus
Authors: Zhuo Min , Laitinen Jarmo T. , Li Xiao-Ching , Hawkins Robert D.
Published: November 2021

Perfusion of hippocampal slices with an inhibitor nitric oxide (NO) synthase blocked induction of long-term potentiation (LTP) produced by a one-train tetanus and significantly reduced LTP by a two-train tetanus, but only slightly reduced LTP by a four-train tetanus. Inhibitors of heme oxygenase, the synthetic enzyme for carbon monoxide (CO), significantly reduced LTP by either a two-train or four-train tetanus. These results suggest that NO and CO are both involved in LTP but may play somewhat different roles. One possibility is that NO serves a phasic, signaling role, whereas CO provides tonic, background stimulation. Another possibility is that NO and CO are phasically activated under somewhat different circumstances, perhaps involving different receptors and second messengers. Because NO is known to be activated by stimulation of NMDA receptors during tetanus, we investigated the possibility that CO might be activated by stimulation of metabotropic glutamate receptors (mGluRs). Consistent with this idea, long-lasting potentiation by the mGluR agonist tACPD was blocked by inhibitors of heme oxygenase but not NO synthase. Potentiation by tACPD was also blocked by inhibitors of soluble guanylyl cyclase (a target of both NO and CO) or cGMP-dependent protein kinase, and guanylyl cyclase was activated by tACPD in hippocampal slices. However, biochemical assays indicate that whereas heme oxygenase is constitutively active in hippocampus, it does not appear to be stimulated by either tetanus or tACPD. These results are most consistent with the possibility that constitutive (tonic) rather than stimulated (phasic) heme oxygenase activity is necessary for potentiation by tetanus or tACPD, and suggest that mGluR activation stimulates guanylyl cyclase phasically through some other pathway.
Hippocampal EEG and Unit Activity Responses to Modulation of Serotonergic Median Raphe Neurons in the Freely Behaving Rat
Authors: Nitz Douglas A. , McNaughton Bruce L.
Published: November 2021

Hippocampal EEG, GABAergic interneurons, and principal cells were recorded simultaneously as rats foraged within one of three environments both before and after modulation of serotonergic inputs to the hippocampus. Median raphe microinjections of the 5-HT1a receptor agonist 8-OH-DPAT were made to produce inhibition of serotonergic neurons in this region. Such microinjections produced behavioral arousal and increases in the amplitude of hippocampal EEG theta. Consistent with the pattern of serotonergic innervation of the hippocampus, the GABAergic interneuron population was affected differentially by the microinjections. Principal cells were generally unaffected by the manipulation and maintained robust spatial firing correlates within the foraging environment. The results provide basic data on the relationship between serotonergic median raphe neurons and hippocampal activity in a behaving animal. The data suggest that behavioral responses to manipulation of the serotonergic system are mediated by brain regions other than the hippocampus or are mediated through changes in the activity of hippocampal interneurons.
Memory Consolidation for Contextual and Auditory Fear Conditioning Is Dependent on Protein Synthesis, PKA, and MAP Kinase
Authors: Schafe Glenn E. , Nadel Nicole V. , Sullivan Gregory M. , Harris Alexander , LeDoux Joseph E.
Published: November 2021

Fear conditioning has received extensive experimental attention. However, little is known about the molecular mechanisms that underlie fear memory consolidation. Previous studies have shown that long-term potentiation (LTP) exists in pathways known to be relevant to fear conditioning and that fear conditioning modifies neural processing in these pathways in a manner similar to LTP induction. The present experiments examined whether inhibition of protein synthesis, PKA, and MAP kinase activity, treatments that block LTP, also interfere with the consolidation of fear conditioning. Rats were injected intraventricularly with Anisomycin (100 or 300 μg), Rp-cAMPS (90 or 180 μg), or PD098059 (1 or 3 μg) prior to conditioning and assessed for retention of contextual and auditory fear memory both within an hour and 24 hr later. Results indicated that injection of these compounds selectively interfered with long-term memory for contextual and auditory fear, while leaving short-term memory intact. Additional control groups indicated that this effect was likely due to impaired memory consolidation rather than to nonspecific effects of the drugs on fear expression. Results suggest that fear conditioning and LTP may share common molecular mechanisms.
Synaptic Reliability Correlates with Reduced Susceptibility to Synaptic Potentiation by Brain-Derived Neurotrophic Factor
Authors: Berninger Benedikt , Schinder Alejandro F. , Poo Mu-ming
Published: November 2021

Recent studies have implicated brain-derived neurotrophic factor (BDNF) in use-dependent modification of hippocampal synapses. BDNF can rapidly potentiate synaptic transmission at glutamatergic synapses by enhancing transmitter release. Using simultaneous perforated patch recording from pairs and triplets of glutamatergic hippocampal neurons, we have examined how the initial state of the glutamatergic synapse determines its susceptibility to synaptic modification by BDNF. We found that the degree of synaptic potentiation by BDNF depends on the initial reliability and strength of the synapse: Relatively weak connections were strongly potentiated, whereas the effect was markedly reduced at stronger synapses. The degree of BDNF-induced potentiation strongly correlated with the initial coefficient of variation (CV) of the amplitude of excitatory postsynaptic currents (EPSCs) and inversely correlated with the initial paired–pulse facilitation, suggesting that synapses with lower release probability (Pr) are more susceptible to the action of BDNF. To determine whether saturation of Pr could have masked the potentiation effect of BDNF in the stronger synapses, we lowered the initial Pr either by reducing the extracellular Ca2+ concentration ([Ca2+]o) or by bath application of adenosine. Synapses that were initially strong remained unaffected by BDNF under these conditions of reduced Pr. Thus, the lack of BDNF effect on synaptic efficacy cannot simply be accounted for by saturation of Pr, but rather may be due to intrinsic changes associated with synaptic maturation that might covary with Pr. Finally, the dependence on initial synaptic strength was also found for divergent outputs of the same presynaptic neuron, suggesting that synaptic terminals with different degrees of responsiveness to BDNF can coexist within in the same neuron.
Growth Factor Modulation of Substrate-Specific Morphological Patterns in Aplysia Bag Cell Neurons
Authors: Gruenbaum Lore M. , Carew Thomas J.
Published: November 2021

Components of the extracellular matrix (ECM) can act not only as passive substrates for neuronal attachment and outgrowth but also as active sites for signal transduction. Thus, specific ECM components may modulate effects of growth factors (GFs) that play an important role in structural changes in development and adult neuronal plasticity. In this study we examined the interaction of cultured Aplysia bag cell neurons (BCNs) with components of ECM and different GFs. Different ECM substrata induce a substrate-specific BCN morphology: BCNs grown on collagen or poly-l-lysine have larger soma diameter and more extensive neurite outgrowth than BCNs grown on laminin or fibronectin. BCNs also interact in a substrate-dependent way with GFs: BDNF treatment leads to a reduction of outgrowth on poly-l-lysine but an enhancement on fibronectin and laminin. CNTF reduces the soma diameter on collagen IV but enlarges it on laminin or fibronectin. In contrast, NGF induces a reduction of both soma diameter and outgrowth, on all substrata. Plating of BCNs in the presence of anti-β1-integrin reduces adhesion to fibronectin but does not change outgrowth. In contrast, RGD peptides block adhesion to laminin and poly-l-lysine and, additionally, reduce outgrowth on laminin. These data suggest that BCNs use different β1-integrin-dependent as well as RGD-dependent mechanisms for adhesion and outgrowth on different ECM substrata, providing possible sites of modulation by specific GFs.
Expression of Fos and Jun Proteins Following Passive Avoidance Training in the Day-Old Chick
Authors: Freeman Fiona M. , Rose Steven P.R.
Published: November 2021

It has been shown previously that the immediate-early genes, c-fos and c-jun mRNA are induced in the 1-day-old chick forebrain after one-trial passive avoidance training in which chicks learn to avoid pecking at a bitter-tasting bead. Here, we have studied the expression of their proteins using antibodies to Fos and Jun. Western blotting disclosed two immunoreactive bands for the anti-Fos antibody (47 and 54 kD) and two immunoreactive bands for the anti-Jun antibody (39 and 54 kD). Two hours post-training there was an increase in the number of Fos-positive stained nuclei in right intermediate medial hyperstriatum ventrale (IMHV) (P < 0.01), left IMHV (P < 0.05), right lobus parolfactorius (LPO) (P < 0.025) and left LPO (P < 0.05) of birds trained on the bitter bead compared with controls that had pecked a water-coated bead. Staining for Jun protein was significantly greater in the right LPO of trained chicks (P < 0.01). Other forebrain regions showed no increase over quiet control levels. The findings are discussed in the context of the cascade of events involved in passive avoidance memory consolidation in the day-old chick.
The rate and impact of substance misuse in psychiatric intensive care units (PICUs) in the UK
Authors: Moyes Hattie Catherine Ann , MacNaboe Lana , Townsend Kate
Published: November 2021

Purpose

This paper aims to understand the current scale of substance misuse in psychiatric intensive care units (PICUs), identify how substance misuse affects members of staff, patients and the running of wards and explore with staff what resources would be most useful to more effectively manage substance misuse and dual diagnosis on PICUs.

Design/methodology/approach

The paper used a mixed-methods approach, using a quantitative survey to determine the extent of substance use in PICUs and a co-design workshop to understand the impact of substance misuse on PICU wards, staff and patients.

Findings

The estimated rate of substance misuse in PICUs over a 12-month period is 67%, with cannabis the most frequently used substance. Despite the range of problems experienced on PICUs because of substance misuse, the availability of training and resources for staff was mixed.

Research limitations/implications

The findings may not be fully generalisable as research participants were members of a national quality improvement programme, and therefore, may not be representative of all PICUs. Data was collected from clinicians only; if patients were included, they might have provided another perspective on substance misuse on PICUs.

Practical implications

This paper emphasises the importance of substance misuse training for PICU staff to adequately respond to patients who misuse substances, improve the ward environment, staff well-being and patient outcomes.

Originality/value

This paper provides an updated estimation of rates of substance misuse in PICUs over a 12-month period and make suggestions for a training programme that can better support staff to address substance misuse on PICUs.
Chemical potential variation effect of new design of graphene antenna for satellite applications
Authors: Rabah Mohammed Amin , Mohammed Bekhti
Published: November 2021

Purpose

The present work aims to analyze the performance of a newly designed graphene-based patch antenna by varying the chemical potential in graphene sheet, using the CST Microwave Studio ® software. This study mainly seeks to discuss and assess the advantage of using graphene, instead of copper, as the radiating patch. It should be noted that graphene is a new material that possesses unique properties. Its parameters are optimized for the purpose of introducing it in satellite technology.

Design/methodology/approach

The use of graphene as a radiating patch of space technology applications, where a polygonal graphene patch antenna element is designed by the CST Microwave Studio ® software with Taconic RF-41 substrate to resonate in the satellite bands.

Findings

Analysis of a graphene patch sheet by a variation in the chemical potential to ensure operation in a space environment.

Originality/value

The increase in the chemical potential for a graphene patch antenna has shown a prominent increase in the values of the gain. A new contribution, by the combination of the antenna performance improvement techniques and the use of graphene as a radiating patch of space technology applications.
Big data and analytics in hospitality and tourism: a systematic literature review
Authors: Mariani Marcello , Baggio Rodolfo
Published: November 2021

Purpose

The purpose of this work is to survey the body of research revolving around big data (BD) and analytics in hospitality and tourism, by detecting macro topical areas, research streams and gaps and to develop an agenda for future research.

Design/methodology/approach

This research is based on a systematic literature review of academic papers indexed in the Scopus and Web of Science databases published up to 31 December 2020. The outputs were analyzed using bibliometric techniques, network analysis and topic modeling.

Findings

The number of scientific outputs in research with hospitality and tourism settings has been expanding over the period 2015–2020, with a substantial stability of the areas examined. The vast majority are published in academic journals where the main reference area is neither hospitality nor tourism. The body of research is rather fragmented and studies on relevant aspects, such as BD analytics capabilities, are virtually missing. Most of the outputs are empirical. Moreover, many of the articles collected relatively small quantities of records and, regardless of the time period considered, only a handful of articles mix a number of different techniques.

Originality/value

This work sheds new light on the emergence of a body of research at the intersection of hospitality and tourism management and data science. It enriches and complements extant literature reviews on BD and analytics, combining these two interconnected topics.
Mapping direct flood impacts from a 2020 extreme flood event in Central Vietnam using spatial analysis techniques
Authors: Luu Chinh , Bui Quynh Duy , von Meding Jason
Published: November 2021

Purpose

In October 2020, Vietnam was repeatedly hit by large storms, including Linfa, Nangka, Saudel and Molave, causing heavy rains and whirlwinds in the Central provinces of Vietnam. The heavy rain led to severe flooding in many localities. The water levels on major rivers broke records of historical flood events in 1950, 1979, 1999, 2007, 2010 and 2016. In response, this paper aims to quantify the impacts of 2020 flooding to support flood risk management activities and the relief agencies that can use the analysis.

Design/methodology/approach

This study demonstrates an approach to quickly map flood impacts on population, schools, health-care facilities, agriculture, transportation and business facilities and assess flood risks using available data and spatial analysis techniques.

Findings

The results show that all districts of Quang Binh were affected by the event, in which 1,014 residential areas, 70 schools, 13 health-care facilities, 32,558 ha of agriculture lands, 402 km road length, 29 km railway, 35 bridges on roads and 239 business facilities were exposed within flooded areas.

Research limitations/implications

This study is limited to direct or tangible impacts, including flooded residential areas, schools, health-care facilities, agriculture land categories, road networks and business facilities. Indirect or intangible impacts such as health, flood pollution and business disruption should be considered in further studies.

Practical implications

These detailed impact maps can support decision-makers and local authorities in implementing recovery activities, allocating relief and devoting human resources and developing flood risk management action plans and land-use planning in the future.

Social implications

This study investigates the context of flood impacts on population, schools, health-care facilities, agriculture, transportation and business facilities. Based on this research, decision-makers can better understand how to support affected communities and target the most at risk people with interventions.

Originality/value

This paper presents a framework to quantify the impacts of the 2020 extreme flood event using available data and spatial analysis techniques in support of flood risk management activities.
Hybrid filter detection network model for secondary user transmission in cognitive radio networks
Authors: Vijaya Saradhi D. , Katragadda Swetha , Valiveti Hima Bindu
Published: November 2021

Purpose

A huge variety of devices accumulates as well distributes a large quantity of data either with the help of wired networks or wireless networks to implement a wide variety of application scenarios. The spectrum resources on the other hand become extremely unavailable with the development of communication devices and thereby making it difficult to transmit data on time.

Design/methodology/approach

The spectrum resources on the other hand become extremely unavailable with the development of communication devices and thereby making it difficult to transmit data on time. Therefore, the technology of cognitive radio (CR) is considered as one of the efficient solutions for addressing the drawbacks of spectrum distribution whereas the secondary user (SU) performance is significantly influenced by the spatiotemporal instability of spectrum.

Findings

As a result, the technique of the hybrid filter detection network model (HFDNM) is suggested in this research work under various SU relationships in the networks of CR. Furthermore, a technique of hybrid filter detection was recommended in this work to enhance the performance of idle spectrum applications. When compared to other existing techniques, the suggested research work achieves enhanced efficiency with respect to both throughputs as well as delay.

Originality/value

The proposed HFDNM improved the transmission delay at 3 SUs with 0.004 s/message and 0.008 s/message when compared with existing NCNC and NNC methods in case of number of SUs and also improved 0.02 s/message and 0.08 s/message when compared with the existing methods of NCNC and NNC in case of channel loss probability at 0.3.