bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural stemness unifies cell tumorigenicity and pluripotent differentiation potential
Authors: Zhang Min , Liu Yang , Shi Lihua , Fang Lei , Xu Liyang , Cao Ying
Published: December 2021

Tumorigenicity and pluripotent differentiation potential are kernel cell properties for tumorgenesis and embryogenesis. A growing number of studies have demonstrated that neural stemness is the source of the two cell properties, because neural stem cells and cancer cells share cell features and regulatory networks and neural stemness has an evolutionary advantage. However, it needs to validate whether neural stemness is a cell property that would unify tumorigenicity and pluripotent differentiation potential. SETDB1/Setdb1 is an epigenetic factor that is upregulated in cancer cells and promotes cancers, and correspondingly, is enriched in embryonic neural cells during vertebrate embryogenesis. We show that knockdown of SETDB1/Setdb1 led to neuronal differentiation in neural stem and cancer cells, concomitant with reduced tumorigenicity and pluripotent differentiation potential in these cells; whereas overexpression caused an opposite effect. On one hand, SETDB1 maintains a regulatory network comprised of proteins involved in developmental programs and basic cellular functional machineries, including epigenetic modifications (EZH2), ribosome biogenesis (RPS3), translation initiation (EIF4G), spliceosome assembly (SF3B1), etc., all of which play active roles in cancers. On the other, it represses transcription of genes promoting differentiation and cell cycle and growth arrest. Moreover, neural stemness, tumorigenicity and pluripotent differentiation potential were simultaneously enhanced during serial transplantation of cancer cells. Expression of proteins involved in developmental programs and basic cellular functional machineries, including SETDB1 and other proteins above, was gradually increased. In agreement with increased expression of spliceosome proteins, alternative splicing events also increased in tumor cells derived from later transplantations, suggesting that different machineries should work concertedly to match the status of high proliferation and pluripotent differentiation potential. The study presents the evidence that neural stemness unifies tumorigenicity and differentiation potential. Tumorigenesis represents a process of gradual loss of original cell identity and gain of neural stemness in somatic cells, which might be a distorted replay of neural induction during normal embryogenesis.
The Kishony Mega-Plate Experiment, a Markov Process
Authors: Kleinman Alan
Published: December 2021

A correct understanding of the DNA evolution of drug resistance is critical in developing strategies for suppressing and preventing this process. The Kishony Mega-Plate Experiment demonstrates this important phenomenon that occurs in the practice of medicine, that of the evolution of drug-resistance. The evolutionary process which the bacteria in this experiment are doing is called a Markov Process or Markov Chain. Understanding this process enables clinicians and researchers to predict the evolution of drug-resistance and develop strategies to prevent this process. This paper will show how to apply the Markov Chain model of DNA evolution to the Kishony Mega-Plate Experiment and why the experiment behaves the way it does by contrasting the Jukes-Cantor model of DNA evolution (a stationary model) with a modification of the Jukes-Cantor model that makes it a non-stationary, non-equilibrium Markov Chain. The numerical behaviors of the stationary and non-stationary models are compared. What this analysis shows is that DNA evolution is a non-stationary, non-equilibrium process and that by using the correct non-stationary, non-equilibrium model that one can simulate and predict the behavior of real evolutionary examples and that these analytical tools can give the clinician guidance on how to use antimicrobial selection pressures for treating infectious diseases. This in turn can help reduce the numbers and costs of hospitalization for sepsis, pneumonia and other infectious diseases.
PERIOD phosphoclusters control temperature compensation of the Drosophila circadian clock
Authors: Joshi Radhika , Cai Yao D. , Xia Yongliang , Chiu Joanna C. , Emery Patrick
Published: December 2021

Temperature compensation is a critical feature of circadian rhythms, but how it is achieved remains elusive. Here, we uncovered the important role played by the Drosophila PERIOD (PER) phosphodegron in temperature compensation. Using CRISPR-Cas9, we introduced a series of mutations that altered three Serines (S44, 45 and 47) belonging to the PER phosphodegron, the functional homolog of mammalian PER2’s S487 phosphodegron, which impacts temperature compensation. While all three Serine to Alanine substitutions lengthened period at all temperatures tested, temperature compensation was differentially affected. S44A and S45A substitutions caused decreased temperature compensation, while S47A resulted in overcompensation. These results thus reveal unexpected functional heterogeneity of phosphodegron residues in thermal compensation. Furthermore, mutations impairing phosphorylation of the pers phosphocluster decreased thermal compensation, consistent with its inhibitory role on S47 phosphorylation. Interestingly, the S47A substitution caused increased accumulation of hyper-phosphorylated PER at warmer temperatures. This finding was corroborated by cell culture assays in which S47A resulted in excessive temperature compensation of phosphorylation-dependent PER degradation. Thus, we show a novel role of the PER phosphodegron in temperature compensation through temperature-dependent modulation of the abundance of hyper-phosphorylated PER. Our work also reveals interesting mechanistic convergences and differences between mammalian and Drosophila temperature compensation of the circadian clock.

Author summary

Circadian rhythms are critical adaptive mechanisms that enable most organisms to adjust their physiology and behavior to the changes that occur in their environment every day. Ambient temperature varies constantly, but interestingly molecular circadian pacemakers do not accelerate with increasing temperature, while most biochemical reactions are sensitive to temperature. This phenomenon of circadian temperature compensation is poorly understood. Using genome editing and transgenic approaches, we found that two phosphorylated motifs in the Drosophila PERIOD protein, which regulate stability, impact temperature compensation. Moreover, we observed that mutation of a key Serine residue controlling PER degradation, S47, affects the accumulation of phosphorylated PER in a temperature-dependent manner, and causes PER degradation kinetics to become overly protected from increased temperature. As a result, the circadian clock of S47 mutant flies is excessively temperature-compensated. Our work thus reveals an interesting mechanism that controls temperature compensation in Drosophila. Moreover, comparison with mammals reveal interesting similarities, but also important differences in how temperature compensation of the circadian clock is achieved.
Novel allosteric mechanism of dual p53/MDM2 and p53/MDM4 inhibition by a small molecule
Authors: Grinkevich Vera V. , Aparna Vema , Fawkner Karin , Issaeva Natalia , Andreotti Virginia , Dickinson Eleanor R. , Hedström Elisabeth , Spinnler Clemens , Inga Alberto , Larsson Lars-Gunnar , Karlén Anders , Wilhelm Margareta , Barran Perdita E. , Okorokov Andrei L. , Selivanova Galina , Zawacka-Pankau Joanna E.
Published: December 2021

Restoration of the p53 tumor suppressor for personalised cancer therapy is a promising strategy. However, high-affinity MDM2 inhibitors have shown substantial side effects in clinical trials. Thus, elucidation of the molecular mechanisms of action of p53 reactivating molecules with alternative functional principle is of the utmost importance.

Here, we report a discovery of a novel allosteric mechanism of p53 reactivation through targeting the p53 N-terminus which blocks both p53/MDM2 and p53/MDM4 interactions. Using biochemical assays and molecular docking, we identified the binding site of two p53 reactivating molecules, RITA and protoporphyrin IX (PpIX). Ion-mobility mass spectrometry revealed that the binding of RITA to serine 33 and serine 37 is responsible for inducing the allosteric shift in p53, which shields the MDM2 binding residues of p53 and prevents its interactions with MDM2 and MDM4. Our results point to an alternative mechanism of blocking p53 interaction with MDM2 and MDM4 and may pave the way for the development of novel allosteric inhibitors of p53/MDM2 and p53/MDM4 interactions.

Contribution to the field

Given the immense importance of the p53 tumor suppressor for cancer, efforts have been made to identify p53 activators, which sterically inhibit MDM2. Because high-affinity MDM2 inhibitors are facing problems with considerable side effects, other approaches are needed to reactivate p53 for improved cancer therapy. The allosteric mechanism of action of p53 activator RITA, which we discovered, and its dependence on the oncogenic switch, is an unexpected turn in the p53 story. Our findings provide a basis for the development of p53 activators with a similar mode of functioning, either through the classical drug discovery route or through the drug repurposing approach. Allosteric modulators might have great potential as single agents, or in combination with the standard of care. Further, p53 modulators could serve as invaluable tools to better understand its biology.
SpaceX: Gene Co-expression Network Estimation for Spatial Transcriptomics
Authors: Acharyya Satwik , Zhou Xiang , Baladandayuthapani Veerabhadran
Published: December 2021

Motivation

The analysis of spatially-resolved transcriptome enables the understanding of the spatial interactions between the cellular environment and transcriptional regulation. In particular, the characterization of the gene-gene co-expression at distinct spatial locations or cell types in the tissue enables delineation of spatial co-regulatory patterns as opposed to standard differential single gene analyses. To enhance the ability and potential of spatial transcriptomics technologies to drive biological discovery, we develop a statistical framework to detect gene co-expression patterns in a spatially structured tissue consisting of different clusters in the form of cell classes or tissue domains.

Results

We develop SpaceX (spatially dependent gene co-expression network), a Bayesian methodology to identify both shared and cluster-specific co-expression network across genes. SpaceX uses an over-dispersed spatial Poisson model coupled with a high-dimensional factor model which is based on a dimension reduction technique for computational efficiency. We show via simulations, accuracy gains in co-expression network estimation and structure by accounting for (increasing) spatial correlation and appropriate noise distributions. In-depth analysis of two spatial transcriptomics datasets in mouse hypothalamus and human breast cancer using SpaceX, detected multiple hub genes which are related to cognitive abilities for the hypothalamus data and multiple cancer genes (e.g. collagen family) from the tumor region for the breast cancer data.

Availability and implementation

The SpaceX R-package is available at github.com/bayesrx/SpaceX.

Contact

xzhousph@umich.edu, veerab@umich.edu

Supplementary information

Supplementary data are available at bookdown.org/satwik91/SpaceX_supplementary/.
Anticancer immunotherapies transition postcapillary venules into high-endothelial venules that generate TCF1+ T lymphocyte niches through a feed-forward loop
Authors: Hua Yichao , Vella Gerlanda , Rambow Florian , Allen Elizabeth , Martinez Asier Antoranz , Duhamel Marie , Junius Steffie , Smeets Ann , Nittner David , Laoui Damya , Dimmeler Stefanie , Hehlgans Thomas , Liston Adrian , Floris Guiseppe , Lambrechts Diether , Merchiers Pascal , Bosisio Francesca Maria , Marine Jean-Christophe , Schlenner Susan , Bergers Gabriele
Published: December 2021

The lack of T-cell infiltrates is a major obstacle to effective immunotherapy in cancer. Conversely, the formation of tumor-associated tertiary-lymphoid-like structures (TA-TLS), which are the local site of humoral and cellular immune responses against cancers, are associated with good prognosis and have recently been detected in Immune Checkpoint Blockade (ICB)-responding patients. However, how these lymphoid aggregates develop remains poorly understood. By employing scRNA sequencing, endothelial fate mapping, and functional multiplex immune profiling, we demonstrate that antiangiogenic immune-modulating therapies evoke the transition of postcapillary venules into inflamed high endothelial venules (HEVs), which generate permissive TA-TLS-like lymphocyte niches with PD1negand PD1+TCF1+CD8 T cell progenitors that differentiate into GrzB+TCF1negTIM3+PD1+CD8 T effector cells. Tumor-HEVs require continuous CD8 and NK cell-derived lymphotoxin signals revealing that tumor-HEV maintenance is actively sculpted by the adaptive immune system through a feed-forward loop.

In Brief

Hua & Vella et al. reveal that effective antiangiogenic immunotherapy transitions postcapillary venules into inflamed high-endothelial venules (HEV), sustained by CD8 T and NK cell-derived signals through a feed-forward loop. Thereby, tumoral HEVs establish perivascular niches in which TCF1+PD1+ lymphocytes expand and produce cytolytic PD1+ TIM3+ CD8 T cells that facilitate anti-tumoral immunity.

Highlights

High endothelial venule induction by anticancer immunotherapies generates perivascular immune niches permissive for TCF1+PD1+CD8 progenitor T cell expansion and production of TCF1negPD1+TIM3+CD8 effector T cells

Tumoral high-endothelial venules exhibit characteristics of inflamed lymph node HEVs and postcapillary venules

Postcapillary venules dynamically transdifferentiate into high-endothelial venules in tumors, which requires continuous signals from surrounding immune cells

CD8 and NK cells drive tumoral high-endothelial venule formation during antiangiogenic immunotherapies in a feed-forward loop via lymphotoxin beta receptor signaling
MEMO: Mass Spectrometry-based Sample Vectorization to Explore Chemodiverse Datasets
Authors: Gaudry Arnaud , Huber Florian , Nothias Louis-Félix , Cretton Sylvian , Kaiser Marcel , Wolfender Jean-Luc , Allard Pierre-Marie
Published: December 2021

In natural products research, chemodiverse extracts coming from multiple organisms are explored for novel bioactive molecules, sometimes over extended periods. Samples are usually analyzed by liquid chromatography coupled with fragmentation mass spectrometry to acquire informative mass spectral ensembles. Such data is then exploited to establish relationships among analytes or samples (e.g. via molecular networking) and annotate metabolites. However, the comparison of samples profiled in different batches is challenging with current metabolomics methods. Indeed, the experimental variation - changes in chromatographical or mass spectrometric conditions - often hinders the direct comparison of the profiled samples. Here we introduce MEMO - MS2 BasEd SaMple VectOrization - a method allowing to cluster large amounts of chemodiverse samples based on their LC-MS/MS profiles in a retention time agnostic manner. This method is particularly suited for heterogeneous and chemodiverse sample sets. MEMO demonstrated similar clustering performance as state-of-the-art metrics taking into account fragmentation spectra. More importantly, such performance was achieved without the requirement of a prior feature alignment step and in a significantly shorter computational time. MEMO thus allows the comparison of vast ensembles of samples, even when analyzed over long periods of time, and on different chromatographic or mass spectrometry platforms. This new addition to the computational metabolomics toolbox should drastically expand the scope of large-scale comparative analysis.

Abstract Figure
A personalizable autonomous neural mass model of epileptic seizures
Authors: Lopez-Sola Edmundo , Sanchez-Todo Roser , Lleal Èlia , Köksal-Ersöz Elif , Yochum Maxime , Makhalova Julia , Mercadal Borja , Guasch-Morgades Maria , Salvador Ricardo , Lozano-Soldevilla Diego , Modolo Julien , Bartolomei Fabrice , Wendling Fabrice , Benquet Pascal , Ruffini Giulio
Published: December 2021

Work in the last two decades has shown that neural mass models (NMM) can realistically reproduce and explain epileptic seizure transitions as recorded by electrophysiological methods (EEG, SEEG). In previous work, advances were achieved by increasing excitation and heuristically varying network inhibitory coupling parameters in the models. Based on these early studies, we provide a laminar NMM capable of realistically reproducing the electrical activity recorded by SEEG in the epileptogenic zone during interictal to ictal states. With the exception of the external noise input into the pyramidal cell population, the model dynamics are autonomous. By setting the system at a point close to bifurcation, seizure-like transitions are generated, including pre-ictal spikes, low voltage fast activity, and ictal rhythmic activity. A novel element in the model is a physiologically motivated algorithm for chloride dynamics: the gain of GABAergic post-synaptic potentials is modulated by the pathological accumulation of chloride in pyramidal cells due to high inhibitory input and/or dysfunctional chloride transport. In addition, in order to simulate SEEG signals for comparison with real seizure recordings, the NMM is embedded first in a layered model of the neocortex and then in a realistic physical model. We compare modelling results with data from four epilepsy patient cases. By including key pathophysiological mechanisms, the proposed framework captures succinctly the electrophysiological phenomenology observed in ictal states, paving the way for robust personalization methods based on NMMs.
Quantitative T1-relaxation corrected metabolite mapping of 12 metabolites in the human brain at 9.4 T
Authors: Wright Andrew Martin , Murali-Manohar Saipavitra , Henning Anke
Published: December 2021

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive imaging modality that enables observation of metabolites. Applications of MRSI for neuroimaging applications has shown promise for monitoring and detecting various diseases. This study builds off previously developed techniques of short TR, 1H FID MRSI by correcting for T1-weighting of the metabolites and utilizing an internal water reference to produce quantitative (mmol kg−1) metabolite maps. This work reports and shows quantitative metabolite maps for 12 metabolites for a single slice. Voxel-specific T1-corrections for water are common in MRSI studies; however, most studies use either averaged T1-relaxation times to correct for T1-weighting of metabolites or omit this correction step entirely. This work employs the use of voxel-specific T1-corrections for metabolites in addition to water. Utilizing averaged T1-relaxation times for metabolites can bias metabolite maps for metabolites that have strong differences between T1-relaxation for GM and WM (i.e. Glu). This work systematically compares quantitative metabolite maps to single voxel quantitative results and qualitatively compares metabolite maps to previous works.

Highlights

Quantitative metabolite maps of 12 metabolites human brains acquired at 9.4 T.

Voxel-specific T1-weighting corrections for water and metabolites.

Comparisons of T1-weighted and T1-corrected metabolite maps.
Chaperoning of the histone octamer by the acidic domain of DNA repair factor APLF
Authors: Corbeski Ivan , Guo Xiaohu , Eckhardt Bruna V. , Fasci Domenico , Wiegant Wouter , Graewert Melissa A. , Vreeken Kees , Wienk Hans , Svergun Dmitri I. , Heck Albert J.R. , van Attikum Haico , Boelens Rolf , Sixma Titia K. , Mattiroli Francesca , van Ingen Hugo
Published: December 2021

Nucleosome assembly requires the coordinated deposition of histone complexes H3-H4 and H2A-H2B to form a histone octamer on DNA. In the current paradigm, specific histone chaperones guide the deposition of first H3-H4 and then H2A-H2B(1–5). Here, we show that the acidic domain of DNA repair factor APLF (APLFAD) can assemble the histone octamer in a single step, and deposit it on DNA to form nucleosomes. The crystal structure of the APLFAD–histone octamer complex shows that APLFAD tethers the histones in their nucleosomal conformation. Mutations of key aromatic anchor residues in APLFAD affect chaperone activity in vitro and in cells. Together, we propose that chaperoning of the histone octamer is a mechanism for histone chaperone function at sites where chromatin is temporarily disrupted.

one sentence summary

Histone chaperone APLF assembles histones H2A-H2B/H3-H4 into histone octamers to deposit them onto DNA and form nucleosomes.
Hemocyte Differentiation to the Megacyte Lineage Enhances Mosquito Immunity Against Plasmodium
Authors: Barletta Ferreira Ana Beatriz , Saha Banhisikha , Trisnadi Nathanie , Talyuli Octavio , Raddi Gianmarco , Barillas-Mury Carolina
Published: December 2021

Silencing Cactus, a suppressor of Toll signaling, in Anopheles gambiae, eliminates Plasmodium ookinetes by enhancing local release of hemocyte-derived microvesicles that promote activation of the mosquito complement-like system. We report that Cactus silencing dramatically increases the proportion of megacytes, a new effector hemocyte subpopulation of large granulocytes, from 5 to 79% of circulating granulocytes. Transcriptomic and morphological analysis, as well as cell counts, in situ hybridization and expression of cell-specific markers, indicate that Cactus silencing triggers granulocyte differentiation into megacytes, a process mediated by the Rel1 transcription factor of the Toll pathway. Megacytes are very plastic cells that can extend long filopodia, tend to form clusters in vivo, and are massively recruited to the basal midgut surface in response to bacterial feeding and Plasmodium infection. We show that hemocyte differentiation to the megacyte lineage greatly enhances mosquito immunity against Plasmodium.
Systemic influences of mammary cancer on monocytes in mice
Authors: Robinson A , Burgess M , Webb S , Louwe PA , Ouyang Z , Skola D , Han CZ , Batada NN , González-Huici V , Cassetta L , Glass CK , Jenkins SJ , Pollard JW
Published: December 2021

There is a growing body of evidence that cancer causes systemic changes. These influences are most evident in the bone marrow and blood, particularly the myeloid compartment. Here we show using mouse models of breast cancer caused by the mammary epithelial expression of the Polyoma middle T antigen that there is an increase in the number of circulating and splenic monocytes. In the circulation, cancer does not affect ratios of classical to non-classical populations monocytes nor their halflives. Single cell RNA sequencing also indicates that cancer does not induce any new monocyte populations. In the bone marrow cancer does not change monocytic progenitor number is unaffected but the proliferation rate of monocytes is higher thus providing an explanation for expansion in the circulating number. Deep RNA sequencing of these monocytic populations reveals cancer causes changes in the classical monocyte compartment with changes evident in bone marrow monocytes but more in the blood suggesting influences in both compartments. Down regulation of interferon type 1 signalling and antigen presentation were the most prominent. Consistent with this analysis down regulated genes are enriched with STAT1/STAT2 binding sites in their promoter, transcription factors required for type 1 interferon signalling. However, these transcriptome changes in mice did not replicate those found in patients with breast cancer. Consequently, mouse models of cancer may be insufficient to study the systemic influences of human cancer.
Phenotyping single-cell motility in microfluidic confinement
Authors: Bentley Samuel A. , Anagnostidis Vasileios , Schlogelhofer Hannah Laeverenz , Gielen Fabrice , Wan Kirsty Y.
Published: December 2021

At all scales, the movement patterns of organisms serve as dynamic read-outs of their behaviour and physiology. We devised a novel droplet microfluidics assay to encapsulate single algal microswimmers inside closed arenas, and comprehensively studied their roaming behaviour subject to a large number of environmental stimuli. We compared two model species,Chlamydomonas reinhardtii(freshwater alga, 2 cilia), andPyramimonas octopus(marine alga, 8 cilia), and detailed their highly-stereotyped behaviours and the emergence of a trio of macroscopic swimming states (smooth-forward, quiescent, tumbling or excitable backward). Harnessing ultralong timeseries statistics, we reconstructed the species-dependent reaction network that underlies the choice of locomotor behaviour in these aneural organisms, and discovered the presence of macroscopic non-equilibrium probability fluxes in these active systems. We also revealed for the first time how microswimmer motility changes instantaneously when a chemical is added to their microhabitat, by inducing deterministic fusion between paired droplets - one containing a trapped cell, and the other, a pharmacological agent that perturbs cellular excitability. By coupling single-cell entrapment with unprecedented tracking resolution, speed and duration, our approach offers unique and potent opportunities for diagnostics, drug-screening, and for querying the genetic basis of micro-organismal behaviour.
LotuS2: An ultrafast and highly accurate tool for amplicon sequencing analysis
Authors: Özkurt Ezgi , Fritscher Joachim , Soranzo Nicola , Ng Duncan Y. K. , Davey Robert P. , Bahram Mohammad , Hildebrand Falk
Published: December 2021

Background

Amplicon sequencing is an established and cost-efficient method for profiling microbiomes. However, many available tools to process this data require both bioinformatics skills and high computational power to process big datasets. Furthermore, there are only few tools that allow for long read amplicon data analysis. To bridge this gap, we developed the LotuS2 (Less OTU Scripts 2) pipeline, enabling user-friendly, resource friendly, and versatile analysis of raw amplicon sequences.

Results

In LotuS2, six different sequence clustering algorithms as well as extensive pre- and post-processing options allow for flexible data analysis by both experts, where parameters can be fully adjusted, and novices, where defaults are provided for different scenarios. We benchmarked three independent gut and soil datasets, where LotuS2 was on average 29 times faster compared to other pipelines - yet could better reproduce the alpha- and beta-diversity of technical replicate samples. Further benchmarking a mock community with known taxa composition showed that, compared to the other pipelines, LotuS2 recovered a higher fraction of correctly identified genera and species (98% and 57%, respectively). At ASV/OTU level, precision and F-score were highest for LotuS2, as was the fraction of correctly reconstructed 16S sequences.

Conclusion

LotuS2 is a lightweight and user-friendly pipeline that is fast, precise and streamlined. High data usage rates and reliability enable high-throughput microbiome analysis in minutes.

Availability

LotuS2 is available from GitHub, conda or via a Galaxy web interface, documented at http://lotus2.earlham.ac.uk/.
Selfee: Self-supervised Features Extraction of animal behaviors
Authors: Jia Yinjun , Li Shuaishuai , Guo Xuan , Hu Junqiang , Xu Xiao-Hong , Zhang Wei
Published: December 2021

Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in laboratories for behavior analysis. However, it has not been achieved to use a fully unsupervised method to extract comprehensive and discriminative features directly from raw behavior video frames for annotation and analysis purposes. Here, we report a self-supervised feature extraction (Selfee) convolutional neural network with multiple downstream applications to process video frames of animal behavior in an end-to-end way. Visualization and classification of the extracted features (Meta-representations) validate that Selfee processes animal behaviors in a comparable way of human understanding. We demonstrate that Meta-representations can be efficiently used to detect anomalous behaviors that are indiscernible to human observation and hint in-depth analysis. Furthermore, time-series analyses of Meta-representations reveal the temporal dynamics of animal behaviors. In conclusion, we present a self-supervised learning approach to extract comprehensive and discriminative features directly from raw video recordings of animal behaviors and demonstrate its potential usage for various downstream applications.
A neural correlate of individual odor preference inDrosophila
Authors: Churgin Matthew A. , Lavrentovich Danylo O. , Smith Matthew A. , Gao Ruixuan , Boyden Edward S. , de Bivort Benjamin
Published: December 2021

Behavior varies even among genetically identical animals raised in the same environment. However, little is known about the circuit or anatomical origins of this individuality. Here, we demonstrate a neural correlate ofDrosophilaodor preference behavior in the olfactory sensory periphery. Namely, idiosyncratic calcium responses in projection neuron (PN) dendrites and densities of the presynaptic protein Bruchpilot in olfactory receptor neuron (ORN) axon terminals correlate with individual preferences in a choice between two aversive odorants. The ORN-PN synapse appears to be a locus of individuality where microscale variation gives rise to idiosyncratic behavior. Simulating microscale stochasticity in ORN-PN synapses of a 3,062 neuron model of the antennal lobe recapitulates patterns of variation in PN calcium responses matching experiments. Conversely, stochasticity in other compartments of this circuit does not recapitulate those patterns. Our results demonstrate how physiological and microscale structural circuit variations can give rise to individual behavior, even when genetics and environment are held constant.
Diverse Protein Architectures and α-N-Methylation Patterns Define Split Borosin RiPP Biosynthetic Gene Clusters
Authors: Imani Aman S. , Lee Aileen R. , Vishwanathan Nisha , de Waal Floris , Freeman Michael F.
Published: December 2021

Borosins are ribosomally synthesized and post-translationally modified peptides (RiPPs) with α-N-methylations installed on the peptide backbone that impart unique properties like proteolytic stability to these natural products. The borosin RiPP family was initially reported only in fungi until our recent discovery and characterization of a Type IV split borosin system in the metal-respiring bacterium Shewanella oneidensis. Here, we used hidden Markov models and sequence similarity networks to identify over 1,600 putative pathways that show split borosin biosynthetic gene clusters are widespread in bacteria. Noteworthy differences in precursor and α-N-methyltransferase open reading frame sizes, architectures, and core peptide properties allow further subdivision of the borosin family into six additional discrete structural types, of which five have been validated in this study.

Abstract Figure
Quality financial inclusion and its determinants in South Africa: evidence from survey data
Authors: Chipunza Kudakwashe Joshua , Fanta Ashenafi
Published: December 2021

Purpose

The study measured quality financial inclusion, a more comprehensive measure of financial inclusion, and examined its determinants at a consumer level in South Africa.

Design/methodology/approach

This study leveraged on FinScope 2015 survey data to compute a quality financial inclusion index using polychoric principal component analysis. Subsequently, a heteroscedasticity consistent ordinary least squares regression model was employed to assess determinants of quality financial inclusion.

Findings

The empirical findings indicated that gender, education, financial literacy, income, location and geographical proximity determine quality financial inclusion. These findings could inform policymakers and financial services providers on how quality financial inclusion can be promoted through tailoring financial products for various socio-demographic groups.

Research limitations/implications

Due to data limitations, the study was confined to South Africa and did not capture digital financial inclusion. Hence, future studies could replicate the study in Sub-Saharan Africa's context and compute an index that captures digital financial inclusion.

Practical implications

These findings could inform policymakers and financial services providers on how quality financial inclusion can be promoted through tailoring financial products for various socio-demographic groups.

Originality/value

This study proposed a more comprehensive measure of quality financial inclusion from a demand-side perspective by accounting for important dimensions that include diversity, affordability, appropriateness and flexibility of financial products and services.
Analysis on the related factors of China's technological innovation ability using greyness relational degree
Authors: Li Li , Li Xican
Published: December 2021

Purpose

In order to make grey relational analysis applicable to the interval grey number, this paper discusses the model of grey relational degree of the interval grey number and uses it to analyze the related factors of China's technological innovation ability.

Design/methodology/approach

First, this paper gives the definitions of the lower bound domain, the value domain, the upper bound domain of interval grey number and the generalized measure and the generalized greyness of interval grey number. Then, based on the grey relational theory, this paper proposes the model of greyness relational degree of the interval grey number and analyzes its relationship with the classical grey relational degree. Finally, the model of greyness relational degree is applied to analyze the related factors of China's technological innovation ability.

Findings

The results show that the model of greyness relational degree has strict theoretical basis, convenient calculation and easy programming and can be applied to the grey number sequence, real number sequence and grey number and real number coexisting sequence. The relational order of the four related factors of China's technological innovation ability is research and development (R&D) expenditure, R&D personnel, university student number and public library number, and it is in line with the reality.

Practical implications

The results show that the sequence values of greyness relational degree have large discreteness, and it is feasible and effective to analyze the related factors of China's technological innovation ability.

Originality/value

The paper succeeds in realizing both the model of greyness relational degree of interval grey number with unvalued information distribution and the order of related factors of China's technological innovation ability.
Investigating the climate-adaptive design strategies of residential earth-sheltered buildings in Iran
Authors: Mirabi Elahe , Akrami Abarghuie Fatemeh
Published: December 2021

Purpose

The earth-sheltered building is an adaptive strategy reducing energy consumption as well as increasing thermal comfort of the residents. Although this idea historically implemented in the city of Yazd, Iran, its effects on thermal comfort have not been studied thoroughly. This paper aims to discuss and analyze energy performance, in terms of parameters such as orientation, underground depth, nocturnal ventilation and its subsequent effects on thermal comfort in earth-sheltered buildings in Yazd.

Design/methodology/approach

Using EnergyPlus software, the obtained numeric data are precisely modeled, simulated and analyzed.

Findings

Results show that there is a direct relationship between depth of construction and energy consumption savings. The more construction depth of earth-sheltered buildings, the more percentage of energy consumption savings, that is of a higher rate in comparison to the aboveground ones. However, in south orientation, energy saving significantly reduces from depth of 2 m downwards and the annual indoor temperature fluctuation decreases by 50%. This subsequently yields to experiencing indoor thermal comfort for a significant number of days throughout the year. Considering the effects of orientation factor, the south orientation regardless of the depth provides the most desired outcome regarding energy savings.

Originality/value

Simulating the model generalized to the sunken courtyard can approve that the results of this research can be applied to the other models.
Cash holding and performance analysis of mutual funds: a case of an emerging financial market
Authors: Khan Faisal , Shah Syed Hamid Ali , Bangash Romana
Published: December 2021

Purpose

This study is about the determinants of cash holding and impact of cash holding on mutual funds’ performance. In addition, the study analyzes the impact of performance-related determinants of cash holding on funds' performance.

Design/methodology/approach

Panel data of ten years of 190 open-end mutual funds are analyzed through fixed effect regression technique. The risk-adjusted funds' performance of cash based portfolios is computed through capital asset pricing model (CAPM) (1964), Fama and French (1993) and Carhart (1997) models.

Findings

The results indicate that small size funds, high charging front-end load funds, high turnover ratio funds, high 12-month fund returns run up, high dividend paying funds and high redemption level funds hold more cash for precautionary purpose to avoid costs of cash short-falls. Further, monthly average raw returns and risk-adjusted performance of funds with the lowest raw and residual cash holding are found higher than the funds with the highest cash holding. An increase in cash is found to dilute performance.

Originality/value

This is a pioneer study in a corporate environment with shallow capital market, reliance of businesses on bank credit, firms exposed to agency issues, wealth expropriations and existence of business groups with political linkages but with opportunities of investments due to expected favorable geo-socio-political situation. The study generates outcomes relevant for other similar economies.
Asymmetric financial reporting quality and firm size: conditional evidence from an emerging market
Authors: Saji T.G.
Published: December 2021

Purpose

The mandatory adoption/convergence of IFRS has increased the information quality of reported earnings in equity markets across the globe. The purpose of the study is to explore whether the mandatory convergence of Indian Accounting Standards (Ind AS) with International Financial Reporting Standards (IFRS) affect the financial reporting quality of listed firms in India.

Design/methodology/approach

The sample includes 355 non-financial publicly listed firms on National Stock Exchange (NSE) of India with 1,065 firm-year observations. The authors use models similar to Jones (1991), and DeFond and Jiambalvo (1994) to investigate value relevance in the period “1st January 2017 to 31st December 2019”. The study uses the quantile regression (QR) analysis to verify our hypothesis.

Findings

The findings suggest that IFRS convergence process adds value to accounting quality of reported earnings in Indian stock market. The authors' QR estimations produce collaborating evidence on the uneven impact of IFRS across quantiles and the financial reporting quality skewed in favour of investors of high-valued firms.

Research limitations/implications

The effects of convergence with IFRS in value relevance of financial statements could be reinforced by considering alternate accrual models and incorporating more accounting measures on an expanded sample of stocks from several global markets.

Practical implications

Presently, convergence of local accounting standards to IFRS in India is only partial. The findings may produce useful insights for regulators and standard setters to further increase the value relevance of financial reports whilst they move towards full convergence.

Originality/value

The study explores the information quality of reported earnings of Indian listed firms in post-IFRS convergence period, which is not properly investigated in the literature. Moreover, the research is unique in terms of applying QR estimations to examine the value relevance of IFRS-converged financial reporting from the emerging market perspective.
Does the short squeeze lead to market abnormality and antileverage effect? Evidence from the Gamestop case
Authors: Vasileiou Evangelos
Published: December 2021

Purpose

This study examines the Gamestop (GME) short squeeze in early 2021. Using intraday data for the period 4/1/2021–5/2/2021, the author provides empirical evidence that the GME stock price exhibited abnormal behavior.

Design/methodology/approach

The author uses the popular Runs test to show that the GME returns were not randomly distributed, which is an indication of a violation of the Efficient Market Hypothesis (EMH). The main objective of the paper is to provide new quantitative evidence that stock returns are abnormal when short squeeze conditions emerge. The author employs the asymmetry Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) models (the Exponential GARCH (EGARCH) and the Threshold GARCH (TGARCH)) and provides evidence that an exceptional time series feature emerged during the examined period: the antileverage effect.

Findings

The results show that the GME returns were not randomly distributed during the examined period and the asymmetry GARCH models indicate that, in contrast to what the time series normally show, volatility increased when the GME prices increased.

Research limitations/implications

This paper presents a new/alternative approach for the study of EMH and abnormal returns in financial markets. Further studies on market performance during similar short squeeze conditions should be carried out in order to obtain empirical evidence for the antileverage effect abnormality.

Practical implications

This paper could be useful for scholars who examine the EMH in financial markets because it suggests an additional method for testing abnormalities. It also presents a useful tool that allows practitioners to monitor for indications of abnormality in the stock market during a short squeeze, since the emergence of the antileverage abnormality could function as such an indication. Additionally, the outcome of this analysis could be useful for regulators because coordination among investors is easier than ever in the Internet era and such events may happen again in the future; even under normal (not short squeeze) conditions and lead to market instability.

Originality/value

This research differs from other studies that examine the GME case because it presents a new way to quantitatively present the abnormal performance of the stock markets for reasons that could be linked with the emergence of short squeeze conditions.
A literature review of leadership training and a novel conceptual model of leader-member exchange theory for new dentists
Authors: Danesh David O. , Huber Thomas P.
Published: December 2021

Purpose

The purpose of the paper is to describe the current state of leadership and leader–member exchange (LMX) theory in dentistry and develop a novel conceptual model of LMX to guide future research and highlight the importance of enhancing leadership training for new dentists.

Design/methodology/approach

A literature review exploring leadership in dentistry and LMX in dentistry was completed. The findings were analyzed with framework analysis to develop a novel conceptual model of LMX specific to dentistry.

Findings

LMX theory was applied to leadership in dentistry, including a focus on new dentists, senior dentists, other dental team members and the patient. A new conceptual model of the New Dentist LMX Quartet, which is unique and specific to new dentist teams, was developed.

Research limitations/implications

The study identifies the need for research in LMX in dentistry, contributes a new conceptual model for LMX theory and identifies future research.

Practical implications

Practitioners, policymakers and educators can utilize this information to explore concepts in leadership and improve training and dental practice.

Originality/value

No other studies specifically exploring LMX in dentistry for new dentists exist. The current literature review and conceptual paper begins the conversation on developing understanding of leadership in dentistry through further research.
Assessing Industry 4.0 readiness in manufacturing: a self-diagnostic framework and an illustrative case study
Authors: Ramanathan Krishnamurthy , Samaranayake Premaratne
Published: December 2021

Purpose

The purpose of this paper is to present an Industry 4.0 Readiness Assessment Framework (I4.0RAF) and demonstrate its applicability and practical relevance through a case study of a large manufacturing firm in an emerging economy.

Design/methodology/approach

The research firstly involved a synthesis of recent literature for the identification of important determinants, and their constituent criteria, for assessing the readiness of a manufacturing firm to transition to an Industry 4.0 setting and structuring them into a readiness assessment framework that can be used as a self-diagnostic tool. The framework was illustrated through a case study. The empirical findings of readiness assessment are validated using semi-structured interviews of senior management of the organization.

Findings

The proposed I4.0RAF was found to be a practically applicable self-diagnostic tool that can be used to assess a firm's readiness to transition to an Industry 4.0 setting with respect to eight important determinants. Cross-functional participation in the assessment helped the organization to determine priorities and interdependencies among the determinants.

Research limitations/implications

The determinants and their constituent criteria can be further streamlined using inputs from practitioners, consultants and academics.

Practical implications

The findings demonstrate the interdependencies between the determinants, help to delineate interventions that can lead to synergistic outcomes and enabls planning to achieve higher levels of Industry 4.0 maturity.

Originality/value

A self-diagnostic tool as a basis for an informed discussion on transitioning to an Industry 4.0 setting is presented and illustrated through a case study in an emerging economy.
Predictors of third-person perceptions about media's influence on vaccination against COVID-19
Authors: Buturoiu Raluca , Vladu Loredana , Durach Flavia , Dumitrache Alexandru
Published: December 2021

Purpose

The present study aims to unveil the main predictors of perceived media influence (the third-person effect (TPE)) on people's opinions towards COVID-19 vaccination. While the TPE has been researched before in medical contexts, predictors of TPE on the topic of vaccination against COVID-19 are understudied.

Design/methodology/approach

This study employs a national survey using an online panel (N = 945) representative for the online population of Romania aged 18 or higher; data were collected during 1–9 April 2021.

Findings

Results indicate that people perceive both close and distant others to be more influenced by media information related to COVID-19 vaccination topics. TPE perception is correlated with belief in conspiracy theories about vaccines/vaccination, perceived incidence of fake news about COVID-19 vaccines/vaccination, perceived usefulness of social networking sites and critical thinking.

Originality/value

Results from this study might explain the success rate of some communication strategies employed with the help of the media. Key findings could be used as starting points for understanding the profile of those who underestimate the media's impact on themselves with respect to COVID-19 immunization and for designing more successful media strategies.