bluuebunny/crossref_metadata_2025 huggingface dataset:
A screening pipeline identifies a broad-spectrum inhibitor of bacterial AB toxins with cross protection against influenza A virus H1N1 and SARS-CoV-2
Authors: Wu Yu , Mahtal Nassim , Swistak Léa , Sagadiev Sara , Acharya Mridu , Demeret Caroline , van der Werf Sylvie , Guivel-Benhassine Florence , Schwartz Olivier , Petracchini Serena , Mettouchi Amel , Paillares Eléa , Caramelle Lucie , Couvineau Pierre , Thai Robert , Barbe Peggy , Keck Mathilde , Brodin Priscille , Machelart Arnaud , Sencio Valentin , Trottein François , Sachse Martin , Chicanne Gaëtan , Payrastre Bernard , Ville Florian , Kreis Victor , Popoff Michel-Robert , Johannes Ludger , Cintrat Jean-Christophe , Barbier Julien , Gillet Daniel , Lemichez Emmanuel
Published: August 2021

A challenge for the development of host-targeted anti-infectives against a large spectrum of AB-like toxin-producing bacteria encompasses the identification of chemical compounds corrupting toxin transport through both endolysosomal and retrograde pathways. Here, we performed a high-throughput screening of small chemical compounds blocking active Rac1 proteasomal degradation triggered by the Cytotoxic Necrotizing Factor-1 (CNF1) toxin, followed by orthogonal screens against two AB toxins hijacking defined endolysosomal (Diphtheria toxin) or retrograde (Shiga-like toxin 1) pathways to intoxicate cells. This led to the identification of the molecule N-(3,3-diphenylpropyl)-1-propyl-4-piperidinamine, referred to as C910. This compound induces the swelling of EEA1-positive early endosomes, in absence of PIKfyve kinase inhibition, and disturbs the trafficking of CNF1 and the B-subunit of Shiga toxin along the endolysosomal or retrograde pathways, respectively. Together, we show that C910 protects cells against 8 bacterial AB toxins including large clostridial glucosylating toxins from Clostridium difficile. Of interest, C910 also reduced viral infection in vitro including influenza A virus subtype H1N1 and SARS-CoV-2. Moreover, parenteral administration of C910 to the mice resulted in its accumulation in lung tissues and reduced lethal influenza infection.
Pairwise Relative Distance (PRED) is an intuitive and robust metric for assessing vector similarity and class separability
Authors: Mittal Aarush Mohit , Lin Andrew C. , Gupta Nitin
Published: August 2021

Scientific studies often require assessment of similarity between ordered sets of values. Each set, containing one value for every dimension or class of data, can be conveniently represented as a vector. The commonly used metrics for vector similarity include angle-based metrics, such as cosine similarity or Pearson correlation, which compare the relative patterns of values, and distance-based metrics, such as the Euclidean distance, which compare the magnitudes of values. Here we evaluate a newly proposed metric, pairwise relative distance (PRED), which considers both relative patterns and magnitudes to provide a single measure of vector similarity. PRED essentially reveals whether the vectors are so similar that their values across the classes are separable. By comparing PRED to other common metrics in a variety of applications, we show that PRED provides a stable chance level irrespective of the number of classes, is invariant to global translation and scaling operations on data, has high dynamic range and low variability in handling noisy data, and can handle multi-dimensional data, as in the case of vectors containing temporal or population responses for each class. We also found that PRED can be adapted to function as a reliable metric of class separability even for datasets that lack the vector structure and simply contain multiple values for each class.
Changes in resting state functional connectivity associated with dynamic adaptation of wrist movements
Authors: Farrens Andria J. , Vahdat Shahabeddin , Sergi Fabrizio
Published: August 2021

Dynamic adaptation is an error-driven process of adjusting planned motor actions to changes in task dynamics (1). Adapted motor plans are consolidated into motor memories that contribute to better performance on re-exposure to the same dynamic condition. In parallel, dynamic perturbations can be compensated for by alternate motor control processes, such as co-contraction, that contribute to error reduction (2). Whether these control strategies share the same neural resources for memory formation is unclear. To address this gap in knowledge, we used a novel fMRI-compatible wrist robot, the MR-SoftWrist (3), to identify neural processes specific to dynamic adaptation and subsequent memory formation. Using the MR-SoftWrist, we acquired fMRI during a motor performance and a dynamic perturbation task to localize brain networks of interest. Resting state fMRI scans were acquired immediately before and after task performance to quantify changes in resting state functional connectivity (rsFC) within these networks. Twenty-four hours later, we assessed behavioral retention of training. A variance decomposition analysis was used to isolate behavior associated with adaptation versus alternate error reduction strategies. Immediately after the dynamic perturbation task, rsFC significantly increased within the corticothalamic-cerebellar network of the trained wrist and decreased interhemispherically within the cortical sensorimotor network. These changes were associated to behavioral measures of initial acquisition and retention, indicative of memory formation. Variance decomposition analysis revealed that increases within the cortico-thalamic-cerebellar network were associated with adaptation, while interhemispheric decreases in rsFC within the sensorimotor network were associated with alternate error reduction processes.

Significance Statement

Motor memory formation processes have been studied using resting state functional connectivity (rsFC) before and after exposure to adaptation tasks. However, due to technical limitations, previous studies have not investigated rsFC within brain regions localized during task execution, nor quantified rsFC within minutes after task performance. The present study used an fMRI-compatible wrist robot to localize relevant brain regions during dynamic adaptation within the cortico-thalamic-cerebellar network and bilateral sensorimotor network. Immediately following dynamic adaptation, we measured significant changes in rsFC within these networks, that were associated with adaptation behavior and with gains in behavior assessed 24 hours later, indicative of memory formation. Variance decomposition analysis identified distinct rsFC networks associated with adaptation specific processes, and with alternate motor control strategies.
Targeted Reactivation of X-linked Endogenous FOXP3 Gene from X-chromosome Inactivation in Human Female Breast Cancer Cells
Authors: Cui Xuelian , Xu Zhifang , Wang Shuaibin , Li Xin , Stringer-Reasor Erica , Bae Sejong , Zeng Leiping , Zhao Dehua , Liu Runhua , Qi Lei S. , Wang Lizhong
Published: August 2021

Unlike autosomal tumor suppressors, which must be inactivated by a two-hit Knudson mechanism, X-linked tumor suppressors can be inactivated by a single hit due to X-chromosome inactivation (XCI). Here, we argue that targeted reactivation of the non-mutated allele from XCI offers a potential therapy for female breast cancers. Towards this goal, we developed a dual CRISPR interference and activation (CRISPRi/a) approach for simultaneously silencing and reactivating multiple X-linked genes using two orthogonal, nuclease-deficient CRISPR/Cas9 (dCas9) proteins. We verified the efficacy for use of Streptococcus pyogenes (Sp) dCas9-KRAB for silencing XIST and Staphylococcus aureus (Sa) dCas9-VPR for activating FOXP3 in various cell lines of human female breast cancers. We confirmed CRISPR reactivation of the non-mutated copy of FOXP3 from XCI in human breast cancer CRL2316 cells, which express a synonymous heterozygous mutation (p.L266L; c.798G>C) in the coding region of FOXP3. Further, simultaneous silencing of XIST from XCI led to enhanced and prolonged FOXP3 reactivation. We optimized CRISPRa by fusing SadCas9 to the demethylase TET1 and observed enhanced FOXP3 activation. Analysis of the conserved CpG-rich region of FOXP3 intron 1 confirmed that CRISPRi/a-mediated simultaneous FOXP3 activation and XIST silencing were accompanied by elevated H4 acetylation, including H4K5ac, H4K8ac, and H4K16ac, and H3K4me3 and lower DNA methylation. This indicates that CRISPRi/a targeting to XIST and FOXP3 loci alters their transcription and their nearby epigenetic modifications. The simultaneous activation and repression of the X-linked, endogenous FOXP3 and XIST from XCI offers a useful research tool and a potential therapeutic for female breast cancers. This approach also provides new routes of targeted therapy for other X-chromosome-linked genetic disorders.
Estimation of Cross-Species Introgression Rates using Genomic Data Despite Model Unidentifiability
Authors: Yang Ziheng , Flouri Tomáš
Published: August 2021

Full likelihood implementations of the multispecies coalescent with introgression (MSci) model takes the genealogical fluctuation across the genome as a major source of information to infer the history of species divergence and gene flow using multilocus sequence data. However, MSci models are known to have unidentifiability issues, whereby different models or parameters make the same predictions about the data and cannot be distinguished by the data. Previous studies have focused on heuristic methods based on gene trees, and does not make an efficient use of the information in the data. Here we study the unidentifiability of MSci models under the full likelihood methods. We characterize the unidentifiability of the bidirectional introgression (BDI) model, which assumes that gene flow occurs in both directions. We derive simple rules for arbitrary BDI models, which create unidentifiability of the label-switching type. In general, an MSci model with k BDI events has 2k unidentifiable modes or towers in the posterior, with each BDI event between sister species creating within-model parameter unidentifiability and each BDI event between non-sister species creating between-model unidentifiability. We develop novel algorithms for processing Markov chain Monte Carlo (MCMC) samples to remove label-switching problems and implement them in the BPP program. We analyze real and synthetic data to illustrate the utility of the BDI models and the new algorithms. We discuss the unidentifiability of heuristic methods and provide guidelines for the use of MSci models to infer gene flow using genomic data.
Quaternary structure independent folding of voltage-gated ion channel pore domain subunits
Authors: Arrigoni Cristina , Lolicato Marco , Shaya David , Rohaim Ahmed , Findeisen Felix , Colleran Claire M. , Dominik Pawel , Kim Sangwoo S. , Schuermann Jonathan , Kossiakoff Anthony A. , Minor Daniel L.
Published: August 2021

Every voltage-gated ion channel (VGIC) superfamily member has an ion conducting pore consisting of four pore domain (PD) subunits that are each built from a common plan comprising an antiparallel transmembrane helix pair, a short, obliquely positioned helix (the pore helix), and selectivity filter. The extent to which this structure, the VGIC-PD fold, relies on the extensive quaternary interactions observed in PD assemblies is unclear. Here, we present crystal structures of three bacterial voltage-gated sodium channel (BacNav) pores that adopt a surprising set of non-canonical quaternary structures and yet maintain the native tertiary structure of the PD monomer. This context-independent structural robustness demonstrates that the VGIC-PD fold, the fundamental VGIC structural building block, can adopt its native-like tertiary fold independent of native quaternary interactions. In line with this observation, we find that the VGIC-PD fold is not only present throughout the VGIC superfamily and other channel classes but has homologs in diverse transmembrane and soluble proteins. Characterization of the structures of two synthetic Fabs (sFabs) that recognize the VGIC-PD fold shows that such sFabs can bind purified full-length channels and indicates that non-canonical quaternary PD assemblies can occur in the context of complete VGICs. Together, our data demonstrate that the VGIC-PD structure can fold independently of higher-order assembly interactions and suggest that full-length VGIC PDs can access previously unknown non-canonical quaternary states. These PD properties have deep implications for understanding how the complex quaternary architectures of VGIC superfamily members are achieved and point to possible evolutionary origins of this fundamental VGIC structural element.
Lupus Gut Microbiota Transplants Cause Autoimmunity and Inflammation
Authors: Ma Yiyangzi , Guo Ruru , Sun Yiduo , Li Xin , He Lun , Li Zhao , Silverman Gregg J. , Chen Guobing , Gao Feng , Yuan Jiali , Wei Qiang , Li Mengtao , Lu Liangjing , Niu Haitao
Published: August 2021

Background

The etiology of systemic lupus erythematosus (SLE) is multifactorial. Recently, growing evidence suggests that the microbiota plays a role in SLE, yet whether gut microbiota participates in the development of SLE remains largely unknown. To investigate this issue, we carried out 16s rDNA sequencing analyses in a cohort of 18 female un-treated active SLE patients and 7 female healthy controls, and performed fecal microbiota transplantation from patients and healthy controls to germ-free mice.

Results

Compared to the healthy controls, we found no significant different microbial diversity but some significantly different species in SLE patients including Turicibacter genus and other 5 species. Fecal transfer from SLE patients to germ free (GF) C57BL/6 mice caused GF mice to develop a series of lupus-like phenotyptic features, which including an increased serum autoimmune antibodies, and imbalanced cytokines, altered distribution of immune cells in mucosal and peripheral immune response, and upregulated expression of genes related to SLE in recipient mice that received SLE fecal microbiota transplantation (FMT). Moreover, the metabolism of histidine was significantly altered in GF mice treated with SLE patient feces, as compared to those which received healthy fecal transplants.

Conclusions

Overall, our results describe a causal role of aberrant gut microbiota in contributing to the pathogenesis of SLE. The interplay of gut microbial and histidine metabolism may be one of the mechanisms intertwined with autoimmune activation in SLE.
Respiratory Alkalosis Provokes Spike-Wave Discharges in Seizure-Prone Rats
Authors: Salvati Kathryn A. , Souza George M.P.R. , Lu Adam C. , Ritger Matthew L. , Guyenet Patrice G. , Abbott Stephen B. , Beenhakker Mark P.
Published: August 2021

Hyperventilation reliably provokes seizures in patients diagnosed with absence epilepsy. Despite this predictable patient response, the mechanisms that enable hyperventilation to powerfully activate absence seizure-generating circuits remain entirely unknown. Using the WAG/Rij rat, an established rodent model of absence epilepsy, we demonstrate that absence seizures are highly sensitive to arterial carbon dioxide, suggesting that seizure-generating circuits are sensitive to pH. Moreover, hyperventilation consistently activated neurons within the intralaminar nuclei of the thalamus, a structure implicated in seizure generation. We show that intralaminar thalamus also contains pH-sensitive neurons. Collectively, these observations suggest that hyperventilation activates pH-sensitive neurons of the intralaminar nuclei to provoke absence seizures.
SMOG 2 and OpenSMOG: Extending the limits of structure-based models
Authors: de Oliveira Antonio B. , Contessoto Vinícius G. , Hassan Asem , Byju Sandra , Wang Ailun , Wang Yang , Dodero-Rojas Esteban , Mohanty Udayan , Noel Jeffrey K. , Onuchic Jose N. , Whitford Paul C.
Published: August 2021

Applying simulations with structure-based (Gō-like) models has proven to be an effective strategy for investigating the factors that control biomolecular dynamics. The common element of these models is that some (or all) of the intra/inter-molecular inter-actions are explicitly defined to stabilize an experimentally-determined structure. To facilitate the development and application of this broad class of models, we previously released the SMOG 2 software package. This suite allows one to easily customize and distribute structure-based (i.e. SMOG) models for any type of polymer-ligand system. Since its original release, user feedback has driven the implementation of numerous enhancements. Here, we describe recent extensions to the software and demonstrate the capabilities of the most recent version, SMOG v2.4. Changes include new tools that aid user-defined customization of force fields, as well as an interface with the OpenMM simulation libraries (OpenSMOG v1.0). To illustrate the utility of these advances, we present several applications of SMOG2 and OpenSMOG, which include systems with millions of atoms, long polymers and explicit ions. We also highlight how one can incorporate non-structure-based (e.g. AMBER-based) energetics to define a hybrid class of models. The representative applications include large-scale rearrangements of the SARS-CoV-2 Spike protein, the HIV-1 capsid in the presence of explicit ions, and crystallographic lattices of ribosomes and proteins. In summary, SMOG 2 and OpenSMOG provide robust support for researchers who seek to apply structure-based models to large and/or intricate biomolecular systems.
A Generic Force Field for Simulating Native Protein Structures Using Dissipative Particle Dynamics
Authors: Vaiwala Rakesh , Ayappa K. Ganapathy
Published: August 2021

A coarse-grained force field for molecular dynamics simulations of native structures of proteins in a dissipative particle dynamics (DPD) framework is developed. The parameters for bonded interactions are derived by mapping the bonds and angles for 20 amino acids onto target distributions obtained from fully atomistic simulations in explicit solvent. A dual-basin potential is introduced for stabilizing backbone angles, to cover a wide spectrum of protein secondary structures. The backbone dihedral potential enables folding of the protein from an unfolded initial state to the folded native structure. The proposed force field is validated by evaluating structural properties of several model peptides and proteins including the SARS-CoV-2 fusion peptide, consisting ofα-helices,β-sheets, loops and turns. Detailed comparisons with fully atomistic simulations are carried out to assess the ability of the proposed force field to stabilize the different secondary structures present in proteins. The compact conformations of the native states were evident from the radius of gyration as well as the high intensity peaks of the root mean square deviation histograms, which were found to lie below 0.4 nm. The Ramachandran-like energy landscape on the phase space of backbone angles (θ) and dihedrals (ϕ) effectively captured the conformational phase space ofα-helices at ∼(ϕ= 50°,θ= 90°) andβ-strands at ∼(ϕ= ±180°,θ= 90° − 120°). Furthermore, the residue-residue native contacts are also well reproduced by the proposed DPD model. The applicability of the model to multidomain complexes is assessed using lysozyme as well as a largeαhelical bacterial pore-forming toxin, cytolysin A. Our studies illustrate that the proposed force field is generic, and can potentially be extended for efficient in-silico investigations of membrane bound polypeptides and proteins using DPD simulations.
Constructing Functional Networks of Phosphorylation Sites Using Co-Phosphorylation
Authors: Ayati Marzieh , Yılmaz Serhan , Chance Mark R. , Koyutürk Mehmet
Published: August 2021

Protein phosphorylation is a ubiquitous regulatory mechanism that plays a central role in cellular signaling. According to recent estimates, up to 70% of human proteins can be phosphorylated. Therefore, characterization of phosphorylation dynamics is critical for understanding a broad range of biological and biochemical processes. Technologies based on mass spectrometry are rapidly advancing to meet the needs for high-throughput screening of phosphorylation. These technologies enable untargeted quantification of thousands of phosphorylation sites in a given sample. Many labs are already utilizing these technologies to comprehensively characterize signaling landscapes by examining perturbations with drugs and knockdown approaches, or by assessing diverse phenotypes in cancers, neuro-degerenational diseases, infectious diseases, and normal development. Here, we comprehensively investigate the concept of “co-phosphorylation”, defined as the correlated phosphorylation of a pair of phosphosites across various biological states. We integrate nine publicly available phospho-proteomics datasets for various diseases (including breast cancer, ovarian cancer and Alzhemier’s disease) and utilize functional data related to sequence, evolutionary histories, kinase annotations, and pathway annotations to investigate the functional relevance of co-phosphorylation. Our results across a broad range of studies consistently show that functionally associated sites tend to exhibit significant positive or negative co-phosphorylation. Specifically, we show that co-phosphorylation can be used to predict with high precision the sites that are on the same pathway or that are targeted by the same kinase. Overall, these results establish co-phosphorylation as a useful resource for analyzing phospho-proteins in a network context, which can help extend our knowledge on cellular signaling and its dysregulation.
Optimized analysis for sensitive detection and analysis of single proteins via interferometric scattering microscopy
Authors: Dastjerdi Houman Mirzaalian , Dahmardeh Mahyar , Gemeinhardt André , Mahmoodabadi Reza Gholami , Köstler Harald , Sandoghdar Vahid
Published: August 2021

It has been shown that interferometric detection of Rayleigh scattering (iSCAT) can reach an exquisite sensitivity for label-free detection of nano-matter, down to single proteins. The sensitivity of iSCAT detection is intrinsically limited by shot noise, which can be indefinitely improved by employing higher illumination power or longer integration times. In practice, however, a large speckle-like background and technical issues in the experimental setup limit the attainable signal-to-noise ratio. Strategies and algorithms in data analysis are, thus, crucial for extracting quantitative results from weak signals, e.g. regarding the mass (size) of the detected nano-objects or their positions. In this article, we elaborate on some algorithms for processing iSCAT data and identify some key technical as well as conceptual issues that have to be considered when recording and interpreting the data. The discussed methods and analyses are made available in the extensive python-based platform, PiSCAT§.
The β-cell primary cilium is an autonomous Ca2+ compartment for paracrine GABA signalling
Authors: Sanchez Gonzalo , Incedal Tugce Ceren , Prada Juan , O’Callaghan Paul , Echeverry Santiago , Nguyen Phuoc My , Xie Beichen , Barg Sebastian , Kreuger Johan , Dandekar Thomas , Idevall-Hagren Olof
Published: August 2021

The primary cilium is an organelle present in most adult mammalian cells and is thought of as an antenna for detection of a variety of signals. Here we use intact mouse pancreatic islets of Langerhans to investigate signalling properties of the primary cilium in β-cells. Using cilia-targeted Ca2+ indicators we find that the resting Ca2+ concentration in the cilium is lower than that of the cytosol, and we uncover a Ca2+ extrusion mechanism in the cilium that effectively insulates the cilium from changes in cytosolic Ca2+. Stimuli that give rise to pronounced cytosolic Ca2+ concentration increases, such as glucose- and depolarization-induced Ca2+ influx, and mobilization of Ca2+ from the ER, was accompanied by minor increases in cilia Ca2+ concentrations that were spatially restricted to a small compartment at the base. Conversely, we observe pronounced Ca2+ concentration changes in the primary cilia of islet β-cells that do not propagate into the cytosol and show that paracrine GABA signalling via cilia-localized GABA-B1-receptors is responsible for this Ca2+ signalling. Finally, we demonstrate that the cilia response to GABA involves ligand-dependent transport of GABA-B1 receptors into the cilium.
Maintenance of conditioned place avoidance induced by gastric malaise requires NMDA activity within the ventral hippocampus
Authors: Hernández-Matias Arturo , Bermúdez-Rattoni Federico , Osorio-Gómez Daniel
Published: August 2021

It has been reported that during chemotherapy treatment, some patients can experience nausea before pharmacological administration, suggesting that contextual stimuli are associated with the nauseating effects. There are attempts to reproduce with animal models the conditions under which this phenomenon is observed to provide a useful paradigm for studying contextual aversion learning and the brain structures involved. This manuscript assessed the hippocampus involvement in acquiring and maintaining long-term conditioned place avoidance (CPA) induced by a gastric malaise-inducing agent, LiCl. Our results demonstrate that a reliable induction of CPA is possible after one acquisition trial. However, CPA establishment requires a 20-min confinement in the compartment associated with LiCl administration. Interestingly, both hippocampal regions seem to be necessary for CPA establishment; nonetheless, inactivation of the ventral hippocampus results in a reversion of avoidance and turns it into preference. Moreover, we demonstrate that activation of dorsal/ventral hippocampal NMDA receptors after CS–US association is required for long-term CPA memory maintenance.
The effect of zolpidem on targeted memory reactivation during sleep
Authors: Carbone Julia , Bibián Carlos , Reischl Patrick , Born Jan , Forcato Cecilia , Diekelmann Susanne
Published: August 2021

According to the active system consolidation theory, memory consolidation during sleep relies on the reactivation of newly encoded memory representations. This reactivation is orchestrated by the interplay of sleep slow oscillations, spindles, and theta, which are in turn modulated by certain neurotransmitters like GABA to enable long-lasting plastic changes in the memory store. Here we asked whether the GABAergic system and associated changes in sleep oscillations are functionally related to memory reactivation during sleep. We administered the GABAA agonist zolpidem (10 mg) in a double-blind placebo-controlled study. To specifically focus on the effects on memory reactivation during sleep, we experimentally induced such reactivations by targeted memory reactivation (TMR) with learning-associated reminder cues presented during post-learning slow-wave sleep (SWS). Zolpidem significantly enhanced memory performance with TMR during sleep compared with placebo. Zolpidem also increased the coupling of fast spindles and theta to slow oscillations, although overall the power of slow spindles and theta was reduced compared with placebo. In an uncorrected exploratory analysis, memory performance was associated with slow spindle responses to TMR in the zolpidem condition, whereas it was associated with fast spindle responses in placebo. These findings provide tentative first evidence that GABAergic activity may be functionally implicated in memory reactivation processes during sleep, possibly via its effects on slow oscillations, spindles and theta as well as their interplay.
Time-dependent transformations of memory representations differ along the long axis of the hippocampus
Authors: Cowan Emily T. , Liu Anli A. , Henin Simon , Kothare Sanjeev , Devinsky Orrin , Davachi Lila
Published: August 2021

Research has shown that sleep is beneficial for the long-term retention of memories. According to theories of memory consolidation, memories are gradually reorganized, becoming supported by widespread, distributed cortical networks, particularly during postencoding periods of sleep. However, the effects of sleep on the organization of memories in the hippocampus itself remains less clear. In a 3-d study, participants encoded separate lists of word–image pairs differing in their opportunity for sleep-dependent consolidation. Pairs were initially studied either before or after an overnight sleep period, and were then restudied in a functional magnetic resonance imaging (fMRI) scan session. We used multivariate pattern similarity analyses to examine fine-grained effects of consolidation on memory representations in the hippocampus. We provide evidence for a dissociation along the long axis of the hippocampus that emerges with consolidation, such that representational patterns for object–word memories initially formed prior to sleep become differentiated in anterior hippocampus and more similar, or overlapping, in posterior hippocampus. Differentiation in anterior hippocampal representations correlated with subsequent behavioral performance. Furthermore, representational overlap in posterior hippocampus correlated with the duration of intervening slow wave sleep. Together, these results demonstrate that sleep-dependent consolidation promotes the reorganization of memory traces along the long axis of the hippocampus.
Wells Fargo: Solar Energy for Los Angeles Branches (A)
Authors: Ovchinnikov Anton , Hvaleva Anastasiya , Lucas Sheri
Published: August 2021

In the first case of a two-part series, a strategic finance manager at Wells Fargo with experience installing solar panel systems on bank branches crunches the numbers for a similar project in the Los Angeles area given the uncertain future of a government rebate.
Early adopters’ responses to a virtual tourism product: Airbnb’s online experiences
Authors: Cenni Irene , Vásquez Camilla
Published: August 2021

Purpose

In April 2020, Airbnb launched “Online Experiences,” (OE) a virtual tourism product responding to pandemic-related restrictions on physical travel. The purpose of this study is to explore the characteristics of this innovative product that were most salient to consumers and in so doing, to provide preliminary insights into the factors related to its success.

Design/methodology/approach

Using a grounded theory approach in this qualitative study, the authors investigated a sample of 500 online consumer reviews of 100 different Airbnb OE. The analysis identified five major themes associated with reviewers’ positive evaluations of OEs.

Findings

The study’s findings corroborate prior research on peer-to-peer businesses regarding the centrality of the host and the social appeal of such services, yet they also reveal newer, multifaceted expectations for OEs’ hosts. Further, consumers reacted positively to both the entertaining and educational aspects of OEs. Finally, reviewers’ comments reflect factors related to pandemic-related conditions such as seeking social interaction and virtual escape, yet they also identify factors that suggest the durative appeal of OEs as a tourism product (e.g. “repeatability” of OEs; OEs as sites for virtual connection with family/friends; OEs as a marketing tool for future travel).

Originality/value

To the best of my knowledge, this is one of the first studies investigating this recently launched virtual tourism product. The findings, thus, represent an important empirical baseline for future research on this topic.
Effectiveness of non-farm diversification on rural household income – evidence and policy implications from India
Authors: Kapoor Shreya , Kapoor Sanjeev
Published: August 2021

Purpose

Doubling farming households’ income through occupational diversification to the non-farm sector has been advocated to be of paramount importance in an agrarian economy such as India. The purpose of this paper is to analyse the effects of non-farm activities on rural household incomes in four different Indian states by using a propensity score matching technique and developing an endogenous switching model.

Design/methodology/approach

The research is based on secondary data taken from four quinquennial rounds of employment and unemployment surveys conducted by the National Sample Survey Organization.

Findings

The matching results indicate a maximum monthly rise in per capita income of Rs. 60 in Gujarat and a minimum increase of Rs. 18 in Rajasthan among rural households employed in the non-farm sector as compared to the farm sector. The findings confirm that rural non-farm structural diversification cannot be viewed as a blueprint for increasing rural household incomes in different states. Further, it suggests the need to segmenting the different states on the basis of agricultural development for increasing rural incomes.

Research limitations/implications

The study argues that Indian states with a strongly developed farm sector i.e. Gujarat and Punjab are not ideally suited to undergo structural changes in their economic pursuit. The estimates suggest that the transition of rural households from farm to non-farm-sector activities is a very weak strategy in agriculturally developed states of Gujarat and Punjab, whereas non-farm diversification becomes a pivotal strategy for increasing rural household incomes in less agriculturally developed states such as Rajasthan and Uttar Pradesh. A contrasting point that arises from these evidence is that although diversification to the non-farm sector leads to higher income, but the resultant figures are very scanty.

Originality/value

The present study contributes to the existing literature by providing evidence and policy implications on rural non-farm diversification in India and its impact on the rural household income. The study can help the policymakers in framing policies aiming at increasing the income of the rural household through the structural transition of the rural economy.
Measuring the housing sector’s contribution to GDP in emerging market countries
Authors: Acolin Arthur , Hoek-Smit Marja , Green Richard K.
Published: August 2021

Purpose

This paper aims to document the economic importance of the housing sector, as measured by its contribution to gross domestic product (GDP), which is not fully recognized. In response to the joint economic and health crises caused by the COVID-19 pandemic, there is an opportunity for emerging market countries to develop and implement inclusive housing strategies that stimulate the economy and improve community health outcomes. However, so far housing does not feature prominently in the recovery plans of many emerging market countries.

Design/methodology/approach

This paper uses national account data and informal housing estimates for 11 emerging market economies to estimate the contribution of housing investments and housing services to the GDP of these countries.

Findings

This paper finds that the combined contribution of housing investments and housing services represents between 6.9% and 18.5% of GDP, averaging 13.1% in the countries with information about both. This puts the housing sector roughly on par with other key sectors such as manufacturing. In addition, if the informal housing sector is undercounted in the official national account figures used in this analysis by 50% or 100%, for example, then the true averages of housing investments and housing services’ contribution to GDP would increase to 14.3% or 16.1% of GDP, respectively.

Research limitations/implications

Further efforts to improve data collection about housing investments and consumption, particularly imputed rent for owner occupiers and informal activity require national government to conduct regular household and housing surveys. Researcher can help make these surveys more robust and leverage new data sources such as scraped housing price and rent data to complement traditional surveys. Better data are needed in order to capture housing contribution to the economy.

Practical implications

The size of the housing sector and its impact in terms of employment and community resilience indicate the potential of inclusive housing investments to both serve short-term economic stimulus and increase long-term community resilience.

Originality/value

The role of housing in the economy is often limited to housing investment, despite the importance of housing services and well-documented methodologies to include them. This analysis highlights the importance of housing to the economy of emerging market countries (in addition to all the non-GDP related impact of housing on welfare) and indicate data limitation that need to be addressed to further strengthen the case for focusing on housing as part of economic recovery plans.
Sales transformation: conceptual domain and dimensions
Authors: Corsaro Daniela , Maggioni Isabella
Published: August 2021

Purpose

This study aims to offer a conceptualization of sales transformation, a phenomenon that is redefining the role of salespeople and the nature of Business-to-Business (B2B) relationships while disrupting the selling logics across a variety of industries.

Design/methodology/approach

Through a two-stage approach, the authors propose and test a conceptual model of sales transformation. The authors conducted 20 interviews and two focus groups with sales directors and managers. The authors then surveyed directors, executives and managers in the sales area (n = 190) and tested a reflective–formative hierarchical model using partial least squares structural equation modeling (PLS-SEM).

Findings

Sales transformation is a multidimensional construct that includes four higher-order dimensions, namely, people, digitalization, integration and acceleration, and 16 sub-dimensions. These dimensions simultaneously contribute to the sales transformation phenomenon that is conceptualized as a systemic process. This study also offers a measurement tool to assess the degree of sales transformation and enhance the value generated through sales.

Originality/value

Although many companies are facing challenges stemming from the process of sales transformation, most studies have only focused on micro-aspects of this transformation. This study provides a holistic view of sales transformation aimed at understanding the complexity of this phenomenon by adopting a macro-level perspective on the different dimensions that contribute to its occurrence and development.
The government spending multiplier in Latin American countries: does the institutional environment matter?
Authors: Acevedo Rafael , Mora Jose U. , Young Andrew T.
Published: August 2021

Purpose

Mora and Acevedo (2019) report that the government spending multipliers in Latin American countries are notably higher than what is typically reported for developed economies. Latin American countries have been inclined toward using procyclical fiscal policies. Those policies have been perceived as being effective at mitigating the effects of the 2008–2009 Great Recession. This study aims to estimate the government spending multiplier using Latin American panel data from 19 Latin American countries from 2000 to 2018. The estimates are conditional on the extent of openness, capital mobility and economic freedom. Based on the results, the latter is important: the less economically free a country, the larger its spending multiplier. Lower economic freedom in Latin American countries can help to account for their large spending multipliers. In particular, restrictions on international trade are positively associated with multipliers. This is the case even while controlling the trade share of GDP.

Design/methodology/approach

The authors provide regression results that are conditional on the extent of openness, capital mobility and economic freedom.

Findings

The less economically free a country, the larger its spending multiplier. Lower economic freedom in Latin American countries can help to account for their large spending multipliers. In particular, restrictions on international trade are positively associated with multipliers. This is the case even while controlling the trade share of GDP.

Originality/value

To the best of the authors’ knowledge, this is first study to estimate the fiscal multiplier conditional on economic freedom levels. The authors provide correctly calculated multipliers conditional on different levels of economic freedom. The authors point the way to future studies considering the effectiveness of fiscal policy conditional on institutional/policy quality.
A methodology for managing public spaces to increase access to essential goods and services by vulnerable populations during the COVID-19 pandemic
Authors: Regal Ludowieg Andrés , Ortega Claudio , Bronfman Andrés , Rodriguez Serra Michelle , Chong Mario
Published: August 2021

Purpose

The purpose of this paper is to present a spatial decision support system (SDSS) to be used by the local authorities of a city in the planning and response phase of a disaster. The SDSS focuses on the management of public spaces as a resource to increase a vulnerable population’s accessibility to essential goods and services. Using a web-based platform, the SDSS would support data-driven decisions, especially for cases such as the COVID-19 pandemic which requires special care in quarantine situations (which imply walking access instead of by other means of transport).

Design/methodology/approach

This paper proposes a methodology to create a web-SDSS to manage public spaces in the planning and response phase of a disaster to increase the access to essential goods and services. Using a regular polygon grid, a city is partitioned into spatial units that aggregate spatial data from open and proprietary sources. The polygon grid is then used to compute accessibility, vulnerability and population density indicators using spatial analysis. Finally, a facility location problem is formulated and solved to provide decision-makers with an adaptive selection of public spaces given their indicators of choice.

Findings

The design and implementation of the methodology resulted in a granular representation of the city of Lima, Peru, in terms of population density, accessibility and vulnerability. Using these indicators, the SDSS was deployed as a web application that allowed decision-makers to explore different solutions to a facility location model within their districts, as well as visualizing the indicators computed for the hexagons that covered the district’s area. By performing tests with different local authorities, improvements were suggested to support a more general set of decisions and the key indicators to use in the SDSS were determined.

Originality/value

This paper, following the literature gap, is the first of its kind that presents an SDSS focused on increasing access to essential goods and services using public spaces and has had a successful response from local authorities with different backgrounds regarding the integration into their decision-making process.
Mining Arabic Twitter conversations on health care: a new approach to analysing Arabic language on social media
Authors: Alqtati Nael , Wilson Jonathan A.J. , De Silva Varuna
Published: August 2021

Purpose

This paper aims to equip professionals and researchers in the fields of advertising, branding, public relations, marketing communications, social media analytics and marketing with a simple, effective and dynamic means of evaluating consumer behavioural sentiments and engagement through Arabic language and script, in vivo.

Design/methodology/approach

Using quantitative and qualitative situational linguistic analyses of Classical Arabic, found in Quranic and religious texts scripts; Modern Standard Arabic, which is commonly used in formal Arabic channels; and dialectical Arabic, which varies hugely from one Arabic country to another: this study analyses rich marketing and consumer messages (tweets) – as a basis for developing an Arabic language social media methodological tool.

Findings

Despite the popularity of Arabic language communication on social media platforms across geographies, currently, comprehensive language processing toolkits for analysing Arabic social media conversations have limitations and require further development. Furthermore, due to its unique morphology, developing text understanding capabilities specific to the Arabic language poses challenges.

Practical implications

This study demonstrates the application and effectiveness of the proposed methodology on a random sample of Twitter data from Arabic-speaking regions. Furthermore, as Arabic is the language of Islam, the study is of particular importance to Islamic and Muslim geographies, markets and marketing.

Social implications

The findings suggest that the proposed methodology has a wider potential beyond the data set and health-care sector analysed, and therefore, can be applied to further markets, social media platforms and consumer segments.

Originality/value

To remedy these gaps, this study presents a new methodology and analytical approach to investigating Arabic language social media conversations, which brings together a multidisciplinary knowledge of technology, data science and marketing communications.
Designing an uncertain bi-objective green leagile capacitated lot sizing problem considering FM/M/C queue system
Authors: Rabbani Masoud , Aghamohamadi Bosjin Soroush , Manavizadeh Neda , Farrokhi-Asl Hamed
Published: August 2021

Purpose

This paper aims to present a novel bi-objective mathematical model for a production-inventory system under uncertainty.

Design/methodology/approach

This paper addresses agile and lean manufacturing concepts alongside with green production methods to design an integrated capacitated lot sizing problem (CLSP). From a methodological perspective, the problem is solved in three phases. In the first step, an FM/M/C queuing system is used to minimize the number of customers waited to receive their orders. In the second step, an effective approach is applied to deal with the fuzzy bi-objective model and finally, a hybrid metaheuristic algorithm is used to solve the problem.

Findings

Some numerical test problems and sensitivity analyzes are conducted to measure the efficiency of the proposed model and the solution method. The results validate the model and the performance of the solution method compared to Gams results in small size test problems and prove the superiority of the hybrid algorithm in comparison with the other well-known metaheuristic algorithms in large size test problems.

Originality/value

This paper presents a novel bi-objective mathematical model for a CLSP under uncertainty. The proposed model is conducted on a practical case and several sensitivity analysis are conducted to assess the behavior of the model. Using a queue system, this problem aims to reduce the items waited in the queue to receive service. Two objective functions are considered to maximize the profit and minimize the negative environmental effects. In this regard, the second objective function aims to reduce the amount of emitted carbon.