bluuebunny/crossref_metadata_2025 huggingface dataset:
Replicable multivariate BWAS with moderate sample sizes
Authors: Spisak Tamas , Bingel Ulrike , Wager Tor
Published: June 2022

Brain-Wide Association Studies (BWAS) have become a dominant method for linking mind and brain over the past 30 years. Univariate models test tens to hundreds of thousands of brain voxels individually, whereas multivariate models (‘multivariate BWAS’) integrate signals across brain regions into a predictive model. Numerous problems have been raised with univariate BWAS, including lack of power and reliability and an inability to account for pattern-level information embedded in distributed neural circuits1–3. Multivariate predictive models address many of these concerns, and offer substantial promise for delivering brain-based measures of behavioral and clinical states and traits2,3.

In their recent paper4, Marek et al. evaluated the effects of sample size on univariate and multivariate BWAS in three large-scale neuroimaging dataset and came to the general conclusion that “BWAS reproducibility requires samples with thousands of individuals”. We applaud their comprehensive analysis, and we agree that (a) large samples are needed when conducting univariate BWAS of individual differences in trait measures, and (b) multivariate BWAS reveal substantially larger effects and are therefore more highly powered. However, we disagree with Marek et al.’s claims that multivariate BWAS provide “inflated in-sample associations” that often fail to replicate (i.e., are underpowered), and that multivariate BWAS consequently require thousands of participants when predicting trait-level individual differences. Here we substantiate that (i) with appropriate methodology, the reported in-sample effect size inflation in multivariate BWAS can be entirely eliminated, and (ii) in most cases, multivariate BWAS effects are replicable with substantially smaller sample sizes (Figure 1).
Pan-cancer analysis reveals the value of FDX1 as a novel biomarker in the prognosis and immunotherapy in human tumors
Authors: Zhang Qingqing , Liu Nanyang , Wu Di , Xu Zhengyu , Wang Yichen , Wang Ping
Published: June 2022

Emerging evidence supports FDX1’s important role in the development and progression of cancer, but no extensive cancer analysis is available to date. This study was the first to comprehensively explore the expression of FDX1 in 33 types of cancer and the significance of FDX1 in clinical prognosis by using bioinformatics techniques. Meanwhile, we analyzed the relationship between FDX1 and pathological stage, as well as immune cell infiltration. Based on this, the important role of FDX1 in tumor immunotherapy was proposed. The expression of FDX1 was significantly different between normal and tumor samples in 17 of 33 types of cancer. Besides, Cox regression analysis showed that FDX1 is a protective gene in Kidney renal clear cell carcinoma (KIRC), Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), Liver hepatocellular carcinoma (LIHC), Kidney renal papillary cell carcinoma (KIRP), Mesothelioma (MESO), and Thyroid carcinoma (THCA). Porphyrin and oxidative metabolism pathway regulating integrator complex was involved in the process. Furthermore, high expression of FDX1 promoted infiltration of Eosinophils and monocyte in Adrenocortical carcinoma (ACC) and Kidney Chromophobe (KICH) by affecting the tumor microenvironment (TME) and was significantly correlated with immune checkpoint genes. Our first pan-cancer analysis elucidates the expression characteristics of FDX1 across different cancers and highlights its potential value as a prognostic biomarker, laying a foundation for further study of its immunotherapy mechanism in various cancers.
Evolutionary divergence in sugar valuation shifts Drosophila suzukii oviposition choice towards ripe fruit
Authors: Cavey Matthieu , Charroux Bernard , Travaillard Solène , Manière Gérard , Berthelot-Grosjean Martine , Quitard Sabine , Minervino Caroline , Detailleur Brice , Grosjean Yaël , Prud’homme Benjamin
Published: June 2022

Behavior evolution can promote the emergence of agricultural pests via ecological niche changes. The underlying neuronal mechanisms are poorly understood. We investigate the chemosensory changes underlying the evolutionary shift of oviposition substrate of the pest Drosophila suzukii from rotten to ripe fruits. Using a model substrate for fermented fruits and genetic manipulations, we show that an increase in valuation of fruit sugars during oviposition decisions drives D. suzukii to oviposit on ripe fruits as opposed to the model D. melanogaster which prefers rotten fruits. Inter-species comparative in vivo calcium imaging of sugar Gustatory Receptor Neurons suggests that increased sugar valuation in D. suzukii is related to neuronal sensitivity changes at multiple levels of the oviposition circuitry. Our results show that the tuning of sugar valuation has contributed to the evolution of oviposition preference on ripe fruit of D. suzukii.
Involvement of ILC1-like innate lymphocytes in human autoimmunity, lessons from alopecia areata
Authors: Britva Rimma Laufer , Keren Aviad , Bertolini Marta , Ullmann Yehuda , Paus Ralf , Gilhar Amos
Published: June 2022

Here, we have explored the involvement of innate lymphoid cells-type 1 (ILC1) in the pathogenesis of alopecia areata (AA), because we found them to be significantly increased around lesional and non-lesional HFs of AA patients. To further explore these unexpected findings, we first co-cultured autologous circulating ILC1-like cells (ILC1lc) with healthy, but stressed, organ-cultured human scalp hair follicles (HFs). ILClc induced all hallmarks of AA ex vivo: they significantly promoted premature, apoptosis-driven HF regression (catagen), HF cytotoxicity/dystrophy and most important for AA pathogenesis, collapse of the HFs physiological immune privilege. NKG2D-blocking or IFNγ-neutralizing antibodies antagonized this. In vivo, intradermal injection of autologous activated, NKG2D+/IFNγ-secreting ILC1lc into healthy human scalp skin xenotransplanted onto SCID/beige mice sufficed to rapidly induce characteristic AA lesions. This provides the first evidence that ILC1lc suffice to induce AA in previously healthy human HFs ex vivo and in vivo, and further questions the conventional wisdom that AA is always an autoantigen-dependent, CD8+ T cell-driven autoimmune disease.
Dominant toxin hypothesis: unravelling the venom phenotype across micro and macroevolution
Authors: Smith Edward G. , Surm Joachim M. , Macrander Jason , Simhi Adi , Amir Guy , Sachkova Maria Y. , Lewandowska Magda , Reitzel Adam M. , Moran Yehu
Published: June 2022

Venom is a complex trait with substantial inter- and intraspecific variability resulting from strong selective pressures acting on the expression of many toxic proteins. However, understanding the processes underlying the toxin expression dynamics that determine the venom phenotype remains unresolved. Here, we use comparative genomics and transcriptomics to reveal that toxin expression in sea anemones evolves rapidly with little constraint and that a single toxin family dictates the venom phenotype in each species. This dominant toxin family is characterized by massive gene duplication events. In-depth analysis of the sea anemone,Nematostella vectensis, revealed significant variation in the number of copies of the dominant toxin (Nv1) across populations, corresponding to significant differences inNv1expression at both the transcript and protein levels. These differences inNv1copies are driven by independent expansion events, resulting in distinct haplotypes that have a restricted geographical distribution. Strikingly, one population has undergone a severe contraction event, causing a near-complete loss of Nv1 production. Our findings across micro- and macroevolutionary scales in sea anemones complement observations of single dominant toxin family present in other venomous organisms and establishes the dominant toxin hypothesis whereby venomous animals have convergently evolved a similar strategy in shaping the venom phenotype.
Aging impairs the clustering and reduces the activity of L-type calcium channels in cardiac pacemaker cells
Authors: Baudot Matthias , Vivas Oscar , Choi Sabrina , Serrano Gabriella , Flores Victor A. , Santana L. Fernando , Moreno Claudia M
Published: June 2022

Every heartbeat is initiated by a spontaneous electrical signal generated inside the cardiac pacemaker. The generation of this electrical signal depends on the coordinated opening and closing of different ion channels, where voltage-gated L-type calcium channels play a central role. Despite the reliability of the pacemaker, all mammals experience a linear slowdown of the pacemaker rate with age. In humans, this slowing can become pathological and constitutes the main cause for the requirement of the implantation of artificial pacemakers. However, the mechanisms behind the age-associated slowdown of the pacemaker are not well understood. Here, we show that age directly alters the function of L-type calcium channels in pacemaker cells from mice. These age-associated alterations include: i) a reduction in the density of the channels at the plasma membrane, ii) a reduction in the clustering of the channels, iii) a decrease in channel open probability, and iv) a reduction in the cooperative gating of the calcium channels. Altogether, these age-associated alterations result in a global reduction of the L-type calcium current density and in a slowdown of the pacemaker diastolic depolarization. Remarkably, increasing the open probability of L-type calcium channels pharmacologically was enough to restore pacemaker rate in old cells to the same levels observed in the young. Overall, our findings provide evidence that proper organization and function of L-type calcium channels is impaired by aging and that this dysfunction contributes to the slowdown of pacemaker cells in old animals.
mb-PHENIX: Diffusion and Supervised Uniform Manifold Approximation for denoising microbiota data
Authors: Cristian Padron-Manrique , Aarón Vázquez-Jiménez , Armando Esquivel-Hernandez Diego , Yoscelina Estrella Martinez Lopez , Daniel Neri-Rosario , Jean Paul Sánchez-Castañeda , David Giron-Villalobos , Osbaldo Resendis-Antonio
Published: June 2022

Motivation

Microbiota data suffers from technical noise (reflected as excess of zeros in the count matrix) and the curse of dimensionality. This complicates downstream data analysis and compromises the scientific discovery’s reliability. Data sparsity makes it difficult to obtain a well-cluster structure and distorts the abundance distributions. Currently, there is a rised need to develop new algorithms with improved capacities to reduce noise and recover missing information.

Results

We present mb-PHENIX, an open-source algorithm developed in Python, that recovers taxa abundances from the noisy and sparse microbiota data. Our method deals with sparsity in the count matrix (in 16S microbiota and shotgun studies) by applying imputation via diffusion onto the supervisedUniform Manifold Approximation Projection(sUMAP) space. Our hybrid machine learning approach allows the user to denoise microbiota data. Thus, the differential abundance of microbes is more accurate among study groups, where abundance analysis fails.

Availability

The mb-PHENIX algorithm is available athttps://github.com/resendislab/mb-PHENIX. An easy-to-use implementation is available on Google Colab (see GitHub)

Contact

Oresendis@inmegen.gob.mx

Supplementary information

Supplementary data are available atBioinformaticsonline.
The Intrinsic Hierarchy of Self – Converging Topography and Dynamics
Authors: Çatal Yasir , Günay Mehmet Akif , Li Chunbo , Wang Jijun , Cui Huiru , Li Wei , Northoff Georg
Published: June 2022

The brain can be characterized by an intrinsic hierarchy in its topography which, as recently shown for the uni-transmodal distinction of core and periphery, converges with its dynamics. Does such intrinsic hierarchical organization in both topography and dynamic also apply to the brain’s inner core itself and its higher-order cognitive functions like self? Applying multiple fMRI data sets, we show how the recently established three-layer topography of self (internal, external, mental) is already present during the resting state and carried over to task states including both task-specific and -unspecific effects. Moreover, the topographic hierarchy converges with corresponding dynamic changes (measured by power-law exponent, autocorrelation window, median frequency, sample entropy, complexity) during both rest and task states. Finally, analogous to the topographic hierarchy, we also demonstrate hierarchy among the different dynamic measures themselves according to background and foreground. Finally, we show task-specific- and un-specific effects in the hierarchies of both dynamics and topography. Together, we demonstrate the existence of an intrinsic topographic hierarchy of self and its convergence with dynamics.
Genomic characterisation of a novel species of Erysipelothrix associated with mortalities among endangered seabirds
Authors: Zhong Jiadong , Medvecky Matej , Tornos Jérémy , Clessin Augustin , Gantelet Hubert , Gamble Amandine , Forde Taya L. , Boulinier Thierry
Published: June 2022

Infectious diseases threaten endangered species, particularly in small isolated populations. Seabird populations on the remote Amsterdam Island in the Indian Ocean have been in decline for the past three decades, with avian cholera caused by Pasteurella multocida proposed as the primary driver. However, Erysipelothrix spp. has also been sporadically detected from albatrosses on Amsterdam Island and may be contributing to some of the observed mortality. In this study, we genomically characterised 16 Erysipelothrix spp. isolates obtained from three Indian yellow-nosed albatross chick carcasses in 2019. Two isolates were sequenced using both Illumina short-read and MinION long-read approaches, which – following hybrid assembly – resulted in closed circular genomes. Mapping of Illumina reads from the remaining isolates to one of these new reference genomes revealed that all 16 isolates were closely related, with a maximum of 13 nucleotide differences distinguishing any pair of isolates. The nucleotide diversity of isolates obtained from the same or different carcasses was similar, suggesting all three chicks were likely infected from a common source. These genomes were compared with a global collection of genomes from E. rhusiopathiae and other species from the same genus. The isolates from albatrosses were phylogenetically distinct, sharing a most recent common ancestor with E. rhusiopathiae. Based on phylogenomic analysis and standard thresholds for average nucleotide identity and digital DNA-DNA hybridisation, these isolates represent a novel Erysipelothrix species, for which we propose the name Erysipelothrix amsterdamensis sp. nov. The type strain is E. amsterdamensis A18Y020dT. The implications of this bacterium for albatross conservation will require further study.
Detection of Autism Spectrum Disorder Using Graph Representation Learning Algorithms and Deep Neural Network, Based on fMRI Signals
Authors: Yousedian Ali , Shayegh Farzaneh , Maleki Zeinab
Published: June 2022

In this paper, we are going to apply graph representation learning algorithms to identify autism spectrum disorder (ASD) patients within a large brain imaging dataset. Since ASD is characterized by social deficits and repetitive behavioral symptoms, it is mainly identified by brain functional connectivity patterns. Attempts to unveil the neural patterns that emerged from ASD are the essence of ASD classification. We claim that considering the connectivity patterns of the brain can be appropriately executed by graph representation learning methods. These methods can capture the whole structure of the brain, both local and global properties. The investigation is done for the brain imaging worldwide multi-site database known as ABIDE (Autism Brain Imaging Data Exchange). The classifier adapted to the features embedded in graphs is a LeNet deep neural network. Among different graph representation techniques, we used AWE, Node2vec, Struct2vec, multi node2vec, and Graph2Img. The best approach was Graph2Img, in which after extracting the feature vectors representative of the brain nodes, the PCA algorithm is applied to the matrix of feature vectors. Although we could not outperform the previous 70% accuracy of 10-fold cross-validation in the identification of ASD versus control patients in the dataset, for leave-one-site-out cross-validation, we could obtain better results (our accuracy: 80%). It is evident that the effect of graph embedding methods is making the connectivity matrix more suitable for applying to a deep network.
ResMiCo: increasing the quality of metagenome-assembled genomes with deep learning
Authors: Mineeva Olga , Danciu Daniel , Schölkopf Bernhard , Ley Ruth E. , Rätsch Gunnar , Youngblut Nicholas D.
Published: June 2022

The number of published metagenome assemblies is rapidly growing due to advances in sequencing technologies. However, sequencing errors, variable coverage, repetitive genomic regions, and other factors can produce misassemblies, which are challenging to detect for taxonomically novel genomic data. Assembly errors can affect all downstream analyses of the assemblies. Accuracy for the state of the art in reference-free misassembly prediction does not exceed an AUPRC of 0.57, and it is not clear how well these models generalize to real-world data. Here, we present the Residual neural network for Misassembled Contig identification (ResMiCo), a deep learning approach for reference-free identification of misassembled contigs. To develop ResMiCo, we first generated a training dataset of unprecedented size and complexity that can be used for further benchmarking and developments in the field. Through rigorous validation, we show that ResMiCo is substantially more accurate than the state of the art, and the model is robust to novel taxonomic diversity and varying assembly methods. ResMiCo estimated 4.7% misassembled contigs per metagenome across multiple real-world datasets. We demonstrate how ResMiCo can be used to optimize metagenome assembly hyperparameters to improve accuracy, instead of optimizing solely for contiguity. The accuracy, robustness, and ease-of-use of ResMiCo make the tool suitable for general quality control of metagenome assemblies and assembly methodology optimization.

Author summary

Metagenome assembly quality is fundamental to all downstream analyses of such data. The number of metagenome assemblies, especially metagenome-assembled genomes (MAGs), is rapidly increasing, but tools to assess the quality of these assemblies lack the accuracy needed for robust quality control. Moreover, existing models have been trained on datasets lacking complexity and realism, which may limit their generalization to novel data. Due to the limitations of existing models, most studies forgo such approaches and instead rely on CheckM to assess assembly quality, an approach that only utilizes a small portion of all genomic information and does not identify specific misassemblies. We harnessed existing large genomic datasets and high-performance computing to produce a training dataset of unprecedented size and complexity and thereby trained a deep learning model for predicting misassemblies that can robustly generalize to novel taxonomy and varying assembly methodologies.
Early life tolerance depends on a subset of specialized dendritic cells and is reinforced by the skin microbiota
Authors: Weckel Antonin , Dhariwala Miqdad O. , Ly Kevin , Ojewumi Oluwasunmisola T. , Riggs Julianne B. , Gonzalez Jeanmarie R. , Dwyer Laura R. , Okoro Joy N. , Leech John M. , Bacino Margot S. , Cho Grace D. , Merana Geil , Anandasabapathy Niroshana , Kumamoto Yosuke , Scharschmidt Tiffany C.
Published: June 2022

Early life establishment of tolerance to commensal bacteria at barrier surfaces carries enduring implications for immune health but remains poorly understood. Here we show that this process is controlled by microbial interaction with a specialized subset of antigen presenting cells. More particularly, we identify CD301b+ type 2 conventional dendritic cells (DC) as a subset in neonatal skin specifically capable of uptake, presentation and generation of regulatory T cells (Tregs) to commensal antigens. In early life, CD301b+ DC2 are enriched for programs of phagocytosis and maturation, while also expressing tolerogenic markers. In both human and murine skin, these signatures were reinforced by microbial uptake. In contrast to their adult counterparts or other early life DC subsets, neonatal CD301b+ DC2 highly expressed the retinoic acid-producing enzyme, RALDH2, deletion of which limited commensal-specific Tregs. Thus, synergistic interactions between bacteria and a specialized DC subset critically support early life tolerance at the cutaneous interface.
Aging causes changes in transcriptional noise across a diverse set of cell types
Authors: Marti G. Edward W. , Chu Steven , Quake Stephen R.
Published: June 2022

Aging and its associated diseases result from complex changes in cell state which can be examined with single-cell transcriptomic approaches. We analyzed gene expression noise, a measure of cellular heterogeneity, across age and many cell types and tissues using the single cell atlas Tabula Muris Senis, and characterized the noise properties of most coding genes. We developed a quantitative, well-calibrated statistical model of single-cell RNAseq measurement from which we sensitively detected changes in gene expression noise. We found thousands of genes with significantly changing gene expression noise with age. Not all genes had increasing noise with age—many showed a robust decreases of noise. There were clear biological correlation between subsets of genes, with a systemic decrease of noise in oxidative phosphorylation pathways while immune pathways involved in antigen presentation saw an increase. These effects were seen robustly across cell types and tissues, impacting many organs of healthy, aging mice.
Hardware evaluation of spike detection algorithms towards wireless brain machine interfaces
Authors: Oprea Alexandru , Zhang Zheng , Constandinou Timothy G.
Published: June 2022

The current trend for implantable Brain Machine Interfaces (BMIs) is to increase the channel count, towards next generation devices that improve on information transfer rate. This however increases the raw data bandwidth for wired or wireless systems that ultimately impacts the power budget (and thermal dissipation). On-implant feature extraction and/or compression are therefore becoming essential to reduce the data rate, however the processing power is of concern. One common feature extraction technique for intracortical BMIs is spike detection. In this work, we have empirically compared the performance, resource utilization, and power consumption of three hardware efficient spike emphasizers, Non-linear Energy Operator (NEO), Amplitude Slope Operator (ASO) and Energy of Derivative (ED), and two common statistical thresholding mechanisms (using mean or median). We also propose a novel median approximation to address the issue of the median operator not being hardware-efficient to implement. These have all been implemented and evaluated on reconfigurable hardware (FPGA) to estimate their hardware efficiency in an ultimate ASIC design. Our results suggest that ED with average thresholding provides the most hardware efficient (low power/resource) choice, while using median has the advantage of improved detection accuracy and higher robustness on threshold multiplier settings. This work is significant because it is the first to implement and compare the hardware and algorithm trade-offs that have to be made before translating the algorithms into hardware instances to design wireless implantable BMIs.
Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: A New Utility for Deep Reinforcement Learning
Authors: Yang Jenny , Soltan Andrew A. S. , Clifton David A.
Published: June 2022

As machine learning-based models continue to be developed for healthcare applications, greater effort is needed in ensuring that these technologies do not reflect or exacerbate any unwanted or discriminatory biases that may be present in the data. In this study, we introduce a reinforcement learning framework capable of mitigating biases that may have been acquired during data collection. In particular, we evaluated our model for the task of rapidly predicting COVID-19 for patients presenting to hospital emergency departments, and aimed to mitigate any site-specific (hospital) and ethnicity-based biases present in the data. Using a specialized reward function and training procedure, we show that our method achieves clinically-effective screening performances, while significantly improving outcome fairness compared to current benchmarks and state-of-the-art machine learning methods. We performed external validation across three independent hospitals, and additionally tested our method on a patient ICU discharge status task, demonstrating model generalizability.
Serological and Molecular Study on Caprine Brucellosis in Puducherry (India) and its Public Health Significance
Authors: Madan Abhishek , Kumaresan Gururaj , Rekha V Bhanu , Andani Dimple , Mishra Anil Kumar , Kumar VJ Ajay , Jacob Thanislass , Vasudevan P Kavita
Published: June 2022

Caprine brucellosis due to Brucella melitensis is an important zoonotic disease. The present study was carried out to address the lack of a comprehensive study on the status of caprine brucellosis in Puducherry, India using serological and molecular tests in goats and to assess the seroprevalence in human risk groups of the aforementioned region to ascertain the public health significance of the disease. Seroprevalence in 120 goats was found to be zero, 3.33% and 18.33% by Rose Bengal agglutination Test (RBT), Standard Tube Agglutination Test (STAT) and Immunoglobulin G Indirect Enzyme Linked Immune Sorbant Assay (IgG iELISA) respectively. Of the 120 goat genital swabs screened, while conventional polymerase chain reaction (PCR) detected genus specific 16S rRNA and Brucella melitensis specific omp2 genes in 17.50% and 5.00% of samples respectively, the OMP31TaqMan® real time PCR with a positive detection of 40.0 % was both the most sensitive and specific for detection of Brucella melitensis. The study provides insight into the optimization of diagnostic tests following cluster wise sampling for brucellosis in goats. The strain of Brucella melitensis in Puducherry was found to be Biovar 3 based upon suggestive results of Restriction Fragment Length Polymorphism (RFLP) of omp2 gene product. Seroprevalence by IgG iELISA was 33.33 % in 30 samples from human subjects. Serological evidence of caprine brucellosis in goats and human subjects and molecular detection of Brucella melitensis in Puducherry, India warrants regular screening, surveillance and reporting of disease in goats and human risk groups.

IMPORTANCE

Brucellosis is an important zoonotic pathogen causing abortions in domestic animals as well as posing risk to livestock keepers and handlers

Control of this disease requires proper surveillance programme, and in this study the peninsular coastal region of India was sampled by a cluster method and evaluated for brucellosis in goats as well as people at risk

This study compared the diagnostic sensitivity of various serological and molecular tests and found that the OMP31 gene TaqMan probe based Real Time assay to be highly sensitive in diagnosing brucellosis

Similarly, in human subjects exposed to risk factors like animal handlers, veterinarians, livestock keepers the sero-positivity was 33.33% by ELISA
Reverse engineering lateral root stable prebranch site formation; Complementary roles for auxin and auxin signalling
Authors: Teixeira Santos Joana , van den Berg Thea , ten Tusscher Kirsten
Published: June 2022

Priming is the process through which periodic elevations in auxin signalling prepattern future sites for lateral root formation, called prebranch sites. Thusfar is has remained a matter of debate to what extent elevations in auxin concentration and/or auxin signalling are critical for priming and prebranch site formation. Recently, we discovered a reflux-and-growth mechanism for priming generating periodic elevations in auxin concentration that subsequently dissipate. Here we reverse engineer a mechanism for prebranch site formation that translates these transient elevations into a persistent increase in auxin signalling, resolving the prior debate into a two-step process of auxin concentration mediated initial signal and auxin signalling capacity mediated memorization. A critical aspect of the prebranch site formation mechanism is its activation in response to time integrated rather than instantaneous auxin signalling. The proposed mechanism is demonstrated to be consistent with prebranch site auxin signalling dynamics, lateral inhibition and symmetry breaking mechanisms and perturbations in auxin homeostasis.

Summary statement

Using computational modeling we reveal the likely complementary roles of auxin and auxin signalling in one of the earliest step in the formation of plant lateral roots, prebranch site formation.
Molecular Epidemiology and Histopathological Classifications of Lung Cancer in Africa: A Scoping Review Protocol
Authors: Asiamah Emmanuel Akomanin , Hlongwa Mbuzeleni , Nyamande Kennedy , Ginindza Themba Geoffrey
Published: June 2022

Introduction

Lung cancer is a leading cause of death globally and an emerging epidemic in Africa. Recent advances in molecular biomarkers and understanding of the cancer epidemiology and population-based genomic profile for early detection, diagnosis and treatment show promise in reducing incidence and mortality rate. However, this is lacking in Africa. The main objective of this scoping review is to map the evidence on lung cancer molecular epidemiology, genomic profile, and histopathological distributions in Africa.

Methods and analysis

This review will be guided by Arksey and O’Malley’s framework and Levac et al.’s recommendation for methodological enhancement for scoping review studies. A search for keywords from scientific databases (PubMed/MEDLINE, EBSCOhost, SCOPUS and Google Scholar) and grey literature will be conducted for evidence on the molecular epidemiology and histopathological classifications of lung cancer in Africa. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA)-Scoping Review Extension guidelines will be used to report screened results. We will use the PRISMA-ScR checklist to ensure the study adheres to sound methodological rigour acceptable for scoping reviews. The study’s search strategy will include Boolean terms (‘AND’ and ‘OR’) and Medical Subject Heading (MeSH) terms.

Ethics and dissemination

This review will not include animal or human participants. Ethics approval and consent to participate are not applicable. Findings of this scoping review will be disseminated via electronic/social media, conferences, meetings with stakeholders and peer-review publications.

Strengths and limitations of the study

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This review will be the first to identify and map evidence that assesses the molecular epidemiological diversity and histopathological distributions of lung cancer in Africa.

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The summary of evidence obtained from relevant studies in the African context will help understand the genetic diversity of lung cancer among high-risk heterogenous African populations and guide future research towards early detection and targeted therapy in the African context.

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The review will include all available studies in the literature with no time or language restrictions. Thus, studies published in languages apart from English will be translated using an online tool.

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There will be no quality appraisal of the included studies.
Female LSD1 Conditional Knockout Mice Have an Increased Bone Mass
Authors: Astleford-Hopper Kristina , Bradley Elizabeth , Mansky Kim C.
Published: June 2022

Osteoclasts are large multinucleated cells that degrade bone mineral and extracellular matrix. Investigating the mechanisms by which osteoclast differentiation is epigenetically regulated is a key to understanding the pathogenesis of skeletal related diseases such as periodontitis and osteoporosis. Lysine specific demethylase 1 (LSD1/KDM1A) is a member of the histone demethylase family that regulates gene expression via the removal of mono-and dimethyl groups from H3K4 and H3K9. Prior to our study, little was known about the effect of LSD1 on skeletal development and osteoclast differentiation. Here we show conditional deletion of LSD1 in the myeloid lineage results in a decrease in osteoclast differentiation and activity. Furthermore, Lsd1cKO female, but not male, mice have an increased bone mass. Lastly, we demonstrate that LSD1 can form a complex with CoREST, HDAC1 and HDAC2 suggesting a mechanism by which the combination of methylation and acetylation of histone residues regulates osteoclast gene expression.
Is the Naked mole-rat a domestic animal?
Authors: Nájera Guillermo Serrano , Kin Koryu
Published: June 2022

The Naked mole-rat (NMR) is becoming a prominent model organism due to its peculiar traits, such as eusociality, extreme longevity, cancer resistance, and reduced pain sensitivity. It belongs to the African mole-rats (AMRs), a family of subterranean rodents that includes solitary, cooperative breeding and eusocial species. We identified and quantified the domestication syndrome (DS) across AMRs, a set of morphological and behavioural traits significantly more common and pronounced among domesticated animals than in their wild counterparts. Surprisingly, the NMR shows apparent DS traits compared to the solitary AMR. We argue that many of the NMR unconventional traits can be a side-effect of self-domestication. Animals can self-domesticate when a reduction of the fear response is naturally selected, such as in islands with no predators, or to improve the group’s harmony in cooperative breeding species. We propose that self-domestication was necessary to increase social tolerance during the evolution of cooperative breeding and eusociality among AMRs. Finally, we discuss how the DS traits are neutral or beneficial for the subterranean niche and how the increased social tolerance of self-domesticated species could be a side effect of the physical properties of the soil. Our hypothesis provides a novel avenue to enhance the understanding of the extraordinary biology of the NMR.
AutoPX: a new software package to process X-ray diffraction data from biomacromolecular crystals
Authors: Wang Lianyu , Yun Yuehui , Zhu Zhongliang , Niu Liwen
Published: June 2022

A new software package, autoPX, for processing X-ray diffraction data from biomacromolecular crystals is reported. This processing software package is designed on the basis of novel methods such as the location of diffraction spots by an improved Canny operator, indexing by a modified Fourier transform, a novel definition of mosaicity that expresses the dispersion state of reciprocal diffraction spots, and the correction of predicted diffraction spot coordinates by homography transform. New programming of some traditional algorithms necessary for integration and scaling is also included. Several examples of crystal structure determination using data from the SSRF beamlines reduced using autoPX, HKL-2000, DIALS and XDS are also demonstrated, and indicate that autoPX is capable of processing diffraction data from biomacromolecular crystals and providing adequate solutions to problems encountered at the SSRF beamlines.
The construction of an accurate Arabic sentiment analysis system based on resources alteration and approaches comparison
Authors: Touahri Ibtissam
Published: June 2022

Purpose

This paper purposed a multi-facet sentiment analysis system.

Design/methodology/approach

Hence, This paper uses multidomain resources to build a sentiment analysis system. The manual lexicon based features that are extracted from the resources are fed into a machine learning classifier to compare their performance afterward. The manual lexicon is replaced with a custom BOW to deal with its time consuming construction. To help the system run faster and make the model interpretable, this will be performed by employing different existing and custom approaches such as term occurrence, information gain, principal component analysis, semantic clustering, and POS tagging filters.

Findings

The proposed system featured by lexicon extraction automation and characteristics size optimization proved its efficiency when applied to multidomain and benchmark datasets by reaching 93.59% accuracy which makes it competitive to the state-of-the-art systems.

Originality/value

The construction of a custom BOW. Optimizing features based on existing and custom feature selection and clustering approaches.
Customer brand engagement and co-production: an examination of key boundary conditions in the sharing economy
Authors: Casidy Riza , Leckie Civilai , Nyadzayo Munyaradzi Wellington , Johnson Lester W.
Published: June 2022

Purpose

Digital platforms have transformed how brands engage with collaborative consumption actors, such as prosumers. This study aims to examine the role of customer innovativeness and perceived economic value as important boundary conditions on the effects of customer brand engagement behavior on co-production, which subsequently influences customer satisfaction.

Design/methodology/approach

The authors test the model using survey data from 430 users of a digital platform (i.e. UBER) in Australia. Hypotheses were tested using the bias-corrected bootstrapping method.

Findings

The findings suggest that customer innovativeness and perceived economic value positively moderate the effects of customer brand engagement behavior on co-production. Further, the mediating effects of co-production on satisfaction are stronger for highly innovative customers and for those who associate high perceived economic value with the brand.

Research limitations/implications

This study provides novel insights on the boundary conditions of the effects of customer brand engagement behavior on co-production. Future research could apply this study’s conceptual framework to other digital platforms to extend the generalizability of this framework.

Practical implications

This study provides managerial insights into how firms can customize marketing strategies to encourage customers as prosumers in co-production by targeting highly innovative customers and focusing on perceived economic value.

Originality/value

This study builds on service-dominant logic and social exchange theory to examine the role of customer innovativeness and perceived economic value as novel boundary conditions in digital platform ecosystems.
Adoption of the COSO methodology for internal Sharīʿah audit
Authors: Bouheraoua Said , Djafri Fares
Published: June 2022

Purpose

Islamic financial institutions (IFIs) are required to establish a Shariīʿah Governance Framework (SGF) to strengthen their Sharīʿah-compliance mechanism and ensure that all relevant IFI regulations are in line with Sharīʿah rules and principles. Effective implementation of the Shariīʿah-compliance function will further promote stakeholder confidence, as well as the integrity of IFIs, by reducing Shariīʿah non-compliance risks. This study aims to examine the internal control framework developed by the Committee of Sponsoring Organizations of the Treadway Commission (COSO) and explore the extent to which it can be incorporated in the Sharīʿah-compliance function of IFIs.

Design/methodology/approach

This study adopts a qualitative method of inquiry, utilizing the inductive method and content analysis to build comprehensive knowledge that will assist in exploring the framework of COSO methodology and the extent to which it can be adopted by IFIs.

Findings

The findings indicate that the existing frameworks of Sharīʿah governance, whether that of the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) or Bank Negara Malaysia (BNM), need to be further developed. Therefore, the adoption of COSO methodology in the internal Sharīʿah audit of IFIs, as suggested by AAOIFI, is not only possible but desirable. The study also finds that the COSO framework places the highest priority on risk management in that it makes it an integral part of the decision-making process in all the institution's activities. As a result, incorporating the comprehensive COSO risk management structure within the Sharīʿah-compliance function will enhance risk management in IFIs.

Originality/value

This study highlights the importance of the COSO internal control framework and examines its components, principles and the possibility of its adoption by IFIs. The findings of this study are expected to contribute to enhancing the Sharīʿah-compliance function of IFIs.
The role of intellectual capital and service agility in banking service provision: the perspective of Brazilian export companies
Authors: Mataveli Mara , Ayala Calvo Juan-Carlos , Gil Alfonso J.
Published: June 2022

Purpose

Banks in emerging markets such as Brazil provide a wide range of services to companies to facilitate the export process. The objective of the present study was to analyze, from the perspective of Brazilian export companies, the relationships between banking intellectual capital (human and organizational), banking agility, banking technologies and company size in banking service provision.

Design/methodology/approach

A sample of 318 Brazilian export companies was surveyed with questionnaires. The research model was tested using structural equation modeling, namely the partial least squares (PLS-SEM) technique and SmartPLS.

Findings

Banking intellectual capital affects banking service provision, banking agility mediates the relationship between intellectual capitals and banking service provision and technology does not moderate the relationship between agility and banking service provision. The size of the company does not moderate the relationship between intellectual capital and banking service provision.

Practical implications

This work indicates that intellectual capital and the banking agility strategy are critical in the provision of banking service provision for exports.

Originality/value

This work illustrates the effect of banks' intangible resources on the provision of banking services from the perspective of Brazilian export companies.
Maximizing customer adoption outcomes in emerging industrial markets via supplier innovativeness and relationship quality
Authors: Nyadzayo Munyaradzi W. , Casidy Riza , Mohan Mayoor
Published: June 2022

Purpose

This paper aims to examine how suppliers doing business with customers in emerging industrial markets can leverage their innovativeness to foster trust and commitment toward maximizing customer adoption behaviors.

Design/methodology/approach

Based on commitment-trust theory, this research uses survey data collected from a large sample of Chinese business-to-business executives, which were then analyzed using three-stage least squares simultaneous estimation models and PROCESS.

Findings

The results show that supplier innovativeness can help customers build trust in a supplier. Consequently, a reciprocal commitment is forged among customers that manifest in favorable adoption decisions, including a higher willingness to pay premium prices. Notably, this approach is beneficial when robust interfirm communications are difficult to establish.

Originality/value

Innovation decisions in interfirm relationships are important for suppliers doing business in emerging markets. This is because customer adoptions in such settings can foster enduring relational market-based assets and other competitive advantages that can improve supplier performance. Unfortunately, the understanding of how interfirm relationships influence innovation-adoption decisions in emerging markets is lacking. The findings of this research shed light on how suppliers interested in entering emerging markets can interact with customer firms in such settings to maximize favorable adoption outcomes.
Customer reference marketing in internationalizing SMEs: a service perspective
Authors: Tolstoy Daniel , Melén Hånell Sara , Özbek Nurgül
Published: June 2022

Purpose

The purpose of this paper is to create a model that compares the effects of product content differentiation and service content differentiation on small- and medium-sized enterprises’ (SMEs) perceived importance of customer reference marketing in foreign markets.

Design/methodology/approach

A theoretical model is developed and tested through multiple regression and mediation analysis, on an effective sample of 188 Swedish SMEs.

Findings

The results show that foreign market business assignments characterized by differentiated services make companies relatively more dependent on relationship learning and customer reference marketing. By contrast, situations of differentiated product content correlate negatively with customer reference marketing.

Practical implications

Reference customers can function as vehicles for international expansion when marketing offerings are complex. The findings imply that in service settings, SMEs need to maintain learning regimes with foreign market customers to effectively use them as references to win new business.

Originality/value

The study applies a service perspective to explain the contingencies of customer reference marketing, particularly in international business settings. The study contributes to international small business literature and research focusing on service–firm internationalization by explaining the marketing mechanisms at play in the internationalization of SMEs. In so doing, the findings can enrich relationship and network perspectives of internationalization and add a missing link to studies on networking and internationalization.
Greenwashed word of mouth (GWWOM): a vibrant influence on customer green behaviour
Authors: Singh Navjit , Gupta Kritika , Kapur Bharti
Published: June 2022

Purpose

The purpose of this study is to examine the role of greenwashed word of mouth (GWWOM) originating from trickery and misleading green marketing practices on customer behavior. The outcomes of this study are expected to contribute in the domain of responsible green marketing. The significance of this study lies in its ability to provide useful recommendations to marketers, policymakers and customers toward accomplishment of sustainable development goals through usage and adoption of environment-friendly products.

Design/methodology/approach

This study is primarily descriptive in nature, as it attempted to investigate the implications of customers' reactions toward greenwashed practices prevailing in the fast-moving consumer goods (FMCG) market. The information gathered through a self-administered online questionnaire was analyzed using Smart PLS software package to verify the proposed hypotheses. The consistency and validity of the measurement and structural models proposed were tested using inferential statistical procedures.

Findings

The results significantly confirmed the mediating role of GWWOM in shaping the relationship between green skepticism and shift in green behavior. It was verified from the results that customers’ futuristic behavioral patterns toward green products are negatively influenced by misleading and false claims of marketers through GWWOM communications.

Practical implications

The primary implications of this study are for marketers in understanding the role of GWWOM on organizations’ reputation. The policymakers may contribute by implementing appropriate changes in regulations to control greenwashed practices. Finally, customers may become more aware about the unethical marketing practices and act responsibly in the market place.

Originality/value

This study revealed an intriguing finding in the sense that customers, who feel cheated by erroneous and mislead green claims of the marketers, are expected to communicate their experiences through variety of channels. Therefore, it is very likely that they may influence others to change their behaviors while going for environmentally safe products and may have significant consequences on the sustainable consumer behavior.