bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial effects in parasite-induced marine diseases of immobile hosts
Authors: Giménez-Romero Àlex , Vazquez Federico , López Cristóbal , Matías Manuel A.
Published: August 2022

Emerging marine infectious diseases pose a substantial threat to marine ecosystems and the conservation of their biodiversity. Compartmental models of epidemic transmission in marine sessile organisms, available only recently, are based on non-spatial descriptions in which space is homogenized and parasite mobility is not explicitly accounted for. However, in realistic scenarios epidemic transmission is conditioned by the spatial distribution of hosts and the parasites' mobility patterns, calling for an explicit description of space. In this work, we develop a spatially explicit individual-based model to study disease transmission by waterborne parasites in sessile marine populations. We investigate the impact of spatial disease transmission through extensive numerical simulations and theoretical analysis. Specifically, the effects of parasite mobility into the epidemic threshold and the temporal progression of the epidemic are assessed. We show that larger values of pathogen mobility imply more severe epidemics, as the number of infections increases, and shorter timescales to extinction. An analytical expression for the basic reproduction number of the spatial model,

R
~

0

, is derived as a function of the non-spatial counterpart,
R
0
, which characterizes a transition between a disease-free and a propagation phase, in which the disease propagates over a large fraction of the system.
Citation counts and journal impact factors do not capture some indicators of research quality in the behavioural and brain sciences
Authors: Dougherty Michael R. , Horne Zachary
Published: August 2022

Citation data and journal impact factors are important components of faculty dossiers and figure prominently in both promotion decisions and assessments of a researcher’s broader societal impact. Although these metrics play a large role in high-stakes decisions, the evidence is mixed about whether they are strongly correlated with indicators of research quality. We use data from a large-scale dataset comprising 45 144 journal articles with 667 208 statistical tests and data from 190 replication attempts to assess whether citation counts and impact factors predict three indicators of research quality: (i) the accuracy of statistical reporting, (ii) the evidential value of the reported data and (iii) the replicability of a given experimental result. Both citation counts and impact factors were weak and inconsistent predictors of research quality, so defined, and sometimes negatively related to quality. Our findings raise the possibility that citation data and impact factors may be of limited utility in evaluating scientists and their research. We discuss the implications of these findings in light of current incentive structures and discuss alternative approaches to evaluating research.
Flight or protection: the genes
Ultrabithorax
and
apterous
in the determination of membranous and sclerotized wings in insects
Authors: Elias-Neto Moysés , Alvarez Niuska , Ventos-Alfonso Alba , Belles Xavier
Published: August 2022

Present-day pterygote insects have two pairs of wings, one in the mesothorax (T2), the other in the metathorax (T3), and both have diverged in structure and function in different groups. Studies in endopterygote and paraneopteran species have shown that the gene
Ultrabithorax
(
Ubx
) specifies the identity and wing structure in T3, whereas the gene
apterous
(
ap
) significantly contributes to forming modified T2 wings. We wondered whether these
Ubx
and
ap
mechanisms operate in the lineage of polyneopterans. To explore this possibility, we used the cockroach
Blattella germanica
(Polyneoptera and Blattodea), in which the T2 wings are sclerotized (tegmina), whereas those of the T3 are membranous. We found that
Ubx
determines the structure of T3 and the membranous wing, while
ap
significantly contributes to form the sclerotized T2 tegmina. These results along with the studies carried out on the beetle
Tribolium castaneum
by Tomoyasu and collaborators suggest that
ap
plays an important role in the sclerotization and melanization of the T2 wings in neopteran groups that have sclerotized forewings. In turn, the sclerotizing properties of
ap
demonstrated in beetles and cockroaches suggest that the origin of this function goes back to the emergence of Neoptera, in the mid Devonian.
Membrane architects: how positive-strand RNA viruses restructure the cell
Authors: Neufeldt Christopher John , Cortese Mirko
Published: August 2022

Virus infection is a process that requires combined contributions from both virus and host factors. For this process to be efficient within the crowded host environment, viruses have evolved ways to manipulate and reorganize host structures to produce cellular microenvironments. Positive-strand RNA virus replication and assembly occurs in association with cytoplasmic membranes, causing a reorganization of these membranes to create microenvironments that support viral processes. Similarities between virus-induced membrane domains and cellular organelles have led to the description of these structures as virus replication organelles (vRO). Electron microscopy analysis of vROs in positive-strand RNA virus infected cells has revealed surprising morphological similarities between genetically diverse virus species. For all positive-strand RNA viruses, vROs can be categorized into two groups: those that make invaginations into the cellular membranes (In-vRO), and those that cause the production of protrusions from cellular membranes (Pr-vRO), most often in the form of double membrane vesicles (DMVs). In this review, we will discuss the current knowledge on the structure and biogenesis of these two different vRO classes as well as comparing morphology and function of vROs between various positive-strand RNA viruses. Finally, we will discuss recent studies describing pharmaceutical intervention in vRO formation as an avenue to control virus infection.
Data-independent acquisition phosphoproteomics of urinary extracellular vesicles enables renal cell carcinoma grade differentiation
Authors: Hadisurya Marco , Lee Zheng-Chi , Luo Zhuojun , Zhang Guiyuan , Ding Yajie , Zhang Hao , Iliuk Anton B. , Pili Roberto , Boris Ronald S. , Tao W. Andy
Published: August 2022

Translating the research capability and knowledge in cancer signaling into clinical settings has been slow and ineffective. Recently, extracellular vesicles (EVs) have emerged as a promising source for developing disease phosphoprotein markers to monitor disease status. This study focuses on the development of a robust data-independent acquisition (DIA) using mass spectrometry to profile urinary EV phosphoproteomics for renal cell cancer (RCC) grades differentiation. We examined gas-phase fractionated (GPF) library, direct DIA, forbidden zones, and several different windowing schemes. After the development of a DIA mass spectrometry method for EV phosphoproteomics, we applied the strategy to identify and quantify urinary EV phosphoproteomes from 57 individuals representing low-grade clear cell RCC, high-grade clear cell RCC, chronic kidney disease (CKD), and healthy control (HC) individuals. Urinary EVs were efficiently isolated by functional magnetic beads and EV phosphopeptides were subsequently enriched by PolyMAC. We quantified 4,057 unique phosphosites and observed that multiple prominent cancer-related pathways, such as ErbB signaling, renal cell carcinoma, and regulation of actin cytoskeleton, were only upregulated in high-grade clear cell RCC, while those correlated with a higher survival rate were elevated in low-grade clear cell RCC only. These results show that EV phosphoproteome analysis utilizing our optimized procedure of EV isolation, phosphopeptide enrichment, and DIA method provides a powerful tool for future clinical applications.
The association between adiposity and atypical energy-related symptoms of depression: a role for metabolic dysregulations
Authors: Alshehri Tahani , Mook-Kanamori Dennis O , de Mutsert Renée , Penninx Brenda WJH , Rosendaal Frits R , le Cessie Saskia , Milaneschi Yuri
Published: August 2022

Background

Adiposity has been shown to be linked with atypical energy-related symptoms (AES) of depression. We used genomics to separate the effect of adiposity from that of metabolic dysregulations to examine whether the link between obesity and AES is dependent on the presence of metabolic dysregulations.

Method

Data were from NEO (n=5734 individuals) and NESDA (n=2238 individuals) cohorts, in which the Inventory of Depressive Symptomatology (IDS-SR30) was assessed. AES profile was based on four symptoms: increased appetite, increased weight, low energy level, and leaden paralysis. We estimated associations between AES and two genetic risk scores (GRS) indexing increasing total body fat with (metabolically unhealthy adiposity, GRS-MUA) and without (metabolically healthy adiposity, GRS-MHA) metabolic dysregulations.

Results

GRS-MUA and GRS-MHA were both associated with higher total body fat in NEO study, but divergently associated with biomarkers of metabolic health (e.g. fasting glucose and HDL) in both cohorts. In the pooled results, per standard deviation, GRS-MUA was specifically associated with a higher AES score (β=0.03, 95%CI: 0.01; 0.05), while there was no association between GRS-MHA and AES (β=-0.01, 95%CI: -0.03; 0.01).

Conclusion

These results suggest that the established link between adiposity and AES profile emerges in the presence of metabolic dysregulations, which may represent the connecting substrate between the two conditions.
Verbal fluency tests assess global cognitive status but have limited diagnostic differentiation: Evidence from a large-scale examination of six neurodegenerative diseases
Authors: Henderson Shalom K. , Peterson Katie A. , Patterson Karalyn , Lambon Ralph Matthew A. , Rowe James B.
Published: August 2022

Objective

Verbal fluency is clinically widely used but its utility in differentiating between neurodegenerative dementias and progressive aphasias, and from healthy controls, remains unclear. We assessed whether the total number of words produced, their psycholinguistic properties, and production order effects could differentiate between Alzheimer’s disease (AD), behavioural variant of frontotemporal dementia (bvFTD), non-fluent and semantic variants of primary progressive aphasia (PPA), progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), and healthy controls.

Methods

Category and letter fluency tasks were administered to 33 controls and 139 patients at their baseline clinical visit: 18 AD, 16 bvFTD, 26 nfvPPA, 26 svPPA, 36 PSP, and 17 CBS. We assessed group differences for total words, psycholinguistic word properties, and associations between production order and exemplar psycholinguistic properties. Receiver Operating Characteristic (ROC) curves determined which measure could best discriminate patient groups and controls.

Results

Total word count distinguished controls from all patient groups, but neither this measure nor the word properties differentiated the patient groups. ROC curves revealed that, when comparing controls to patients, the strongest discriminators were total word count followed by word frequency. Word frequency was the strongest discriminator for svPPA versus other groups. Fluency word counts were associated with global severity as measured by Addenbrooke’s Cognitive Examination-Revised (ACE-R).

Conclusions

Verbal fluency is an efficient test for assessing global brain-cognitive health but has limited utility in differentiating between cognitively- and anatomically-disparate patient groups. This outcome is consistent with the fact that verbal fluency requires many different aspects of higher cognition and language.
Exogenous sequences in tumors and immune cells (exotic): a tool for estimating the microbe abundances in tumor RNAseq data
Authors: Hoyd Rebecca , Wheeler Caroline E , Liu YunZhou , Singh Malvenderjit Jagjit , Muniak Mitchell , Denko Nicolas , Carbone David , Mo Xiaokui , Spakowicz Daniel
Published: August 2022

The microbiome affects cancer, from carcinogenesis to response to treatments. New evidence suggests that microbes are also present in many tumors, though the scope of how they affect tumor biology and clinical outcomes is unclear. A broad survey of tumor microbiome samples across several independent datasets is needed to identify robust correlations for follow-up testing. We created a tool to carefully identify the tumor microbiome within RNAseq datasets and then applied it to samples collected through the Oncology Research Information Exchange Network (ORIEN) and The Cancer Genome Atlas (TCGA). We showed how the processing removes contaminants and batch effects to yield microbe abundances consistent with non-high-throughput sequencing-based approaches. We sought to establish clinical relevance by correlating the microbe abundances with various clinical and tumor measurements, such as age and tumor hypoxia. This process leveraged the two datasets and raised up only the concordant (significant and in the same direction) associations. We identify associations with survival and clinical variables that are highly cancer-specific and relatively few associations with immune composition. Finally, we explore potential mechanisms by which microbes and tumors may interact using a network approach. Alistipes, a common gut commensal, showed the highest network degree centrality and was associated with genes related to metabolism and inflammation. The exotic tool can support the discovery of microbes in tumors in a way that leverages the many existing and growing RNAseq datasets.

Statement of Significance

The intrinsic tumor microbiome holds great potential for its ability to predict various aspects of cancer biology and as a target for rational manipulation. Here, we describe a tool to quantify microbes from within tumor RNAseq and apply it to two independent datasets. We show new associations with clinical variables that justify biomarker uses and more experimentation into the mechanisms by which tumor microbiomes affect cancer outcomes.
A Neural Index Reflecting the Amount of Cognitive Resources Available during Memory Encoding: A Model-based Approach
Authors: Ma Si , Popov Vencislav , Zhang Qiong
Published: August 2022

Humans have a limited amount of cognitive resources to process various cognitive operations at a given moment. The Source of Activation Confusion (SAC) model of episodic memory proposes that resources are consumed during each processing and once depleted they need time to recover gradually. This has been supported by a series of behavioral findings in the past. However, the neural substrate of the resources is not known. In the present study, over an existing EEG dataset of a free recall task (Kahana et al., 2022), we provided a neural index reflecting the amount of cognitive resources available for forming new memory traces. Unique to our approach, we obtained the neural index not through correlating neural patterns with behavior outcomes or experimental conditions, but by demonstrating its alignment with a latent quantity of cognitive resources inferred from the SAC model. In addition, we showed that the identified neural index can be used to propose novel hypothesis regarding other long-term memory phenomena. Specifically, we found that according to the neural index, neural encoding patterns for subsequently recalled items correspond to greater available cognitive resources compared with that for subsequently unrecalled items. This provides a mechanistic account for the long-established subsequent memory effects (SMEs, i.e. differential neural encoding patterns between subsequently recalled versus subsequently unrecalled items), which has been previously associated with attention, fatigue and properties of the stimuli.
Transcriptomic and epigenetic assessment of ageing male skin identifies disruption of Ca2+homeostasis; exacerbated by smoking and UV exposure
Authors: Pease Louise I. , Wordsworth James , Shanley Daryl
Published: August 2022

Skin ageing has been widely associated with the formation and presence of increasing quantities of senescent cells, the presence of which are thought to reduce cell renewal. This study aimed to identify key factors influencing fibroblast and skin aging in European males using RNA-seq data. Key differences in study designs included known sources of biological differences (sex, age, ethnicity), experimental differences, and environmental factors known to accelerate skin ageing (smoking, UV exposure) as well as study specific batch effects which complicated the analysis. To overcome these complications samples were stratified by these factors and differential expression assessed using Salmon and CuffDiff. Functional enrichment and consistency across studies, stratification’s and tools identified age related alterations in the transcriptomes of fibroblasts and skin. Functional enrichment of results identified alterations in protein targeting to membranes and the ER, and altered calcium homeostasis in aged fibroblasts. Extension to skin controlled for differences in fibroblast culturing methods confirming transient age related alterations in intracellular calcium homeostasis. In middle aged males (40-65) increased keratinisation, skin, epithelial and epidermal development was seen in conjunction with alterations to ER Ca2+uptake, leading to the identification of related processes including; an unfolded protein response, altered metabolism, increased MMP expression, and altered Ca2+handling, which were further exacerbated by UV-exposure. Interestingly the genes and processes subsequently decreased in old males (> 65), which exhibited signs of increased senescence. Extension to Illumina 450k array data from ageing skin uncovered evidence of epigenetic regulation; genes and isoforms with overlapping differentially methylated CpGs were differentially expressed. Smoking led to additional enrichment of genes relating to tissue development, cell adhesion, vasculature development, peptide cross-linking, calcium homeostasis, cancer and senescence. The results consistently identified alterations in ER and golgi Ca2+uptake, which disrupt intracellular and extracellular calcium gradients that regulate metabolic and differentiation signalling in skin and fibroblasts, leading to age related declines skin structure and function. Interestingly many diseases and infections with overlapping molecular consequences, (ER Ca2+stress, reduced protein targeting to membranes) including COVID-19 are identified by the analysis, suggesting that COVID-19 infection compounds pre-existing cellular stresses in aged males, which could help explain higher COVID-19 mortality rates in aged males, as well as highlighting potential ways to reduce them.
Probe set selection for targeted spatial transcriptomics
Authors: Kuemmerle Louis B. , Luecken Malte D. , Firsova Alexandra B. , de Andrade e Sousa Lisa Barros , Straßer Lena , Heumos Lukas , Mekki Ilhem Isra , Mahbubani Krishnaa T. , Sountoulidis Alexandros , Balassa Tamás , Kovacs Ferenc , Horvath Peter , Piraud Marie , Ertürk Ali , Samakovlis Christos , Theis Fabian J.
Published: August 2022

Targeted spatial transcriptomics methods capture the topology of cell types and states in tissues at single cell- and subcellular resolution by measuring the expression of a predefined set of genes. The selection of an optimal set of probed genes is crucial for capturing and interpreting the spatial signals present in a tissue. However, current selections often rely on marker genes, precluding them from detecting continuous spatial signals or novel states. We present Spapros, an end-to-end probe set selection pipeline that optimizes both probe set specificity for cell type identification and within-cell-type expression variation to resolve spatially distinct populations while taking into account prior knowledge, as well as probe design and expression constraints. To facilitate data analysis and interpretation, Spapros also provides rules for cell type identification. We evaluated Spapros by selecting probes on 6 different data sets and built an evaluation pipeline with 12 quality metrics to find that Spapros outperforms other selection approaches in both cell type recovery and recovering expression variation beyond cell types. Furthermore, we used Spapros to design a SCRINSHOT experiment of adult lung tissue to demonstrate how probes selected with Spapros identify cell types of interest and detect spatial variation even within cell types. Spapros enables optimal probe set selection, probe set evaluation, and probe design, as a freely available Python package.
Red blood cell lingering modulates hematocrit distribution in the microcirculation
Authors: Rashidi Yazdan , Simionato Greta , Zhou Qi , John Thomas , Kihm Alexander , Bendaoud Mohammed , Krüger Timm , Bernabeu Miguel O. , Kaestner Lars , Laschke Matthias W. , Menger Michael D. , Wagner Christian , Darras Alexis
Published: August 2022

The distribution of red blood cells (RBCs) in the microcirculation determines the oxygen delivery and solute transport to tissues. This process relies on the partitioning of RBCs at successive bifurcations throughout the microvascular network and it is known since the last century that RBCs partition disproportionately to the fractional blood flow rate, therefore leading to heterogeneity of the hematocrit (i.e. volume fraction of RBCs in blood) in microvessels. Usually, downstream of a microvascular bifurcation, the vessel branch with a higher fraction of blood flow receives an even higher fraction of RBC flux. However, both temporal and time-average deviations from this phaseseparation law have been observed in recent works. Here, we quantify how the microscopic behavior of RBCs lingering (i.e. RBCs temporarily residing near the bifurcation apex with diminished velocity) influences their partitioning, through combined in vivo experiments and in silico simulations. We developed an approach to quantify the cell lingering at highly-confined capillary-level bifurcations and demonstrate that it correlates with deviations of the phase-separation process from established empirical predictions by Pries et al. Furthermore, we shed light on how the bifurcation geometry and cell membrane rigidity can affect the lingering behavior of RBCs, e.g. rigid cells tend to linger less than softer ones. Taken together, RBC lingering is an important mechanism that should be considered when studying how abnormal RBC rigidity in diseases such as malaria and sickle-cell disease could hinder the microcirculatory blood flow or how the vascular networks are altered under pathological conditions (e.g. thrombosis, aneurysm).
Enhanced methionine cycle suppresses naïve CD8+ T-cell maturation
Authors: Saragovi A , Zheng X , Abramovich I , Cohen-Daniel L , Zhuoning L , Raifer H , Omar I , Swisa A , Kuchersky M , Drori A , Marini F , Toker O , Somech R , Schmidl Ch , Hendrickson RC , Gottlieb E , Huber M , Berger M
Published: August 2022

The metabolic pathways controlling naive CD8+ T (Tn) cell maturation following thymic egress remain mostly undefined. This is important because immature Tn are a major component of peripheral immune tolerance in newborns and under lymphopenia. In this study we demonstrate that TMRM, a mitochondrial membrane potential marker, could be applied to rapidly identify an immature Tn cell population in the periphery. Applying this marker to perform metabolic and proteomic analysis, we show that immature Tn cells maintain accelerated methionine cycle in respect to mature Tn. This unique metabolic state was associated with restricted Tbx21 locus and diminished immune response in vitro and in vivo. Following our findings, we demonstrate that inhibition of methionine cycle leads to rapid functional maturation of Tn and recovery of immune response to stimuli. Our work provides insight into the way the rate of methionine cycling regulates T cell maturation, opening a path for metabolic manipulation of immune tolerance.
Leaf side determines the relative importance of dispersal versus host filtering in the phyllosphere microbiome
Authors: Smets Wenke , Chock Mason K , Walsh Corinne M , Vanderburgh Caihong Qiu , Kau Ethan , Lindow Steve E , Fierer Noah , Koskella Britt
Published: August 2022

Leaf surface-associated bacterial communities play a significant role in plant health and have therefore been the focus of increasing interest. Despite this, we currently lack a predictive understanding of how leaf-associated bacterial communities are structured within and across hosts, including how leaf traits shape this variation and how community assembly processes may differ across distinct microbial habitats on a leaf. In this study, we characterize the composition of bacterial phyllosphere communities from the upper and lower leaf surfaces of 66 plants across 24 species grown at a common site using 16S rRNA amplicon sequencing. By comparing leaves that vary in pH and stomatal densities and analyzing the leaf surfaces separately, we were able to test the key factors shaping the phyllosphere across host plant species from diverse geographical origins. We found a surprisingly large shared/core microbiome across species, as well as a strong effect of plant species and native origin in shaping composition. Importantly, we found the lower leaf side, where pH values are generally lower and stomatal densities higher, to have lower taxonomic richness relative to the upper leaf side. While the upper leaf side community appears to be more strongly influenced by dispersal effects, the lower leaf appears to be more strongly influenced by plant host filtering effects, as supported by higher relative abundance of shared core taxa and higher signatures of endemism. This work highlights important differences in community assembly processes across the upper and lower leaf microbiomes and underscores the importance of considering differences among habitats within a host when explaining microbial community assembly and composition.
Resistance screening and in-silico characterization of cloned novel RGA from multi race resistant Lentil germplasm against Fusarium wilt (Fusarium oxysporum f. sp. lentis)
Authors: Nishmitha K , Singh Rakesh , Dubey Sunil C , Akthar Jameel , Kamil Deeba
Published: August 2022

Fusarium wilt caused by Fusarium oxysporum f. sp. lentis (Fol) is the most devastating disease of lentil present worldwide and in India. Identification of multi-race fusarium wilt resistance genes and incorporation into existing cultivar will help to reduce yield loss. In the present study, a hundred lentil germplasm were screened against seven prevalent races of Fol and accession IC201561, EC714243 and EC718238 were identified resistant. The typical R gene codes for the nucleotide-binding site and leucine-rich repeats (NBS-LRR) at the C terminal linked to either Toll/interleukin 1-like receptor (TIR) or coiled-coil (CC) at the N terminal. In the present study degenerate primers designed from the NBS region amplifying P-loop to GLPLA motif isolated forty-five resistance gene analogues (RGA) from identified resistant accessions. The sequence alignment identified both classes of RGA, TIR and non-TIR based on the presence of Aspartate (D) and Tryptophan (W) at the end of kinase motif respectively. The phylogenetic analysis grouped RGA into six classes, LRGA1 to LRGA6 determining the diversity of RGA present in the host. Grouping of RGA identified from Lens nigricans, LnRGA 2, 9, 13 with I2 reveals a probable role in Fusarium resistance. The similarity index of 27.85% to 86.98% was found among RGA and 26.83% to 49.41% between known R genes, I2, Gpa2, M and L6. Active binding sites present along the conserved motifs have grouped the RGA into 13 groups. ADP/ATP being the potential ligand determines ATP binding and ATP hydrolysis activity of RGA. The isolated RGA can be used in developing marker linked to the functional R gene. Further, expression analysis and full-length gene isolation further pave path to identifying the molecular mechanism involved in resistance.
Deriving Schwann Cells from hPSCs Enables Disease Modeling and Drug Discovery for Diabetic Peripheral Neuropathy
Authors: Majd Homa , Amin Sadaf , Ghazizadeh Zaniar , Cesiulis Andrius , Arroyo Edgardo , Lankford Karen , Farahvashi Sina , Chemel Angeline K. , Okoye Mesomachukwu , Scantlen Megan D. , Tchieu Jason , Calder Elizabeth L. , Le Rouzic Valerie , Arab Abolfazl , Goodarzi Hani , Pasternak Gavril , Kocsis Jeffery D. , Chen Shuibing , Studer Lorenz , Fattahi Faranak
Published: August 2022

Schwann cells (SCs) are the myelinating and non-myelinating glia of the peripheral nervous system (PNS) and are essential for its function. Defects in SCs are associated with many PNS disorders including diabetic peripheral neuropathy (DPN), a condition affecting millions of patients. Here we present a strategy for deriving and purifying SCs from human pluripotent stem cells (hPSCs). The scalable cultures of SCs allow basic and translational applications such as high-resolution molecular and functional characterization, developmental studies, modeling and mechanistic understanding of SC diseases and drug discovery. Our hPSC-derived SCs recapitulate the key molecular features of primary SCs and are capable of engrafting efficiently and producing myelin in injured sciatic nerves in rats. We further established an hPSC-based in vitro model of DPN that revealed the selective vulnerability of human SCs to hyperglycemia-induced cytotoxicity. We established a high-throughput screening system that identified a candidate drug that counteracts glucose-mediated cytotoxicity in SCs and normalizes glucose-induced transcriptional and metabolic abnormalities in SCs. Treatment of hyperglycemic mice with this drug candidate rescues sensory function, prevents SC death, and counteracts myelin damage in sciatic nerves suggesting considerable potential as a novel treatment for DPN.
Development and evaluation of statistical and Artificial Intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production
Authors: Beck Kristen L. , Haiminen Niina , Agarwal Akshay , Carrieri Anna Paola , Madgwick Matthew , Kelly Jennifer , Pylro Victor , Kawas Ban , Wiedmann Martin , Ganda Erika
Published: August 2022

The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. These methods could be used to identify ingredients that deviate from their typical microbial composition, which could indicate food fraud or safety issues. The objective of this study was to assess the feasibility of using shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. Contrastive PCA, cluster-based methods, and explainable AI were evaluated for the detection of two anomalous sample classes using longitudinal metagenomic profiling of fluid milk compared to baseline samples collected under comparable circumstances. Traditional methods (alpha and beta diversity, clustering-based contrastive PCA, MDS, and dendrograms) failed to differentiate anomalous sample classes; however, explainable AI was able to classify anomalous vs. baseline samples and indicate microbial drivers in association with antibiotic use. We validated the potential for explainable AI to classify different milk sources using larger publicly available fluid milk 16s rDNA sequencing datasets and demonstrated that explainable AI is able to differentiate between milk storage methods, processing stage, and season. Our results indicate the application of artificial intelligence continues to hold promise in the realm of microbiome data analysis and could present further opportunities for downstream analytic automation to aid in food safety and quality.

IMPORTANCE

We evaluated the feasibility of using untargeted metagenomic se-quencing of raw milk for detecting anomalous food ingredient content with artificial intelligence methods in a study specifically designed to test this hypothesis. We also show through analysis of publicly available fluid milk microbial data that our artificial intelligence approach is able to successfully predict milk in different stages of process-ing. The approach could potentially be applied in the food industry for safety and quality control.
Molecular docking studies of potential inhibitors of acyl carrier protein and acetyl CoA Carboxylase in Plasmodium falciparum
Authors: Salifu Elliasu Y. , Rashid Issahaku A. , Abugri James , Osei Festus , Ayariga Joseph Atia
Published: August 2022

Malaria caused by Plasmodium falciparum, remains one of the most fatal parasitic diseases that has affected nearly a third of the world’s population. The major impediment to the treatment of malaria is the emergence of resistance of the P. falciparum parasite to current anti-malaria therapeutics such as Artemisinin (ART)-based combination therapy (ACT). This has resulted in countless efforts to develop novel therapeutics that will counter this resistance with the aim to control and eradicate the disease. The application of in silico modelling techniques has gained a lot of recognition in antimalarial research in recent times through the identification of biological components of the parasite for rational drug design. In this study we employed various in silico techniques such as the Virtual screening, molecular docking and molecular dynamic simulations to identify potential new inhibitors of biotin acetyl-coenzyme A (CoA) carboxylase and enoyl-acyl carrier reductase, two enzyme targets that play a crucial role in fatty acid synthesis in the Plasmodium parasite. Initially, 9 hit compounds were identified for each of the two enzymes from the ZincPharmer database. Subsequently, all hit compounds bind favourably to the active sites of the two enzymes as well as show excellent pharmacokinetic properties. Three (3) of the hits for the biotin acetyl-coenzyme A (CoA) carboxylase and six (6) of the enoyl-acyl carrier reductase showed good toxicity properties. The compounds were further evaluated based on the Molecular Dynamics (MD) simulation that confirmed the binding stability of the compounds to the targeted proteins. Overall, the lead compounds Zinc38980461, Zinc05378039, and Zinc15772056, were identified for acetyl-coenzyme A (CoA) carboxylase whiles zinc94085628, zinc93656835, zinc94080670, zinc1774609, zinc94821232 and Zinc94919772 were identified as lead compounds for enoyl-acyl carrier reductase. The identified compounds can be developed as a treatment option for the malaria disease although, experimental validation is suggested for further evaluation of the work.
UBA52 is crucial in HSP90 ubiquitylation and neurodegenerative signaling during early phase of Parkinson’s disease
Authors: Tiwari Shubhangini , Singh Abhishek , Gupta Parul , Singh Sarika
Published: August 2022

Protein aggregation is one of the major pathological events in age-related Parkinson’s disease (PD) pathology, predominantly regulated by the ubiquitin-proteasome system (UPS). UPS essentially requires core component ubiquitin however, its role in PD pathology is obscure. This study aimed to investigate the role of ubiquitin encoding genes in the early phase of PD pathology. Wild-type human Myc-α-synuclein transfected neurons, α-synuclein-PFFs treated cells, rotenone-induced sporadic models of PD and SNCA C57BL/6J-Tg (Th-SNCA*A30P*A53T)39 Eric/J transgenic mice showed downregulated level of UBA52 in conjunction with significant downregulation of tyrosine hydroxylase (TH) and neuronal death. In silico predictions, mass spectrometric analysis and co-immunoprecipitation findings suggested strong interaction of UBA52 with α-synuclein, HSP90 and E3-ubiquitin ligase CHIP, besides its co-localization with α-synuclein in the mitochondrion. Next, in vitro ubiquitylation assay indicated an imperative requirement of the lysine-63 residue of UBA52 in CHIP-mediated HSP90 ubiquitylation. Myc-UBA52 expressed neurons exhibited the downregulated α-synuclein protein abundance with increased TH and restored proteasome activity during the diseased condition. Furthermore, Myc-UBA52 expression inhibited the augmented HSP90 protein level along with its various client proteins, HSP75 (homologue of HSP90 in mitochondrion) and ER stress-related markers during early PD. Taken together, data highlights the critical role of UBA52 in HSP90 ubiquitylation in parallel to its potential contribution to the modulation of various disease-related neurodegenerative signaling targets during the early phase of PD pathology.
Using the ANDROMEDA by Prosilico Software for Prediction of the Human Pharmacokinetics of 4 Compounds of Natural Origin - Colistin, Curucumin, UCN-01 and Voclosporin
Authors: Fagerholm Urban , Hellberg Sven , Alvarsson Jonathan , Spjuth Ola
Published: August 2022

Abstract

Background

It is important that pharmacokinetic (PK) prediction methods are validated, and also for compounds with varying physicochemical properties, molecular weights and PK characteristics.

Methods

The objective was to investigate how well the ANDROMEDA by Prosilico software predicts the clinical PK of four compounds of natural origin and with PK obstacles, not yet fully characterized PK, and/or inaccurate lab method-based predictions - colistin (negligible absorption, good metabolic stability, significant excretion), curucumin (low solubility, apparently poor bioavailability), UCN-01 (extremely high degree of plasma protein binding, metabolic stability, long half-life and poor PK prediction) and voclosporin (poorly understood PK).

Results

All categorial predictions except one were correct, and the median prediction error was 2.5-fold. Largest prediction errors were found for the unbound fraction in plasma (>24-fold), clearance (178-fold) and half-life (90-fold) of UCN-01. Corresponding errors for clearance and half-life obtained with allometry were greater, 5800- and 145-fold, respectively. Extremely high affinity for alpha1-acid glycoprotein could explain these large prediction errors for this compound. A substantial amount of data and knowledge was added with the predictions.

Conclusion

Despite challenging compounds and PK, predictions were comparably good. The results further validated ANDROMEDA by Prosilico for human clinical PK-predictions.
Numerical calculation of inchworm actuator reliability: effect of space temperature and material parameters
Authors: Dong Hangjia , Li Tuanjie , Wang Zuowei , Ning Yuming
Published: August 2022

Purpose

The inchworm actuator is widely applied in space industry. One of the major issues in space instrumentation is the reliability, especially under space thermal load. The purpose of this paper is to present a numerical calculation method for the inchworm actuator reliability with considering the effect of space temperature.

Design/methodology/approach

First, the structure of designed inchworm actuator is introduced, and the main failure reason is analyzed. Then the wear model is proposed with considering the space temperature, and an experiment device is designed to verify the wear model. Finally, the reliability calculation method is developed based on the working principle of the inchworm actuator.

Findings

The numerical calculation method can be applied to calculate the reliability of the inchworm actuator with considering the space temperature. And the results provide a new perspective to discuss the influences of the temperature and driving voltage on the reliability of inchworm actuators.

Originality/value

This work presents a reliability calculation method of inchworm actuators with considering the space temperature.
Hostile takeover threats, managerial myopia and asset redeployability
Authors: Chatjuthamard Pattanaporn , Boonlert-U-Thai Kriengkrai , Jiraporn Pornsit , Uyar Ali , Kilic Merve
Published: August 2022

Purpose

Exploiting two novel measures of takeover vulnerability and asset redeployability, this paper aims to investigate the effect of the takeover market on redeployable assets. Redeployable assets are those with alternative uses. Asset redeployability is a crucial concept in the literature on investment irreversibility.

Design/methodology/approach

In addition to the standard regression analysis, the authors execute several robustness checks: propensity score matching, entropy balancing, instrumental-variable analysis and generalized method of moment dynamic panel data analysis.

Findings

The authors’ results reveal that more takeover threats reduce asset redeployability significantly, corroborating the managerial myopia hypothesis. Hostile takeover threats reduce managers’ job security and thus induce them to myopically focus on the current utilization of assets in the short run, rather than how they may be deployed in the long run, resulting in less asset redeployability.

Originality/value

To the best of the authors’ knowledge, this study is the first to investigate the effect of takeover threats on asset redeployability. Because the authors’ measure of takeover vulnerability is principally based on the staggered passage of state legislations, which are plausibly exogenous, the authors’ results likely reflect causality, rather than merely an association.
Service failure research in the hospitality and tourism industry: a synopsis of past, present and future dynamics from 2001 to 2020
Authors: Akarsu Tugra Nazli , Marvi Reza , Foroudi Pantea
Published: August 2022

Purpose

When service failure occurs, it leads to dissatisfaction, lack of trust and avoidance behaviour among customers, and it can also be seen as a threat to the survival of the business. This paper aims to investigate the current and potential dynamics of service failure research within the tourism and hospitality area.

Design/methodology/approach

By adopting qualitative, quantitative (citation and text mining) and science-mapping tools (descriptive, conceptual and intellectual), this study analyses 99 key papers on service failure in 18 major hospitality and tourism journals over a 20-year span.

Findings

The research on service recovery strategies, recovery efforts, pre- and post-failure and post-recovery in the service encounter and the impacts of justice on post-recovery and post-complaint behaviour are identified as the major streams of service failure research. While emotional labour, rumination and satisfaction recovery were identified as emerging themes, service failure perceptions and social media were found as the developed and substantial trends.

Practical implications

This study presents a comprehensive understanding of service failure research development in the hospitality and tourism industry. This study propose three areas – circumstantial cues, interactional cues and crisis management – that practitioners need to understand to minimise service failure during the service interaction.

Originality/value

To the best of the authors’ knowledge, no prior bibliometric study has investigated the current and future dynamics of service failure in the hospitality and tourism industry and offered a research agenda based on this gap in the literature.
Japanese industrial technological structure based on the number of patent applications by technical field
Authors: Yamada Hirokazu
Published: August 2022

Purpose

This research outlines the technological structure of the entire Japanese manufacturing and service industry using the patent information from research and development (R&D) activities to set R&D goals.

Design/methodology/approach

By analyzing the technological development capability of individual companies, the direction of the companies' R&D activities and current state of technological fusion between them can be understood. A group of companies participating in a particular product/service market must have the same technological development capabilities. As a result, the ratio of patent applications by a company to the total number of applications in a technical field will be similar across companies. This study uses the inter-company correlation coefficient of the ratio of patent applications by technical field as an index of technological development capability. A total of 167 major companies covering the major industries of Japan were analyzed. The analysis period was 15 years from 2004 to 2018, and the technical fields were rearranged to 42 fields with reference to the International Patent Classification (IPC)-Technology Concordance used by the World Intellectual Property Organization (WIPO). Considering the fluctuation in patent application opportunities, the number of patent applications was collected for at least three years for the analysis of patent applications by technical field, company and industry.

Findings

Examining the entire Japanese industry, the research found that chemicals, ceramics, non-ferrous metals and electrical/electronic equipment act as intermediaries between the respective groups and are linked to the transportation equipment, electrical/electronic equipment and information and communication services industries that are currently driving the Japanese economy. However, the technical connections between these groups are relatively loose. Over the last 15 years, the propagation structure of technical knowledge information has not changed. The progress of technological fusion remains within the scope of commerce and is conditioned by commerce.

Originality/value

Studies focusing on the technological development capability between companies and the technological structure of the Japanese manufacturing and service industries are almost non-existent since 2000 when Japan's economic growth slowed. The analytical methods presented in this research can be applied to individual companies to gain an understanding of technical positions of companies and can be useful for planning a technical environment, business or R&D strategy.
Risks of data-driven technologies in sustainable supply chain management
Authors: Ozkan-Ozen Yesim Deniz , Sezer Deniz , Ozbiltekin-Pala Melisa , Kazancoglu Yigit
Published: August 2022

Purpose

With the rapid change that has taken place with digitalization and data-driven approaches in supply chains, business environment become more competitive and reaching sustainability in supply chains become even more challenging. In order to manage supply chains properly, in terms of considering environmental, social and economic impacts, organizations need to deal with huge amount of data and improve organizations' data management skills. From this view, increased number of stakeholders and dynamic environment reveal the importance of data-driven technologies in sustainable supply chains. This complex structure results in new kind of risks caused by data-driven technologies. Therefore, the aim of the study to analyze potential risks related to data privacy, trust, data availability, information sharing and traceability, i.e. in sustainable supply chains.

Design/methodology/approach

A hybrid multi-criteria decision-making (MCDM) model, which is the integration of step-wise weight assessment ratio analysis (SWARA) and TOmada de Decisao Interativa Multicriterio (TODIM) methods, is going to be used to prioritize potential risks and reveal the most critical sustainability dimension that is affected from these risks.

Findings

Results showed that economic dimension of the sustainable supply chain management (SSCM) is the most critical concept while evaluating risks caused by data-driven technologies. On the other hand, risk of data security, risk of data privacy and weakness of information technology systems and infrastructure are revealed as the most important risks that organizations should consider.

Originality/value

The contribution of the study is expected to guide policymakers and practitioners in terms of defining potential risks causes by data-driven technologies in sustainable supply chains. In future studies, solutions can be suggested based on these risks for achieving sustainability in all stages of the supply chain causes by data-driven technologies.