bluuebunny/crossref_metadata_2025 huggingface dataset:
Global terrestrial nitrogen uptake and nitrogen use efficiency
Authors: Peng Yunke , Prentice Iain Colin , Bloomfield Keith J. , Campioli Matteo , Guo Zhiwen , Sun Yuanfeng , Tian Di , Wang Xiangping , Vicca Sara , Stocker Benjamin D.
Published: November 2022

Plant biomass production (BP), nitrogen uptake (Nup) and their ratio, nitrogen use efficiency (NUE), must be quantified to understand how nitrogen (N) cycling constrains terrestrial carbon (C) uptake. But the controls of key plant processes determiningNupand NUE, including BP, C and N allocation, tissue C:N ratios and N resorption efficiency (NRE), remain poorly known. We compiled measurements from 804 forest and grassland sites and derived regression models for each of these processes with growth temperature, vapour pressure deficit, stand age, soil C:N ratio, fAPAR (remotely sensed fraction of photosynthetically active radiation absorbed by green vegetation) and growing-season average daily incident photosynthetic photon flux density (gPPFD) (effectively the seasonal concentration of light availability, which increases polewards) as predictors. An empirical model for leaf N was based on optimal photosynthetic capacity (a function of gPPFD and climate) and observed leaf mass-per-area. The models were used to produce global maps ofNupand NUE. Global BP was estimated as 72 Pg C/yr;Nupas 950 Tg N/yr; and NUE as 76 gC/gN. Forest BP was found to increase with growth temperature and fAPAR and to decrease with stand age, soil C:N ratio and gPPFD. Forest NUE is controlled primarily by climate through its effect on C allocation – especially to leaves, being richer in N than other tissues. NUE is greater in colder climates, where N is less readily available, because belowground allocation is increased. NUE is also greater in drier climates because leaf allocation is reduced. NRE is enhanced (further promoting NUE) in both cold and dry climates. These findings can provide observationally based benchmarks for model representations of C–N cycle coupling. State-of-the-art vegetation models in the TRENDY ensemble showed variable performance against these benchmarks, and models including coupled C–N cycling produced relatively poor simulations ofNupand NUE.
Research and conservation priorities to protect wildlife from collisions with vehicles
Authors: Medrano-Vizcaíno Pablo , Grilo Clara , González-Suárez Manuela
Published: November 2022

The rapidly expanding global road network poses threats to wildlife, including direct mortality. Given limited knowledge and resources, strategic allocation is critical. We introduce a method to identify priority areas and taxa to study and protect affected by vehicle collisions using Latin America as a case study. In this region high biodiversity and an expanding road network can result in high impacts from roads, yet emerging research expertise offers opportunities for action. To identify priority targets we combined predicted spatially-explicit roadkill rates for birds and mammals with information about the current road network and species conservation status. Priority areas for conservation (with many species susceptible to roadkill but few or inexistent roads) were largely concentrated in the Amazon; while priority areas for research (unstudied regions with many roads and many species susceptible to roadkill) occur in various areas from Southern Mexico to Chile. Priority taxa for conservation reflected studied, roadkill-susceptible groups (eg, vultures and armadillos), while priority taxa for research were defined as either poorly-studied roadkill-susceptible groups or unstudied groups of conservation concern (eg, cuckoos and shrew opossums). Our approach offers a tool that could be applied to other areas and taxa to facilitate a more strategic allocation of resources in conservation and research in road ecology.
Identifying cross-lineage dependencies of cell-type specific regulators in gastruloids
Authors: Braccioli Luca , van den Brand Teun , Saiz Noemi Alonso , Fountas Charis , Celie Patrick H. N. , Kazokaitė-Adomaitienė Justina , de Wit Elzo
Published: November 2022

Correct gene expression levels in space and time are crucial for normal development. Advances in genomics enable the inference of gene regulatory programs that are active during development. However, this approach cannot capture the complex multicellular interactions that occur during embryogenesis. Compared to model organisms such as fruit flies and zebrafish, the growth of mammalian embryosin uterofurther complicates the analysis of cell-cell communication during development. However,in vitromodels of mammalian development such as gastruloids can overcome this limitation. Using time-resolved single-cell chromatin accessibility analysis, we have delineated the regulatory landscape during gastruloid development and thereby identified the critical drivers of developmental transitions. We observed that gastruloids develop from pluripotent cells driven by the transcription factor (TF) dimer OCT4-SOX2 and differentiate along two main branches. A mesoderm branch characterized by the TF MSGN1 and a spinal cord branch characterized by CDX1, 2, 4 (CDX). Consistent with our lineage reconstruction, ΔCDX gastruloids fail to form spinal cord. Conversely,Msgn1ablation inhibits the development of paraxial mesoderm, as expected. However, this also abolished spinal cord cells, which is surprising given that MSGN1 is not associated with differentiation along this branch. Therefore, formation of paraxial mesoderm is required for spinal cord development. To validate this, we generated chimeric gastruloids using ΔMSGN1 and wildtype cells, which formed both spinal cord and paraxial mesoderm. Strikingly, ΔMSGN1 cells specifically contributed to spinal cord, suggesting that cell-cell interactions between paraxial mesoderm and spinal cord are necessary for the formation of the latter. Our work has important implications for the study of cell-cell communication in development and how gene regulatory programs are functionally executed to form complex multicellular developmental structures.
Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data
Authors: Augustin David , Lambert Ben , Wang Ken , Walz Antje-Christine , Robinson Martin , Gavaghan David
Published: November 2022

Variability is an intrinsic property of biological systems and is often at the heart of their complex behaviour. Examples range from cell-to-cell variability in cell signalling pathways to variability in the response to treatment across patients. A popular approach to model and understand this variability is nonlinear mixed effects (NLME) modelling. However, estimating the parameters of NLME models from measurements quickly becomes computationally expensive as the number of measured individuals grows, making NLME inference intractable for datasets with thousands of measured individuals. This shortcoming is particularly limiting for snapshot datasets, common e.g. in cell biology, where high-throughput measurement techniques provide large numbers of single cell measurements. We extend earlier work by Hasenauer et al (2011) to introduce a novel approach for the estimation of NLME model parameters from snapshot measurements, which we call filter inference. Filter inference is a new variant of approximate Bayesian computation, with dominant computational costs that do not increase with the number of measured individuals, making efficient inferences from snapshot measurements possible. Filter inference also scales well with the number of model parameters, using state-of-the-art gradient-based MCMC algorithms, such as the No-U-Turn Sampler (NUTS). We demonstrate the properties of filter inference using examples from early cancer growth modelling and from epidermal growth factor signalling pathway modelling.

Author summary

Nonlinear mixed effects (NLME) models are widely used to model differences between individuals in a population. In pharmacology, for example, they are used to model the treatment response variability across patients, and in cell biology they are used to model the cell-to-cell variability in cell signalling pathways. However, NLME models introduce parameters, which typically need to be estimated from data. This estimation becomes computationally intractable when the number of measured individuals – be they patients or cells – is too large. But, the more individuals are measured in a population, the better the variability can be understood. This is especially true when individuals are measured only once. Such snapshot measurements are particularly common in cell biology, where high-throughput measurement techniques provide large numbers of single cell measurements. In clinical pharmacology, datasets consisting of many snapshot measurements are less common but are easier and cheaper to obtain than detailed time series measurements across patients. Our approach can be used to estimate the parameters of NLME models from snapshot time series data with thousands of measured individuals.
“An optimized pipeline for live imaging whole Arabidopsis leaves at cellular resolution”
Authors: Harline Kate , Roeder Adrienne
Published: November 2022

Live imaging is the gold standard for determining how cellular development gives rise to organs. However, tracking all individual cells across whole organs over large developmental time windows is extremely challenging. In this work, we provide a comparably simple method for confocal live imaging ofArabidopsis thalianafirst leaves across early development. Our imaging method works for both wild-type leaves and the complex curved leaves of thejaw-1Dmutant. We find that dissecting the cotyledons, affixing a coverslip above the samples and mounting samples with perfluorodecalin yields optimal imaging series for robust cellular and organ level analysis. We provide details of our complementary image processing steps in MorphGraphX software for segmenting cells, tracking the cell lineages, and measuring a suite of cellular growth properties. We also provide MorphoGraphX image processing scripts that we developed to automate analysis of segmented images and data presentation. Our imaging techniques and processing steps combine into a robust imaging pipeline. With this pipeline we are able to examine important nuances in the cellular growth and differentiation ofjaw-Dversus WT leaves that have not been demonstrated before. Our pipeline is a practical starting place for researchers new to live imaging plant leaves, but also to anyone interested in improving the throughput and reliability of their live imaging process.
The circadian clock is disrupted in pancreatic cancer
Authors: Schwartz Patrick B. , Nukaya Manabu , Berres Mark E. , Rubinstein Clifford D. , Wu Gang , Hogenesch John B. , Bradfield Christopher A. , Ronnekleiv-Kelly Sean M.
Published: November 2022

Disruption of the circadian clock is linked to cancer development and progression. Establishing this connection has proven beneficial for understanding cancer pathogenesis, determining prognosis, and uncovering novel therapeutic targets. However, barriers to characterizing the circadian clock in human pancreas and human pancreatic cancer – one of the deadliest malignancies – have hindered an appreciation of its role in this cancer. Here, we employed normalized coefficient of variation (nCV) and clock correlation analysis in human population-level data to determine the functioning of the circadian clock in pancreas cancer and adjacent normal tissue. We found a substantially attenuated clock in the pancreatic cancer tissue. Then we exploited our existing mouse pancreatic transcriptome data to perform an analysis of the human normal and pancreas cancer samples using a machine learning method, cyclic ordering by periodic structure (CYCLOPS). Through CYCLOPS ordering, we confirmed the nCV and clock correlation findings of an intact circadian clock in normal pancreas with robust cycling of several core clock genes. However, in pancreas cancer, there was a loss of rhythmicity of many core clock genes with an inability to effectively order the cancer samples, providing substantive evidence of a dysregulated clock. The implications of clock disruption were further assessed with aBmal1knockout pancreas cancer model, which revealed that an arrhythmic clock caused accelerated cancer growth and worse survival, accompanied by chemoresistance and enrichment of key cancer-related pathways. These findings provide strong evidence for clock disruption in human pancreas cancer and demonstrate a link between circadian disruption and pancreas cancer progression.

Author Summary

The circadian clock is a regulator of human homeostasis. Dysfunction of the clock can lead to the development of diseases, including cancer. Although several cancers have been shown to have a dysfunctional clock which may alter prognosis or change treatment, this has been suggested but not demonstrated in pancreatic cancer. Investigation of this link is important because pancreatic cancer is highly lethal with few effective treatment options. Here we use recently pioneered bioinformatics approaches to assess clock functionality in human pancreatic cancer specimens, where we demonstrate that the clock is dysfunctional relative to normal pancreatic tissue. We then knocked out the core clock gene,Bmal1, in pancreatic cancer cells, which led to faster tumor growth and worse survival in mice and enhanced chemotherapeutic resistance to standard chemotherapy agents used in the treatment of pancreatic cancer. Collectively, our findings establish human pancreatic cancer as having clock dysfunction and clock dysfunction causing a more aggressive cancer.
Targeting BET Proteins downregulates miR-33a to promote synergy with PIM inhibitors in CMML
Authors: Letson Christopher T. , Balasis Maria E. , Newman Hannah , Binder Moritz , Vedder Alexis , Kinose Fumi , Ball Markus , Kruer Traci , Quintana-Gonzalez Ariel , Lasho Terra L. , Finke Christy M. , Almada Luciana L. , Grants Jennifer M. , Zhang Guolin , Fernandez-Zapico Martin E. , Gaspar-Maia Alexandre , Lancet Jeffrey , Komrokji Rami , Haura Eric , Reuther Gary W. , Karsan Aly , Rix Uwe , Patnaik Mrinal M. , Padron Eric
Published: November 2022

Preclinical studies in myeloid neoplasms have demonstrated efficacy of Bromodomain and Extra-Terminal protein inhibitors (BETi). However, BETi demonstrate poor single agent activity in clinical trials. Several studies suggest that combination with other anti-cancer inhibitors may enhance the efficacy of BETi. To nominate BETi combination therapies for myeloid neoplasms, we used a chemical screen with therapies currently in clinical cancer development. We identified PIM inhibitors (PIMi) as therapeutically synergistic with BETi in myeloid leukemia models. Mechanistically, we show that PIM kinase is increased after BETi treatment, and that PIM kinase upregulation is sufficient to induce resistance to BETi and sensitize cells to PIMi. Further, we demonstrate that miR-33a downregulation is the underlying mechanism driving PIM1 upregulation. We also show that GM-CSF hypersensitivity, a hallmark of chronic myelomonocytic leukemia (CMML), represents a molecular signature for sensitivity to combination therapy and credential this using patient-derived xenografts supporting the clinical investigation of this combination.
The Choice of Reference Frame Alters Interpretations of Non-Linear Gait
Authors: Ho Tyler K. , Kreter Nicholas , Jensen Cameron B. , Fino Peter C.
Published: November 2022

Introduction

Humans regularly follow non-linear trajectories, such as turning, during everyday ambulation. However, globally-defined and locally-defined reference frames fall out of alignment during non- linear locomotion, which complicates spatiotemporal and biomechanical analyses of gait. Thus, the choice of the locally-defined reference frame is an important methodological consideration. This study investigated how different definitions of reference frame change the results and interpretations of common gait measures.

Methods

Nine healthy adults completed two walking trials around a circular track. Kinematic data were collected via motion capture and used to calculate step length, step width, anteroposterior margin of stability, and mediolateral margin of stability using three different locally-defined reference frames: walkway-fixed, body-fixed, and trajectory-fixed. Linear-mixed effects models compared the effect of reference frame on each gait measure, and the effect of reference frame on conclusions about a known effect of turning gait – asymmetrical stepping patterns.

Results

All four gait measures differed significantly across the three reference frames. A significant interaction of reference frame and step type (i.e. inside vs outside step) on all four gait measures (p< 0.001) indicated conclusions about asymmetry differed based on the choice of reference frame.

Conclusion

The choice of reference frame will change the calculated gait measures and may alter the conclusions of studies investigating non-linear gait. Care should be taken when comparing studies that used different reference frames, as results cannot be easily harmonized. Future studies of non-linear gait need to justify and detail their choice of reference frame.
Phase-separating pyrenoid proteins form complexes in the dilute phase
Authors: He Guanhua , GrandPre Trevor , Wilson Hugh , Zhang Yaojun , Jonikas Martin C. , Wingreen Ned S. , Wang Quan
Published: November 2022

While most studies of biomolecular phase separation have focused on the condensed phase, relatively little is known about the dilute phase. Theory suggests that stable complexes form in the dilute phase of two-component phase-separating systems, impacting phase separation; however, these complexes have not been interrogated experimentally. We show that such complexes indeed exist, using anin vitroreconstitution system of a phase-separated organelle, the algal pyrenoid, consisting of purified proteins Rubisco and EPYC1. Applying fluorescence correlation spectroscopy (FCS) to measure diffusion coefficients, we found that complexes form in the dilute phase with or without condensates present. The majority of these complexes contain exactly one Rubisco molecule. Additionally, we developed a simple analytical model which recapitulates experimental findings and provides molecular insights into the dilute phase organization. Thus, our results demonstrate the existence of protein complexes in the dilute phase, which could play a significant role in the stability, dynamics, and regulation of condensates.
Tracking SARS-CoV-2 genomic variants in wastewater sequencing data withLolliPop
Authors: Dreifuss David , Topolsky Ivan , Icer Baykal Pelin , Beerenwinkel Niko
Published: November 2022

During the COVID-19 pandemic, wastewater-based epidemiology has progressively taken a central role as a pathogen surveillance tool. Tracking viral loads and variant outbreaks in sewage offers advantages over clinical surveillance methods by providing unbiased estimates and enabling early detection. However, wastewater-based epidemiology poses new computational research questions that need to be solved in order for this approach to be implemented broadly and successfully. Here, we address the variant deconvolution problem, where we aim to estimate the relative abundances of genomic variants from next-generation sequencing data of a mixed wastewater sample. We introduceLolliPop, a computational method to solve the variant deconvolution problem by simultaneously solving least squares problems and kernel-based smoothing of relative variant abundances from wastewater time series sequencing data. We derive multiple approaches to compute confidence bands, and demonstrate the application of our method to data from the Swiss wastewater surveillance efforts.
Multiplexed neuropeptide mapping in ant brains integrating microtomography and 3D mass spectrometry imaging
Authors: Geier Benedikt , Gil-Mansilla Esther , Liutkeviciute Zita , Hellinger Roland , Broeck Jozef Vanden , Oetjen Janina , Liebeke Manuel , Gruber Christian W.
Published: November 2022

Neuropeptides are important regulators of animal physiology and behavior. Hitherto large-scale localization of neuropeptides mainly relied on immunohistochemical methods requiring the availability of antibody panels, while another limiting factor has been the brain’s opacity for subsequent light or fluorescence microscopy. To address these limitations, we integrated high-resolution mass spectrometry imaging (MSI) with microtomography for a multiplexed mapping of neuropeptides in two evolutionary distant ant species,Atta sexdensandLasius niger. For analyzing the spatial distribution of chemically diverse peptide molecules across the brain in each species, the acquisition of serial mass spectrometry images was essential. As a result, we have comparatively mapped the 3D distributions of eight conserved neuropeptides throughout the brain micro-anatomy. We demonstrate that integrating the 3D MSI data into high-resolution anatomy models can be critical for studying organs with high plasticity such as brains of social insects. Several peptides, like the tachykinin-related peptides TK1 and TK4, were widely distributed in many brain areas of both ant species, whereas others, for instance myosuppressin was restricted to specific regions only. Also, we detected differences at the species level; many peptides were identified in the optic lobe ofL. niger, but only one peptide (ITG-like) was found in this region inA. sexdens. Our approach provides the basis for investigating fundamental neurobiological processes by visualizing the unbiased 3D neurochemistry in its complex anatomic environment.

Significance statement

Until recently, the inability to detect entire molecules such as neuropeptides within their spatial biological context and simultaneously link their occurrence to anatomically and physiologically relevant areas has limited our understanding of complex neurochemical processes. This situation has now changed dramatically with the optimization of a new multiplexed imaging method based on mass spectrometry, which enables us to study previously invisible processes at the microscopic scale. With the marriage of mass spectrometry imaging and microtomography, we show that it has become possible to build high-resolution maps of neuropeptides in complex anatomical structures as small as ant brains. These maps, embedded in the 3D neuroanatomy, expand the understanding of the spatial organization of brain chemistry and provide a baseline for neurobiological and neurochemical studies.
OsPSTOLbut notTaPSTOLcan play a role in nutrient use efficiency and works through conserved pathways in both wheat and rice
Authors: Milner Matthew , Bowden Sarah , Craze Melanie , Wallington Emma J.
Published: November 2022

There is a large demand to reduce inputs for current crop production, particularly phosphate and nitrogen inputs which are the two most frequently added supplements to agricultural production. Gene characterization is often limited to the native species from which it was identified, but may offer benefits to other species. To understand ifOsPSTOL, a gene identified from rice which improves tolerance to low P growth conditions, might improve performance and provide the same benefit in wheat,OsPSTOLwas transformed into wheat and expressed from a constitutive promoter. The ability ofOsPSTOLto improve nutrient acquisition under low phosphate or low nitrogen was evaluated. Here we show thatOsPSTOLworks through a conserved pathway in wheat and rice to improve yields under both low phosphate and low nitrogen. This increase is yield is mainly driven by improved uptake from the soil driving increased biomass and ultimately increased seed number, but does not change the concentration of N in the straw or grain. Overexpression ofOsPSTOLin wheat modifies N regulated genes to aid in this uptake whereas the putative homologTaPSTOLdoes not suggesting that expression ofOsPSTOLin wheat can help to improve yields under low input agriculture.
DISRUPTOR: Computational identification of oncogenic mutants disrupting protein interactions
Authors: Kugler V , Lieb A , Guerin N , Donald BR , Stefan E , Kaserer T
Published: November 2022

We report an Osprey-based computational protocol to prospectively identify oncogenic mutations that act via disruption of molecular interactions. It is applicable to analyze both protein-protein and protein-DNA interfaces and has been validated on a dataset of clinically relevant mutations. In addition, it was used to predict previously uncharacterized patient mutations in CDK6 and p16 genes, which were experimentally confirmed to impair complex formation.
The dark kinase STK32A regulates hair cell planar polarity opposite of EMX2 in the developing mouse inner ear
Authors: Jia Shihai , Ratzan Evan M. , Goodrich Ellison J. , Abrar Raisa , Heiland Luke , Tarchini Basile , Deans Michael R.
Published: November 2022

The vestibular maculae of the inner ear contain sensory receptor hair cells that detect linear acceleration, contribute to equilibrioception, and thereby coordinate posture and ambulatory movements. These hair cells are divided between two groups, separated by a line of polarity reversal (LPR), with oppositely oriented planar-polarized stereociliary bundles that detect motion in opposite directions. The transcription factor EMX2 is known to establish this planar polarized organization by regulating the distribution of the transmembrane receptor GPR156 at the hair cell surface in one group of cells, however those genes regulated by EMX2 in this context were previously not known. We have identified the serine threonine kinase STK32A as a downstream effector negatively regulated by EMX2.Stk32ais expressed in hair cells on one side of the LPR in a pattern complementary toEmx2due to transcriptional repression.Stk32ais necessary to align the intrinsic polarity of the bundle with the core planar cell polarity (PCP) proteins in EMX2-negative regions, and is sufficient to reorient bundles when ectopically expressed in neighboring EMX2-positive regions. We demonstrate that STK32a reinforces LPR formation by regulating the apical localization of GPR156. These observations support a model in which bundle orientation is determined through separate mechanisms in hair cells on opposite sides of the LPR, with EMX2-mediated repression ofStk32adetermining the position of the LPR.

Highlights

STK32A is a planar polarity effector that is negatively regulated by the transcription factor EMX2

Stk32a is necessary and sufficient to determine vestibular hair cell stereociliary bundle orientation

STK32A contributes to the post-translational regulation of GPR156, preventing GPR156 localization in the absence of EMX2
Non-neutralizing antibody responses to vesicular stomatitis virus-vectored influenza A virus vaccines correlate with protection
Authors: Wittwer Kevin , Zimmer Gert , Rommel Marcel , Krebs Yvonne , Rezinciuc Svetlana , Sawatsky Bevan , Pfaller Christian K.
Published: November 2022

Seasonal influenza virus infections remain a major global public health burden. In addition, influenza A virus (IAV) exhibits high pandemic potential through zoonotic spread from avian hosts to humans. Currently licensed IAV vaccines are mainly directed against the immuno-dominant surface protein hemagglutinin (HA). Since HA is antigenically highly variable, IAV can escape vaccine-derived immunity through antigenic drift. However, vaccine preparations such as the live-attenuated influenza vaccine (LAIV) also contain other more conserved viral antigens, whose contribution to influenza immunity are not fully elucidated. To determine the extent to which conserved LAIV antigens contribute to establishing protective immunity against heterologous IAV strains, we generated vesicular stomatitis virus-based single-round vector vaccines expressing individual LAIV antigens, and tested their ability to protect mice from a heterologous challenge with two IAV strains, PR8[H1N1] and rSC35M[H7N7]. We found that immunization with nucleoprotein (NP), ion channel M2, and the stem-region of HA (HAstem), but not matrix protein (M1), provide protection from severe disease caused by either IAV strain. This effect correlated with development of non-neutralizing antibodies cross-reactive with both virus strains. Notably, the individual antigens induced specific IgG subclass profiles with different reactivity against PR8 and rSC35M. Sera from vaccinated animals activated Fc-gamma receptor IV-mediated effector functions, suggesting that they can induce cell-mediated immune defense mechanisms, such as antibody-dependent cellular cytotoxicity and antibody-dependent cellular phagocytosis. Combination of the most potent antigens NP and M2 in a mixed vaccination resulted in enhanced protection against IAV challenge, suggesting that the antibody responses against these antigens were synergistic. Our results demonstrate the potency of NP and M2 proteins to serve as conserved antigen targets, resulting in broad protection against severe IAV disease.
A synthetic KLHL20 ligand to validate CUL3KLHL20as a potent E3 ligase for targeted protein degradation
Authors: Farrell Brian M. , Gerth Fabian , Yang Cheng-Hao R. , Yeh Johannes T.-H.
Published: November 2022

Targeted protein degradation (TPD) has risen as a promising therapeutic modality. Leveraging the catalytic nature of the ubiquitin–proteasome enzymatic machinery, TPD exhibits higher potency to eliminate disease-causing target proteins such as oncogenic transcription factors that may otherwise be difficult to abrogate by conventional inhibitors. However, there are challenges that remain. Currently, nearly all degraders engage CUL4CRBNor CUL2VHLas the E3 ligase for target ubiquitination. While their immediate efficacies are evident, the narrowed E3 ligase options make TPD vulnerable to potential drug resistance. In addition, E3 ligases show differential tissue expression and have intrinsic limitations in accessing varying types of disease-relevant targets. As the success of TPD is closely associated with the ability of E3 ligases to efficiently polyubiquitinate the target of interest, the long-term outlook of TPD drug development will depend on whether E3 ligases such as CUL4CRBNand CUL2VHLare accessible to the targets of interest. To overcome these potential caveats, a broad collection of actionable E3 ligases is required. Here, we designed a macrocyclic degrader engaging CUL3KLHL20for targeting BET proteins and validated CUL3KLHL20as an E3 ligase system suitable for TPD. This work thus contributes to the expansion of usable E3 ligases for potential drug development.
Band-gap assessment from X-ray powder diffraction using artificial intelligence
Authors: Gómez-Peralta Juan Iván , Bokhimi Xim , García-Peña Nidia Guadalupe , Quintana-Owen Patricia , Rodríguez-Gattorno Geonel
Published: November 2022

X-ray diffraction is a phenomenon that stems from the interaction of the electron density of a crystalline material and the electric field of the X-ray waves. The product of this interaction, the diffraction pattern, provides a picture of the reciprocal space of the atomic distribution in terms of intensities of certain scattering wavevectors. In this manner, a correlation between those intensities seen in a diffraction pattern and the electronic properties of a material is suggested. This correlation, if it exists, may not be directly proposed using analytical expressions. This article shows for the first time the feasibility of assessing the band gap of metal–organic frameworks (MOFs) and organic and inorganic materials from their X-ray powder diffraction pattern. The band gaps were assessed with convolutional neural networks (CNNs). These CNNs were developed using simulated X-ray powder diffraction patterns and the band gaps calculated with density functional theory. The diffraction patterns were simulated with different crystal sizes, from 10 nm to the macrocrystalline size. In addition, the reported band gaps of MOFs and organic compounds in the Quantum MOF Database and the Organic Materials Database data sets were used, which were calculated with the PBE functional. Furthermore, the band gaps calculated by Kim et al. [Sci. Data (2020), 7, 387] for inorganic compounds with the HSE functional were used. The developed CNNs were tested with simulated diffraction patterns of compounds different from those used to train the CNNs, as well as with experimentally recorded diffraction patterns. The developed CNNs allowed the assessment of the band gap of the compounds with a root-mean-square error as low as 0.492 eV after training with over 64 000 diffraction patterns.
New refinement strategies for a pseudoatom databank – toward rapid electrostatic interaction energy estimations
Authors: Bojarowski Sławomir Antonii , Gruza Barbara , Trzybiński Damian , Kamiński Radosław , Hoser Anna Agnieszka , Kumar Prashant , Woźniak Krzysztof , Dominiak Paulina Maria
Published: November 2022

Pseudoatom databanks, collections of parameters from the multipole model of electron densities for various atom types, are used to replace the Independent Atom Model with the more accurate Transferable Aspherical Atom Model (TAAM) in crystal structure refinements. The databanks are also employed to reconstruct the electron density of a molecule, crystal or biomacromolecular complex in a fast yet accurate way and compute various properties such as the energy of electrostatic interactions, for example. A even faster but similarly accurate model for estimations of electrostatic energy exists called aug-PROmol [Bojarowski, Kumar & Dominiak (2016). ChemPhysChem, 17, 2455–2460]. A model analogous to aug-PROmol cannot be built from the current pseudoatom databanks, as they perform badly when truncated to the monopole level. Here, new strategies for multipole model refinements were sought, leading to better parametrization at the monopole level. This would allow the creation of a pseudoatom databank in a single route of model parametrization, which would be suitable for both crystal structure refinement and rapid electrostatic energy calculations. Here it is shown that the cumulative approach to multipole model refinements, as opposed to simultaneous or iterative refinements of all multipole model parameters (Pv
, κ, Plm
, κ′), leads to substantially different models of electron density. Cumulative refinement of two blocks of parameters, the first with Pv
and κ and then the second with Plm
and κ′, leads to the P

v
κ|P

lm
κ′ model having promising properties. The P

v
κ|P

lm
κ′ model is as good as the University at Buffalo DataBank (UBDB) in X-ray structure TAAM refinements and electrostatic energy estimations, especially for less polar molecules. When truncated to the monopole level, the P

v
κ model has a chance to replace aug-PROmol in fast yet accurate electrostatics energy calculations, although some improvements in κ parametrization for polar functional groups are still needed. The P

v
κ model is also a source of point charges which behave similarly to restrained electrostatic potential (RESP) charges in electrostatic interaction energy estimations.
Four-position disorder of cationic protonated guanylurea in a stable three-dimensional network in the structure of a triple salt decavanadate complex (HGU+)(H2Met2+)2(H3O+)(V10O28
6−)·8H2O
Authors: Chatkon Aungkana , Haller Joseph P. , Haller Kenneth J.
Published: November 2022

A triple salt of decavanadate, V10O28
6−, containing mixed organic guanylurea (diaminomethylideneurea cation, HGU+) and metforminium(2+) (H2Met2+) cations and hydronium (H3O+) cations, has been synthesized by heating metformin hydrochloride, picolinic acid, and sodium metavanadate in aqueous solution at pH 4 and 333 K followed by maintaining the solution at 300 K overnight to give an orange crystalline product. As commonly observed, the V10O28
6− anion lies on an inversion center. Charge is balanced by two H2Met2+ dications and two monocations, one HGU+ and one H3O+, substitutionally disordered about another inversion center. The HGU+ cation is further positionally disordered by rotation of 26.3 (4)° about an axis approximately along the direction of the three essentially collinear N atoms of the cation, thereby hydrogen bonding to two adjacent rows of cluster O atoms running diagonally across the equatorial plane of the V10O28
6− anion. The highly concerted nature of the HGU+...cluster interaction in each orientation suggests a synthon that likely preexisted in solution and perhaps, along with heat, contributes to the degradation of the metformin to HGU+. The structure of the salt exhibits a complex charge-stabilized hydrogen-bonded network involving extended C
4
4(8) chains of the water molecules and the H2Met2+ cations linking the chains into two-dimensional sheets parallel to the bc plane, and V10O28
6− anions linking those sheets into a three-dimensional structure through Ow—H...O, N—H...O and C—H...O intermolecular interactions. The disordered HGU+ cation and the H3O+ cation occupy spaces with excess volume in the three-dimensional network structure.
Zr3Mn3Sn4Ga: a new hexagonal Ti6Sn5-type quaternary intermetallic
Authors: Clausse Thomas , Diop Léopold V. B. , Martin Nicolas P. , Sibille Romain , Mazet Thomas
Published: November 2022

The discovery of a new quaternary intermetallic compound of composition Zr3Mn3Sn4Ga during a survey of the Zr–Mn–Sn–Ga phase diagram is reported. Single-crystal X-ray diffraction reveals that the new compound crystallizes in a hexagonal lattice (space group P63/mmc, No. 194). The analysis of single-crystal X-ray diffraction data indicates that the atomic arrangement is an ordered variant of the high-temperature hexagonal Ti6Sn5 crystal structure. From a simple geometry point of view, the unit cell consists of GaZr3 octahedra chains and Mn chains growing along the sixfold symmetry axis c. The Mn chains are stacked within the ab basal plane in a kagome geometry, with large interatomic distances. The possible slight levels of Sn/Ga and Zr/Mn mixed occupancy based on additional results of electron probe microanalysis and single-crystal neutron diffraction are discussed. It is noteworthy that this compound is the first quaternary intermetallic discovered in this structure and the first Ti6Sn5 derivative bearing a magnetic metal, namely Mn, in the 6g position, which may give rise to interesting physical properties.
Understanding and application of quality costs in automotive manufacturing companies in North Macedonia: empirical study
Authors: Velkoska Cvetanka , Tomov Mite
Published: November 2022

Purpose

This study aims at presenting deeper insights regarding the understanding and application of the quality costs (CoQ) in the automotive manufacturing industry. The empirical research included three general determinants: reasons for, difficulties during and benefits from implementing quality costs, as well as two specific determinants: measuring and evaluating quality cost elements.

Design/methodology/approach

The empirical research methodology employs the expert evaluation method – the Delphi method, using a survey questionnaire comprising a total of 200 questions, and answered by 9 companies.

Findings

The survey results showed that companies do recognize the reasons for implementing quality costs as a need arising from the quality management standards, the lack of knowledge of quality costs by employees and management as the biggest difficulty while the biggest benefit includes the quality costs enhance the company competitiveness. The costs competence and qualification, the quality management system costs, the costs for improvement, the production control costs, the input control costs, the new measuring and control equipment calibration costs, the costs related to scrap, repairs and product finishing are the most significant elements of the quality costs.

Research limitations/implications

This study is limited by the small number of surveyed companies from the automotive cluster.

Practical implications

The proposed quality costs model provides to the management to conceive CoQ elements as possible drivers in the improvement process of product quality. The structure and the nature of the CoQ elements is expected to advance the process of detailing the quality costs elements.

Originality/value

The novelty of this paper refers to development of a generic quality cost model, whose relevance is confirmed by the structuring of the model with elements published in literature and validating in research companies.
How do different Industry 4.0 technologies support certain Circular Economy practices?
Authors: Lei Zhimei , Cai Shanshan , Cui Li , Wu Lin , Liu Yiwei
Published: November 2022

Purpose

Uncovering the relationship between Industry 4.0 (I4.0) technologies and circular economy (CE) practices is critical not only for implementing CE but also for leveraging I4.0 to achieve sustainable development goals. However, the potential connection between them – especially how different I4.0 technologies may influence various CE practices – remains inadequately researched. The purpose of this study was to quantitatively explore the impacts of various I4.0 technologies on CE practices.

Design/methodology/approach

A mixed method consisting of a systematic literature review, content analysis, and social network analysis was adopted. First, 266 articles were selected and mined for contents of I4.0 technologies and CE practices; 27 I4.0 technologies and 21 CE practices were identified. Second, 62 articles were found that prove the positive influence of I4.0 technologies on CE practices, and 124 relationships were identified. Third, based on evidence supporting the link between I4.0 technologies and CE practices, a two-mode network and two one-mode networks were constructed, and their network density and degree centrality indicators were analyzed.

Findings

I4.0 technologies have a low application scope and degree for promoting CE. The adoption of a single I4.0 technology has limited effect on CE practices, and wider benefits can be realized through integrating I4.0 technologies. The Internet of Things (IoT), additive manufacturing, big data and analytics, and artificial intelligence (AI) are among the top technologies promoting CE implementation and reduction and recycling were identified as the main mechanism. The integration of these technologies is the most popular and effective. Twelve CE practices were identified to be the most widely implemented and supported by I4.0 technologies.

Research limitations/implications

First, only journal articles, reviews, and online publications written in English were selected, excluding articles published in other languages. Therefore, the results obtained only represent a specific group of scholars, which may be fragmented to a certain extent. Second, because the extraction of the impact of I4.0 on CE mainly relies on a manual literature review, this paper only provides the statistics of the number of publications involving relationships, while lacking the weight measurement of relationships.

Originality/value

A comprehensive, quantitative, and visual analysis method was employed to unveil the current implementation levels of I4.0 technologies and CE practices. Further, it was explored how different I4.0 technologies can affect various CE aspects, how different I4.0 technologies are integrated to promote CE realization, and how various CE practices are implemented simultaneously by I4.0 technologies.
An IoT-based and cloud-assisted AI-driven monitoring platform for smart manufacturing: design architecture and experimental validation
Authors: Caiazzo Bianca , Murino Teresa , Petrillo Alberto , Piccirillo Gianluca , Santini Stefania
Published: November 2022

Purpose

This work aims at proposing a novel Internet of Things (IoT)-based and cloud-assisted monitoring architecture for smart manufacturing systems able to evaluate their overall status and detect eventual anomalies occurring into the production. A novel artificial intelligence (AI) based technique, able to identify the specific anomalous event and the related risk classification for possible intervention, is hence proposed.

Design/methodology/approach

The proposed solution is a five-layer scalable and modular platform in Industry 5.0 perspective, where the crucial layer is the Cloud Cyber one. This embeds a novel anomaly detection solution, designed by leveraging control charts, autoencoders (AE) long short-term memory (LSTM) and Fuzzy Inference System (FIS). The proper combination of these methods allows, not only detecting the products defects, but also recognizing their causalities.

Findings

The proposed architecture, experimentally validated on a manufacturing system involved into the production of a solar thermal high-vacuum flat panel, provides to human operators information about anomalous events, where they occur, and crucial information about their risk levels.

Practical implications

Thanks to the abnormal risk panel; human operators and business managers are able, not only of remotely visualizing the real-time status of each production parameter, but also to properly face with the eventual anomalous events, only when necessary. This is especially relevant in an emergency situation, such as the COVID-19 pandemic.

Originality/value

The monitoring platform is one of the first attempts in leading modern manufacturing systems toward the Industry 5.0 concept. Indeed, it combines human strengths, IoT technology on machines, cloud-based solutions with AI and zero detect manufacturing strategies in a unified framework so to detect causalities in complex dynamic systems by enabling the possibility of products’ waste avoidance.
The role of internal market orientation on the adoption of external market orientation in retail banking
Authors: Zebal Mostaque A. , Sharif Taimur R. , Crumbly Jack , Zebal Anushe
Published: November 2022

Purpose

The purpose of this study was to investigate the role of internal market orientation on the adoption of external market orientation among the retail banks in the United Arab Emirates (UAE). This study adds to the previous research regarding external market orientation. It also develops an empirical model on the basis of the results.

Design/methodology/approach

This study used a self-administered structured questionnaire to collect data from the front-line marketing and non-marketing employees from the banks. Data were collected from 98 branches of all the 49 banks that operate in the UAE. Two major emirates of the UAE, namely, Abu Dhabi and Dubai, were considered for data collection. Each bank contributed responses from a minimum of two branches, and 113 completed questionnaires were received out of 196 respondents approached for data collection. The reliability, convergent and discriminant validity issues of the data were assessed, and the results of these confirmed the appropriateness of the data used in this study.

Findings

Direct entry regression and multivariate analysis of variance were used for identifying the conclusions surrounding the hypotheses of the study. The results measured the extent of internal market orientation and employees’ organisational commitment. They both confirmed their positive role on the adoption of external market orientations among the retail banks in the UAE. The results of the study further provided evidence that once an external market orientation focus is adopted, this benefits customer loyalty and satisfaction in addition to overall positive business outcomes for the banks concerned.

Originality/value

The findings of this study support the theoretical arguments of the role of employees and internal market orientation on the adoption of external market orientation. This study further identifies the reason why the adoption of external market orientation is critical for the success of banks.