bluuebunny/crossref_metadata_2025 huggingface dataset:
CRISPR activation rescues abnormalities in SCN2A haploinsufficiency-associated autism spectrum disorder
Authors: Tamura Serena , Nelson Andrew D. , Spratt Perry W.E. , Kyoung Henry , Zhou Xujia , Li Zizheng , Zhao Jingjing , Holden Stephanie S. , Sahagun Atehsa , Keeshen Caroline M. , Lu Congyi , Hamada Elizabeth C. , Ben-Shalom Roy , Pan Jen Q. , Paz Jeanne T. , Sanders Stephan J. , Matharu Navneet , Ahituv Nadav , Bender Kevin J.
Published: April 2022

The majority of autism spectrum disorder (ASD) risk genes are associated with ASD due to haploinsufficiency, where only one gene copy is functional. Here, using SCN2A haploinsufficiency, a major risk factor for ASD, we show that increasing the expression of the existing functional SCN2A allele with CRISPR activation (CRISPRa) can provide a viable therapeutic approach. We first demonstrate therapeutic potential by showing that restoring Scn2a expression in adolescent heterozygous Scn2a conditional knock-in mice rescues electrophysiological deficits associated with Scn2a haploinsufficiency. Next, using an rAAV-CRISPRa based treatment, we restore electrophysiological deficits in both Scn2a heterozygous mice and human stem-cell-derived neurons. Our results provide a novel therapeutic approach for numerous ASD-associated genes and demonstrate that rescue of Scn2a haploinsufficiency, even at adolescent stages, can ameliorate neurodevelopmental phenotypes.
Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates
Authors: Inward Rhys P.D. , Jackson Felix , Dasgupta Abhishek , Lee Graham , Battle Anya Lindström ,   Global.health consortium, Parag Kris V. , Kraemer Moritz U.G.
Published: April 2022

SARS-CoV-2 case data are primary sources for estimating epidemiological parameters and for modelling the dynamics of outbreaks. Understanding biases within case based data sources used in epidemiological analyses are important as they can detract from the value of these rich datasets. This raises questions of how variations in surveillance can affect the estimation of epidemiological parameters such as the case growth rates. We use standardised line list data of COVID-19 from Argentina, Brazil, Mexico and Colombia to estimate delay distributions of symptom-onset-to-confirmation, -hospitalisation and -death as well as hospitalisation-to-death at high spatial resolutions and throughout time. Using these estimates, we model the biases introduced by the delay from symptom-onset-to-confirmation on national and state level case growth rates (rt) using an adaptation of the Richardson-Lucy deconvolution algorithm. We find significant heterogeneities in the estimation of delay distributions through time and space with delay difference of up to 19 days between epochs at the state level. Further, we find that by changing the spatial scale, estimates of case growth rate can vary by up to 0.13 d-1. Lastly, we find that states with a high variance and/or mean delay in symptom-onset-to-diagnosis also have the largest difference between the rt estimated from raw and deconvolved case counts at the state level. We highlight the importance of high-resolution case based data in understanding biases in disease reporting and how these biases can be avoided by adjusting case numbers based on empirical delay distributions. Code and openly accessible data to reproduce analyses presented here are available.
Endo-lysosomal assembly variations among Human Leukocyte Antigen class I (HLA-I) allotypes
Authors: Olson Eli , Ceccarelli Theadora , Raghavan Malini
Published: April 2022

The extreme polymorphisms of HLA-I proteins enable the presentation of diverse peptides to cytotoxic T lymphocytes (CTL). The canonical endoplasmic reticulum (ER) HLA-I assembly pathway enables presentation of cytosolic peptides, but effective intracellular surveillance requires multi-compartmental antigen sampling. Endo-lysosomes are generally sites of HLA class II assembly, but human monocytes and monocyte-derived dendritic cells (moDCs) also contain significant reserves of endo-lysosomal HLA-I molecules. We hypothesized variable influences of HLA-I polymorphisms upon outcomes of endo-lysosomal trafficking, as the stabilities and peptide occupancies of cell surface HLA-I are variable. For example, in moDCs, compared with HLA-B*08:01, HLA-B*35:01 displays reduced cell-surface stability and greater receptivity to exogenous peptide. Perturbations of endo-lysosomal pH negatively affect the surface expression of moDC HLA-B*35:01 but not HLA-B*08:01, causing HLA-B*35:01 accumulation in LAMP1+ compartments. These findings reveal the intersection of the vacuolar cross-presentation pathway with a constitutive assembly pathway for HLA-B*35:01. Notably, cross-presentation of epitopes derived from two soluble antigens was also more efficient for B*35:01 compared to B*08:01, even when matched for T cell response sensitivity, and more affected by cathepsin inhibition. Thus, HLA-I polymorphisms dictate the degree of endo-lysosomal assembly, which can supplement ER assembly for constitutive HLA-I expression and increase the efficiency of cross-presentation.
Normative sleep spindle database and findings from 772 healthy children from birth through 18 years
Authors: Kwon Hunki , Walsh Katherine G. , Berja Erin D. , Manoach Dara S. , Eden Uri T. , Kramer Mark A. , Chu Catherine J.
Published: April 2022

Work in the last two decades has identified sleep spindles, discrete “sigma band” oscillations during stage 2 sleep, as a key oscillatory mechanism required for off-line memory consolidation. Although, sleep spindles are known to evolve concomitant with brain maturation and reflect cognitive function across the lifespan, the details of this developmental trajectory are unknown. To address this, we curated a database of sleep electroencephalograms from 772 developmentally normal children to characterize spindles from birth through 18 years. After validating an automated spindle detector against ~20,000 hand-marked spindles across ages, we demonstrate that sleep spindle features follow distinct age-specific patterns in distribution, rate, duration, frequency, estimated refractory period, and inter-hemispheric spindle lag. These data expand our current knowledge of normal physiological brain development and provide a large normative database to detect deviations in sleep spindles to aid discovery, biomarker development, and diagnosis in pediatric neurodevelopmental disorders.
The impact of sparsity in low-rank recurrent neural networks
Authors: Herbert Elizabeth , Ostojic Srdjan
Published: April 2022

Neural population dynamics are often highly coordinated, allowing task-related computations to be understood as neural trajectories through low-dimensional subspaces. How the network connectivity and input structure give rise to such activity can be investigated with the aid of low-rank recurrent neural networks, a recently-developed class of computational models which offer a rich theoretical framework linking the underlying connectivity structure to emergent low-dimensional dynamics. This framework has so far relied on the assumption of all-to-all connectivity, yet cortical networks are known to be highly sparse. Here we investigate the dynamics of low-rank recurrent networks in which the connections are randomly sparsified, which makes the network connectivity formally full-rank. We first analyse the impact of sparsity on the eigenvalue spectrum of low-rank connectivity matrices, and use this to examine the implications for the dynamics. We find that in the presence of sparsity, the eigenspectra in the complex plane consist of a continuous bulk and isolated outliers, a form analogous to the eigenspectra of connectivity matrices composed of a low-rank and a full-rank random component. This analogy allows us to characterise distinct dynamical regimes of the sparsified low-rank network as a function of key network parameters. Altogether, we find that the low-dimensional dynamics induced by low-rank connectivity structure are preserved even at high levels of sparsity, and can therefore support rich and robust computations even in networks sparsified to a biologically-realistic extent.

Author summary

In large networks of neurons, the activity displayed by the population depends on the strength of the connections between each neuron. In cortical regions engaged in cognitive tasks, this population activity is often seen to be highly coordinated and low-dimensional. A recent line of theoretical work explores how such coordinated activity can arise in a network of neurons in which the matrix defining the connections is constrained to be mathematically low-rank. Until now, this connectivity structure has only been explored in fully-connected networks, in which every neuron is connected to every other. However, in the brain, network connections are often highly sparse, in the sense that most neurons do not share direct connections. Here, we test the robustness of the theoretical framework of low-rank networks to the reality of sparsity present in biological networks. By mathematically analysing the impact of removing connections, we find that the low-dimensional dynamics previously found in dense low-rank networks can in fact persist even at very high levels of sparsity. This has promising implications for the proposal that complex cortical computations which appear to rely on low-dimensional dynamics may be underpinned by a network which has a fundamentally low-rank structure, albeit with only a small fraction of possible connections present.
Structural interplay between DNA-shape protein recognition and supercoiling: the case of IHF
Authors: Watson George D. , Chan Elliot W. , Leake Mark C. , Noy Agnes
Published: April 2022

The integration host factor (IHF) is a prominent example of indirect readout as it imposes one of the strongest bends on relaxed linear DNA. However, the relation between IHF and torsionally constrained DNA, as occurs physiologically, remains unclear. By using atomistic molecular dynamics simulations on DNA minicircles, we reveal, for the first time, the reciprocal influence between a DNA-bending protein and supercoiling. While the increased curvature of supercoiled DNA enhances wrapping around IHF, the protein pins the position of plectonemes, organizing the topology of the loop in a unique and specific manner. In addition, IHF restrains underor overtwisted DNA depending on whether the complex is formed in negatively or positively supercoiled DNA. This effectively enables IHF to become a ‘supercoiling buffer’ that dampens changes in the surrounding superhelical stress through DNA breathing around the protein or complex dissociation. We finally provide evidence of DNA bridging by IHF and reveal that these bridges divide DNA into independent topological domains. We anticipate that the crosstalk detected here between the ‘active’ DNA and the multifaceted IHF could be common to other DNA-protein complexes relying on the deformation of DNA.
SARS-CoV-2 Omicron is specifically restricted in its replication in human lung tissue, compared to other variants of concern
Authors: Alfi Or , Hamdan Marah , Wald Ori , Yakirevitch Arkadi , Wandel Ori , Oiknine-Djian Esther , Gvili Ben , Knoller Hadas , Rozendorn Noa , Golan Hadar , Adar Sheera , Vorontsov Olesya , Mandelboim Michal , Zakay-Rones Zichria , Oberbaum Menachem , Panet Amos , Wolf Dana G.
Published: April 2022

SARS-CoV-2 Omicron variant has been characterized by decreased clinical severity, raising the question of whether early variant-specific interactions within the mucosal surfaces of the respiratory tract could mediate its attenuated pathogenicity. Here, we employed ex vivo infection of native human nasal and lung tissues to investigate the local-mucosal susceptibility and innate immune response to Omicron, compared to Delta and earlier SARS-CoV-2 variants of concern (VOC). We show that the replication of Omicron in lung tissues is highly restricted compared to other VOC, whereas it remains relatively unchanged in nasal tissues. Mechanistically, Omicron induced a much stronger antiviral interferon response in infected tissues compared to Delta and earlier VOC - a difference which was most striking in the lung tissues, where the innate immune response to all other SARS-CoV-2 VOC was blunted. Our data provide new insights to the reduced lung involvement and clinical severity of Omicron.
Understanding the transcriptional response to ER stress in Chinese hamster ovary cells using multiplexed single cell RNA-seq
Authors: Tzani Ioanna , Castro-Rivadeneyra Marina , Boi Stefano , Clarke Colin
Published: April 2022

Single cell RNA-seq (scRNA-seq) has recently been shown to provide a powerful method for the analysis of transcriptional heterogeneity in Chinese hamster ovary (CHO) cells. A potential drawback of current scRNA-seq platforms is that the cost can limit the complexity of experimental design and therefore the utility of the approach. In this manuscript, we report the use of oligonucleotide barcoding to perform multiplexed CHO cell scRNA-seq to study the impact of tunicamycin (TM), an inducer of the unfolded protein response (UPR). For this experiment, we treated a CHO-K1 GS cell line with 10μg/ml tunicamycin and acquired samples at 1, 2, 4 and 8 hr post-treatment as well as a non-treated TM-control. We transfected cells with sample-specific polyadenylated ssDNA oligonucleotide barcodes enabling us to pool all cells for scRNA-seq. The sample from which each cell originated was subsequently determined by the oligonucleotide barcode sequence. Visualisation of the transcriptome data in a reduced dimensional space confirmed that cells were not only separable by sample but were also distributed according to time post-treatment. These data were subsequently utilised to perform weighted gene co-expression analysis (WGCNA) and uncovered groups of genes associated with TM treatment. For example, the expression of one group of coexpressed genes was found to increase over the time course and were enriched for biological processes associated with ER stress. The use of multiplexed single cell RNA-seq has the potential to reduce the cost associated with higher sample numbers and avoid batch effects for future studies of CHO cell biology.

Highlights

Polyadenylated ssDNA oligonucleotide labelling is a viable strategy for multiplexed CHO cell scRNA-seq analysis.

To demonstrate the effectiveness of the method we conducted an experiment to study the CHO cell response to tunicamycin treatment.

scRNA-seq was carried out on an untreated control and at 4 time points post tunicamycin treatment. Cells from each sample were transfected with a unique oligonucleotide barcode and pooled for single cell transcriptomics.

Each sample was demultiplexed post-sequencing and gene expression profiles of > 5,300 cells were obtained across the experiment. Following dimensionality reduction and visualisation, the cells were distributed according to sample identity.

Analysis of the resulting data enabled improved understanding of the transcriptional response to tunicamycin treatment. Three gene coexpression modules were found to be correlated with the tunicamycin time course. Gene set enrichment analysis revealed the over representation of genes related to biological processes associated with ER stress, and protein misfolding in one of these groups of coexpressed genes.

Further use of this approach will enable the CHO cell biology community to perform increasingly complex single cell experiments in a cost-effective manner.
Robust inference of expression state in bulk and single-cell RNA-Seq using curated intergenic regions
Authors: Costa Sara S. Fonseca , Rosikiewicz Marta , Roux Julien , Wollbrett Julien , Bastian Frederic B. , Robinson-Rechavi Marc
Published: April 2022

RNA-Seq is a powerful technique to provide quantitative information on gene expression. While many applications focus on estimated expression levels, it is also important to determine which genes are actively transcribed, and which are not. The problem can be viewed as simply setting a biologically meaningful threshold for calling a gene expressed. We propose to define this threshold per sample relative to the background level for non-expressed genomic features, inferred by the amount of reads mapped to intergenic regions of the genome. To this aim, we first define a stringent set of reference intergenic regions, based on available bulk RNA-Seq libraries for each species. We provide predefined regions selected for different animal species with varying genome annotation quality through the Bgee database. We then call genes expressed if their level of expression is significantly higher than the background noise. This approach can be applied to bulk as well as single-cell RNA-Seq, on a single library as well as on a combination of libraries over one condition. We show that the estimated proportion of expressed genes is biologically meaningful and stable between libraries originating from the same tissue, in both model and non-model organisms.
Establishment of a social conditioned place preference paradigm for the study of social reward in female mice
Authors: Harda Zofia , Chrószcz Magdalena , Misiołek Klaudia , Klimczak Marta , Szumiec Łukasz , Kaczmarczyk-Jarosz Maria , Parkitna Jan Rodriguez
Published: April 2022

Social interactions can be and often are rewarding. The effect of social contact strongly depends on circumstances, and the reward may be driven by varied motivational processes, ranging from parental or affiliative behaviors to investigation or aggression. Reward associated with nonreproductive interactions in rodents is measured using the social conditioned place preference (sCPP) paradigm, where a change in preference for an initially neutral context confirms reinforcing effects of social contact. Here, we revised the sCPP method and reexamined social reward in adult female mice. Contrary to earlier studies, we found that robust rewarding effects of social contact could be detected in adult (14-week-old) female C57BL/6 mice when the sCPP task was refined to remove confounding factors. Strikingly, the rewarding effects of social interaction were only observed among female siblings who remained together from birth. Contact with same-age nonsiblings was not rewarding even after 8 weeks of cohousing. Other factors critical for the social reward effect in the sCPP paradigm included the number of conditioning sessions and the inherent preference for contextual cues. Thus, we show that social interaction is rewarding in adult female mice, but this effect strictly depends on the familiarity of the interaction partners. Furthermore, by identifying confounding factors, we provide a behavioral model to study the mechanisms underlying the rewarding effects of nonreproductive social interaction in adult mice.
A Sequence Labeling Framework for Extracting Drug-Protein Relations from Biomedical Literature
Authors: Luo Ling , Lai Po-Ting , Wei Chih-Hsuan , Lu Zhiyong
Published: April 2022

Automatic extracting interactions between chemical compound/drug and gene/protein is significantly beneficial to drug discovery, drug repurposing, drug design, and biomedical knowledge graph construction. To promote the development of the relation extraction between drug and protein, the BioCreative VII challenge organized the DrugProt track. This paper describes the approach we developed for this task. In addition to the conventional text classification framework that has been widely used in relation extraction tasks, we propose a sequence labeling framework to drug-protein relation extraction. We first comprehensively compared the cutting-edge biomedical pre-trained language models for both frameworks. Then, we explored several ensemble methods to further improve the final performance. In the evaluation of the challenge, our best submission (i.e., the ensemble of models in two frameworks via major voting) achieved the F1-score of 0.795 on the official test set. Further, we realized the sequence labeling framework is more efficient and achieves better performance than the text classification framework. Finally, our ensemble of the sequence labeling models with majority voting achieves the best F1-score of 0.800 on the test set.

Database URL

https://github.com/lingluodlut/BioCreativeVII_DrugProt
The role of capacity constraints in Convolutional Neural Networks for learning random versus natural data
Authors: Tsvetkov Christian , Malhotra Gaurav , Evans Benjamin D. , Bowers Jeffrey S.
Published: April 2022

Convolutional neural networks (CNNs) are often described as promising models of human vision, yet they show many differences from human abilities. We focus on a superhuman capacity of top-performing CNNs, namely, their ability to learn very large datasets of random patterns. We verify that human learning on such tasks is extremely limited, even with few stimuli. We argue that the performance difference is due to CNNs’ overcapacity and introduce biologically inspired mechanisms to constrain it, while retaining the good test set generalisation to structured images as characteristic of CNNs. We investigate the efficacy of adding noise to hidden units’ activations, restricting early convolutional layers with a bottleneck, and using a bounded activation function. Internal noise was the most potent intervention and the only one which, by itself, could reduce random data performance in the tested models to chance levels. We also investigated whether networks with biologically inspired capacity constraints show improved generalisation toout-of-distributionstimuli, however little benefit was observed. Our results suggest that constraining networks with biologically motivated mechanisms paves the way for closer correspondence between network and human performance, but the few manipulations we have tested are only a small step towards that goal.
Downregulating α-synuclein in iPSC-derived dopaminergic neurons mimics electrophysiological phenotype of the A53T mutation
Authors: Hornauer Philipp , Prack Gustavo , Anastasi Nadia , Ronchi Silvia , Kim Taehoon , Donner Christian , Fiscella Michele , Borgwardt Karsten , Taylor Verdon , Jagasia Ravi , Roqueiro Damian , Hierlemann Andreas , Schröter Manuel
Published: April 2022

Parkinson’s disease (PD) is a common debilitating neurodegenerative disorder, characterized by a progressive loss of dopaminergic (DA) neurons. Mutations, gene dosage increase, and single nucleotide polymorphisms in the α-synuclein-encoding gene SNCA either cause or increase the risk for PD. However, neither the function of α-synuclein in health and disease, nor its role throughout development is fully understood. Here, we introduce DeePhys, a new tool that allows for data-driven functional phenotyping of neuronal cell lines by combining electrophysiological features inferred from high-density microelectrode array (HD-MEA) recordings with a robust machine learning workflow. We apply DeePhys to human induced pluripotent stem cell (iPSC)-derived DA neuron-astrocyte co-cultures harboring the prominent SNCA mutation A53T and an isogenic control line. Moreover, we demonstrate how DeePhys can facilitate the assessment of cellular and network-level electrophysiological features to build functional phenotypes and to evaluate potential treatment interventions. We find that electrophysiological features across all scales proved to be highly specific for the A53T phenotype, enabled to predict the genotype and age of individual cultures with high accuracy, and revealed a mutant-like phenotype after downregulation of α-synuclein.
String-Pulling as a Behavioral Assessment of Skilled Forelimb Motor Function in a Middle Cerebral Artery Occlusion Rat Model
Authors: Hart Muriel , Blackwell Ashley A. , Whishaw Ian Q. , Wallace Douglas G. , Cheatwood Joseph L.
Published: April 2022

Stroke is a leading cause of long-term disability in humans and frequently results in bilateral impairments in fine motor control. Many behavioral tasks used to assess rodent models of stroke evaluate a single limb; however, recent work has demonstrated that bilateral hand-over-hand movements used to pull in a string assess skilled movement of both hands.

Devascularization focused on the forelimb portion of sensorimotor cortex has been observed to produce persistent disruptions in the topographical organization of string-pulling behavior. The current study examined changes in string-pulling after a more clinically relevant rodent model of stroke via middle cerebral artery occlusion (MCAO). Detailed movement analyses revealed disruptions in the bilateral organization of string-pulling and fine motor control of both hands. Rats missed the string more often with both hands, and when the string was missed on the impaired side, rats continued to cycle through subcomponents of string-pulling behavior as if the string were grasped in the hand. Rats also failed to make a grasping motion with the impaired hand when the string was missed and instead, demonstrated an open-handed raking-like motion. No differences were found in time to approach or to complete the string-pulling task to obtain a reward, demonstrating the importance of using a detailed functional analysis of movement to detect changes in performance. String-pulling behavior is sensitive at detecting changes in bilateral rhythmical hand control following MCAO providing a foundation for future work to investigate other models of stroke and to evaluate the efficacy of therapeutic interventions that enhance neuroplasticity.
Designing microplate layouts using artificial intelligence
Authors: Francisco Rodríguez María Andreína , Puigvert Jordi Carreras , Spjuth Ola
Published: April 2022

Microplates are indispensable in large-scale biomedical experiments but the physical location of samples and controls on the microplate can significantly affect the resulting data and quality metric values. We introduce a new method based on constraint programming for designing microplate layouts that reduces unwanted bias and limits the impact of batch effects after error correction and normalisation. We demonstrate that our method applied to dose-response experiments leads to more accurate regression curves and lower errors when estimating IC50/EC50, and for drug screening leads to increased sensitivity, when compared to random layouts. It also reduces the risk of inflated scores from common microplate quality assessment metrics such as Z’ factor and SSMD. We make our method available via a suite of tools (PLAID) including a reference constraint model, a web application, and Python notebooks to evaluate and compare designs when planning microplate experiments.
Shedding Light on the Black Box of a Neural Network Used to Detect Prostate Cancer in Whole Slide Images by Occlusion-Based Explainability
Authors: Krajňanský Vojtěch , Gallo Matej , Nenutil Rudolf , Němeček Michal , Holub Petr , Brázdil Tomáš
Published: April 2022

Diagnostic histopathology is facing increasing demands due to aging populations and expanding healthcare programs. Semi-automated diagnostic systems employing deep learning methods are one approach to alleviate this pressure, with promising results for many routine diagnostic procedures. However, one major issue with deep learning approaches is their lack of interpretability—after adequate training they perform their assigned tasks admirably, but do not explain how they reach their conclusions. Knowledge of how a given method performs its task with high sensitivity and specificity would be advantageous to understand the key features responsible for diagnosis, and should in turn allow fine-tuning of deep learning approaches.

This paper presents a deep learning-based system for carcinoma detection in whole slide images of prostate core biopsies, achieving state-of-the-art performance; 100% area under curve and sensitivity of 0.978 for 8 detected false positives on average per slide.

Furthermore, we investigated various methods to extract the key features used by the neural network for classification. Of these, the technique called occlusion, adapted to whole slide images, analyzes the sensitivity of the detection system to changes in the input images. This technique produces heatmaps indicating which parts of the image have the strongest impact on the system’s output that a histopathologist can examine to identify the network’s reasoning behind a given classification. Reassuringly, the heatmaps identified several prevailing histomorphological features characterizing carcinoma, e.g. single-layered epithelium, presence of small lumina, and hyperchromatic nuclei with halos.

A convincing finding was the recognition of their mimickers in non-neoplastic tissue. The results show that the neural network approach to recognize prostatic cancer is similar to that taken by a human pathologist at medium optical resolution. The use of explain-ability heatmaps provides added value for automated digital pathology to analyze and fine-tune deep learning systems, and improves trust in computer-based decisions.
A ROS-dependent mechanism to drive progression through S phase
Authors: Kirova Dilyana Georgieva , Judasova Kristyna , Vorhauser Julia , Zerjatke Thomas , Leung Jacky Kieran , Glauche Ingmar , Mansfeld Jörg
Published: April 2022

Long considered as cytotoxic reagents, reactive oxygen species (ROS) at the right concentration promote cell proliferation in cell culture, stem cells and model organisms. However, how ROS signaling is coordinated with cell cycle progression and integrated into the cell cycle control machinery on the molecular level remains unsolved. Here, we report oscillations of mitochondrial ROS during the cell cycle that target cyclin-dependent kinase 2 (CDK2). Chemical and metabolic interference with ROS production decrease T-loop phosphorylation on CDK2, impeding its full activation and thus efficient DNA replication. ROS regulate CDK2 activity through oxidation of a conserved cysteine residue in close proximity to the T-loop, which prevents binding of the T-loop phosphatase KAP. Together our data reveal how ROS couple mitochondrial metabolism to DNA replication and cell cycle progression, and provide a solution to the longstanding conundrum of how KAP activity towards CDKs can be cell cycle-regulated.
Human iPSC-Vascular Smooth Muscle Cell Spheroids Demonstrate Size-dependent Alterations in Cellular Viability and Secretory Function
Authors: Islam Sara , Parker Jackson , Dash Biraja C. , Hsia Henry
Published: April 2022

Human induced pluripotent stem cells and their differentiated vascular cells have been revolutionizing the field of regenerative wound healing. These cells are shown to be rejuvenated with immense potentials in secreting paracrine factors. Recently, hiPSC-derived vascular smooth muscle cells (hiPSC-VSMC) have shown regenerative wound healing ability via their paracrine secretion. The quest to modulate the secretory function of these hiPSC-VSMC is an ongoing effort and involves the use of both biochemical and biophysical stimuli. This study explores the development and optimization of a reproducible, inexpensive protocol to form hiPSC-VSMC derived spheroids to investigate the implications of spheroid size on viability and paracrine secretion. Our data shows the successful formation of different sizes of spheroids using various amount of hiPSC-VSMC. The hiPSC-VSMC spheroids formed with 10000 cells strike an ideal balance between overall cell health and maximal paracrine secretion. The conditioned medium from these spheroids was found to be bioactive in enhancing human dermal fibroblast cell proliferation and migration. This research will inform future studies on the optimal spheroid size for regenerative wound healing applications.
Mass extravasation and tubular uptake of red blood cells results in toxic injury to the tubules during kidney ischemia from venous clamping
Authors: McLarnon Sarah R. , Johnson Chloe , Sun Jingping , Wei Qingqing , Csanyi Gabor , O’Herron Phillip , Marshall Brendan , Sullivan Jennifer C. , Barrett Amanda , O’Connor Paul M.
Published: April 2022

Vascular congestion is common in ischemic acute kidney injury (AKI) and represents densely packed red blood cells (RBC) in the kidney circulation. In this study we tested the hypothesis that ‘vascular congestion directly promotes tubular injury’.

Studies were performed in male and female Wistar-Kyoto rats. Vascular congestion and tubular injury were examined between renal venous clamping, arterial clamping and venous clamping of blood perfused and blood free kidneys. Vessels were occluded for either 15 or 45 minutes without reperfusion.

We found that venous clamping resulted in greater vascular congestion than arterial clamping, particularly in the outer-medullary region (P<0.001). Venous clamping resulted in significant tubular injury, including cell swelling, tubular degeneration and luminal cast formation following as little as 15 minutes of occlusion. Tubular injury was significantly less following arterial clamping (P<0.001). Numerous red droplets were observed within tubular cells which were most prominent following venous clamping. Electron microscopy and immunohistochemistry identified these as derived from RBCs and indicated that RBCs from congested renal capillaries were extravasated and phagocytosed by tubular cells. CD235a staining confirmed tubular uptake and secretion of RBCs. Cast formation and tubular swelling were absent from blood free kidneys following venous clamping (P<0.001).

Our data demonstrate that congestion of the kidney results in the rapid, mass extravasation and uptake of RBCs by tubular cells causing toxic injury to the tubules. Tubular toxicity from extravasation of RBCs appears to be a major component of tubular injury in ischemic AKI which has not previously been recognized.
Protein Kinase C Delta Regulates Mononuclear Phagocytes and Hinders Response to Immunotherapy in Cancer
Authors: Chaib Mehdi , Holt Jeremiah , Sipe Laura M. , Bohm Margaret S. , Clarice Sydney J. , Yarbro Johnathan R. , Tanveer Ubaid , Hollingsworth T.J. , Wei QingQing , Thomas Paul G. , Hayes D. Neil , Makowski Liza
Published: April 2022

Checkpoint immunotherapy unleashes T cell antitumor potential which has revolutionized cancer treatment showing unprecedented long-term responses. However, most patients do not respond to immunotherapy which often correlates with a dysfunctional or immunosuppressive myeloid compartment. The mononuclear phagocyte system (MPS) is a sub-class of myeloid cells comprising monocytes, macrophages and dendritic cells which plays a crucial role in tissue homeostasis. However, accumulating evidence suggests that mononuclear phagocytes contribute to all phases of tumorigenesis including orchestrating inflammatory events during de novo carcinogenesis, contribution to the progression of established tumors and promotion of resistance to checkpoint blockade. Thus, targeting the MPS could be an effective strategy to enhance checkpoint blockade efficacy and promote control of tumors. Here, we found that protein kinase C delta (PKCδ), a serine/threonine kinase, is abundantly expressed by mononuclear phagocytes in several human and mouse tumors. PKCδ−/−mice were more resistant to growth of various cancers compared to wild-type mice and were more responsive to anti-PD-1 immunotherapy. Furthermore, we found that tumors from PKCδ−/−mice harbor a Th-1-skewed immune landscape including increased antigen cross-presentation and T cell activation. Depletion of mononuclear phagocytesin vivoaltered tumor growth in wild-type mice, but not in PKCδ−/−mice. In addition, coinjection of PKCδ−/−-deficient M2-like macrophages with cancer cells into wild-type mice markedly delayed tumor growth and significantly increased intratumoral T cell activation compared to wild-type M2-like macrophages coinjected with cancer cells. Finally, intrinsic loss of PKCδ−/−functionally reprogrammed macrophages and dendritic cells by promoting their antigen presenting and cross-presenting capacity and triggered type I and type II interferon signaling. Thus, PKCδ might be targeted to reprogram mononuclear phagocytes and augment checkpoint blockade efficacy.
StORF-Reporter: Finding Genes between Genes
Authors: Dimonaco Nicholas J. , Aubrey Wayne , Kenobi Kim , Clare Amanda , Creevey Christopher J.
Published: April 2022

Large regions of prokaryotic genomes are currently without any annotation, in part due to well-established limitations of annotation tools. For example, it is routine for annotation tools to misreport or completely omit genes using alternative start codons. Therefore, we present StORF-Reporter, a tool that takes an annotated genome and returns missing CDS genes from unannotated regions. StORF-Reporter consists of two parts. The first begins with the extraction of unannotated regions from an annotated genome. Next, Stop-ORFs (StORFs) are identified in these unannotated regions. StORFs are open reading frames that are delimited by stop codons and thus can capture those genes most often missing in genome annotations.

We show that this methodology recovers genes missing from canonical genome annotations. We inspected the results of the genomes of model organisms, the pangenome of Escherichia coli, and a further 6,223 prokaryotic genomes of 179 genera from the Ensembl Bacteria database. StORF-Reporter was able to extend the core, soft-core and accessory gene-collections, identify novel gene families and extend families into additional genera. The high levels of sequence conservation observed between genera suggest that many of these StORF sequences are likely to be functional genes that must now be added to the canonical annotations.
The mouse claustrum synaptically connects cortical network motifs
Authors: Qadir Houman , Stewart Brent W. , VanRyzin Jonathan W. , Wu Qiong , Chen Shuo , Seminowicz David A. , Mathur Brian N.
Published: April 2022

Spatially distant areas of cerebral cortex coordinate their activity into networks that are integral to cognitive processing. A common structural motif of cortical networks is co-activated frontal and posterior cortical regions. Knowledge of the neural circuit mechanisms underlying such widespread inter-areal cortical coordination is lacking. Using anesthetized mouse functional magnetic resonance imaging (fMRI) we discovered that mouse frontal cortical functional connectivity reflects the common cortical network motif in its functional connectivity to posterior cortices, but also demonstrates significant functional connectivity with the claustrum. Exploring whether the claustrum may synaptically support such network architecture, we used a channelrhodopsin-assisted electrophysiological circuit mapping approach to assess the strength of synaptic connectivity of 35 unique frontal cortico-claustral-cortical connections through 1,050 subtype-identified claustrum projection neurons. We observed significant trans-claustral synaptic connectivity from the anterior cingulate cortex and prelimbic prefrontal cortex back to originating frontal cortical regions as well as to posteriorly-lying visual and parietal association cortices contralaterally. The infralimbic prefrontal cortex possessed significant trans-claustral synaptic connectivity with the posteriorly-lying retrosplenial cortex, but to a far lesser degree with visual and parietal association cortices. These data reveal discrete extended cortical pathways through the claustrum that are positioned to support cortical network motifs central to cognitive control functions.
Obtaining Xenopus tropicalis Embryos by In Vitro Fertilization
Authors: Lane Maura , Khokha Mustafa K.
Published: April 2022

Xenopus is a powerful model system for cell and developmental biology in part because frogs produce thousands of eggs and embryos year-round. In vitro fertilization (IVF) is ideal for obtaining developmentally synchronized embryos for microinjection or when natural mating has failed to produce a fertilization. In IVF, females are induced to ovulate, and then eggs are collected by manual expression. After testes are collected from a euthanized male frog, the eggs are fertilized in vitro. The embryos are then treated with cysteine to remove the sticky protective jelly coat. Dejellied embryos are much easier to manipulate during microinjection or when sorting in a Petri dish. The jelly coat is also very difficult to penetrate with an injection needle. After microinjection, embryos are maintained in Petri dishes until desired stages are reached. Although in vitro fertilization in X. laevis and X. tropicalis is similar, critical differences in solutions, handling of testis, response of fertilized eggs directly after introduction of sperm, and developmental timing are required for successful fertilization in X. tropicalis.
Non-singular fixed-time pose tracking control for spacecraft with dead-zone input
Authors: Ji Yuxia , Chen Li , Zhang Jun , Zhang Dexin , Shao Xiaowei
Published: April 2022

Purpose

The purpose of this paper is to investigate the pose control of rigid spacecraft subject to dead-zone input, unknown external disturbance and parametric uncertainty in space maneuvering mission.

Design/methodology/approach

First, a 6-Degree of Freedom (DOF) dynamic model of rigid spacecraft with dead-zone input, unknown external disturbances and parametric uncertainty is derived. Second, a super-twisting-like fixed-time disturbance observer (FTDO) with strong robustness is developed to estimate the lumped disturbances in fixed time. Based on the proposed observer, a non-singular fixed-time terminal sliding-mode (NFTSM) controller with superior performance is proposed.

Findings

Different from the existing sliding-mode controllers, the proposed control scheme can directly avoid the singularity in the controller design and speed up the convergence rate with improved control accuracy. Moreover, no prior knowledge of lumped disturbances’ upper bound and its first derivatives is required. The fixed-time stability of the entire closed-loop system is rigorously proved in the Lyapunov framework. Finally, the effectiveness and superiority of the proposed control scheme are proved by comparison with existing approaches.

Research limitations/implications

The proposed NFTSM controller can merely be applied to a specific type of spacecrafts, as the relevant system states should be measurable.

Practical implications

A NFTSM controller based on a super-twisting-like FTDO can efficiently deal with dead-zone input, unknown external disturbance and parametric uncertainty for spacecraft pose control.

Originality/value

This investigation uses NFTSM control and super-twisting-like FTDO to achieve spacecraft pose control subject to dead-zone input, unknown external disturbance and parametric uncertainty.
Building synergies between operations culture, operational routines, and supplier monitoring: implications for buyer performance
Authors: Shafiq Asad , Johnson P. Fraser , Klassen Robert D.
Published: April 2022

Purpose

Pressured by various stakeholder groups to improve the sustainability performance of their emerging economy suppliers, multinational firms continue to expand their supplier monitoring. Leveraging the strategy literature on alliances and the buyer-supplier relationship management literature, the authors propose that a buyer firm's efforts to proactively develop cultural sensitivity and operations cognizance to understand the operational culture and routines of its suppliers can ameliorate some shortcomings of supplier monitoring, thereby improving the performance of the buyer firm.

Design/methodology/approach

Using primary survey data from a sample of US manufacturing firms, combined with secondary data of supplier monitoring and financial performance, this research examines the relationship between supplier monitoring, cultural sensitivity, operations cognizance, and buyer firm performance.

Findings

Supplier monitoring was associated with positive but diminishing returns for financial and sustainability performance for the buyer. Second, increasing cultural sensitivity and operations cognizance for suppliers in emerging economies were associated with improved buyer performance. Finally, the synergistic use of supplier monitoring and operations cognizance was associated with improved buyer firm financial performance.

Originality/value

While the buyer-supplier relationship literature has mainly treated organizational differences between dyadic supply chain partners as exogenous to the context in which their relationship evolves, the authors posit that buyer firms' efforts to understand such differences can affect the value of buyer-directed interactions, such as supplier monitoring. This research adds to the theoretical understanding of the process of developing relational mechanisms with emerging economy suppliers. In particular, efforts of buyer firms to better understand the operational culture and routines of their suppliers can complement monitoring and are associated with a positive impact on performance.
Regional well-being in Romania: assessment after a decade of EU accession
Authors: Lazar Dorina , Litan Cristian Marius
Published: April 2022

Purpose

This paper aims to study through a comprehensive set of socioeconomic indicators the regional level of well-being achieved in Romania, and monitor the improvements and disparities in well-being after a decade of accession to the European Union.

Design/methodology/approach

A dashboard of 20 socioeconomic indicators for measuring nine dimensions of well-being for Romanian counties is proposed. Using the Adjusted Mazziotta-Pareto method are built composite indicators, which allow us to assess the trend of overall welfare scores for each county. The data are collected at the county level, for 42 counties, and each year from 2006 to 2017, from administrative sources.

Findings

The overall well-being index has an increasing trend for all counties, but the growth rate varies from one county to another. The economic factors, geographic location and share of the urban population matter. For most counties, the evolution of well-being scores is below that recorded at the country level. Romania has registered significant improvements in health, housing, income and access to public utilities dimensions. The counties are ranked by level of well-being. Some empirical measures suggest a slight tendency of socioeconomic disparities to increase over time.

Originality/value

The paper attempts to fill some gaps in measuring the level and disparities of welfare in a fast-growing emerging economy. The Romanian regional context is to a lesser extent explored in a multidimensional approach, from spatial and temporal points of view.
Framing the strategic R&D paradigm shift in Big Pharma: a content analysis of pharmaceutical annual reports
Authors: Schramm Mary E. , Place Katie R. , Laskin Alexander V.
Published: April 2022

Purpose

Between 1985 and 2000, the six largest US pharmaceutical firms entered a very active period of partnerships with other pharmaceutical firms to expand their knowledge of biotechnology-based research and development (R&D) frameworks and to bolster the growth of their drug portfolios. The purpose of this study is to examine the annual reports published by these companies for evidence of strategic framing of these partnerships.

Design/methodology/approach

A content analysis method was most appropriate for this study, as it allows for analysis of a large amount of information and accurate analysis over time. Ninety-six annual reports from the six major US pharmaceutical firms (Abbott, Bristol Myers Squibb, Eli Lilly, Johnson and Johnson, Merck, and Pfizer) were coded. The final codebook included 18 categories derived from framing theory. After collection, the data were uploaded to SPSS for statistical analysis.

Findings

Results indicate that mention of partnerships grew considerably in depth and length over time, but companies did not consistently employ frames to describe why or how they engaged in external partnerships.

Originality/value

This is the first study to assess mentions of pharmaceutical firms' external efforts to build their R&D programs and drug portfolios, from the intersecting perspectives of framing theory and the resource-based view (RBV) of the firm, to illustrate how changes were communicated to shareholders during a dynamic period of change within the industry.