bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractAutomatic 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 URLhttps://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

AbstractConvolutional 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

AbstractParkinson’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

AbstractStroke 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

AbstractMicroplates 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

AbstractDiagnostic 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

SUMMARYLong 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

AbstractHuman 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

ABSTRACTVascular 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

AbstractCheckpoint 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

ABSTRACTLarge 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

SummarySpatially 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.
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.