bluuebunny/crossref_metadata_2025_split huggingface dataset:
Precision RNAi using synthetic shRNAmir target sites
Authors: Hoffmann Thomas , Hörmann Alexandra , Corcokovic Maja , Zmajkovic Jakub , Hinterndorfer Matthias , Salkanovic Jasko , Spreitzer Fiona , Köferle Anna , Gitschtaler Katrin , Popa Alexandra , Oberndorfer Sarah , Andersch Florian , Schäfer Markus , Fellner Michaela , Budano Nicole , Ruppert Jan G. , Chetta Paolo , Wurm Melanie , Zuber Johannes , Neumüller Ralph A. 
Published: November 2022

AbstractLoss-of-function genetic tools are widely applied for validating therapeutic targets, but their utility remains limited by incomplete on- and uncontrolled off-target effects. We describe artificial RNA interference (ARTi) based on synthetic, ultra-potent, off-target-free shRNAs that enable efficient and inducible suppression of any gene upon introduction of a synthetic target sequence into non-coding transcript regions. ARTi establishes a scalable loss-of-function tool with full control over on- and off-target effects.
Structural modelling of human complement FHR1 and two of its synthetic derivatives provides insight into theirin-vivofunctions
Authors: Ruiz-Molina Natalia , Parsons Juliana , Decker Eva L. , Reski Ralf 
Published: November 2022

ABSTRACTHuman complement is the first line of defence against invading pathogens and is involved in tissue homeostasis. Complement-targeted therapies to treat several diseases caused by a dysregulated complement are highly desirable. Despite huge efforts invested in their development, only very few are currently available, and a deeper understanding of the numerous interactions and complement regulation mechanisms is indispensable. Two important complement regulators are human Factor H (FH) and Factor H-related protein 1 (FHR1). MFHR1 and MFHR13, two promising therapeutic candidates based on these regulators, combine the dimerization and C5-regulatory domains of FHR1 with the central C3-regulatory and cell surface-recognition domains of FH. Here, we used AlphaFold2 to model the structure of these two synthetic regulators. Moreover, we used AlphaFold-Multimer (AFM) to study possible interactions of C3 fragments and membrane attack complex (MAC) components C5, C7 and C9 in complex with FHR1, MFHR1, MFHR13 as well as the best-known MAC regulators vitronectin (Vn), clusterin and CD59, whose experimental structures remain undetermined. AFM successfully predicted the binding interfaces of FHR1 and the synthetic regulators with C3 fragments and suggested binding to C3. The models revealed structural differences in binding to these ligands through different interfaces. Additionally, AFM predictions of Vn, clusterin or CD59 with C7 or C9 agreed with previously published experimental results. Because the role of FHR1 as a MAC regulator has been controversial, we analysed possible interactions with C5, C7 and C9. AFM predicted interactions of FHR1 with proteins of the terminal complement complex (TCC) as indicated by experimental observations, and located the interfaces in FHR11-2and FHR4-5. According to AFM predictions, FHR1 might partially block the C3b binding site in C5, inhibiting C5 activation, and block C5b-7 complex formation and C9 polymerization, with similar mechanisms of action as clusterin and vitronectin. Here, we generate hypotheses and provide the basis for the design of rational approaches to understand the molecular mechanism of MAC inhibition, which will facilitate the development of further complement therapeutics.
Epigenomic tomography for probing spatially-defined molecular state in the brain
Authors: Liu Zhengzhi , Deng Chengyu , Zhou Zirui , Xiao Ya , Jiang Shan , Zhu Bohan , Naler Lynette B. , Jia Xiaoting , Yao Danfeng (Daphne) , Lu Chang 
Published: November 2022

ABSTRACTSpatially-resolved genomic profiling is critical for understanding biology in a spatially ordered organ such as mammalian brain. Single-cell spatial genomic assays were developed recently for this purpose but they remain costly and labor-intensive for examining brain tissues across substantial dimensions and surveying a collection of brain samples. Here we demonstrate a new approach, brain epigenomic tomography, that maps spatial epigenomic variations at the scale of centimeters. We profiled neuronal and glial fractions of mouse neocortex slices with 0.5 mm thickness using a low-input technology. H3K27me3 or H3K27ac features across these slices were grouped into clusters based on their spatial variation patterns. Our approach reveals striking dynamics in frontal and caudal cortex due to kainic acid-induced seizure, linked with transmembrane ion transporter, exocytosis of synaptic vesicles, and secretion of neurotransmitter. Epigenomic tomography provides a powerful and cost-effective tool for profiling and discerning brain samples based on their spatial epigenomes.
Efficient Gene Transduction in Pigs and Macaques with the Engineered AAV Vector AAV.GT5 for Hemophilia B Gene Therapy
Authors: Kashiwakura Yuji , Endo Kazuhiro , Ugajin Atsushi , Kikuchi Tomohiro , Hishikawa Shuji , Nakamura Hitoyasu , Katakai Yuko , Baatartsogt Nemekhbayar , Hiramoto Takafumi , Hayakawa Morisada , Kamoshita Nobuhiko , Yamazaki Shoji , Kume Akihiro , Mori Harushi , Sata Naohiro , Sakata Yoichi , Muramatsu Shin-ichi , Ohmori Tsukasa 
Published: November 2022

AbstractGene therapy for hemophilia using adeno-associated virus (AAV) vectors allows long-term coagulation factor expression. We examined the potential of a novel engineered liver-tropic AAV3B-based vector AAV.GT5 for hemophilia B gene therapy.In vitrotransduction with AAV.GT5 in human hepatocytes was more than 100 times higher than with AAV-Spark100, whilein vivotransduction efficacy into the liver and the increase in coagulation factor IX (FIX) antigen following intravenous injection of these vectors were similar in PXB mice (chimeric mice with a humanized liver) and macaques. The discrepancy was due to the low recovery and short half-life of AAV.GT5 in blood, depending on the positive charge of the heparin-binding site in the original AAV3B. The intra-hepatic vascular administration of AAV.GT5, but not AAV-Spark100, enhanced vector transduction into the liver and reduced vector distribution to the kidney in pigs. In macaques, the intra-hepatic artery injection of AAV.GT5 yielded a comparable increase in FIX antigen with a one-third dosage of peripheral venous administration. Two of four macaques who received AAV.GT5 intravenously did not develop neutralizing antibodies (NAbs) against AAV.GT5, while AAV-Spark100 induced serotype-specific NAbs in all four macaques. The NAb produced after the administration was relatively specific to the serotype and less responsive to the other serotype. As a result, the administration of AAV.GT5 successfully boosted FIX expression in one animal previously given AAV-Spark100. Thus, AAV.GT5 has different biodistribution and immunogenic characteristics compared with AAV-Spark100, and the intra-hepatic vascular administration may lessen the vector dose and avoid vector distribution to other organs.Key PointsThe AAV.GT5 vector has a strong transduction efficacy in human hepatocytes but has a faster clearance after systemic administration.Intra-hepatic vascular administration of the AAV.GT5 vector is an effective liver transduction method for hemophilia gene therapy.
Multi-omics analyses of single cell-derived colorectal cancer organoids reveal intratumor heterogeneity and immune response diversity
Authors: Yue Jian-Hui , Li Jie , Xu Qu-Miao , Ma Qi-Wang , Chen Chao , Liu Song-Ming , Sun Hai-Xi , Sui Qiao-Qi , Mu Feng , Ding Pei-Rong , Liu Long-Qi , Perez-Moreno Mirna , Zhang Xi 
Published: November 2022

AbstractColorectal cancer (CRC) organoids have similar genomic and functional characteristics to the original specimens. They have become a novel and promising tumor model. However, systematic research of heterogeneity and evolution based on tumor organoids and unbiased evaluation of CD4+T cell-mediated tumor recognition is presently lacking. Here, we study the variability in genomic characterization and single-cell transcriptome between different tumor organoid clones derived from the same CRC patient. While clone-specific differences in driver gene mutations and cancer stem cell (CSC) subpopulations were observed, inter-clone heterogeneity was even more prevalent. Using single-cell RNA sequencing, we found that compared with bulk organoids, CRC organoid clones are mainly composed of cancer stem cells and transiently-amplifying cells (TACs), but no epithelial-mesenchymal transition (EMT)-like (S100A4+CDH1-) cells. In addition, we study the phenotypic characteristics and TCR properties of tumor-reactive CD4+T cells by coupling the organoid-TILs co-culture model, single-cell profiling, and recognition testing of candidate TCRs. We found that the proliferating CD4+T cells increased significantly from 7.1% to 35.4%, and the TCR clonotypes increased from 110 to 1043 after co-culture with organoids. Moreover, 4 of 10 (40%) candidate TCRs with a significant increase in clone abundance exhibited tumor recognition. These results provide evidence that the proliferating CD4+T cells with clonal expansion after co-culture with tumor organoids are the potential tumor-reactive T cells. Collectively, we reconstructed intra-patient heterogeneity in single cell-derived organoid models and characterized the phenotypic characteristics and functional properties of tumor-reactive CD4+T cells.
Brief temporal perturbations in somatosensory reafference disrupt perceptual and neural attenuation and increase supplementary motor-cerebellar connectivity
Authors: Kilteni Konstantina , Houborg Christian , Ehrsson H. Henrik 
Published: November 2022

AbstractIntrinsic delays in sensory feedback can be detrimental for motor control. As a compensation strategy, the brain predicts the sensory consequences of movement via a forward model on the basis of a copy of the motor command. Using these predictions, the brain attenuates the somatosensory reafference to facilitate the processing of exafferent information. Theoretically, this predictive attenuation gets disrupted by (even minimal) temporal errors between the predicted and the actual reafference, but direct evidence for such disruption is lacking since previous neuroimaging studies contrasted conditions of nondelayed reafferent input with exafferent one. Here, we combined psychophysics with functional magnetic resonance imaging to test whether subtle perturbations in the timing of somatosensory reafference disrupt its predictive processing. Twenty-eight participants generated touches on their left index finger by tapping a sensor with their right index finger. The touches on the left index finger were delivered at the time of the two fingers’ contact or with a 100 ms delay. We found that such brief temporal perturbations disrupted the attenuation of the somatosensory reafference both at the perceptual and neural level, leading to greater somatosensory and cerebellar responses and weaker somatosensory connectivity with the cerebellum proportionally to perceptual changes. Moreover, we observed increased connectivity of the supplementary motor area with the cerebellum during the perturbations. We interpret these effects as the failure of the forward model to predictively attenuate the delayed somatosensory reafference and the return of the prediction error to the motor centers, respectively.Significance statementOur brain receives the somatosensory feedback of our movements with delay. To counteract these delays, motor control theories postulate that the brain predicts the timing of the somatosensory consequences of our movements and attenuates sensations received at that timing. This makes a self-generated touch feel weaker than an identical external touch. However, how subtle temporal errors between the predicted and the actual somatosensory feedback perturb this predictive attenuation remains unknown. We show that such errors make the otherwise attenuated touch feel stronger, elicit stronger somatosensory responses, weaken the cerebellar connectivity with somatosensory areas, and increase it with motor areas. These findings show that motor and cerebellar areas are fundamental in forming temporal predictions about the sensory consequences of our movements.
Deep Domain Adversarial Neural Network for the Deconvolution of Cell Type Mixtures in Tissue Proteome Profiling
Authors: Wang Fang , Yang Fan , Huang Longkai , Song Jiangning , Gasser Robin B. , Aebersold Ruedi , Wang Guohua , yao Jianhua 
Published: November 2022

AbstractCell type deconvolution is a computational method for the determination/resolution of cell type proportions from bulk sequencing data, frequently used for the analysis of divergent cell types in tumor tissue samples. However, deconvolution technology is still in its infancy for the analysis of cell types using proteomic data due to challenges with repeatability/reproducibility, variable reference standards and the lack of single-cell proteomic reference data. Here, we developed a novel deep learning-based deconvolution method (scpDeconv) tailored to proteomic data. scpDeconv uses an autoencoder to leverage the information from bulk proteomic data to improve the quality of single-cell proteomic data, and employs a domain adversarial architecture to bridge the single-cell and bulk data distributions and transfer labels from single-cell data to bulk data. Extensive experiments validated the performance of scpDeconv in the deconvolution of proteomic data produced from various species/sources and different proteomic technologies. This method should find broad applicability to areas including tumor microenvironment interpretation and clinical diagnosis/classification.
Transcriptional diversity in synaptic gene sets is sufficient to discriminate cortical neuronal identity
Authors: Adam Amparo Roig , López Jose Martínez , van der Spek Sophie ,   The SYNGO consortium, Sullivan Patrick F , Smit August B. , Verhage Matthijs , Hjerling-Leffler Jens 
Published: November 2022

AbstractSynapse diversity has been described from different perspectives, ranging from the specific neurotransmitters released, to their diverse biophysical properties and proteome profiles. However, synapse diversity at the transcriptional level has not been systematically identified across all synapse populations in the brain. To quantify postsynaptic and identify specific synaptic features of neuronal cell types we combined the SynGO (Synaptic Gene Ontology) database with single-cell RNA sequencing data of the mouse neocortex. We show that cell types can be discriminated by synaptic genes alone with the same power as all genes. The cell type discriminatory power is not equally distributed across synaptic genes as we could identify functional categories and synaptic compartments with greater cell type specific expression. Synaptic genes, and specific SynGO categories, belonged to three different types of gene modules: gradient expression over all cell types, gradient expression in selected cell types and cell class- or type-specific profiles. This data provides a deeper understanding of synapse diversity in the neocortex and identifies potential markers to selectively identify synapses from specific neuronal populations.
Thermodynamic Parameters Contributions of Single Internal Mismatches In RNA/DNA Hybrid Duplexes
Authors: Xiang Tongjun , Feng Huibao , Xing Xin-hui , Zhang Chong 
Published: November 2022

ABSTRACTNucleic acid is a fundamental component of life. The thermodynamic is a basic physical quantity for nucleic acid and has been adopted in varieties of biotechnological applications. However, the parameters predicting thermodynamic parameters of RNA/DNA hybrid duplexes is incomplete and thus lead to the inability to proper predicting the properties. To address this problem, we measured for 99 RNA/DNA hybrid duplexes with 11 nucleotide length in a 1 M NaCl buffer using UV absorbance thermal denaturation. Thermodynamic parameters were obtained by fitting absorbance versus temperature profiles using SciPy non-linear curve fit. A dataset of 228 duplexes were constructed combining with literature experimental thermodynamic parameters for fitting a full set of all 113 possible Watson-Crick and single internal mismatch involving nearest-neighbor parameters using singular value decomposition. The new nearest-neighbor parameters predict thermodynamic parameters of RNA/DNA hybrid duplexes within an average error of 0.26 kcal/mol (3.55%) in free energy at 37°C (ΔG°37), 5.05 kcal/mol (6.70%) in enthalpy (ΔH°), 16.3 cal/mol·K (7.50%) in entropy (ΔS°) and 1.14°C (2.91%) in melting temperature (Tm). The highest accuracy of all parameters reported. We observed a trend of increased stability for mismatch involving pairs of rG/dT >> rU/dG > rG/dA > rG/dG ≈ rA/dC ≈ rA/dG > rC/dA ≈ rC/dT > rU/dT ≈ rU/dC >> rA/dA >> rC/dC, which can be explained by different hydrogen bond conditions in mismatch pairs. We further compared the stability with RNA/RNA and DNA/DNA duplexes and found a backbone structure depended pattern in these three kinds of nucleic acid duplexes. This nearest-neighbor parameter set could enhance thermodynamical understanding of RNA/DNA combination and have potential usage in predicting on- and off-target RNA-DNA binding activity when applied to biotechnological applications such as CRISPR/Cas systems, RNAi and qPCR.
Leverage Edu: caught between novelty and efficiency
Authors: Kumari Deepa , Srivastava Ritu 
Published: November 2022

Learning outcomes
The learning outcomes are as follows:
1. enable students to appreciate how a platform company can navigate through diminishing network effects;
2. enable students to foresee the downside of scaling up a platform business;
3. enable students to appreciate the trade-off between an efficiency-centric and a novelty-centric business model for platform businesses; and
4. enable students to create a platform business model canvas for a company.

Case overview/synopsis
The teaching case discusses the dilemma of Akshay Chaturvedi, the founder of Leverage Edu, an artificial intelligence-enabled platform for students seeking admission to foreign universities. It had received nearly US$9.6m in funding until December 2021.
Chaturvedi wanted to make the best use of his funds, but was torn between turning Leverage Edu into an “efficient platform” and transforming it into a “novelty-centric platform”. The teaching note attempts to resolve Chaturvedi’s dilemma by analyzing competitors using the platform canvas model and determining how Chaturvedi could create and use network effects to Leverage Edu’s advantage. The case is based on secondary data that is freely available in the public domain.

Complexity academic level
This case is intended for MBA Entrepreneurship students taking a platform business elective. It can also be used in faculty and management development programs under the banner “Technology and Platform Businesses”.

Supplementary materials
Teaching notes are available for educators only.

Subject code
CSS 3: Entrepreneurship.
QMS external quality auditors’ competency requirements: perspectives from accredited certification bodies in Malaysia
Authors: Ab Wahid Roslina , Tan Peck-Leong 
Published: November 2022

PurposeThe purpose of the study is to identify the perceived lack of certain core knowledge, skills and attributes in external quality auditors (EQAs) that contributes to an audit process that does not add value for client organizations. This paper describes the development of a competency requirement framework for quality management system (QMS) EQAs that would improve their capability and audit performance.Design/methodology/approachA review of relevant international literature on auditor competence and education, clients' expectations on external auditors, explicit and implicit expectations based on ISO 9001:2015 and ISO 19011:2018, and current auditor capability was conducted to obtain insights into the present situation and requirements of the environment. A survey questionnaire was then utilized in the collection of data from 19 heads of certification and technical reviewers of accredited certification bodies (CBs) in Malaysia. Univariate and bivariate analysis were used in analyzing the data from respondents.FindingsThe overall results show that the most important components of knowledge for EQAs to possess are quality management principles, system and standards; risk management; and business process and operations management. In terms of skills, the most important skills for auditors are auditing and report writing and critical/analytical thinking, followed by communication/interpersonal/people/ICT and team management. Attributes such as integrity, being ethical, professional and objective are found to be most important in EQAs to be effective and add value to the audits. Based on the results, the competency requirement framework of EQAs was developed.Originality/valueThis paper presents the knowledge, skills, attitudes and experience needed by EQAs identified by the CBs which is then developed into a competency requirements framework for future auditor training. The resulting framework from the study can be used by accreditation bodies, CBs and training organizations to evaluate and improve the auditors' competence and audit performance in the future.
Forward and backward mixed-mode crack estimation using artificial neural network
Authors: Khademalrasoul Abdolghafour , Hatampour Zahra , Oulapour Masoud , Alavi Seyed Enayatollah 
Published: November 2022

PurposeIn this manuscript, the authors aimed to demonstrate the influences of influential parameters in mixed-mode crack propagation phenomenon. The authors attempted to cover almost all surrounding issues of this subject as the authors know simulating of propagating cracks as internal strong discontinuity is a complicated issue.Design/methodology/approachIn this manuscript, the authors demonstrated the influences of influential parameters in mixed-mode crack propagation phenomenon. The authors attempted to cover almost all surrounding issues of this subject as the authors know simulating of propagating cracks as internal strong discontinuity is a complicated issue. Furthermore, three different scenarios for crack growth are considered. In reality, edge-cracked plate, center-cracked plate and cracked plate in the presence of void and inclusion are studied. In fact, by designing suitable artificial neural network's (ANN) architectures all the three aforementioned conditions are trained and estimated through those architectures with very good agreement with input data. Also by conducting a series of sensitivity analysis, the most affecting factors in mixed-mode crack propagation in different situations are demonstrated. The obtained results are very interesting and useful for other researchers and also the authors hope the results would be cited by researchers.FindingsThe influential parameters on mixed-mode crack propagation were found in this paper.Originality/valueThe computer code using MATLAB was prepared to study the mixed-mode crack paths. Also using ANNs toolbox, the crack path estimation was investigated.