bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeting TACC3 represents a novel vulnerability in highly aggressive breast cancers with centrosome amplification
Authors: Saatci Ozge , Akbulut Ozge , Cetin Metin , Sikirzhytski Vitali , Sahin Ozgur 
Published: May 2022

AbstractCentrosome amplification (CA) is a hallmark of cancer that is strongly associated with highly aggressive disease and worse clinical outcome. However, there are no effective strategies targeting cancer cells with CA while sparing normal cells. Here, we identified Transforming Acidic Coiled-Coil Containing Protein 3 (TACC3) to be overexpressed in tumors with CA, and its high expression is associated with dramatically worse clinical outcome. We demonstrated that TACC3 forms distinct functional interactions in mitotic and non-mitotic cancer cells with CA to facilitate centrosome clustering (CC) and transcriptional repression of tumor suppressors, respectively. We showed, for the first time, that TACC3 interacts with the Kinesin Family Member C1 (KIFC1) via its TACC domain in mitotic cells with CA and inhibition of TACC3 blocks this interaction, leading to apoptosis via multipolar spindle formation and activation of spindle assembly checkpoint (SAC)/CDK1/p-Bcl2 axis. In interphase, TACC3 interacts with the members of the nucleosome remodeling and deacetylase (NuRD) complex (HDAC2 and MBD2) in nucleus, and its inhibition causes p53-independent G1 arrest and apoptosis by blocking these interactions and activating the transcription of key tumor suppressors (e.g., p21, p16 and APAF1). Notably, inducing CA by chemical (cytochalasin D) or genomic (PLK4 overexpression or p53 loss) modulations renders cancer cells highly sensitive to TACC3 inhibition. Targeting TACC3 by small molecule inhibitors or guide RNAs strongly inhibits growth of organoids and breast cancer cell line- and patient-derived xenografts with CA. Altogether our results pave the way towards therapeutic targeting of TACC3 in highly aggressive cancers.
Long-term functional regeneration of radiation-damaged salivary glands through delivery of a neurogenic hydrogel
Authors: Li Jianlong , Sudiwala Sonia , Berthoin Lionel , May Alison J. , Mohabbat Seayar , Sinada Hanan , Gaylord Eliza A. , Pacheco Noel Cruz , Lombaert Isabelle M.A. , Jeon Oju , Alsberg Eben , Bahney Chelsea S. , Knox Sarah M. 
Published: May 2022

AbstractSalivary gland acinar cells are severely depleted after radiotherapy for head and neck cancer, leading to loss of saliva and extensive oro-digestive complications. With no regenerative therapies available, organ dysfunction is irreversible. Here using the adult murine system, we demonstrate radiation-damaged salivary glands can be functionally regenerated via sustained delivery of the neurogenic muscarinic receptor agonist, cevimeline. We show that endogenous gland repair coincides with increased nerve activity and acinar cell division that is limited to the first week post-radiation, with extensive acinar cell degeneration, dysfunction and cholinergic denervation occurring thereafter. However, we discovered that mimicking cholinergic muscarinic input via sustained local delivery of a cevimeline-alginate hydrogel was sufficient to regenerate innervated acini and retain physiological saliva secretion at non-irradiated levels over the long-term (> 3 months). Thus, we reveal a novel regenerative approach for restoring epithelial organ structure and function that has significant implications for human patients.TeaserNovel application of an injectable neurogenic-based hydrogel for restoring the structure and function of radiation-damaged tissue.
Held out wings RNA binding activity in the cytoplasm during early spermatogenesis
Authors: Agapiou Michaela , Hopes Tayah , Hobor Fruzsina , Bretman Amanda , Edwards Thomas A. , Aspden Julie L. 
Published: May 2022

AbstractHeld out wings (HOW) is an RNA-binding protein essential for spermatogenesis in Drosophila melanogaster. HOW is a signal transduction and activation of RNA (STAR) protein, regulating post-transcriptional gene expression. The characteristics of RNA-binding by the conserved short cytoplasmic isoform, HOW(S), are unknown. In vivo RIP-seq identified 121 novel transcripts bound by HOW(S) in germ stem cells and spermatogonia, many with signal transduction functions. (A/G/U)CUAAC motifs were enriched in 3’-UTRs and GCG(A/U)G in 5’-UTRs. HOW binds with high-affinity to sites containing CUAAC motifs from lola and hipk mRNAs. This study provides new insight into STAR protein-RNA interactions and functions in spermatogenesis.
A preclinical model to investigate normal tissue damage following fractionated radiotherapy to the head and neck
Authors: Juvkam Inga Solgård , Zlygosteva Olga , Arous Delmon , Galtung Hilde Kanli , Malinen Eirik , Søland Tine Merete , Edin Nina Jeppesen 
Published: May 2022

AbstractRadiotherapy of head and neck cancer is known to cause both early and late-occurring toxicities. To better appraise normal tissue responses and their dependence on treatment parameters such as radiation field and type, as well as dose and fractionation scheme, a preclinical model with relevant endpoints is required. 12-week old female C57BL/6J mice were irradiated with 100 or 180 kV X-rays to total doses ranging from 30 to 85 Gy, given in 10 fractions over 5 days. The radiation field covered the oral cavity, swallowing structures, and salivary glands. Monte Carlo simulations were employed to estimate tissue dose distribution. The follow-up period was 35 days, in order to study the early radiation-induced effects. Baseline and post irradiation investigations included macroscopic and microscopic examinations of the skin, lips, salivary glands, and oral mucosa. Saliva sampling was performed to assess the salivary gland function following radiation exposure. A dose dependent radiation dermatitis in the skin was observed for doses above 30 Gy. Oral mucositis in the tongue appeared as ulcerations on the ventral surface of the tongue for doses of 75-85 Gy. The irradiated mice showed significantly reduced saliva production compared to controls. In summary, a preclinical model to investigate a broad panel of normal tissue responses following fractionated irradiation of the head and neck region was established. The optimal dose to study early radiation-induced effects was found to be around 75 Gy, as this was the highest tolerated dose that gave acute effects similar to what is observed in cancer patients.
Camera-based monitoring of Bogong moths in Alpine Australia reveals drivers of migratory behaviour
Authors: Wallace Jesse R A , Reber Therese , Khaldy Lana , Mathews-Hunter Benjamin , Green Ken , Dreyer David , Warrant Eric J 
Published: May 2022

AbstractThe Bogong moth Agrotis infusa is well known for its remarkable annual round-trip migration from its breeding grounds across eastern Australia to its aestivation sites in the Australian Alps, to which it provides an important annual influx of nutrients. Over recent years, we have benefited from a growing understanding of the navigational abilities of the Bogong moth. Meanwhile, the population of Bogong moths has been shrinking. Recently, the ecologically and culturally important Bogong moth was listed as endangered by the IUCN Red List, and the establishment of a program for long-term monitoring of its population has been identified as critical for its conservation. Here, we present the results of two years of monitoring of the Bogong moth population in the Australian Alps using a recently developed method for automated monitoring of flying insects, named Camfi. We found that the evening flights of Bogong moths occur throughout summer, and are modulated by daily weather factors. We present a simple heuristic model of the arrival to and departure from aestivation sites by Bogong moths, and confirm results obtained from fox-scat surveys which found that aestivating Bogong moths occupy higher elevations as the summer progresses. We also present the first recorded observations of the impact of bushfire smoke on aestivating Bogong moths. We observed a dramatic reduction in the size of a cluster of aestivating Bogong moths during the fire, and evidence of a large departure from the fire-affected area the day after the fire. Our results highlight the challenges of monitoring Bogong moths in the wild, and support the continued use of automated camera-based methods for that purpose.
Deep Learning-Based Parameter Estimation for Neurophysiological Models of Neuroimaging Data
Authors: Griffiths John David , Wang Zheng , Ather Syed Hussain , Momi Davide , Rich Scott , Diaconescu Andreea , McIntosh Anthony Randal , Shen Kelly 
Published: May 2022

AbstractConnectome-based neural mass modelling is the emerging computational neuroscience paradigm for simulating large-scale network dynamics observed in whole-brain activity measurements such as fMRI, M/EEG, and related techniques. Estimating physiological parameters by fitting these models to empirical data is challenging however, due to large network sizes, often physiologically detailed fast-timescale system equations, and the need for long (e.g. tens of minutes) simulation runs. Here we introduce a novel approach to connectome-based neural mass model parameter estimation by employing optimization tools developed for deep learning. We cast the system of differential equations representing both neural and haemodynamic activity dynamics as a deep neural network, implemented within a widely used machine learning programming environment (PyTorch). This allows us to use robust industry-standard optimization algorithms, automatic differentiation for computation of gradients, and other useful functionality. The approach is demonstrated using a connectome-based network with nodal dynamics specified by the two-state RWW mean-field neural mass model equations, which we use here as a model of fMRI-measured activity and correlation fluctuations. Additional optimization constraints are explored and prove fruitful, including restricting the model to domains of parameter space near a bifurcation point that yield metastable dynamics. Using these techniques, we first show robust recovery of physiological model parameters in synthetic data and then, as a proof-of-principle, apply the framework to modelling of empirical resting-state fMRI data from the Human Connectome Project database. For resting state activity, the system can be understood as a deep net that receives uncorrelated noise on its input layer, which is transformed into network-wide modelled functional connectivity on its output layer. This is consistent with the prevailing conception in theoretical neuroscience of resting-state functional connectivity patterns as an emergent phenomenon that is driven by (effectively) random activity fluctuations, which are then in turn spatiotemporally filtered by anatomical connectivity and local neural dynamics.
The role of the environment in transmission of antimicrobial resistance between humans and animals: a modelling study
Authors: Lepper Hannah C. , Woolhouse Mark E.J. , van Bunnik Bram A.D. 
Published: May 2022

AbstractBackgroundAntimicrobial resistance can be transmitted between animals and humans both directly or indirectly, through transmission via the environment (such as fomites or sewage). However, there is a lack of understanding of, and quantitative evidence about, the contribution of the environment to AMR epidemiology. In this study we incorporate the transmission of resistance via the environment into a mathematical model to study the potential importance of this form of transmission for human resistance levels and any effects of the impact of interventions to reduce antibiotic consumption in animals.MethodsWe developed a compartmental model of human-animal AMR transmission with an additional environmental compartment. We compared the outcomes of this model under different human-animal-environment transmission scenarios, conducted a sensitivity analysis, and investigated the impact of curtailing antibiotic usage in animals on resistance levels in humans.ResultsOur findings suggest that human resistance levels are most sensitive to both parameters associated with the human compartment (rate of loss of resistance from humans) and parameters associated with the environmental compartment (rate of loss of resistance from the environment and the transmission rate from the environment to humans). The impact of curtailing antibiotic consumption in animals on long term prevalence of AMR in humans was weaker when environmental transmission was assumed to be high.ConclusionsThis study highlights that environment-human sharing of resistance can influence the epidemiology of resistant bacterial infections in humans and reduce the impact of interventions that curtail antibiotic consumption in animals. More data on the types and dynamics of resistance in the environment and frequency of human-environment transmission is crucial to understanding the population dynamics of antibiotic resistance.
Mechanism of Mg2+ Mediated Encapsulation of an Anionic Cognate Ligand in a Bacterial Riboswitch
Authors: Kumar Sunil , Reddy Govardhan 
Published: May 2022

AbstractRiboswitches in bacteria regulate gene expression and are targets for antibiotic development. The fluoride riboswitch is essential for bacteria’s survival as it is critical to maintaining the F− ion concentration below the toxic level. The anionic cognate ligand, F− ion, is encapsulated by three Mg2+ ions in a trigonal pyramidal arrangement bound to the ligand-binding domain (LBD) of the riboswitch. The assembly mechanism of this intriguing LBD structure and its role in transcription initiation are not clear. Computer simulations using both coarse-grained and all-atom RNA models show that F− and Mg2+ binding to the LBD are essential to stabilize the LBD structure and tertiary stacking interactions. We propose that the first two Mg2+ ions sequentially bind to the LBD through water-mediated outer-shell coordination. The first bound Mg2+ should undergo a transition to a direct inner shell interaction through dehydration to strengthen its interaction with LBD before the binding of the second Mg2+ ion. The binding of the third Mg2+ and F− to the LBD occurs in two modes. In the first mode, the third Mg2+ binds first to the LBD, followed by F− binding. In the second mode, Mg2+ and F− form a water-mediated ion pair and bind to the LBD simultaneously, which we propose to be the efficient binding mode. We show that the linchpin hydrogen bonds involved in the antiterminator helix formation and transcription initiation are stable only after F− binding. The intermediates populated during riboswitch folding and cognate-ligand binding are potential targets for discovering new antibiotics.
The evolutionary potential of the influenza A virus hemagglutinin is highly constrained by intersegment epistasis
Authors: Liu Tongyu , Wang Yiquan , Tan Timothy J C , Wu Nicholas C , Brooke Christopher B 
Published: May 2022

AbstractThe ongoing antigenic evolution of the influenza A virus (IAV) hemagglutinin (HA) gene limits efforts to effectively control the spread of the virus in the human population through vaccination. The factors that influence and constrain the evolutionary potential of the HA gene remain poorly understood. Efforts to understand the mechanisms that govern HA antigenic evolution typically examine the HA gene in isolation and ignore the importance of balancing HA receptor-binding activities with the receptor-destroying activities of the viral neuraminidase (NA) for maintaining viral fitness. We hypothesized that the need to maintain functional balance with NA significantly constrains the evolutionary potential of the HA gene. We used deep mutational scanning to show that variation in NA activity significantly reshapes the HA fitness landscape by modulating the overall mutational robustness of the HA protein. Consistent with this, we observe that different NA backgrounds support the emergence of distinct repertoires of HA escape variants under neutralizing antibody pressure. Our results reveal a critical role for intersegment epistatic interactions in shaping the evolutionary potential of the HA gene.
Finite element analysis of lateral response of lightweight foamed concrete-filled cold-formed steel walls
Authors: Alabbadi Ghadeer , Allouzi Rabab 
Published: May 2022

PurposeThe purpose of this study is to improve the lateral capacity of Cold-Formed Steel (CFS) frame walls filled with lightweight foamed concrete (LFC) and supported with straw boards by introducing structural foamed concrete and/or bracing.Design/methodology/approachFinite element models are developed and calibrated based on previous experimental work. Then, these models are extended to conduct a parametric study to quantify the effect of filling CFS walls and structural LFC and the effect of supporting CFS walls with bracing.FindingsResults of the study conclude that the finite element analysis can be used to simulate and analyze the lateral capacity of CFS walls effectively since the maximum deviation between calibrated and experimental results is 10%. The structural LFC usage in CFS walls improves the lateral capacity considerably by (25–75) % depending on the wall properties. Besides, the application of lateral bracing does not always have a positive effect on the lateral performance of these walls.Originality/valueAlthough CFS walls are preferred due to it is light in weight, low in cost, easy to install and recyclable, low seismic performance, buckling vulnerability, poor thermal insulation and sound insulation properties, low lateral stiffness, and low shear strength limit their use. This study proposes the use of structural foamed concrete and a different bracing method than what is available in the literature. This can overcome the drawbacks of the CFS walls alone which can permit the usage of such walls in mid-rise buildings and other applications.
A branch-and-price algorithm for robust parallel batch scheduling problem with uncertain size
Authors: Wang Ting , Shao Xiaoling , Yan Xue 
Published: May 2022

PurposeIn intelligent scheduling, parallel batch processing can reasonably allocate production resources and reduce the production cost per unit product. Hence, the research on a parallel batch scheduling problem (PBSP) with uncertain job size is of great significance to realize the flexibility of product production and mass customization of personalized products.Design/methodology/approachThe authors propose a robust formulation in which the job size is defined by budget constrained support. For obtaining the robust solution of the robust PBSP, the authors propose an exact algorithm based on branch-and-price framework, where the pricing subproblem can be reduced to a robust shortest path problem with resource constraints. The robust subproblem is transformed into a deterministic mixed integer programming by duality. A series of deterministic shortest path problems with resource constraints is derived from the programming for which the authors design an efficient label-setting algorithm with a strong dominance rule.FindingsThe authors test the performance of the proposed algorithm on the extension of benchmark instances in literature and compare the infeasible rate of robust and deterministic solutions in simulated scenarios. The authors' results show the efficiency of the authors' algorithm and importance of incorporating uncertainties in the problem.Originality/valueThis work is the first to study the PBSP with uncertain size. To solve this problem, the authors design an efficient exact algorithm based on Dantzig–Wolfe decomposition. This can not only enrich the intelligent manufacturing theory related to parallel batch scheduling but also provide ideas for relevant enterprises to solve problems.
Optimization-based hexapod robot locomotion generation
Authors: Liu Fusheng , He Zhihang , Qiao Yue , Liu Xinxin , Li Xuelong , Wei Wang , Su Bo , Dang Ruina 
Published: May 2022

Purpose
The purpose of this paper is specifically to provide a more intelligent locomotion planning method for a hexapod robot based on trajectory optimization, which could reduce the complexity of locomotion design, shorten time of design and generate efficient and accurate motion.

Design/methodology/approach
The authors generated locomotion for the hexapod robot based on trajectory optimization method and it just need to specify the high-level motion requirements. Here the authors first transcribed the trajectory optimization problem to a nonlinear programming problem, in which the specified motion requirements and the dynamics with complementarity constraints were defined as the constraints, then a nonlinear solver was used to solve. The leg compliance was taken into consideration and the generated motions were deployed on the hexapod robot prototype to prove the utility of the method and, meanwhile, the influence of different environments was considered.

Findings
The generated motions were deployed on the hexapod robot and the movements were demonstrated very much in line with the planning. The new planning method does not require lots of parameter-tuning work and therefore significantly reduces the cycle for designing a new locomotion.

Originality/value
A locomotion generation method based on trajectory optimization was constructed for a 12-degree of freedom hexapod robot. The variable stiffness compliance of legs was considered to improve the accuracy of locomotion generation. And also, different from some simulation work before, the authors have designed the locomotion in three cases and constructed field tests to demonstrate its utility.