bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hyperglycemic conditions induce rapid cell dysfunction-promoting transcriptional alterations in human aortic endothelial cells
Authors: Bayaraa Odmaa , Inman Claire K. , Thomas Sneha A. , Al Jallaf Fatima , Alshaikh Manar , Idaghdour Youssef , Ashall Louise 
Published: December 2022

AbstractHyperglycemia is a major risk factor in the development of diabetic complications and promotes vascular complications through dysregulation of endothelial cell function. Various mechanisms have been proposed for endothelial cell dysregulation but the early transcriptomic alterations of endothelial cells under hyperglycemic conditions are not well documented. Here we use deep time-series RNA-seq profiling of human aortic endothelial cells (HAECs) following exposure to normal (NG) and high glucose (HG) conditions over a time course from baseline to 24 h to identify the early and transient transcriptomic changes, alteration of molecular networks, and their temporal dynamics. The analysis revealed that the most significant pathway activation/inhibition events take place in the 1- to 4-h transition and identified distinct clusters of genes that underlie a cascade of coordinated transcriptional events unique to HG conditions. Temporal co-expression and causal network analysis implicate the activation of type 2 diabetes (T2D) and growth factor signalling pathways including STAT3 and NF-κB. These results document HAEC transcriptional changes induced by hyperglycemic conditions and provide basic insight into the rapid molecular alterations that promote endothelial cell dysfunction.
Habitat selection by free-roaming domestic dogs in rabies endemic countries in rural and urban settings
Authors: Cunha Silva Laura , Friker Brian , Warembourg Charlotte , Kanankege Kaushi , Wera Ewaldus , Berger-González Monica , Alvarez Danilo , Dürr Salome 
Published: December 2022

AbstractDomestic dogs can affect human health through bites and pathogen transmission, particularly in resource-poor countries where dogs, including owned ones, predominantly roam freely. Habitat and resource selection analysis methods are commonplace in wildlife studies but have not been used to investigate the environmental resource use of free-roaming domestic dogs (FRDD). The present study implements GPS devices to investigate habitat selection by FRDD from an urban site and a rural site in Indonesia, and one urban and two rural sites in Guatemala (N = 321 dogs). Spatial mixed effects logistic regression models, accounting for heterogeneous distribution of the resources, showed that patterns of habitat selection by FRDD were similar across study sites. The most preferred resources were anthropogenic, being buildings and roads, which implies selection for human proximity. Vegetation and open fields were less preferred and steep terrain was avoided, indicating that FRDD were synanthropic and that their space patterns likely optimised energy use. Results presented here provide novel data on FRDD habitat selection patterns, while improving our understanding of dog roaming behaviour. These findings provide insights into possible high-risk locations for pathogen transmission for diseases such as rabies, and can assist management authorities in the planning and deployment of efficient disease control campaigns, including oral vaccination.
Discrimination of normal and cancerous human skin tissues based on laser-induced spectral shift fluorescence microscopy
Authors: Niazi A. , Parvin P. , Jafargholi A. , Basam M. A. , Khodabakhshi Z. , Bavali A. , Kamyab Hesari K. , Sohrabizadeh Z. , Hassanzadeh T. , Shirafkan Dizaj L. , Amiri R. , Heidari O. , Aghaei M. , Atyabi F. , Ehtesham A. , Moafi A. 
Published: December 2022

AbstractA homemade spectral shift fluorescence microscope (SSFM) is coupled with a spectrometer to record the spectral images of specimens based on the emission wavelength. Here a reliable diagnosis of neoplasia is achieved according to the spectral fluorescence properties of ex-vivo skin tissues after rhodamine6G (Rd6G) staining. It is shown that certain spectral shifts occur for nonmelanoma/melanoma lesions against normal/benign nevus, leading to spectral micrographs. In fact, there is a strong correlation between the emission wavelength and the sort of skin lesions, mainly due to the Rd6G interaction with the mitochondria of cancerous cells. The normal tissues generally enjoy a significant red shift regarding the laser line (37 nm). Conversely, plenty of fluorophores are conjugated to unhealthy cells giving rise to a relative blue shift i.e., typically SCC (6 nm), BCC (14 nm), and melanoma (19 nm) against healthy tissues. In other words, the redshift takes place with respect to the excitation wavelength i.e., melanoma (18 nm), BCC (23 nm), and SCC (31 nm) with respect to the laser line. Consequently, three data sets are available in the form of micrographs, addressing pixel-by-pixel signal intensity, emission wavelength, and fluorophore concentration of specimens for prompt diagnosis.
Design of MMP-1 inhibitors via SAR transfer and experimental validation
Authors: Umedera Kohei , Yoshimori Atsushi , Bajorath Jürgen , Nakamura Hiroyuki 
Published: December 2022

AbstractNew matrix metalloproteinase 1 (MMP-1) inhibitors were predicted using the structure–activity relationship (SAR) transfer method based on a series of analogues of kinesin-like protein 11 (KIF11) inhibitors. Compounds 5–7 predicted to be highly potent against MMP-1 were synthesized and tested for MMP-1 inhibitory activity. Among these, compound 6 having a Cl substituent at the R1 site was found to possess ca. 3.5 times higher inhibitory activity against MMP-1 than the previously reported compound 4. The observed potency was consistent with the presence of an SAR transfer event between analogous MMP-1 and KIF11 inhibitors. Pharmacophore fitting revealed that the higher inhibitory activity of compound 6 compared to compound 4 against MMP-1 might be due to a halogen bond interaction between the Cl substituent of compound 6 and residue ARG214 of MMP-1.
Bootstrapping random forest and CHAID for prediction of white spot disease among shrimp farmers
Authors: Edeh Michael Onyema , Dalal Surjeet , Obagbuwa Ibidun Christiana , Prasad B. V. V. Siva , Ninoria Shalini Zanzote , Wajid Mohd Anas , Adesina Ademola Olusola 
Published: December 2022

AbstractTechnology is playing an important role is healthcare particularly as it relates to disease prevention and detection. This is evident in the COVID-19 era as different technologies were deployed to test, detect and track patients and ensure COVID-19 protocol compliance. The White Spot Disease (WSD) is a very contagious disease caused by virus. It is widespread among shrimp farmers due to its mode of transmission and source. Considering the growing concern about the severity of the disease, this study provides a predictive model for diagnosis and detection of WSD among shrimp farmers using visualization and machine learning algorithms. The study made use of dataset from Mendeley repository. Machine learning algorithms; Random Forest classification and CHAID were applied for the study, while Python was used for implementation of algorithms and for visualization of results. The results achieved showed high prediction accuracy (98.28%) which is an indication of the suitability of the model for accurate prediction of the disease. The study would add to growing knowledge about use of technology to manage White Spot Disease among shrimp farmers and ensure real-time prediction during and post COVID-19.
The formulation of irrigation and nitrogen application strategies under multi-dimensional soil fertility targets based on preference neural network
Authors: Lou Shuai , Hu Rui-Qi , Liu Yue , Zhang Wan-feng , Yang Shu-Qing 
Published: December 2022

AbstractWith the aim of improving soil fertility, it is of great significance to put forward optimal irrigation and nitrogen fertilizer application strategies for improving land productivity and alleviating non-point source pollution effects. To overcome this task, a 6-hidden layer neural network with a preference mechanism, namely Preference Neural network (PNN), has been developed in this study based on the field data from 2018 to 2020. PNN takes soil total nitrogen, organic matter, total salt, pH, irrigation time and target soil depth as input, and irrigation amount and nitrogen application rate (N rate) as output, and the prior preference matrix was used to adjust the learning of weight matrix of each layer. The outcomes indicated that the predictive accuracy of PNN for irrigation amount were (R2 = 0.913, MAE = 0.018, RMSE = 0.022), and for N rate were (R2 = 0.943, MAE = 0.009, RMSE = 0.011). The R2 predicted by PNN at the irrigation amount and N rate were 40.03% to more than 99% and 40.33% to more than 99% higher than those obtained using support vector regression (SVR), linear regression (LR), logistic regression (LOR) and traditional back propagation neural network (BPNN), respectively. In addition, compared with the neural network (Reverse Multilayer Perceptron, RMLP) with the same structure but no preference structure, the R2 of the predicted irrigation amount and N rate by PNN increased by 25.81% and 27.99%, respectively. The results showed that, through the irrigation of 93 to 102, 92 to 98 and 92 to 98 mm, along with nitrogen applications of 65 to 71, 64 to 73 and 72 to 81 kg/hm2 at 17, 59 and 87 days after sowing, respectively, the organic matter, total nitrogen, total salt content and pH of the soil would reach high fertility levels simultaneously.
RBDtector: an open-source software to detect REM sleep without atonia according to visual scoring criteria
Authors: Röthenbacher Annika , Cesari Matteo , Doppler Christopher E. J. , Okkels Niels , Willemsen Nele , Sembowski Nora , Seger Aline , Lindner Marie , Brune Corinna , Stefani Ambra , Högl Birgit , Bialonski Stephan , Borghammer Per , Fink Gereon R. , Schober Martin , Sommerauer Michael 
Published: December 2022

AbstractREM sleep without atonia (RSWA) is a key feature for the diagnosis of rapid eye movement (REM) sleep behaviour disorder (RBD). We introduce RBDtector, a novel open-source software to score RSWA according to established SINBAR visual scoring criteria. We assessed muscle activity of the mentalis, flexor digitorum superficialis (FDS), and anterior tibialis (AT) muscles. RSWA was scored manually as tonic, phasic, and any activity by human scorers as well as using RBDtector in 20 subjects. Subsequently, 174 subjects (72 without RBD and 102 with RBD) were analysed with RBDtector to show the algorithm’s applicability. We additionally compared RBDtector estimates to a previously published dataset. RBDtector showed robust conformity with human scorings. The highest congruency was achieved for phasic and any activity of the FDS. Combining mentalis any and FDS any, RBDtector identified RBD subjects with 100% specificity and 96% sensitivity applying a cut-off of 20.6%. Comparable performance was obtained without manual artefact removal. RBD subjects also showed muscle bouts of higher amplitude and longer duration. RBDtector provides estimates of tonic, phasic, and any activity comparable to human scorings. RBDtector, which is freely available, can help identify RBD subjects and provides reliable RSWA metrics.
Recurrent connections facilitate symmetry perception in deep networks
Authors: Sundaram Shobhita , Sinha Darius , Groth Matthew , Sasaki Tomotake , Boix Xavier 
Published: December 2022

AbstractSymmetry is omnipresent in nature and perceived by the visual system of many species, as it facilitates detecting ecologically important classes of objects in our environment. Yet, the neural underpinnings of symmetry perception remain elusive, as they require abstraction of long-range spatial dependencies between image regions and are acquired with limited experience. In this paper, we evaluate Deep Neural Network (DNN) architectures on the task of learning symmetry perception from examples. We demonstrate that feed-forward DNNs that excel at modelling human performance on object recognition tasks, are unable to acquire a general notion of symmetry. This is the case even when the feed-forward DNNs are architected to capture long-range spatial dependencies, such as through ‘dilated’ convolutions and the ‘transformers’ design. By contrast, we find that recurrent architectures are capable of learning a general notion of symmetry by breaking down the symmetry’s long-range spatial dependencies into a progression of local-range operations. These results suggest that recurrent connections likely play an important role in symmetry perception in artificial systems, and possibly, biological ones too.
SSTR2 as an anatomical imaging marker and a safety switch to monitor and manage CAR T cell toxicity
Authors: Alcaina Yago , Yang Yanping , Vedvyas Yogindra , McCloskey Jaclyn E. , Jin Moonsoo M. 
Published: December 2022

AbstractThe ability to image adoptively transferred T cells in the body and to eliminate them to avoid toxicity will be vital for chimeric antigen receptor (CAR) T cell therapy, particularly against solid tumors with higher risk of off-tumor toxicity. Previously, we have demonstrated the utility of somatostatin receptor 2 (SSTR2) for CAR T cell imaging, illustrating the expansion and contraction of CAR T cells in tumor as well as off-tumor expansion. Using intercellular adhesion molecule 1 (ICAM-1)-specific CAR T cells that secrete interleukin (IL)-12 as a model, herein we examined the potential of SSTR2 as a safety switch when combined with the SSTR2-specific maytansine-octreotate conjugate PEN-221. Constitutive secretion of IL-12 led to continuous expansion of CAR T cells after rapid elimination of tumors, causing systemic toxicity in mice with intact MHC expression. Treatment with PEN-221 rapidly reduced the abundance of CAR T cells, decreasing the severity of xenogeneic graft-versus-host disease (GvHD), and prolonged survival. Our study supports the development of SSTR2 as a single genetic marker for CAR T cells that is readily applicable to humans both for anatomical detection of T cell distribution and an image-guided safety switch for rapid elimination of CAR T cells.
Interdependent effects of fluid injection parameters on triggered aseismic slip and seismicity
Authors: Mandal Riddhi , Lui Semechah K. Y. 
Published: December 2022

AbstractIn the context of fluid-induced seismicity, various injection parameters have been shown to affect fault behaviour differently, although existing studies about their effects sometimes show contradictory results. Aseismic slip is also known to affect seismicity, but its exact contribution remains elusive. To address these, we perform numerical modelling to understand the effects of injection volume and rate on long-term seismic and aseismic fault slip behavior. Our results suggest that both parameters can affect various aspects of fault behaviour to different extents, and, in some cases, their roles are interdependent, thus they should be examined simultaneously in order to fully characterize their effects on triggered fault responses. Within the model space, we observe the fault predominantly releasing aseismic energy, which plays a significant role in altering the timing of triggered earthquakes that follow and exhibits lasting impacts in subsequent seismic cycles. In terms of seismic responses, increasing injection rate enhances the size of the triggered cluster, while increasing injection volume increases seismicity rate of the sequence. Detailed characterization of the patterns of earthquake occurrence and moment release with respect to different injection parameters can offer insights into establishing safe bounds of injection operation and potentially mitigate seismic hazard.
Anti-osteopontin therapy leads to improved edema and infarct size in a murine model of ischemic stroke
Authors: Spitzer Daniel , Puetz Tim , Armbrust Moritz , Dunst Maika , Macas Jadranka , Croll Florian , Plate Karl-Heinz , Reiss Yvonne , Liebner Stefan , Harter Patrick N. , Guérit Sylvaine , Devraj Kavi 
Published: December 2022

AbstractIschemic stroke is a serious neurological disorder that is associated with dysregulation of the neurovascular unit (NVU) and impairment of the blood–brain barrier (BBB). Paradoxically, reperfusion therapies can aggravate NVU and BBB dysfunction, leading to deleterious consequences in addition to the obvious benefits. Using the recently established EPAM-ia method, we identified osteopontin as a target dysregulated in multiple NVU cell types and demonstrated that osteopontin targeting in the early acute phase post-transient middle cerebral artery occlusion (tMCAO) evolves protective effects. Here, we assessed the time course of osteopontin and CD44 receptor expression in NVU cells and examined cerebroprotective effects of osteopontin targeting in early and late acute phases of ischemic stroke. Expression analysis of osteopontin and CD44 receptor post-tMCAO indicated increased levels of both, from early to late acute phases, which was supported by their co-localization in NVU cells. Combined osteopontin targeting in early and late acute phases with anti-osteopontin antibody resulted in further improvement in BBB recovery and edema reduction compared to targeting only in the early acute phase comprising the reperfusion window. Combined targeting led to reduced infarct volumes, which was not observed for the single early acute phase targeting. The effects of the therapeutic antibody were confirmed both in vitro and in vivo in reducing osteopontin and CD44 expression. Osteopontin targeting at the NVU in early and late acute phases of ischemic stroke improves edema and infarct size in mice, suggesting anti-osteopontin therapy as promising adjunctive treatment to reperfusion therapy.
Quasioptics for increasing the beam efficiency of wireless power transfer systems
Authors: Pereira Ricardo A. M. , Carvalho Nuno Borges 
Published: December 2022

AbstractThe highest beam efficiency in a wireless power transfer (WPT) system that uses focusing components was 51%, using a $$\approx {3}\,{\textrm{m}}$$

≈
3

m

diameter reflector for a transfer distance of $${7.62}\,{\textrm{m}}$$

7.62

m

. We have beaten that record, and present here a system that surpasses it by 25%. Using the quasioptical framework for reducing spillover losses in WPT, we present a double-reflector system that achieved a higher beam efficiency than the state-of-the-art. The transmitting and receiving antennas were 3D-printed conical smooth-walled horn antennas, specially designed for this purpose. The theoretical analysis enabled the design of a $${5}\,{\textrm{m}}$$

5

m

system, whose energy focus location has been experimentally verified. Then, the complete system was experimented upon, enabling a high beam transfer efficiency of 63.75%. Additionally, the advantage of using quasioptics in radiative wireless power transfer applications is discussed, as well as the sensitivity of its systems. Finally, a comparison with the state-of-the-art is done by the proposal of new figures-of-merit, relating the systems’ physical dimensions and beam efficiency. This research is a paradigm shift by presenting a promising path for future WPT research through quasioptics, whose high efficiencies may enable commercial applications of this technology for solving power supply issues in our society.
Frequency modulation of cortical rhythmicity governs behavioral variability, excitability and synchrony of neurons in the visual cortex
Authors: Khamechian Mohammad Bagher , Daliri Mohammad Reza 
Published: December 2022

AbstractResearch in cognitive neuroscience has renewed the idea that brain oscillations are a core organization implicated in fundamental brain functions. Growing evidence reveals that the characteristic features of these oscillations, including power, phase and frequency, are highly non-stationary, fluctuating alongside alternations in sensation, cognition and behavior. However, there is little consensus on the functional implications of the instantaneous frequency variation in cortical excitability and concomitant behavior. Here, we capitalized on intracortical electrophysiology in the macaque monkey’s visual area MT performing a visuospatial discrimination task with visual cues. We observed that the instantaneous frequency of the theta–alpha oscillations (4–13 Hz) is modulated among specific neurons whose RFs overlap with the cued stimulus location. Interestingly, we found that such frequency modulation is causally correlated with MT excitability at both scales of individual and ensemble of neurons. Moreover, studying the functional relevance of frequency variations indicated that the average theta–alpha frequencies foreshadow the monkey’s reaction time. Our results also revealed that the neural synchronization strength alters with the average frequency shift in theta–alpha oscillations, suggesting frequency modulation is critical for mutually adjusting MTs’ rhythms. Overall, our findings propose that theta–alpha frequency variations modulate MT’s excitability, regulate mutual neurons’ rhythmicity and indicate variability in behavior.
Nanoreactors in action for a durable microactuator using spontaneous combustion of gases in nanobubbles
Authors: Uvarov Ilia V. , Svetovoy Vitaly B. 
Published: December 2022

AbstractA number of recent studies report enhancement of chemical reactions on water microdroplets or inside nanobubbles in water. This finding promises exciting applications, although the mechanism of the reaction acceleration is still not clear. Specifically, the spontaneous combustion of hydrogen and oxygen in nanobubbles opens the way to fabricate truly microscopic engines. An example is an electrochemical membrane actuator with all three dimensions in the micrometer range. The actuator is driven by short voltage pulses of alternating polarity, which generate only nanobubbles. The device operation is, however, restricted by a fast degradation of the electrodes related to a high current density. Here it is demonstrated that the actuator with ruthenium electrodes does not show signs of degradation in the long-term operation. It is the only material able to withstand the extreme conditions of the alternating polarity electrolysis. This property is due to combination of a high mechanical hardness and metallic conductivity of ruthenium oxide. The actuator combines two features considered impossible: on-water catalysis and combustion in a microscopic volume. It provides an exceptional opportunity to drive autonomous microdevices especially for medical or biological applications.