bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cerebrovascular super-resolution 4D Flow MRI – using deep learning to non-invasively quantify velocity, flow, and relative pressure
Authors: Ferdian E. , Marlevi D. , Schollenberger J. , Aristova M. , Edelman E.R. , Schnell S. , Figueroa C.A. , Nordsletten D.A. , Young A.A. 
Published: August 2021

ABSTRACTThe development of cerebrovascular disease is tightly coupled to changes in cerebrovascular hemodynamics, with altered flow and relative pressure indicative of the onset, development, and acute manifestation of pathology. Image-based monitoring of cerebrovascular hemodynamics is, however, complicated by the narrow and tortuous vasculature, where accurate output directly depends on sufficient spatial resolution. To address this, we present a method combining dedicated deep learning and state-of-the-art 4D Flow MRI to generate super-resolution full-field images with coupled quantification of relative pressure using a physics-driven image processing approach. The method is trained and validated in a patient-specificin-silicocohort, showing good accuracy in estimating velocity (relative error: 12.0 ± 0.1%, mean absolute error (MAE): 0.07 ± 0.06 m/s at peak velocity), flow (relative error: 6.6 ± 4.7%, root mean square error (RMSE): 0.5 ± 0.1 mL/s at peak flow), and with maintained recovery of relative pressure through the circle of Willis (relative error: 11.0 ± 7.3%, RMSE: 0.3 ± 0.2 mmHg). Furthermore, the method is applied to anin-vivovolunteer cohort, effectively generating data at <0.5mm resolution and showing potential in reducing low-resolution bias in relative pressure estimation. Our approach presents a promising method to non-invasively quantify cerebrovascular hemodynamics, applicable to dedicated clinical cohorts in the future.
Sea lice(Lepeophtherius salmonis)detection and quantification around aquaculture installations using environmental DNA
Authors: Krolicka Adriana , Nilsen Mari Mæland , Provan Fiona , Hansen Brian Klitgaard , Jacobsen Magnus Wulf , Baussant Thierry 
Published: August 2021

AbstractThe naturally occurring ectoparasite salmon lice (Lepeophtherirus salmonis) poses a great challenge for the salmon farming industry, as well as for wild salmonids in the Northern hemisphere. To better control the infestation pressure and protect the production, there is a need to provide fish farmers with sensitive and efficient tools for rapid early detection and monitoring of the parasitic load. This can be achieved by targetingL. salmonisDNA in environmental samples. Here, we developed and tested a newL. salmonisspecific DNA-based assay (qPCR assay) for detection and quantification from seawater samples using an analytical pipeline compatible with the Environmental Sample Processor (ESP) for autonomous water sample analysis of gene targets. Specificity of the L. salmonis qPCR assay was demonstrated through in-silico DNA analyses covering sequences of differentL. salmonisisolates. Seawater was spiked with known numbers of nauplii and copepodite free-swimming (planktonic) stages ofL. salmonisto investigate the relationship with the number of marker gene copies (MGC). Finally, field samples collected at different times of the year in the vicinity of a salmon production farm in Western Norway were analyzed forL. salmonisdetection and quantification. The assay specificity was high and a high correlation between MGC and planktonic stages ofL. salmoniswas established in the laboratory conditions. In the field,L. salmonisDNA was consequently detected, but with MGC number below that expected for one copepodite or nauplii. We concluded that onlyL. salmonistissue or eDNA residues were detected. This novel study opens for a fully automatizedL. salmonisDNA quantification using ESP robotic to monitor the parasitic load, but the challenge remains the adequate sampling of a volume of seawater sufficiently large to be representative of outbreaks and load around fish farms.
Rapid 3D-STORM imaging of diverse molecular targets in tissue
Authors: Albrecht Nicholas E. , Jiang Danye , Hobson Robert , Speer Colenso M. , Samuel Melanie A. 
Published: August 2021

AbstractThe precise organization of fine scale molecular architecture is critical for the nervous system and other biological functions and would benefit from nanoscopic imaging methods with improved accessibility, throughput, and native tissue compatibility. Here, we report RAIN-STORM, a rapid and scalable imaging approach that enables three-dimensional nanoscale target visualization for multiple subcellular and intracellular targets within tissue at depth. RAIN-STORM utilizes conventional tissue samples, readily available reagents in optimized formulas, requires no specialized sample handling, and is suitable for commercial instrumentation. To illustrate RAIN-STORM’s ability for quantitative high-resolution nanoscopic tissue imaging, we utilized the well-organized but structurally complex retina. We show that RAIN-STORM is rapid and versatile, enabling 3D nanoscopic imaging of over 20 distinct targets to reveal known and novel nanoscale features of synapses, neurons, glia, and vascular. Further, imaging parameters are compatible with a wide range of tissue sources and molecular targets across a spectrum of biological structures. Finally, we show that this method can be applied to clinically derived samples and reveal the nanoscale distribution of molecular targets within human samples. RAIN-STORM thus enables rapid 3D imaging for a range of molecules, paving the way for high throughput studies of nanoscopic molecular features in intact tissue from diverse sources.
Control of invasive Phragmites australis (European common reed) alters macroinvertebrate communities
Authors: Robichaud C.D. , Basso J.V. , Rooney R.C. 
Published: August 2021

AbstractWetland restoration often involves invasive plant species suppression to encourage the recovery of native-dominated vegetation communities. However, assessment of recovery is usually focused only on vegetation and the response of other critical wetland biota, such as macroinvertebrates, is seldom assessed. We characterized the aquatic, semi-aquatic, and terrestrial macroinvertebrate communities in remnant, uninvaded marsh to identify restoration targets and compared this to the communities in Phragmites australis-invaded marsh, and in formerly invaded marsh that was treated with the herbicide glyphosate in 2016 to simultaneously evaluate the effects of invasion and of invasive species suppression. We sampled invertebrates in 2017 and 2018 to track two years following herbicide treatment. The invertebrate community composition captured by the emergence traps was similar between P. australis and remnant marsh, suggesting invasion has little effect on macroinvertebrate community structure. There was also high concordance between the aquatic and emerging invertebrate communities in the invaded and uninvaded habitats. In contrast, herbicide-treated sites had a unique community composition, characterized by very high densities of Chironomidae (Diptera) and low taxa richness and evenness. Herbicide-treated sites also exhibited low concordance between the aquatic and emerging invertebrate communities, potentially attributable to the sparse emerging vegetation cover providing limited substrates for emergence. Herbicide-based invasive species control results in considerable changes to the macroinvertebrate community in freshwater marshes for at least two years after treatment, which may have consequences for aquatic food webs and species that rely on macroinvertebrates as prey.
Instructions and experiential learning have similar impacts on pain and pain-related brain responses but produce dissociations in value-based reversal learning
Authors: Atlas Lauren Y. , Dildine Troy C. , Palacios-Barrios Esther E. , Yu Qingbao , Reynolds Richard C. , Banker Lauren A. , Grant Shara S. , Pine Daniel S. 
Published: August 2021

AbstractRecent data suggest that interactions between systems involved in higher order knowledge and associative learning drive responses during appetitive and aversive learning. However, it is unknown how these systems impact subjective responses, such as pain. We tested how instructions and reversal learning influence pain and pain-evoked brain activation. Healthy volunteers (n = 40) were either instructed about contingencies between cues and aversive outcomes or learned through experience in a paradigm where contingencies reversed three times. We measured predictive cue effects on pain and heat-evoked brain responses using functional magnetic resonance imaging. Predictive cues dynamically modulated pain perception as contingencies changed, regardless of whether participants received contingency instructions. Heat-evoked responses in the insula, anterior cingulate, and putamen updated as contingencies changed, whereas the periaqueductal gray and thalamus responded to initial contingencies throughout the task. Quantitative modeling revealed that expected value was shaped purely by instructions in the Instructed Group, whereas expected value updated dynamically in the Uninstructed Group as a function of error-based learning. These differences were accompanied by dissociations in the neural correlates of value-based learning in the rostral anterior cingulate, medial prefrontal cortex, and orbitofrontal cortex. These results show how predictions impact subjective pain. Moreover, imaging data delineate three types of networks involved in pain generation and value-based learning: those that respond to initial contingencies, those that update dynamically during feedback-driven learning as contingencies change, and those that are sensitive to instruction. Together, these findings provide multiple points of entry for therapies designs to impact pain.
Spatial Analysis of Neural Cell Proteomic Profiles following Ischemic Stroke in Mice using High-Plex Digital Spatial Profiling
Authors: Noll Jessica M. , Augello Catherine J. , Kürüm Esra , Pan Liuliu , Pavenko Anna , Nam Andy , Ford Byron D. 
Published: August 2021

AbstractStroke is ranked as the fifth leading cause of death and the leading cause of adult disability. The progression of neuronal damage after stroke is recognized to be a complex integration of glia, neurons, and the surrounding extracellular matrix, therefore potential treatments must target the detrimental effects created by these interactions. In this study, we examined the spatial cellular and neuroinflammatory mechanisms occurring early after ischemic stroke utilizing Nanostring Digital Spatial Profiling (DSP) technology. Male C57bl/6 mice were subjected to photothrombotic middle cerebral artery occlusion (MCAO) and sacrificed at three-days post-ischemia. Spatial distinction of the ipsilateral hemisphere was studied according to the regions of interest: the ischemic core, peri-infarct tissues, and peri-infarct normal tissue (PiNT) in comparison to the contralateral hemisphere. We demonstrated that the ipsilateral hemisphere initiates distinct spatial regulatory proteomic profiles with DSP technology that can be identified consistently with the immunohistochemical markers, FJB, GFAP, and Iba-1. The core border profile demonstrated an induction of neuronal death, apoptosis, autophagy, immunoreactivity, and early degenerative proteins. Most notably, the core border resulted in a decrease of the neuronal proteins Map2 and NeuN, an increase in the autophagy proteins BAG3 and CTSD, an increase in the microglial and peripheral immune invasion proteins Iba1, CD45, CD11b, and CD39, and an increase in the neurodegenerative proteins BACE1, APP, αβ 1-42, ApoE, and hyperphosphorylated tau protein S-199. The peri-infarct region demonstrated increased astrocytic immunoreactivity, apoptotic, and neurodegenerative proteomic profile, with an increase in BAG3, GFAP, and hyperphosphorylated tau protein S-199. The PiNT region displayed minimal changes compared to the contralateral cortex with only an increase in GFAP. Overall, our data highlight the importance of identifying ischemic mechanisms in a spatial manner to understand the complex, dynamic interactions throughout ischemic progression and repair as well to introduce potential targets for successful therapeutic interventions.
A large-sample crisis? Exaggerated false positives by popular differential expression methods
Authors: Li Yumei , Ge Xinzhou , Peng Fanglue , Li Wei , Li Jingyi Jessica 
Published: August 2021

AbstractWe report a surprising phenomenon about identifying differentially expressed genes (DEGs) from population-level RNA-seq data: two popular bioinformatics methods, DESeq2 and edgeR, have unexpectedly high false discovery rates (FDRs). Via permutation analysis on an immunotherapy RNA-seq dataset, we observed that DESeq2 and edgeR identified even more DEGs after samples’ condition labels were randomly permuted. Motivated by this, we evaluated six DEG identification methods (DESeq2, edgeR, limma-voom, NOISeq, dearseq, and the Wilcoxon rank-sum test) on population-level RNA-seq datasets. We found that the FDR control was often failed by the three popular parametric methods—DESeq2, edgeR, and limma-voom— and the new non-parametric method dearseq. In particular, the actual FDRs of DESeq2 and edgeR sometimes exceeded 20% when the target FDR threshold was only 5%. Although NOISeq, a non-parametric method used by GTEx, controlled the FDR better than the other four methods did, its power was much lower than that of the Wilcoxon rank-sum test, a classic nonparametric test that consistently controlled the FDR and achieved good power in our evaluation. Based on these results, for population-level RNA-seq studies, we recommend the Wilcoxon rank-sum test.
Erytra Blood Group Analyser and Kode Technology testing of SARS-CoV-2 antibodies among convalescent patients and vaccinated individuals
Authors: Weinstock Christof , Flegel Willy A , Srivastava Kshitij , Kaiser Sabine , Schrezenmeier Hubert , Tsamadou Chrysanthi , Ludwig Carolin , Jahrsdörfer Bernd , Bovin Nicolai V , Henry Stephen M 
Published: August 2021

SummarySurveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic requires tests to monitor antibody formation and prevalence. We detected SARS-CoV-2 antibodies using red cells coated by Kode technology with short peptides derived from the SARS-CoV-2 spike protein. Such modified red cells, called C19-kodecytes, can be used as reagent cells in any manual or automated column agglutination assay. We investigated the presence of SARS-CoV-2 antibodies in 130 samples from COVID-19 convalescent plasma donors using standard manual technique, two FDA authorized ELISA assays and a virus neutralisation assay. The sensitivity of the C19-kodecyte assay was 88%, comparable to the anti-SP and anti-NCP ELISAs (86% and 83%) and the virus neutralisation assay (88%). The specificity of the C19-kodecyte assay was 90% (anti-SP 100% and anti-NCP 97%). Likewise, 231 samples from 73 vaccinated individuals were tested with an automated analyser and we monitored the appearance and persistence of SARS-CoV-2 antibodies. The C19-kodecyte assay is a robust tool for SARS-CoV-2 antibody detection. Automated blood group analyser use enables large-scale SARS-CoV-2 antibody testing for vaccination monitoring in population surveys.
Differentials and determinants of immunization coverage among children aged 12-36 months in India: Analysis of nationally-representative, population-based survey data
Authors: Naaz Eram , Akhtar Saddaf Naaz , Malik Manzoor Ahmad , Pradhan Jalandhar 
Published: August 2021

AbstractIntroductionImmunization coverage among children is still a major public health concern in India and other low-middle income countries. Low coverage likely risks the health of children and therefore impacts their overall growth. We therefore examined the immunization coverage rates among children aged 12-36 months in India and its states. We also explored the associated factors affecting immunization coverage among children aged 12-36 in India.MethodsWe used data from 75th round of the National Sample Survey Organizations (NSSO), collected from July 2017 to June 2018. The analytical sample of children aged 12-36 months information cases was 15887. Immunization coverage rates of India and its states were calculated. We evaluated the immunization coverage rate by background characteristics in India and its states. We performed multinomial logistic regression analysis to estimate the factors associated with the immunization coverage in India.ResultsAbout 61.95% were fully immunized, 35.62% were partially immunized and the rest 2.43% had not received any vaccine. The children aged 21-28 months (0.50; p<0.01) & 29-36 months (0.35; p<0.01), belonging to North-Eastern regions (0.60; p<0.01) were found to be significantly less likely to receive fully immunization. Likewise, urban children are (1.26; p<0.1) found to be more likely to receive fully immunization. The lowest fully immunization has been seen in Daman and Diu (1.73%) followed by Nagaland (6.93%), NCT Delhi (34.71%), and Tripura (46.33%).ConclusionsChild immunization is a key public health concern and vital challenge to be addressed. Socio-economic characteristics play a key role in immunization coverage. Therefore necessary policy measures must be taken to address the challenges of poor immunization coverage and its impact on health and wellbeing of children
Characterisation of type 2 diabetes subgroups and their association with ethnicity and clinical outcomes: a UK real-world data study using the East London Database
Authors: Mathur Rohini , Hull Sally A , Hodgson Sam , Finer Sarah 
Published: August 2021

AbstractBackgroundSubgroups of type 2 diabetes (T2DM) have been well characterised in experimental studies. However, it is unclear whether T2DM subgroups can be identified in UK based real-world populations and if they impact clinical outcomes.AimTo derive T2DM subgroups using primary care data from a multi-ethnic population, evaluate associations with glycaemic control, treatment initiation and vascular outcomes, and understand how these vary by ethnicity.Design and settingAn observational cohort study in the East London Primary Care Database from 2008-2018.MethodLatent class analysis using age, sex, glycated haemoglobin, and body mass index at diagnosis was used to derive T2DM subgroups in White, South Asian, and Black groups. Time to treatment initiation and vascular outcomes was estimated using multivariable Cox-proportional hazards regression.Results31,931 adults with T2DM were included: 47% south Asian, 25% White, 20% Black. We replicated two previously described subgroups, ‘Mild Age-Related Diabetes’ (MARD), ‘Mild Obesity-related Diabetes (MOD), and characterised a third ‘Severe Hyperglycaemic Diabetes’ (SHD). Compared to MARD, SHD had the poorest long term glycaemic control, fastest initiation of antidiabetic treatment (HR 2.02, 1.76-2.32), and highest risk of microvascular complications (HR 1.38, 1.28-1.49). MOD had the highest risk of macrovascular complications (HR 1.50, 1.23-1.83). Subgroup differences in treatment initiation were most pronounced for the White group, and vascular complications for the Black group.ConclusionsClinically useful T2DM subgroups, identified at diagnosis, can be generated in routine real-world multi-ethnic populations, and may offer a pragmatic means to develop stratified primary care pathways and improve healthcare resource allocation.How this fits inPrevious studies of predominantly White European populations have identified four T2DM subgroups. In the UK the clinical measures necessary to replicate these subgroups are only available in secondary care data, limiting their usefulness for diabetes management in primary care settings. In this study, we demonstrate how clinically meaningful T2DM subgroups can be pragmatically generated using real-world primary care data. Furthermore, we highlight important differences between T2DM subgroups with respect to vascular outcomes, treatment initiation, and HbA1c control. Diabetes subgroups are a useful heuristic for helping clinician decision-making which, in turn, this can lead to a more personalised design of diabetes care focussed on more intensive management of subgroups most at risk of complications, such as those with severe hyperglycaemia at time of diagnosis.
Nurse-physician Communication around Identifying Palliative Care Needs in Nursing Home Residents
Authors: van der Steen Jenny T. , Jongen Esmée A. , Dekker Natashe Lemos , Bagchus Lotje , Pasman H. Roeline W. , Onwuteaka-Philipsen Bregje D. , Achterberg Wilco P. 
Published: August 2021

AbstractObjectiveTo assess experiences of medical practitioners who are on the staff of nursing homes with communication with nursing staff about identifying emerging and changing (palliative) care needs of residents of nursing homes in the Netherlands.DesignQualitative interview study.Setting and ParticipantsFifteen physicians and two nurse practitioners employed by eight care organizations in the western urbanized region of the Netherlands.MethodsWe conducted individual semi-structured interviews in 2018 informed by a topic list that was based on a qualitative dataset about facilitators to palliative care in dementia reported by elderly care physicians. The interviews were recorded, transcribed verbatim and analysed with Atlas.ti. We used both deductive and inductive coding adding refined codes related to communication.ResultsAll interviewees expressed appreciation for nursing staff on whom they relied to communicate palliative care needs, yet they reported a variety of communication challenges around important changes in resident’s condition which were covered by two themes. (1) Teamwork was facilitated or impeded by team size and structure, quality of relationships and clarity in hierarchical relationships. (2) Continuity of information was affected by (in)effective routes of consultation and (lack of) detail in communicating observations.Conclusions and ImplicationsAlso in the case of on-staff physicians, functioning of the multidisciplinary team and accurate sharing of observed changes in nursing home residents’ condition are crucial for physicians to be able to address palliative care needs. The physicians’ expressions of how they would favor nursing staff to communicate can inspire interprofessional training, such as reporting objective observations and phrasing a clear request for help while avoiding overly demanding appeals.