cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Dynamic fMRI networks predict success in a behavioral weight loss program among older adults
Creators: name: Wu, Guorong
name: Mokhtari, Fatemeh
name: Simpson, Sean L.
name: Rejeski, W. Jack
name: Burdette, Jonathan H.
name: Zhu, Yingying
name: Laurienti, Paul J.
Publisher: name: Elsevier
Year: 2018

description: More than one-third of adults in the United States are obese, with a higher prevalence among older adults. Obesity among older adults is a major cause of physical dysfunction, hypertension, diabetes, and coronary heart diseases. Many people who engage in lifestyle weight loss interventions fail to reach targeted goals for weight loss, and most will regain what was lost within 1-2 years following cessation of treatment. This variability in treatment efficacy suggests that there are important phenotypes predictive of success with intentional weight loss that could lead to tailored treatment regimen, an idea that is consistent with the concept of precision-based medicine. Although the identification of biochemical and metabolic phenotypes are one potential direction of research, neurobiological measures may prove useful as substantial behavioral change is necessary to achieve success in a lifestyle intervention. In the present study, we use dynamic brain networks from functional magnetic resonance imaging (fMRI) data to prospectively identify individuals most likely to succeed in a behavioral weight loss intervention. Brain imaging was performed in overweight or obese older adults (age: 65-79 years) who participated in an 18-month lifestyle weight loss intervention. Machine learning and functional brain networks were combined to produce multivariate prediction models. The prediction accuracy exceeded 95%, suggesting that there exists a consistent pattern of connectivity which correctly predicts success with weight loss at the individual level. Connectivity patterns that contributed to the prediction consisted of complex multivariate network components that substantially overlapped with known brain networks that are associated with behavior emergence, self-regulation, body awareness, and the sensory features of food. Future work on independent datasets and diverse populations is needed to corroborate our findings. Additionally, we believe that efforts can begin to examine whether these models have clinical utility in tailoring treatment.
Accounting For The Neutrino Sphere Width In Effective And Full Calculations Of Neutrino Oscillations
Creators: name: HANSEN, Rasmus S. L.
Publisher: name: Zenodo
Year: 2018

description: The neutrino flavour evolution in a supernova can be described either in terms of neutrino fields or as the evolution of individual neutrinos. There is no reason to think that the two approaches should give contradicting results, and both has their advantages. One of the advantages of using individual neutrinos is that it becomes clear that the finite width of the neutrino sphere must lead to the averaging over the oscillation phase due to the different emission points, and therefore to a reduction of the effective mixing angle. On this poster, we go into the details of this argument and interpret it in terms of the density matrix formalism by taking into account the often neglected collision term.
Semi-Supervised Discriminative Classification Robust to Sample-Outliers and Feature-Noises
Creators: name: Wang, Tao
name: Shi, Feng
name: Thung, Kim-Han
name: Wu, Guorong
name: Adeli, Ehsan
name: An, Le
name: Shen, Dinggang
Publisher: name: Institute of Electrical and Electronics Engineers (IEEE)
Year: 2018

description: Discriminative methods commonly produce models with relatively good generalization abilities. However, this advantage is challenged in real-world applications (e.g., medical image analysis problems), in which there often exist outlier data points (sample-outliers) and noises in the predictor values (feature-noises). Methods robust to both types of these deviations are somewhat overlooked in the literature. We further argue that denoising can be more effective, if we learn the model using all the available labeled and unlabeled samples, as the intrinsic geometry of the sample manifold can be better constructed using more data points. In this paper, we propose a semi-supervised robust discriminative classification method based on the least-squares formulation of linear discriminant analysis to detect sample-outliers and feature-noises simultaneously, using both labeled training and unlabeled testing data. We conduct several experiments on a synthetic, some benchmark semi-supervised learning, and two brain neurodegenerative disease diagnosis datasets (for Parkinson's and Alzheimer's diseases). Specifically for the application of neurodegenerative diseases diagnosis, incorporating robust machine learning methods can be of great benefit, due to the noisy nature of neuroimaging data. Our results show that our method outperforms the baseline and several state-of-the-art methods, in terms of both accuracy and the area under the ROC curve.
66259: Letter: To Marion Scott.
Creators: name: Project Team, First World War Poetry Digital Archive
Publisher: name: University of Oxford
Year: 2024
Subjects: classificationCode: 430304
subject: British history
classificationCode: 430308
subject: European history (excl. British, classical Greek and Roman)
classificationCode: 430316
subject: International history

description: Dated 'Wednesday 12th' (?). Hopes Marion Scott's health is well / discusses various reviews of his music and poems in 'The Sunday Times' and the 'Telegraph' / the poet F.W. Howells / Scott's articles / the progress of the war / deaths in his battalion / the poet W. W. Gibson's volume 'Friends' / discussing Shakespeare, etc. in France / includes the poem 'Dust', from the 'Hospital Pictures' series. | File description(s):Envelope containing letter.
Dated 'Wednesday 12th' (?). Hopes Marion Scott's health is well / discusses various reviews of his music and poems in 'The Sunday Times' and the 'Telegraph' / the poet F.W. Howells / Scott's articles / the progress of the war / deaths in his battalion / the poet W. W. Gibson's volume 'Friends' / discussing Shakespeare, etc. in France / includes the poem 'Dust', from the 'Hospital Pictures' series.
Dated 'Wednesday 12th' (?). Hopes Marion Scott's health is well / discusses various reviews of his music and poems in 'The Sunday Times' and the 'Telegraph' / the poet F.W. Howells / Scott's articles / the progress of the war / deaths in his battalion / the poet W.W. Gibson's volume 'Friends' / discussing Shakespeare, etc. in France / includes the poem 'Dust', from the 'Hospital Pictures' series.
Dated 'Wednesday 12th' [December 1917]. Hopes Marion Scott's health is well / discusses various reviews of his music and poems in 'The Sunday Times' and the 'Telegraph' / the poet F.W. Howells / Scott's articles / the progress of the war / deaths in his battalion / the poet W. W. Gibson's volume 'Friends' / discussing Shakespeare, etc. in France / includes the poem 'Dust', from the 'Hospital Pictures' series.
Additional file 2 of iIL13Pred: improved prediction of IL-13 inducing peptides using popular machine learning classifiers
Creators: name: Arora, Pooja
name: Periwal, Neha
name: Goyal, Yash
name: Sood, Vikas
name: Kaur, Baljeet
Publisher: name: figshare
Year: 2024
Subjects: subject: Space Science
subject: Molecular Biology
subject: Chemical Sciences not elsewhere classified
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Cancer

description: Additional file 2: Table S3. Parameter range of seven machine learning models used in iIL13Pred for prediction of IL-13 inducing and non-inducing peptides.
sj-docx-1-mso-10.1177_20552173221092411 - Supplemental material for Early vs. late treatment initiation in multiple sclerosis and its impact on cost of illness: A register-based prospective cohort study in Sweden
Creators: name: Karampampa, Korinna
name: Gyllensten, Hanna
name: Murley, Chantelle
name: Alexanderson, Kristina
name: Kavaliunas, Andrius
name: Olsson, Tomas
name: Manouchehrinia, Ali
name: Hillert, Jan
name: Friberg, Emilie
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: 110904 Neurology and Neuromuscular Diseases
subject: FOS: Clinical medicine
subject: Neuroscience

description: Supplemental material, sj-docx-1-mso-10.1177_20552173221092411 for Early vs. late treatment initiation in multiple sclerosis and its impact on cost of illness: A register-based prospective cohort study in Sweden by Korinna Karampampa, Hanna Gyllensten, Chantelle Murley, Kristina Alexanderson, Andrius Kavaliunas, Tomas Olsson, Ali Manouchehrinia, Jan Hillert and Emilie Friberg in Multiple Sclerosis Journal – Experimental, Translational and Clinical
sj-pdf-3-jhs-10.1177_17531934221101563 - Supplemental material for Risk factors for reoperation after flexor tendon repair: a registry study
Creators: name: Svingen, Jonas
name: Wiig, Monica
name: Turesson, Christina
name: Farnebo, Simon
name: Arner, Marianne
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: 110314 Orthopaedics
subject: FOS: Clinical medicine
subject: 110604 Sports Medicine
subject: FOS: Health sciences
subject: 110323 Surgery

description: Supplemental material, sj-pdf-3-jhs-10.1177_17531934221101563 for Risk factors for reoperation after flexor tendon repair: a registry study by Jonas Svingen, Monica Wiig, Christina Turesson, Simon Farnebo and Marianne Arner in Journal of Hand Surgery (European Volume)
Additional file 5 of Genetic insights into the association of statin and newer nonstatin drug target genes with human longevity: a Mendelian randomization analysis
Creators: name: Chen, Han
name: Zhou, Xiaoying
name: Hu, Jingwen
name: Li, Shuo
name: Wang, Zi
name: Zhu, Tong
name: Cheng, Hong
name: Zhang, Guoxin
Publisher: name: figshare
Year: 2024
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 5: Fig. S3. Visualization of Colocalisation analysis. Colocalisation analysis of the cis-eQTL for the LDLR expressed in blood tissues and human lifespan in the discovery (A) and validation (B) datasets. Each dot represents an SNP at the LDLR locus. The dots in the scatter plots are colored according to their linkage disequilibrium to the colocalisation lead variant. The P values of the SNPs in the LDLR locus were extracted from the eQTL-Gen database in the blood tissue and from the human lifespan GWAS databases.
Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis
Creators: name: Wu, Guorong
name: Shen, Dinggang
name: Gao, Yaozong
name: Yang, Jianhua
name: Cao, Xiaohuan
name: Guo, Yanrong
Publisher: name: Elsevier
Year: 2017

description: In prostate cancer radiotherapy, computed tomography (CT) is widely used for dose planning purposes. However, because CT has low soft tissue contrast, it makes manual contouring difficult for major pelvic organs. In contrast, magnetic resonance imaging (MRI) provides high soft tissue contrast, which makes it ideal for accurate manual contouring. Therefore, the contouring accuracy on CT can be significantly improved if the contours in MRI can be mapped to CT domain by registering MRI with CT of the same subject, which would eventually lead to high treatment efficacy. In this paper, we propose a bi-directional image synthesis based approach for MRI-to-CT pelvic image registration. First, we use patch-wise random forest with auto-context model to learn the appearance mapping from CT to MRI domain, and then vice versa. Consequently, we can synthesize a pseudo-MRI whose anatomical structures are exactly same with CT but with MRI-like appearance, and a pseudo-CT as well. Then, our MRI-to-CT registration can be steered in a dual manner, by simultaneously estimating two deformation pathways: 1) one from the pseudo-CT to the actual CT and 2) another from actual MRI to the pseudo-MRI. Next, a dual-core deformation fusion framework is developed to iteratively and effectively combine these two registration pathways by using complementary information from both modalities. Experiments on a dataset with real pelvic CT and MRI have shown improved registration performance of the proposed method by comparing it to the conventional registration methods, thus indicating its high potential of translation to the routine radiation therapy.
sj-docx-2-jcn-10.1177_08830738221047668 - Supplemental material for Impact of the Updated Guideline for Pediatric Brain Death Determination on Current Practice
Creators: name: Krawiec, Conrad
name: Mysore, Mohan R.
name: Mathur, Mudit
name: Fang, Xinying
name: Zhou, Shouhao
name: Thomas, Neal J.
name: Nakagawa, Thomas A.
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: 110904 Neurology and Neuromuscular Diseases
subject: FOS: Clinical medicine
subject: 111403 Paediatrics
subject: Neuroscience

description: Supplemental material, sj-docx-2-jcn-10.1177_08830738221047668 for Impact of the Updated Guideline for Pediatric Brain Death Determination on Current Practice by Conrad Krawiec, Mohan R. Mysore, Mudit Mathur, Xinying Fang, Shouhao Zhou, Neal J. Thomas and Thomas A. Nakagawa in Journal of Child Neurology
Learning non-linear patch embeddings with neural networks for label fusion
Creators: name: Benkarim, Oualid M.
name: Gispert, Juan D.
name: Wu, Guorong
name: Piella, Gemma
name: Sanroma, Gerard
name: Molinuevo, Jose Luis
name: Shen, Dinggang
name: Camara, Oscar
name: Alzheimer's Disease Neuroimaging Initiative
name: Ballester, Miguel A. Gonzalez
Publisher: name: Elsevier
Year: 2017

description: In brain structural segmentation, multi-atlas strategies are increasingly being used over single-atlas strategies because of their ability to fit a wider anatomical variability. Patch-based label fusion (PBLF) is a type of such multi-atlas approaches that labels each target point as a weighted combination of neighboring atlas labels, where atlas points with higher local similarity to the target contribute more strongly to label fusion. PBLF can be potentially improved by increasing the discriminative capabilities of the local image similarity measurements. We propose a framework to compute patch embeddings using neural networks so as to increase discriminative abilities of similarity-based weighted voting in PBLF. As particular cases, our framework includes embeddings with different complexities, namely, a simple scaling, an affine transformation, and non-linear transformations. We compare our method with state-of-the-art alternatives in whole hippocampus and hippocampal subfields segmentation experiments using publicly available datasets. Results show that even the simplest versions of our method outperform standard PBLF, thus evidencing the benefits of discriminative learning. More complex transformation models tended to achieve better results than simpler ones, obtaining a considerable increase in average Dice score compared to standard PBLF.
A General Strategy for Aliphatic C-H Functionalization Enabled by Organic Photoredox Catalysis
Creators: name: Nicewicz, David A.
name: Alexanian, Erik J.
name: Margrey, Kaila A.
name: Czaplyski, William L.
Publisher: name: American Chemical Society (ACS)
Year: 2018

description: Synthetic transformations that functionalize unactivated aliphatic C-H bonds in an intermolecular fashion offer unique strategies for the synthesis and late-stage derivatization of complex molecules. Herein we report a general approach to the intermolecular functionalization of aliphatic C-H bonds using an acridinium photoredox catalyst and phosphate salt under blue LED irradiation. This strategy encompasses a range of valuable C-H transformations, including the direct conversions of a C-H bond to C-N, C-F, C-Br, C-Cl, C-S, and C-C bonds, in all cases using the alkane substrate as the limiting reagent. Detailed mechanistic studies are consistent with the intermediacy of a putative oxygen-centered radical as the hydrogen atom-abstracting species in these processes.
sj-pdf-1-ajs-10.1177_03635465221097118 – Supplemental material for Outcomes for the Arthroscopic Treatment of Femoroacetabular Impingement Syndrome With Acetabular Retroversion: A 3D Computed Tomography Analysis
Creators: name: Alter, Thomas D.
name: Knapik, Derrick M.
name: Lambers, Floor
name: Sivasundaram, Lakshmanan
name: Malloy, Philip
name: Chahla, Jorge
name: Nho, Shane J.
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: 110314 Orthopaedics
subject: FOS: Clinical medicine
subject: 110604 Sports Medicine
subject: FOS: Health sciences
subject: 110323 Surgery

description: Supplemental material, sj-pdf-1-ajs-10.1177_03635465221097118 for Outcomes for the Arthroscopic Treatment of Femoroacetabular Impingement Syndrome With Acetabular Retroversion: A 3D Computed Tomography Analysis by Thomas D. Alter, Derrick M. Knapik, Floor Lambers, Lakshmanan Sivasundaram, Philip Malloy, Jorge Chahla and Shane J. Nho in The American Journal of Sports Medicine
sj-doc-5-tam-10.1177_17588359221127678 – Supplemental material for Cancer immune profiling unveils biomarkers, immunological pathways, and cell type score associated with glioblastoma patients’ survival
Creators: name: Moreno, Daniel Antunes
name: da Silva, Luciane Sussuchi
name: Gomes, Isabella
name: Leal, Letícia Ferro
name: Berardinelli, Gustavo Noriz
name: Gonçalves, Gisele Melo
name: Pereira, Caio Augusto
name: Santana, Iara Viana Vidigal
name: Matsushita, Marcus de Medeiros
name: Bhat, Krishna
name: Lawler, Sean
name: Reis, Rui Manuel
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: 111299 Oncology and Carcinogenesis not elsewhere classified
subject: FOS: Clinical medicine
subject: 111702 Aged Health Care
subject: FOS: Health sciences
subject: 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified
subject: 110203 Respiratory Diseases

description: Supplemental material, sj-doc-5-tam-10.1177_17588359221127678 for Cancer immune profiling unveils biomarkers, immunological pathways, and cell type score associated with glioblastoma patients’ survival by Daniel Antunes Moreno, Luciane Sussuchi da Silva, Isabella Gomes, Letícia Ferro Leal, Gustavo Noriz Berardinelli, Gisele Melo Gonçalves, Caio Augusto Pereira, Iara Viana Vidigal Santana, Marcus de Medeiros Matsushita, Krishna Bhat, Sean Lawler and Rui Manuel Reis in Therapeutic Advances in Medical Oncology
Multi-modal classification of neurodegenerative disease by progressive graph-based transductive learning
Creators: name: Nie, Feiping
name: Wu, Guorong
name: Adeli, Ehsan
name: Wang, Zhengxia
name: Zhu, Yingying
name: Zhu, Xiaofeng
name: ADNI and PPMI
name: Munsell, Brent
Publisher: name: Elsevier
Year: 2017

description: Graph-based transductive learning (GTL) is a powerful machine learning technique that is used when sufficient training data is not available. In particular, conventional GTL approaches first construct a fixed inter-subject relation graph that is based on similarities in voxel intensity values in the feature domain, which can then be used to propagate the known phenotype data (i.e., clinical scores and labels) from the training data to the testing data in the label domain. However, this type of graph is exclusively learned in the feature domain, and primarily due to outliers in the observed features, may not be optimal for label propagation in the label domain. To address this limitation, a progressive GTL (pGTL) method is proposed that gradually finds an intrinsic data representation that more accurately aligns imaging features with the phenotype data. In general, optimal feature-to-phenotype alignment is achieved using an iterative approach that: (1) refines inter-subject relationships observed in the feature domain by using the learned intrinsic data representation in the label domain, (2) updates the intrinsic data representation from the refined inter-subject relationships, and (3) verifies the intrinsic data representation on the training data to guarantee an optimal classification when applied to testing data. Additionally, the iterative approach is extended to multi-modal imaging data to further improve pGTL classification accuracy. Using Alzheimer's disease and Parkinson's disease study data, the classification accuracy of the proposed pGTL method is compared to several state-of-the-art classification methods, and the results show pGTL can more accurately identify subjects, even at different progression stages, in these two study data sets.
Application of Integrated Drug Screening/Kinome Analysis to Identify Inhibitors of Gemcitabine-Resistant Pancreatic Cancer Cell Growth
Creators: name: Kireev, Dmitri
name: Herring, Laura E.
name: Axtman, Allison D.
name: East, Michael P.
name: Lee, Benjamin
name: Okumu, Denis O.
name: Johnson, Gary L.
name: McDonald, Ian M.
name: Willson, Timothy M.
name: Baines, Antonio T.
name: Golitz, Brian T.
name: Zuercher, William J.
name: Yeh, Jen Jen
name: Gilbert, Thomas S. K.
name: Wells, Carrow I.
name: Graves, Lee M.
name: Krulikas, Linas J.
Publisher: name: Elsevier
Year: 2018

description: Continuous exposure of a pancreatic cancer cell line MIA PaCa-2 (MiaS) to gemcitabine resulted in the formation of a gemcitabine-resistant subline (MiaR). In an effort to discover kinase inhibitors that inhibited MiaR growth, MiaR cells were exposed to kinase inhibitors (PKIS-1 library) in a 384-well screening format. Three compounds (UNC10112721A, UNC10112652A, and UNC10112793A) were identified that inhibited the growth of MiaR cells by more than 50% (at 50 nM). Two compounds (UNC10112721A and UNC10112652A) were classified as cyclin-dependent kinase (CDK) inhibitors, whereas UNC10112793A was reported to be a PLK inhibitor. Dose-response experiments supported the efficacy of these compounds to inhibit growth and increase apoptosis in 2D cultures of these cells. However, only UNC10112721A significantly inhibited the growth of 3D spheroids composed of MiaR cells and GFP-tagged cancer-associated fibroblasts. Multiplexed inhibitor bead (MIB)-mass spectrometry (MS) kinome competition experiments identified CDK9, CLK1-4, DYRK1A, and CSNK1 as major kinase targets for UNC10112721A in MiaR cells. Another CDK9 inhibitor (CDK-IN-2) replicated the growth inhibitory effects of UNC10112721A, whereas inhibitors against the CLK, DYRK, or CSNK1 kinases had no effect. In summary, these studies describe a coordinated approach to discover novel kinase inhibitors, evaluate their efficacy in 3D models, and define their specificity against the kinome.
A Dual Immunotherapy Nanoparticle Improves T-Cell Activation and Cancer Immunotherapy
Creators: name: Qi, Yanfei
name: Roche, Kyle C.
name: Wang, Andrew Z.
name: Vincent, Benjamin G.
name: Serody, Jonathan S.
name: Yang, Feifei
name: Mi, Yu
name: Smith, Christof C.
Publisher: name: Wiley
Year: 2018

description: Combination immunotherapy has recently emerged as a powerful cancer treatment strategy. A promising treatment approach utilizes coadministration of antagonistic antibodies to block checkpoint inhibitor receptors, such as antiprogrammed cell death-1 (aPD1), alongside agonistic antibodies to activate costimulatory receptors, such as antitumor necrosis factor receptor superfamily member 4 (aOX40). Optimal T-cell activation is achieved when both immunomodulatory agents simultaneously engage T-cells and promote synergistic proactivation signaling. However, standard administration of these therapeutics as free antibodies results in suboptimal T-cell binding events, with only a subset of the T-cells binding to both aPD1 and aOX40. Here, it is shown that precise spatiotemporal codelivery of aPD1 and aOX40 using nanoparticles (NP) (dual immunotherapy nanoparticles, DINP) results in improved T-cell activation, enhanced therapeutic efficacy, and increased immunological memory. It is demonstrated that DINP elicits higher rates of T-cell activation in vitro than free antibodies. Importantly, it is demonstrated in two tumor models that combination immunotherapy administered in the form of DINP is more effective than the same regimen administered as free antibodies. This work demonstrates a novel strategy to improve combination immunotherapy using nanotechnology.
Supplemental Material - National Treatment Patterns and Outcomes for Hospitalized Patients with Chronic Limb-Threatening Ischemia and End-Stage Kidney Disease
Creators: name: Shah, Samir K.
name: Neal, Dan
name: Berceli, Scott A.
name: Segal, Mark
name: Cooper, Michol A.
name: Huber, Thomas S.
name: Upchurch, Gilbert R.
name: Scali, Salvatore T.
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: Cardiology
subject: 110323 Surgery
subject: FOS: Clinical medicine

description: Supplemental Material for National Treatment Patterns and Outcomes for Hospitalized Patients with Chronic Limb-Threatening Ischemia and End-Stage Kidney Disease by Samir K. Shah, Dan Neal, Scott A. Berceli, Mark Segal, Michol A. Cooper, Thomas S. Huber, Gilbert R. Upchurch, and Salvatore T. Scali in Vascular and Endovascular Surgery
Significance-based community detection in weighted networks.
Creators: name: Palowitch, John
name: Nobel, Andrew B
name: Bhamidi, Shankar
Publisher: name: The University of North Carolina at Chapel Hill University Libraries
Year: 2018

description: Community detection is the process of grouping strongly connected nodes in a network. Many community detection methods for un-weighted networks have a theoretical basis in a null model. Communities discovered by these methods therefore have interpretations in terms of statistical significance. In this paper, we introduce a null for weighted networks called the continuous configuration model. First, we propose a community extraction algorithm for weighted networks which incorporates iterative hypothesis testing under the null. We prove a central limit theorem for edge-weight sums and asymptotic consistency of the algorithm under a weighted stochastic block model. We then incorporate the algorithm in a community detection method called CCME. To benchmark the method, we provide a simulation framework involving the null to plant "background" nodes in weighted networks with communities. We show that the empirical performance of CCME on these simulations is competitive with existing methods, particularly when overlapping communities and background nodes are present. To further validate the method, we present two real-world networks with potential background nodes and analyze them with CCME, yielding results that reveal macro-features of the corresponding systems.
Direct Aryl C-H Amination with Primary Amines Using Organic Photoredox Catalysis
Creators: name: Margrey, Kaila A.
name: Levens, Alison
name: Nicewicz, David A.
Publisher: name: Wiley
Year: 2017

description: The direct catalytic C-H amination of arenes is a powerful synthetic strategy with useful applications in pharmaceuticals, agrochemicals, and materials chemistry. Despite the advances in catalytic C-H functionalization, the use of aliphatic amine coupling partners is limited. Described herein is the construction of C-N bonds, using primary amines, by direct C-H functionalization with an acridinium photoredox catalyst under an aerobic atmosphere. A wide variety of primary amines, including amino acids and more complex amines are competent coupling partners. Various electron-rich aromatics and heteroaromatics are useful scaffolds in this reaction, as are complex, biologically active arenes. We also describe the ability to functionalize arenes that are not oxidized by an acridinium catalyst, such as benzene and toluene, thus supporting a reactive amine cation radical intermediate.
The Meta-Net Strategic Research Agenda For Language Technology   In Europe: An Extended Summary
Creators: name: Rehm, Georg
Publisher: name: Zenodo
Year: 2018

description: Recognising Europe’s exceptional demand and opportunities for multilingual language technologies, 60 leading research centres in 34 European countries joined forces in meta-net, a European Network of Excellence. meta-net has developed a Strategic Research Agenda (sra) for multilingual Europe – the complex planning and discussion process took more than two years to complete. While the complete sra has been published elsewhere (Rehm & Uszkoreit 2013), this heavily condensed version provides an extended summary as an alternative mode of access and to enable interested parties to familiarise themselves with its key concepts in an efficient way.
Supplemental Material - 2020 BASHH national clinical audit: Management of infection with Neisseria gonorrhoeae
Creators: name: Phyu, Khine
name: Curtis, Hilary
name: Wallace, Harriet
name: Goodall, Lisa
name: Apea, Vanessa
name: Iveson, Helen
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: 110309 Infectious Diseases
subject: FOS: Health sciences

description: Supplemental Material for 2020 BASHH national clinical audit: Management of infection with Neisseria gonorrhoeae by Khine Phyu, Hilary Curtis, Harriet Wallace, Lisa Goodall, Vanessa Apea, Helen Iveson, and on behalf of the members of the British Society for Sexual Health and HIV National Audit Group in International Journal of STD & AIDS.
sj-docx-1-ehi-10.1177_11786302221146020 – Supplemental material for Human Health Risk Assessment due to Heavy Metals in Ground and Surface Water and Association of Diseases With Drinking Water Sources: A Study From Maharashtra, India
Creators: name: Mawari, Govind
name: Kumar, Naresh
name: Sarkar, Sayan
name: Frank, Arthur L
name: Daga, Mradul Kumar
name: Singh, Mongjam Meghachandra
name: Joshi, Tushar Kant
name: Singh, Ishwar
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: 111799 Public Health and Health Services not elsewhere classified
subject: FOS: Health sciences

description: Supplemental material, sj-docx-1-ehi-10.1177_11786302221146020 for Human Health Risk Assessment due to Heavy Metals in Ground and Surface Water and Association of Diseases With Drinking Water Sources: A Study From Maharashtra, India by Govind Mawari, Naresh Kumar, Sayan Sarkar, Arthur L Frank, Mradul Kumar Daga, Mongjam Meghachandra Singh, Tushar Kant Joshi and Ishwar Singh in Environmental Health Insights
Predictive Model for Site-Selective Aryl and Heteroaryl C-H Functionalization via Organic Photoredox Catalysis
Creators: name: Zecri, Frederic
name: McManus, Joshua B.
name: Nicewicz, David A.
name: Bonazzi, Simone
name: Margrey, Kaila A.
Publisher: name: American Chemical Society (ACS)
Year: 2017

description: Direct C-H functionalization of aromatic compounds is a useful synthetic strategy that has garnered much attention because of its application to pharmaceuticals, agrochemicals, and late-stage functionalization reactions on complex molecules. On the basis of previous methods disclosed by our lab, we sought to develop a predictive model for site selectivity and extend this aryl functionalization chemistry to a selected set of heteroaromatic systems commonly used in the pharmaceutical industry. Using electron density calculations, we were able to predict the site selectivity of direct C-H functionalization in a number of heterocycles and identify general trends observed across heterocycle classes.
Predicting Adverse Drug Effects from Literature- and Database-Mined Assertions
Creators: name: Sedykh, Alexander
name: La, Mary K.
name: Tropsha, Alexander
name: Muratov, Eugene
name: Fourches, Denis
Publisher: name: Springer Nature
Year: 2018

description: IntroductionGiven that adverse drug effects (ADEs) have led to post-market patient harm and subsequent drug withdrawal, failure of candidate agents in the drug development process, and other negative outcomes, it is essential to attempt to forecast ADEs and other relevant drug-target-effect relationships as early as possible. Current pharmacologic data sources, providing multiple complementary perspectives on the drug-target-effect paradigm, can be integrated to facilitate the inference of relationships between these entities.ObjectiveThis study aims to identify both existing and unknown relationships between chemicals (C), protein targets (T), and ADEs (E) based on evidence in the literature.Materials and MethodsCheminformatics and data mining approaches were employed to integrate and analyze publicly available clinical pharmacology data and literature assertions interrelating drugs, targets, and ADEs. Based on these assertions, a C-T-E relationship knowledge base was developed. Known pairwise relationships between chemicals, targets, and ADEs were collected from several pharmacological and biomedical data sources. These relationships were curated and integrated according to Swanson's paradigm to form C-T-E triangles. Missing C-E edges were then inferred as C-E relationships.ResultsUnreported associations between drugs, targets, and ADEs were inferred, and inferences were prioritized as testable hypotheses. Several C-E inferences, including testosterone†’myocardial infarction, were identified using inferences based on the literature sources published prior to confirmatory case reports. Timestamping approaches confirmed the predictive ability of this inference strategy on a larger scale.ConclusionsThe presented workflow, based on free-access databases and an association-based inference scheme, provided novel C-E relationships that have been validated post hoc in case reports. With refinement of prioritization schemes for the generated C-E inferences, this workflow may provide an effective computational method for the early detection of potential drug candidate ADEs that can be followed by targeted experimental investigations.
Scintillation Light Simulation In The Context Of Dune Dual Phase Liquid Argon Tpc
Creators: name: CHAPPUIS, Anne
Publisher: name: Zenodo
Year: 2018

description: In a LArTPC, the scintillation light is an important signal as it will provide the t0 for track reconstruction, may improve the calorimetric performances and can be used as a inner trigger for non-beam rare events. However, the optical properties of liquid argon for scintillation light wavelength are poorly known. A detailed light simulation allows us to study the impact of these parameters (e.g. absorption and scattering length) on the amount of light collected and drove the protoDUNE-DP photon collector positioning.

The amount of photons produced by a charged particle crossing the active volume is large whereas their probability to be collected by the light detector is low. In order to avoid tracking down all photons for each track, a light map has been generated and parametrized for protoDUNE-DP. As for the DUNE module trigger optimization studies, this method is still too heavy, and new technics are being developed.
Additional file 1 of Exploring the needs and coping strategies of family caregivers taking care of dying patients at home: a field study
Creators: name: Zhang, Xiaotian
name: Xu, Tianmeng
name: Qin, Yuan
name: Wang, Minghui
name: Li, Zhaoyu
name: Song, Jingyu
name: Tang, Qianqian
name: Wang, Zidan
name: Xu, Lijie
name: Wu, Lingling
name: Yue, Peng
Publisher: name: figshare
Year: 2023
Subjects: subject: Medicine
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Cancer
subject: Science Policy
subject: Mental Health

description: Supplementary Material 1
sj-docx-1-cmp-10.1177_07388942221145352 - Supplemental material for Relative political capacity: A dataset to evaluate the performance of nations, 1960–2018
Creators: name: Fisunoglu, Ali
name: Kang, Kyungkook
name: Kugler, Tad
name: Arbetman-Rabinowitz, Marina
Publisher: name: SAGE Journals
Year: 2022
Subjects: subject: 220104 Human Rights and Justice Issues
subject: FOS: Philosophy, ethics and religion
subject: 160607 International Relations
subject: FOS: Political science

description: Supplemental material, sj-docx-1-cmp-10.1177_07388942221145352 for Relative political capacity: A dataset to evaluate the performance of nations, 1960–2018 by Ali Fisunoglu, Kyungkook Kang, Tad Kugler and Marina Arbetman-Rabinowitz in Conflict Management and Peace Science
Chemotext: A Publicly Available Web Server for Mining Drug-Target-Disease Relationships in PubMed
Creators: name: Capuzzi, Stephen J.
name: Tropsha, Alexander
name: Pozefsky, Diane
name: Baker, Nancy
name: Lam, Wai In
name: Muratov, Eugene N.
name: O'Banion, Colin P.
name: Thornton, Thomas E.
name: Liu, Kammy
Publisher: name: American Chemical Society (ACS)
Year: 2018

description: Elucidation of the mechanistic relationships between drugs, their targets, and diseases is at the core of modern drug discovery research. Thousands of studies relevant to the drug-target-disease (DTD) triangle have been published and annotated in the Medline/PubMed database. Mining this database affords rapid identification of all published studies that confirm connections between vertices of this triangle or enable new inferences of such connections. To this end, we describe the development of Chemotext, a publicly available Web server that mines the entire compendium of published literature in PubMed annotated by Medline Subject Heading (MeSH) terms. The goal of Chemotext is to identify all known DTD relationships and infer missing links between vertices of the DTD triangle. As a proof-of-concept, we show that Chemotext could be instrumental in generating new drug repurposing hypotheses or annotating clinical outcomes pathways for known drugs. The Chemotext Web server is freely available at http://chemotext.mml.unc.edu .
Making and Undoing Forming / and Unforming
Creators: name: ANNE-MARIE ELIZABETH MAY
Publisher: name: Monash University
Year: 2020
Subjects: Art

description: This exegesis charts a program of studio-led research into the use of making and undoing or forming and unforming focusing on the production of haptic, optical and spatial intensities. As two interrelated dimensions of forming, making and undoing are approached as a dynamic event in which materials, production procedures and presentation processes intertwine to focus on the slippages from one state to another. The research draws on Gilles Deleuze’s theorisation of sensation in his collaboration with Felix Guattari to position methodologies of making and undoing or forming and unforming as a group of operative processes that produce critical effects.
Computing hemodynamic response functions from concurrent spectral fiber-photometry and fMRI data
Creators: name: Cerri, Domenic H.
name: Shih, Yen-Yu I.
name: Wang, Tzu-Wen
name: Chao, Tzu-Hao H.
name: Zhang, Wei-Ting
name: Hsu, Li-Ming
Publisher: name: SPIE, the international society for optics and photonics
Year: 2022

description: Significance: Although emerging evidence suggests that the hemodynamic response function (HRF) can vary by brain region and species, a single, canonical, human-based HRF is widely used in animal studies. Therefore, the development of flexible, accessible, brain-region specific HRF calculation approaches is paramount as hemodynamic animal studies become increasingly popular. Aim: To establish an fMRI-compatible, spectral, fiber-photometry platform for HRF calculation and validation in any rat brain region. Approach: We used our platform to simultaneously measure (a) neuronal activity via genetically encoded calcium indicators (GCaMP6f), (b) local cerebral blood volume (CBV) from intravenous Rhodamine B dye, and (c) whole brain CBV via fMRI with the Feraheme contrast agent. Empirical HRFs were calculated with GCaMP6f and Rhodamine B recordings from rat brain regions during resting-state and task-based paradigms. Results: We calculated empirical HRFs for the rat primary somatosensory, anterior cingulate, prelimbic, retrosplenial, and anterior insular cortical areas. Each HRF was faster and narrower than the canonical HRF and no significant difference was observed between these cortical regions. When used in general linear model analyses of corresponding fMRI data, the empirical HRFs showed better detection performance than the canonical HRF. Conclusions: Our findings demonstrate the viability and utility of fiber-photometry-based HRF calculations. This platform is readily scalable to multiple simultaneous recording sites, and adaptable to study transfer functions between stimulation events, neuronal activity, neurotransmitter release, and hemodynamic responses.
Past is prologue: host community assembly and the risk of infectious disease over time
Creators: name: Wilfahrt, Peter A.
name: Halliday, Fletcher W.
name: Heckman, Robert W.
name: Mitchell, Charles E.
Publisher: name: Wiley
Year: 2018

description: Infectious disease risk is often influenced by host diversity, but the causes are unresolved. Changes in diversity are associated with changes in community structure, particularly during community assembly; therefore, by incorporating change over time, host community assembly may provide a framework to resolve causation. In turn, community assembly can be driven by many processes, including resource enrichment. To test the hypothesis that community assembly causally links host diversity to future disease, we experimentally manipulated host diversity and resource supply to hosts, then allowed communities to assemble for 2 years (surveyed 2012-2014). Initially, host diversity increased disease. Subsequently, host diversity did not directly alter disease. However, host diversity determined the trajectory of host community assembly, altering colonisation by exotic host species and richness-independent host phylogenetic diversity, which together reversed the initial increase in disease. Ultimately, incorporating the temporal dimension of community assembly revealed novel mechanisms linking host diversity to future disease.
Impact of US Smoke-free Air Laws on Restaurant and Bar Employment, 1990-2015
Creators: name: Shafer, Paul
Publisher: name: Oxford University Press (OUP)
Year: 2017

description: INTRODUCTION: Secondhand smoke exposure is responsible for an estimated 50000 deaths per year among nonsmokers in the United States. Smoke-free air laws reduce secondhand smoke exposure but often encounter opposition over concerns about their economic impact. Expansion of these laws has stagnated and efforts to weaken existing laws may exacerbate existing disparities in exposure. Studies at the state and local levels have found that smoke-free air laws do not generally have an adverse effect, but there are no recent estimates of the impact of these laws nationally. METHODS: Employment and sales are two measures commonly used to estimate the economic impact of smoke-free air laws. Sales data are gathered by state and local taxing authorities but not uniformly across jurisdictions. Dynamic panel models are used to estimate a population-weighted national average treatment effect of smoke-free air laws on restaurant and bar employment using data from the Quarterly Census of Employment and Wages for 1990 to 2015. RESULTS: A one-percentage point increase in population covered by a restaurant smoke-free air law is associated with a small increase (approximately 0.01%) in restaurant employment (b = .0001, p < .001). The percentage of state population covered by a bar smoke-free air law was not associated with bar employment. DISCUSSION: Smoke-free air laws are a powerful tool for protecting hospitality workers and patrons from the dangers of secondhand smoke. Using data from over more than two decades, these results suggest that smoke-free air laws in the United States do not generally have any meaningful effect on restaurant and bar employment. IMPLICATIONS: Smoke-free air laws are associated with reductions in negative health outcomes and decreased smoking prevalence. Despite this clear public health argument and strong public support, passage of new laws has stagnated and exemptions are being used to weaken existing laws. The ability to make both a health and business case in support of existing laws may also bolster the case for expansion. This study provides an updated look at the economic impact of smoke-free air laws nationally through 2015. The lack of adverse findings provides additional support for these laws as public health win-win.
sj-pdf-7-hpq-10.1177_13591053221144440 – Supplemental material for Adjusting to the COVID-19 Outbreak in the United States: The impact of disruptions on habits and changes in health behaviors
Creators: name: Andrade, Fernanda C
name: Hoyle, Rick H
name: Burnell, Kaitlyn
Publisher: name: SAGE Journals
Year: 2023
Subjects: subject: 170199 Psychology not elsewhere classified
subject: FOS: Psychology
subject: 110319 Psychiatry (incl. Psychotherapy)
subject: FOS: Clinical medicine
subject: 111799 Public Health and Health Services not elsewhere classified
subject: FOS: Health sciences

description: Supplemental material, sj-pdf-7-hpq-10.1177_13591053221144440 for Adjusting to the COVID-19 Outbreak in the United States: The impact of disruptions on habits and changes in health behaviors by Fernanda C Andrade, Rick H Hoyle and Kaitlyn Burnell in Journal of Health Psychology
Perovskite Quantum Dots In Liquid Scintillator
Creators: name: GOODING, Diana
Publisher: name: Zenodo
Year: 2018

description: Quantum dots are semiconducting crystals with dimensions on the order of nanometers. Due to quantum confinement, their size gives rise to optical properties that resemble those of single atoms, rather than bulk material. One of these is their absorption of light shorter than a characteristic wavelength and reemission in a narrow peak around that wavelength. An emergent class of these materials, perovskites, can emit in the UV range, at the peak quantum efficiency of a typical photomultiplier tube. This unique photoluminescence makes perovskites ideal wavelength shifters. Moreover, their chemistry and ease of synthesis provide a straight-forward method to suspend heavy elements in organic scintillators. The NuDot collaboration has been investigating the light yield of perovskite-doped liquid scintillator. A review of the current results will be presented.
sj-docx-3-cpc-10.1177_10556656221148902 - Supplemental material for Treatment of Asymmetric Crying Face by Fascia lata Grafting
Creators: name: Lei, Bowen
name: Huang, Qinghua
name: Li, Binghang
name: Ma, Hengyuan
name: Yang, Bin
Publisher: name: SAGE Journals
Year: 2023
Subjects: Surgery

description: Supplemental material, sj-docx-3-cpc-10.1177_10556656221148902 for Treatment of Asymmetric Crying Face by Fascia lata Grafting by Bowen Lei, MD, Qinghua Huang, MD, Binghang Li, MD, Hengyuan Ma, MD, and Bin Yang, MD, PHD in The Cleft Palate Craniofacial Journal
Modernization of Enoxaparin Molecular Weight Determination Using Homogeneous Standards
Creators: name: Liu, Jian
name: Szajek, Anita Y.
name: Muratov, Eugene N.
name: Xu, Yongmei
name: Arnold, Katelyn M.
name: Capuzzi, Stephen J.
name: Tropsha, Alexander
name: Carrick, Kevin
Publisher: name: MDPI
Year: 2017

description: Enoxaparin is a low-molecular weight heparin used to treat thrombotic disorders. Following the fatal contamination of the heparin supply chain in 2007-2008, the U.S. Pharmacopeia (USP) and U.S. Food and Drug Administration (FDA) have worked extensively to modernize the unfractionated heparin and enoxaparin monographs. As a result, the determination of molecular weight (MW) has been added to the monograph as a measure to strengthen the quality testing and to increase the protection of the global supply of this life-saving drug. The current USP calibrant materials used for enoxaparin MW determination are composed of a mixture of oligosaccharides; however, they are difficult to reproduce as the calibrants have ill-defined structures due to the heterogeneity of the heparin parent material. To address this issue, we describe a promising approach consisting of a predictive computational model built from a library of chemoenzymatically synthesized heparin oligosaccharides for enoxaparin MW determination. Here, we demonstrate that this test can be performed with greater efficiency by coupling synthetic oligosaccharides with the power of computational modeling. Our approach is expected to improve the MW measurement for enoxaparin.