115 Works
Additional file 2 of Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
Jing Tian, Mingzhen Zhu, Zijing Ren, Qiang Zhao, Puqing Wang, Colin K. He, Min Zhang, Xiaochun Peng, Beilei Wu, Rujia Feng & Minglong Fu
Additional file 2: Figure S2. Selection of the optimal number of clusters.
Additional file 15 of Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
Jing Tian, Mingzhen Zhu, Zijing Ren, Qiang Zhao, Puqing Wang, Colin K. He, Min Zhang, Xiaochun Peng, Beilei Wu, Rujia Feng & Minglong Fu
Additional file 15: Supplementary methods. Description of normalization methods used data normalization.
Additional file 4 of Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
Jing Tian, Mingzhen Zhu, Zijing Ren, Qiang Zhao, Puqing Wang, Colin K. He, Min Zhang, Xiaochun Peng, Beilei Wu, Rujia Feng & Minglong Fu
Additional file 4: Table S2. Performance of the SVM model on tumor types.
sj-docx-1-jop-10.1177_02698811221127954 – Supplemental material for Therapeutic (Sub)stance: Current practice and therapeutic conduct in preparatory sessions in substance-assisted psychotherapy—A systematized review
Sascha B Thal, Michelle Wieberneit, Jason M Sharbanee, Petra M Skeffington, Paris Baker, Raimondo Bruno, Tobias Wenge & Stephen J Bright
Supplemental material, sj-docx-1-jop-10.1177_02698811221127954 for Therapeutic (Sub)stance: Current practice and therapeutic conduct in preparatory sessions in substance-assisted psychotherapy—A systematized review by Sascha B Thal, Michelle Wieberneit, Jason M Sharbanee, Petra M Skeffington, Paris Baker, Raimondo Bruno, Tobias Wenge and Stephen J Bright in Journal of Psychopharmacology
sj-docx-2-jop-10.1177_02698811221127954 – Supplemental material for Therapeutic (Sub)stance: Current practice and therapeutic conduct in preparatory sessions in substance-assisted psychotherapy—A systematized review
Sascha B Thal, Michelle Wieberneit, Jason M Sharbanee, Petra M Skeffington, Paris Baker, Raimondo Bruno, Tobias Wenge & Stephen J Bright
Supplemental material, sj-docx-2-jop-10.1177_02698811221127954 for Therapeutic (Sub)stance: Current practice and therapeutic conduct in preparatory sessions in substance-assisted psychotherapy—A systematized review by Sascha B Thal, Michelle Wieberneit, Jason M Sharbanee, Petra M Skeffington, Paris Baker, Raimondo Bruno, Tobias Wenge and Stephen J Bright in Journal of Psychopharmacology
Quantitative selenium speciation in feed by enzymatic probe sonication and ion chromatography-inductively coupled plasma mass spectrometry
Zhiming Xiao, Jitong Wang, Jiangpeng Guo, Decheng Suo, Shi Wang, Jing Tian, Lili Guo & Xia Fan
A rapid, sensitive and species preservative analytical method for the simultaneous determination of six selenium (Se) species has been developed. Enzymatic probe sonication (EPS) was investigated as a novel and alternative technology for the extraction of Se species from feed matrices and the results were compared with the conventional hot water extraction, enzymatic hydrolysis and sequential extraction. The critical parameters of EPS such as enzyme types, extraction time, temperature, ultrasonic power and sample/enzyme ratio were...
Additional file 2 of Frequency of occurrence and habitat selection shape the spatial variation in the antibiotic resistome in riverine ecosystems in eastern China
Chunxia Jiang, Haiyang Chen, Hans-Peter Grossart, Quanfa Zhang, Robby Stoks, Yi Zhao, Feng Ju, Wenzhi Liu & Yuyi Yang
Additional file 2: Fig. S1Number (a) and relative abundance (b) of ARGs detected inriverine ecosystems of eastern China. R represents rhizosphere soil; SBrepresents surface bulk soil (0-20 cm below bulk soil surface); BB represents bottombulk soil (40-60 cm below bulk soil surface); S represents sediment (0-20 cmbelow sediment surface); SR and NR represent rhizosphere soil in the south andnorth, respectively; SSB and NSB represent surface bulk soil (0-20 cm belowbulk soil surface) in the south...
Additional file 2 of Frequency of occurrence and habitat selection shape the spatial variation in the antibiotic resistome in riverine ecosystems in eastern China
Chunxia Jiang, Haiyang Chen, Hans-Peter Grossart, Quanfa Zhang, Robby Stoks, Yi Zhao, Feng Ju, Wenzhi Liu & Yuyi Yang
Additional file 2: Fig. S1Number (a) and relative abundance (b) of ARGs detected inriverine ecosystems of eastern China. R represents rhizosphere soil; SBrepresents surface bulk soil (0-20 cm below bulk soil surface); BB represents bottombulk soil (40-60 cm below bulk soil surface); S represents sediment (0-20 cmbelow sediment surface); SR and NR represent rhizosphere soil in the south andnorth, respectively; SSB and NSB represent surface bulk soil (0-20 cm belowbulk soil surface) in the south...
Additional file 17 of High density linkage maps, genetic architecture, and genomic prediction of growth and wood properties in Pinus radiata
Jules S. Freeman, Gancho T. Slavov, Jakob B. Butler, Tancred Frickey, Natalie J. Graham, Jaroslav Klápště, John Lee, Emily J. Telfer, Phillip Wilcox & Heidi S. Dungey
Additional file 17: Table S5. Matrix of Pearson’s phenotypic correlation coefficients between growth and wood property traits analysed in the Pinus radiata QTL population. Two tailed P-values *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.
Appendix_S1 from Correction to ‘A triple threat: high population density, high foraging intensity and flexible habitat preferences explain high impact of feral cats on prey’ 2022 by Hamer et al.
Rowena P. Hamer, Riana Z. Gardiner, Kirstin M. Proft, Christopher N. Johnson & Menna E. Jones
Electronic supplementary material associated with http://dx.doi.org/10.1098/rspb.2022.1985
Additional file 2 of High density linkage maps, genetic architecture, and genomic prediction of growth and wood properties in Pinus radiata
Jules S. Freeman, Gancho T. Slavov, Jakob B. Butler, Tancred Frickey, Natalie J. Graham, Jaroslav Klápště, John Lee, Emily J. Telfer, Phillip Wilcox & Heidi S. Dungey
Additional file 2: Table S2. SNP ranking criteria used for the Pinus radiata QTL and FWK mapping populations.
Additional file 4 of High density linkage maps, genetic architecture, and genomic prediction of growth and wood properties in Pinus radiata
Jules S. Freeman, Gancho T. Slavov, Jakob B. Butler, Tancred Frickey, Natalie J. Graham, Jaroslav Klápště, John Lee, Emily J. Telfer, Phillip Wilcox & Heidi S. Dungey
Additional file 4: Fig. S1. Frequency distributions for the phenotypic traits measured in the QTL and FWK Pinus radiata populations in this study. QTL population: (A) Ring area (mm2); (B) Density (kg/m3) Silviscan; (C) Radial cell diameter (μm); (D) Tangential cell diameter (μm); (E) Fibre coarseness (μm/m); (F) Cell wall thickness (μm); (G) Specific surface area (m2/kg); (H) Microfibril angle (degrees); (I) Modulus of elasticity (GPa); (J) Density prediction for first 5 mm core (maximum...
Additional file 2 of Developing a shortened version of the dementia knowledge assessment scale (DKAS-TC) with a sample in Taiwan: an item response theory approach
Su-Pin Hung, Yi-Han Liao, Claire Eccleston & Li-Jung Elizabeth Ku
Additional file 2: Appendix 2: Table 1. The short-form of the Dementia Knowledge Assessment Scale-Traditional Chinese version (DKAS-s). Table 2. Chinese/English statements about dementia in the short-form of Dementia Knowledge Assessment Scale-Traditional Chinese version (DKAS-s)
sj-pdf-2-pmj-10.1177_02692163221132089 – Supplemental material for Co-designing Community Out-of-hours Palliative Care Services: A systematic literature search and review
Christine Low, Pathmavathy Namasivayam & Tony Barnett
Supplemental material, sj-pdf-2-pmj-10.1177_02692163221132089 for Co-designing Community Out-of-hours Palliative Care Services: A systematic literature search and review by Christine Low, Pathmavathy Namasivayam and Tony Barnett in Palliative Medicine
Additional file 10 of Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
Jing Tian, Mingzhen Zhu, Zijing Ren, Qiang Zhao, Puqing Wang, Colin K. He, Min Zhang, Xiaochun Peng, Beilei Wu, Rujia Feng & Minglong Fu
Additional file 10: Table S7. Clinical information of CGGA DNAm dataset.
Additional file 1 of Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
Jing Tian, Mingzhen Zhu, Zijing Ren, Qiang Zhao, Puqing Wang, Colin K. He, Min Zhang, Xiaochun Peng, Beilei Wu, Rujia Feng & Minglong Fu
Additional file 1: Figure S1. Architecture of the autoencoder.
Manuscript Supplementary Information from Dominant carnivore loss benefits native avian and invasive mammalian scavengers
Matthew W. Fielding, Calum X. Cunningham, Jessie C. Buettel, Dejan Stojanovic, Luke A. Yates, Menna E. Jones & Barry W. Brook
Contains further methodology information, model structure, model selection results and model output
Appendix S1. Supplementary information from Top predator restricts the niche breadth of prey: effects of assisted colonization of Tasmanian devils on a widespread omnivorous prey
Vincent P. Scoleri, Janeane Ingram, Christopher N. Johnson & Menna E. Jones
Few landscape-scale experiments test the effects of predators on the abundance and distribution of prey across habitat gradients. We use the assisted colonization of a top predator, the Tasmanian devil (Sarcophilus harrisii), to test the impacts of predation on the abundance, habitat use and temporal activity of a widespread prey species, the omnivorous common brushtail possum (Trichosurus vulpecula). Before introduction of devils to Maria Island, Tasmania, Australia, in 2012, possums were abundant in open grasslands...
Designing MATLAB course for undergraduates in cartography and geographic information science: linking research and teaching
Jing Tian, Chang Ren, Yingzhe Lei & Yiheng Wang
Participation of undergraduate students in research helps them nurture critical thinking, develop research skills, enhance self-confidence, and clarify their education or career paths. The curriculum is central to integrating teaching and research, and is a primary source for providing undergraduate research experience. This study designed a MATLAB course for undergraduate students in Cartography and Geographic Information Science. This course integrated various models of research–teaching nexus and combined MATLAB with the profession, aiming to benefit students’...
Loss of the crumbs cell polarity complex disrupts epigenetic transcriptional control and cell cycle progression in the developing retina.
Nicholas Owen, Maria Toms, Yuan Tian, Lyes Toualbi, Rose Richardson, Rodrigo Young, Dhani Tracey-White, Pawan Dhami, Stephan Beck & Mariya Moosajee
The crumbs cell polarity complex plays a crucial role in apical-basal epithelial polarity, cellular adhesion, and morphogenesis. Homozygous variants in human CRB1 result in autosomal recessive Leber congenital amaurosis (LCA) and retinitis pigmentosa (RP), with no established genotype-phenotype correlation. The associated protein complexes have key functions in developmental pathways; however the underlying disease mechanism remains unclear. Using the oko meduzym289/m289 (crb2a-/- ) zebrafish, we performed integrative transcriptomic (RNA-seq data) and methylomic (reduced representation bisulphite sequencing,...
The dual-crosslinked prospective values of RAI14 for the diagnosis and chemosurveillance in triple negative breast cancer
Ranliang Cui, Jie Zou, Yan Zhao, Ting Zhao, Li Ren & Yueguo Li
The exploration of non-invasive biomarkers for assessing tumor response is critical to optimize treatment decisions. In this study, we aimed at determining the potential role of RAI14 in the early diagnosis and evaluation of chemotherapy efficacy in triple-negative breast cancer (TNBC). We recruited 116 patients newly diagnosed with breast cancer, 30 patients with benign breast disease and 30 healthy controls. In addition, 57 TNBC patients were collected in serum at different time points (C0, C2...
The dual-crosslinked prospective values of RAI14 for the diagnosis and chemosurveillance in triple negative breast cancer
Ranliang Cui, Jie Zou, Yan Zhao, Ting Zhao, Li Ren & Yueguo Li
The exploration of non-invasive biomarkers for assessing tumor response is critical to optimize treatment decisions. In this study, we aimed at determining the potential role of RAI14 in the early diagnosis and evaluation of chemotherapy efficacy in triple-negative breast cancer (TNBC). We recruited 116 patients newly diagnosed with breast cancer, 30 patients with benign breast disease and 30 healthy controls. In addition, 57 TNBC patients were collected in serum at different time points (C0, C2...
Impairments, and physical design and culture of a rehabilitation unit influence stroke survivor activity: qualitative analysis of rehabilitation staff perceptions
Heidi Janssen, Marie-Louise Bird, Julie Luker, Ben Sellar, Angela Berndt, Samantha Ashby, Annie McCluskey, Louise Ada, Jannette Blennerhassett, Julie Bernhardt & Neil J. Spratt
This study aimed to investigate rehabilitation staff perceptions of factors influencing stroke survivor activity outside of dedicated therapy time for the purpose of supporting successful translation of activity promoting interventions in a rehabilitation unit. Purposive sampling of multi-disciplinary teams from four rehabilitation units was performed, and semi-structured interviews were conducted by telephone, digitally audio-recorded and then transcribed verbatim. A stepped iterative process of thematic analysis was employed until data saturation was reached. All but one...
Additional file 3 of Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
Jing Tian, Mingzhen Zhu, Zijing Ren, Qiang Zhao, Puqing Wang, Colin K. He, Min Zhang, Xiaochun Peng, Beilei Wu, Rujia Feng & Minglong Fu
Additional file 3: Table S1. Top 100 mRNAs or 100 methylation features of the whole TCGA dataset.
Additional file 3 of Deep learning algorithm reveals two prognostic subtypes in patients with gliomas
Jing Tian, Mingzhen Zhu, Zijing Ren, Qiang Zhao, Puqing Wang, Colin K. He, Min Zhang, Xiaochun Peng, Beilei Wu, Rujia Feng & Minglong Fu
Additional file 3: Table S1. Top 100 mRNAs or 100 methylation features of the whole TCGA dataset.
Affiliations
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University of Tasmania115
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Chinese Academy of Sciences55
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Central South University47
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Shanghai University of Traditional Chinese Medicine46
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Tianjin Medical University Cancer Institute and Hospital46
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Chinese Academy of Medical Sciences & Peking Union Medical College45
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Hubei University of Medicine44
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Shuguang Hospital44
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Johns Hopkins University42
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Shanghai Jiao Tong University42