cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5311120
title: Supplementary Material for: Antibiotic Susceptibility and Molecular Characterization of Escherichia coli O157 Isolates from Urinary Tract Infections

description: <b><i>Background:</i></b><i>Escherichia coli O157</i> is an important food-borne pathogen that can cause diarrhoea, hemorrhagic colitis, and hemolytic uraemic syndrome. Enterobacterial repetitive intergenic consensus sequence PCR (ERIC-PCR) and multilocus sequence typing (MLST) are good methods for molecular typing and the extensive use of antibiotics is a contributing factor to the increasing incidence of antimicrobial-resistant for these strains. <b><i>Objectives:</i></b> The aim of this study was to determine the prevalence, antimicrobial resistance, and genetic diversity of <i>E. coli O157</i> based on the prevalence of urinary tract infection (UTI) in Hubei, China. <b><i>Results:</i></b> We obtained 23 (8.07%) <i>E. coli O157</i> isolates from 285 UTI patients in Hubei, China. All isolates were subjected to antibiotic susceptibility analysis, and molecular typing was performed using ERIC-PCR and MLST. Antimicrobial susceptibility results indicated that most strains were resistant to penicillin (95.65%), chloramphenicol (73.91%), and ampicillin (69.57%). All isolates were discovered to be multiresistant (resistance to more than 3 antibiotics). Genetic variability analysis showed that all of the isolates were grouped into 4 clusters both by ERIC-PCR and MLST. <b><i>Conclusion:</i></b> Our findings demonstrated the presence of <i>E. coli O157</i> in UTIs, provided insights into the dissemination of antibiotic-resistant strains, and improved our knowledge of <i>E. coli O157</i> risk assessment in UTIs.
DOI: 10.6084/m9.figshare.5311117.v1
title: Dataset for: PROGNOSTIC AND FUNCTIONAL ROLE OF SUBTYPE-SPECIFIC TUMOR-STROMA INTERACTION IN BREAST CANCER

description: None of the clinically relevant gene expression signatures available for breast cancer were specifically developed to capture the influence of the microenvironment on tumor cells. Here, we attempted to build subtype-specific signatures derived from an in vitro model reproducing tumor cell modifications after interaction with activated or normal stromal cells. Gene expression signatures derived from HER2+, luminal and basal breast cancer cell lines (treated by normal fibroblasts or cancer-associated fibroblasts conditioned media) were evaluated in clinical tumors by in silico analysis on published gene expression profiles (GEPs). Patients were classified as microenvironment-positive (µENV+ve), i.e with tumors showing molecular profiles suggesting activation by the stroma, or negative (µENV-ve) based on correlation of their tumors’ GEP with the respective subtype-specific signature. Patients with estrogen receptor alpha (ER)+/HER2-/µENV+ve tumors were characterized by 2.5-fold higher risk of developing distant metastases (HR= 2.546; 95% Cl: 1.751-3.701, P=9.84E-07), while µENV status did not affect, or only suggested the risk of distant metastases, in women with HER2+ (HR=1.541; 95% Cl: 0.788-3.012, P=0.206) or ER-/HER2- tumors (HR=1.894; 95% Cl: 0.938-3.824; P=0.0747), respectively. In ER+/HER2- tumors, the µENV status remained significantly associated with metastatic progression (HR=2.098; CI: 1.214-3.624; P=0.00791) in multivariable analysis including size, age and genomic grade index. Validity of our in vitro model was also supported by in vitro biological endpoints such as cell growth (MTT-assay) and migration/invasion (Transwell-assay). In vitro-derived gene signatures tracing the bidirectional interaction with cancer activated fibroblasts is subtype-specific and adds independent prognostic information to classical prognostic variables in women with ER+/HER2- tumors.
DOI: 10.6084/m9.figshare.5311123.v1
title: Dataset for: Military training elicits marked increases in plasma metabolomic signatures of energy metabolism, lipolysis, fatty acid oxidation, and ketogenesis

description: Military training studies provide unique insight into metabolic responses to extreme physiologic stress induced by multiple-stressor environments, and the impacts of nutrition in mediating these responses. Advances in metabolomics have provided new approaches for extending current understanding of factors modulating dynamic metabolic responses in these environments. In this study whole-body metabolic responses to strenuous military training were explored in relation to energy balance and macronutrient intake by performing non-targeted global metabolite profiling on plasma collected from 25 male Soldiers before and after completing 4-d, 51-km cross-country ski march that produced high total daily energy expenditures [25.4 MJ/d (SD 2.3)] and severe energy deficits [13.6 MJ/d (SD 2.5)]. Of 737 identified metabolites, 478 changed during the training. Increases in 88% of the free fatty acids and 91% of the acylcarnitines, and decreases in 88% of the mono- and di-acylglycerols detected within lipid metabolism pathways were observed. Smaller increases in 75% of the tricarboxylic acid cycle intermediates, and 50% of the branched-chain amino acid metabolites detected were also observed. Changes in multiple metabolites related to lipid metabolism were correlated with body mass loss and energy balance, but not with energy and macronutrient intakes or energy expenditure. These findings are consistent with an increase in energy metabolism, lipolysis, fatty acid oxidation, ketogenesis, and branched-chain amino acid catabolism during strenuous military training. The magnitude of the energy deficit induced by undereating relative to high energy expenditure appears to drive these changes, particularly within lipid metabolism pathways.
DOI: 10.6084/m9.figshare.5311114
title: Dataset for: Bioinformatory-assisted analysis of next-generation sequencing data for precision medicine in pancreatic cancer

description: Pancreatic ductal adenocarcinoma (PDAC) is a tumor with an extremely poor prognosis, predominantly due to chemotherapy resistance and numerous somatic mutations. Consequently, PDAC is a prime candidate for the use of sequencing to identify causative mutations, facilitating subsequent administration of targeted therapy. In a feasibility study, we retrospectively assessed the therapeutic recommendations of a novel, evidence-based software that analyzes Next-generation sequencing (NGS) data using a large panel of pharmacogenomic biomarkers for efficacy and toxicity. Tissue from 14 patients with PDAC was sequenced using NGS with a 620 gene panel. FASTQ files were fed into the TreatmentMAP software. The results were compared with chemotherapy in the patients, including all side effects. No changes in therapy were made. Known driver mutations for PDAC were confirmed, e.g. KRAS, TP53. Software analysis revealed positive biomarkers for predicted effective and ineffective treatments in all patients. At least one biomarker associated with increased toxicity could be detected in all patients. Patients had been receiving one of the currently approved chemotherapy agents. In two patients, toxicity could have been correctly predicted by the software analysis. Results suggest NGS, in combination with an evidence-based software, could be conducted within a two-week period - thus being feasible for clinical routine. Therapy recommendations were principally off-label use. Based on the predominant KRAS mutations, other drugs were predicted to be ineffective. The pharmacogenomic biomarkers indicative of increased toxicity could be retrospectively linked to reported negative side effects in the respective patients. Finally, the occurrence of somatic and germline mutations in cancer syndrome-associated genes is noteworthy, despite a high frequency of these particular variants in the background population. These results suggest software-analysis of NGS data provides evidence-based information on effective, ineffective, and toxic drugs, potentially forming the basis for precision cancer medicine in PDAC.
DOI: 10.6084/m9.figshare.5311141.v1
title: Skin Autofluorescence Datasets

description: Skin Autofuorescence (SAF) measurements of a healthy population (n=2,780) and of individuals with Cardiovascular Disease (CVD, n=50), Diabetes (DM, n=111) and mixed disease phenotypes (n=74).
DOI: 10.6084/m9.figshare.5311108
title: Dataset for: Evaluation of metastatic potential of malignant cells by image processing of digital holographic microscopy data

description: Cell refractive index (RI) was proposed as a putative cancer biomarker of great potential, being correlated with cell content and morphology, cell division rate and membrane permeability. We used Digital Holographic Microscopy (DHM) to compare RI and dry mass density of two B16 murine melanoma sublines of different metastatic potential. Using statistical methods, the phase shifts distribution within the reconstructed quantitative phase images (QPIs) was analyzed by the method of bimodality coefficients. The observed correlation of RI and bimodality profile with the cells metastatic potential was validated by real time impedance based-assay and clonogenic tests. We suggest RI and QPIs histograms bimodality analysis to be developed as optical biomarkers useful in label-free detection and quantitative evaluation of cell metastatic potential.
DOI: 10.6084/m9.figshare.5311111
title: Dataset for: Acyl-CoA Binding Domain-Containing Protein 3 Functions as a Scaffold to Organize the Golgi Stacking Proteins and a Rab33b-GAP

description: Golgin45 plays important roles in Golgi stack assembly and is known to bind both the Golgi stacking protein GRASP55 and Rab2 in the medial-Golgi cisternae. In this study, we sought to further characterize the cisternal adhesion complex using a proteomics approach. We report here that Acyl-CoA Binding Domain Containing 3 (ACBD3) is likely to be a novel binding partner of Golgin45. ACBD3 interacts with Golgin45 via its GOLD domain, and its co-expression significantly increases Golgin45 targeting to the Golgi. Further, ACBD3 recruits TBC1D22, a Rab33b GTPase Activating Protein (GAP), to a large multi-protein complex, containing Golgin45 and GRASP55. These results suggest that ACBD3 may provide a scaffolding to organize the Golgi stacking proteins and a Rab33b-GAP at the medial-Golgi.
DOI: 10.6084/m9.figshare.5311114.v1
title: Dataset for: Bioinformatory-assisted analysis of next-generation sequencing data for precision medicine in pancreatic cancer

description: Pancreatic ductal adenocarcinoma (PDAC) is a tumor with an extremely poor prognosis, predominantly due to chemotherapy resistance and numerous somatic mutations. Consequently, PDAC is a prime candidate for the use of sequencing to identify causative mutations, facilitating subsequent administration of targeted therapy. In a feasibility study, we retrospectively assessed the therapeutic recommendations of a novel, evidence-based software that analyzes Next-generation sequencing (NGS) data using a large panel of pharmacogenomic biomarkers for efficacy and toxicity. Tissue from 14 patients with PDAC was sequenced using NGS with a 620 gene panel. FASTQ files were fed into the TreatmentMAP software. The results were compared with chemotherapy in the patients, including all side effects. No changes in therapy were made. Known driver mutations for PDAC were confirmed, e.g. KRAS, TP53. Software analysis revealed positive biomarkers for predicted effective and ineffective treatments in all patients. At least one biomarker associated with increased toxicity could be detected in all patients. Patients had been receiving one of the currently approved chemotherapy agents. In two patients, toxicity could have been correctly predicted by the software analysis. Results suggest NGS, in combination with an evidence-based software, could be conducted within a two-week period - thus being feasible for clinical routine. Therapy recommendations were principally off-label use. Based on the predominant KRAS mutations, other drugs were predicted to be ineffective. The pharmacogenomic biomarkers indicative of increased toxicity could be retrospectively linked to reported negative side effects in the respective patients. Finally, the occurrence of somatic and germline mutations in cancer syndrome-associated genes is noteworthy, despite a high frequency of these particular variants in the background population. These results suggest software-analysis of NGS data provides evidence-based information on effective, ineffective, and toxic drugs, potentially forming the basis for precision cancer medicine in PDAC.
DOI: 10.6084/m9.figshare.5311111.v1
title: Dataset for: Acyl-CoA Binding Domain-Containing Protein 3 Functions as a Scaffold to Organize the Golgi Stacking Proteins and a Rab33b-GAP

description: Golgin45 plays important roles in Golgi stack assembly and is known to bind both the Golgi stacking protein GRASP55 and Rab2 in the medial-Golgi cisternae. In this study, we sought to further characterize the cisternal adhesion complex using a proteomics approach. We report here that Acyl-CoA Binding Domain Containing 3 (ACBD3) is likely to be a novel binding partner of Golgin45. ACBD3 interacts with Golgin45 via its GOLD domain, and its co-expression significantly increases Golgin45 targeting to the Golgi. Further, ACBD3 recruits TBC1D22, a Rab33b GTPase Activating Protein (GAP), to a large multi-protein complex, containing Golgin45 and GRASP55. These results suggest that ACBD3 may provide a scaffolding to organize the Golgi stacking proteins and a Rab33b-GAP at the medial-Golgi.
DOI: 10.6084/m9.figshare.5311102
title: Dataset for: The Effect of Fear of Falling on Vestibular Feedback Control of Balance

description: Vestibular sensation contributes to cervical-head stabilisation and fall prevention. To what extent fear of falling influences the associated vestibular feedback processes is currently undetermined. We used galvanic vestibular stimulation (GVS) to induce vestibular reflexes while participants stood at ground level and on a narrow walkway at 3.85 m height to induce fear of falling. Fear was confirmed by questionnaires and elevated skin conductance. Full-body kinematics was measured to differentiate the whole-body centre of mass response (CoM) into component parts (cervical, axial trunk, appendicular short-latency and medium-latency). We studied the effect of fear of falling on each component to discern their underlying mechanisms. Statistical parametric mapping analysis provided sensitive discrimination of early GVS and height effects. Kinematic analysis revealed responses at 1 mA stimulation previously believed marginal through EMG and force plate analysis. The GVS response comprised a rapid, anode-directed cervical-head acceleration, a short-latency cathode-directed acceleration (cathodal-buckling) of lower extremities and pelvis, an anode-directed upper thorax acceleration and subsequently a medium-latency anode-directed acceleration of all body parts. At height, head and upper thorax early acceleration were unaltered, however short-latency lower extremity acceleration was increased. The effect of height on balance was a decreased duration and increased rate of change of the CoM acceleration pattern. These results demonstrate that fear modifies vestibular control of balance, whereas cervical-head stabilisation is governed by different mechanisms unaffected by fear of falling. The mechanical pattern of cathodal-buckling, and its modulation by fear of falling both support the hypothesis that short-latency responses contribute to regulate balance.
DOI: 10.6084/m9.figshare.5311105
title: Dataset for: Recurrence-associated gene signature optimizes recurrence free survival prediction of colorectal cancer

description: High throughput gene expression profiling has showed great promise in providing insight into molecular mechanisms. Metastasis-related mRNAs may potentially enrich genes with the ability to predict cancer recurrence，therefore we attempted to build a recurrence-associated gene signature to improve prognostic prediction of colorectal cancer (CRC). We identified 2848 differentially expressed mRNAs by analyzing CRC tissues with or without metastasis. For the selection of prognostic genes, a LASSO Cox regression model was employed. Using this method, a 13-mRNA signature was identified and then validated in two independent Gene Expression Omnibus (GEO) cohorts. This classifier could successfully discriminate the high-risk patients in discovery cohort (HR = 5.27, 95%CI= 2.30-12.08, P &lt; 0.0001). Analysis in two independent cohorts yielded consistent results (GSE14333: HR=4.55, 95%CI=2.18 – 9.508, P&lt;0.0001) (GSE33113: HR=3.26, 95%CI=2.16 – 9.16, P=0.0176). Further analysis revealed that the prognostic value of this signature was independent of tumor stage, postoperative chemotherapy and somatic mutation. Receiver operating characteristic (ROC) analysis showed that the area under receiver operating characteristic curve (AUC) of this signature was 0.8861 and 0.8157 in the discovery and validation cohort, respectively. A nomogram was constructed for clinicians, which did well in the calibration plots. Furthermore, this 13-mRNA signature outperformed other known gene signatures, including oncotypeDX colon cancer assay. Single-sample gene-set enrichment analysis (ssGSEA) revealed that a group of pathways related to drug resistance, cancer metastasis and stemness were significantly enriched in the high-risk patients. In conclusion, this 13-mRNA signature may be a useful tool for prognostic evaluation and will facilitate personalized management of CRC patients.
DOI: 10.6084/m9.figshare.5311108.v1
title: Dataset for: Evaluation of metastatic potential of malignant cells by image processing of digital holographic microscopy data

description: Cell refractive index (RI) was proposed as a putative cancer biomarker of great potential, being correlated with cell content and morphology, cell division rate and membrane permeability. We used Digital Holographic Microscopy (DHM) to compare RI and dry mass density of two B16 murine melanoma sublines of different metastatic potential. Using statistical methods, the phase shifts distribution within the reconstructed quantitative phase images (QPIs) was analyzed by the method of bimodality coefficients. The observed correlation of RI and bimodality profile with the cells metastatic potential was validated by real time impedance based-assay and clonogenic tests. We suggest RI and QPIs histograms bimodality analysis to be developed as optical biomarkers useful in label-free detection and quantitative evaluation of cell metastatic potential.
DOI: 10.6084/m9.figshare.5311093
title: Dataset for: Phagocytosis and Inflammation: Exploring the effects of the components of E-cigarette vapour on macrophages.

description: E-cigarettes are perceived as harmless; however, evidence of their safety is lacking. New data suggests E-cigarettes discharge a range of compounds capable of physiological damage to users. We previously established that cigarette smoke caused defective alveolar macrophage phagocytosis. The present study compared the effect E-cigarette of components; E-liquid flavours, nicotine, vegetable glycerine, and propylene glycol on phagocytosis, pro-inflammatory cytokine secretion, and phagocytic recognition molecule expression using differentiated THP-1 macrophages. Similar to CSE, phagocytosis of NTHi bacteria was significantly decreased by E-liquid flavouring (11.65-15.75%) vs. control (27.01%). Nicotine also decreased phagocytosis (15.26%). E-liquid, nicotine, and E-liquid + nicotine reduced phagocytic recognition molecules; SR-A1 and TLR-2. IL-8 secretion increased with flavour and nicotine, while TNFα, IL-1β, IL-6, MIP-1α, MIP-1β, and MCP-1 decreased after exposure to most flavours and nicotine. PG, VG, or PG:VG mix also induced a decrease in MIP-1α and MIP-1β. We conclude that E-cigarettes can cause macrophage phagocytic dysfunction, expression of phagocytic recognition receptors and cytokine secretion pathways. As such, E-cigarettes should be treated with caution by users, especially those who are non-smokers.
DOI: 10.6084/m9.figshare.5311096
title: Dataset for: Male apoE*3-Leiden.CETP – mice on high-fat high-cholesterol diet exhibit a biphasic dyslipidemic response, mimicking the changes in plasma lipids observed through life in men.

description: The physiological adaptations resulting in the development of the metabolic syndrome in man occur over a time span of several decades. This combined with the prohibitive financial cost and ethical concerns to measure key metabolic parameters repeatedly in subjects for the major part of their life span, makes that comprehensive longitudinal human data sets are virtually non-existent. While experimental mice are often used, little is known whether this species is in fact an adequate model to better understand the mechanisms that drive the metabolic syndrome in man. We took up the challenge to study the response of male apoE*3-Leiden.CETP mice (with a humanized lipid profile) to a high-fat high-cholesterol diet for six months. Study parameters include body weight, food intake, plasma and liver lipids, hepatic transcriptome, VLDL – triglyceride production and importantly the use of stable isotopes to measure hepatic de novo lipogenesis, gluconeogenesis, and biliary/fecal sterol secretion to assess metabolic fluxes. The key observations include 1) high inter-individual variation, 2) a largely unaffected hepatic transcriptome at 2, 3 and 6 months, 3) a biphasic response curve of the main metabolic features over time, and 4) maximum insulin resistance preceding dyslipidemia. The biphasic response in plasma triglyceride and total cholesterol appears to mimic that of men in cross-sectional studies. Combined, these observations suggest that studies such as these can help to delineate the causes of metabolic derangements in patients suffering from metabolic syndrome.
DOI: 10.6084/m9.figshare.5311102.v1
title: Dataset for: The Effect of Fear of Falling on Vestibular Feedback Control of Balance

description: Vestibular sensation contributes to cervical-head stabilisation and fall prevention. To what extent fear of falling influences the associated vestibular feedback processes is currently undetermined. We used galvanic vestibular stimulation (GVS) to induce vestibular reflexes while participants stood at ground level and on a narrow walkway at 3.85 m height to induce fear of falling. Fear was confirmed by questionnaires and elevated skin conductance. Full-body kinematics was measured to differentiate the whole-body centre of mass response (CoM) into component parts (cervical, axial trunk, appendicular short-latency and medium-latency). We studied the effect of fear of falling on each component to discern their underlying mechanisms. Statistical parametric mapping analysis provided sensitive discrimination of early GVS and height effects. Kinematic analysis revealed responses at 1 mA stimulation previously believed marginal through EMG and force plate analysis. The GVS response comprised a rapid, anode-directed cervical-head acceleration, a short-latency cathode-directed acceleration (cathodal-buckling) of lower extremities and pelvis, an anode-directed upper thorax acceleration and subsequently a medium-latency anode-directed acceleration of all body parts. At height, head and upper thorax early acceleration were unaltered, however short-latency lower extremity acceleration was increased. The effect of height on balance was a decreased duration and increased rate of change of the CoM acceleration pattern. These results demonstrate that fear modifies vestibular control of balance, whereas cervical-head stabilisation is governed by different mechanisms unaffected by fear of falling. The mechanical pattern of cathodal-buckling, and its modulation by fear of falling both support the hypothesis that short-latency responses contribute to regulate balance.