bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of mixed methods to investigate case definitions to improve the identification of serious injury cases from hospital episode data
Authors: Cryer Colin , Davie Gabrielle , Gulliver Pauline , Samaranayaka Ari 
Published: July 2019

IntroductionIt has been commonplace internationally, when using hospital data, to use the principal diagnosis to identify injury cases and the first external cause of injury code (E-code) to identify the main cause. Our purpose was to investigate alternative operational definitions of serious non-fatal injury to identify cases of interest for injury surveillance, both overall and for four common causes of injury.MethodsSerious non-fatal injury cases were identified from New Zealand (NZ) hospital discharge data using an alternative definition: that is, case selection using principal and additional diagnoses. Separately, identification of cause used all E-codes on the discharge record. Numbers of cases identified were contrasted with those captured using the usual definition. Views of NZ government stakeholders were sought regarding the acceptability of the additional cases found using these alternative definitions. Views of international experts were also canvassed.ResultsWhen using all diagnoses there was a 7% increase in ‘all injury’ cases identified, a 17% increase in self-harm cases and 8% increase in falls cases. Use of all E-codes resulted in a 4% increase in self-harm cases, 2% increase in assault cases and 1% increase in both falls and motor vehicle traffic crash cases.DiscussionA case definition based solely on principal diagnosis fails to count a material number of serious non-fatal injury cases that are of interest to the injury prevention community. There is a need, therefore, to use an alternative case definition that includes additional diagnoses. Use of multiple E-codes to classify cause of injury should be considered.
Animal farming and the risk of lymphohaematopoietic cancers: a meta-analysis of three cohort studies within the AGRICOH consortium
Authors: El-Zaemey Sonia , Schinasi Leah H , Ferro Gilles , Tual Séverine , Lebailly Pierre , Baldi Isabelle , Nordby Karl-Christian , Kjærheim Kristina , Schüz Joachim , Monnereau Alain , Brouwer Maartje , Koutros Stella , Hofmann Jonathan , Kristensen Petter , Kromhout Hans , Leon Maria E , Beane Freeman Laura E 
Published: July 2019

ObjectiveAnimal farming entails a variety of potential exposures, including infectious agents, endotoxins and pesticides, which may play a role in the aetiology of lymphohaematopoietic cancers (LHCs). The aim of this study was to assess whether farming specific animal species is associated with the risk of overall LHC or its subtypes.MethodsData from three prospective cohort studies in the USA, France and Norway which are part of the Agricultural Cohort consortium and which collected information about animal farming and cancer were used. Analyses included 316 270 farmers and farm workers. Adjusted Cox models were used to investigate the associations of 13 histological subtypes of LHC (n=3282) with self-reported livestock (cattle, pigs and sheep/goats) and poultry (ever/never and numbers raised) farming. Cohort-specific HRs were combined using random-effects meta-analysis.ResultsEver animal farming in general or farming specific animal species was not meta-associated with overall LHC. The risk of myeloid malignancies decreased with increasing number of livestock (p trend=0.01). Increased risk of myeloproliferative neoplasms was seen with increasing number of sheep/goats (p trend <0.01), while a decreased risk was seen with increasing number of livestock (p trend=0.02). Between cohorts, we observed heterogeneity in the association of type of animal farmed and various LHC subtypes.ConclusionsThis large-scale study of three prospective agricultural cohorts showed no association between animal farming and LHC risk, but few associations between specific animal species and LHC subtypes were observed. The observed differences in associations by countries warrant further investigations.
Multidisciplinary home-based rehabilitation in inoperable lung cancer: a randomised controlled trial
Authors: Edbrooke Lara , Aranda Sanchia , Granger Catherine L , McDonald Christine F , Krishnasamy Mei , Mileshkin Linda , Clark Ross A , Gordon Ian , Irving Louis , Denehy Linda 
Published: July 2019

BackgroundLung cancer is associated with poor health-related quality of life (HRQoL) and high symptom burden. This trial aimed to assess the efficacy of home-based rehabilitation versus usual care in inoperable lung cancer.MethodsA parallel-group, assessor-blinded, allocation-concealed, randomised controlled trial. Eligible participants were allocated (1:1) to usual care (UC) plus 8 weeks of aerobic and resistance exercise with behaviour change strategies and symptom support (intervention group (IG)) or UC alone. Assessments occurred at baseline, 9 weeks and 6 months. The primary outcome, change in between-group 6 min walk distance (6MWD), was analysed using intention-to-treat (ITT). Subsequent analyses involved modified ITT (mITT) and included participants with at least one follow-up outcome measure. Secondary outcomes included HRQoL and symptoms.ResultsNinety-two participants were recruited. Characteristics of participants (UC=47, IG=45): mean (SD) age 64 (12) years; men 55%; disease stage n (%) III=35 (38) and IV=48 (52); radical treatment 46%. There were no significant between-group differences for the 6MWD (n=92) at 9 weeks (p=0.308) or 6 months (p=0.979). The mITT analyses of 6MWD between-group differences were again non-significant (mean difference (95% CI): 9 weeks: −25.4 m (−64.0 to 13.3), p=0.198 and 6 months: 41.3 m (−26.7 to 109.4), p=0.232). Significant 6-month differences, favouring the IG, were found for HRQoL (Functional Assessment of Cancer Therapy–Lung: 13.0 (3.9 to 22.1), p=0.005) and symptom severity (MD Anderson Symptom Inventory–Lung Cancer: −2.2 (−3.6 to –0.9), p=0.001).ConclusionsHome-based rehabilitation did not improve functional exercise capacity but there were improvements in patient-reported exploratory secondary outcomes measures observed at 6 months.Trial registrationAustralian New Zealand Clinical Trials Registry (ACTRN12614001268639).
Motion modeling of a non-holonomic wheeled mobile robot based on trajectory tracking control
Authors: Han Xuefeng , Ge Mingda , Cui Jicheng , Wang Hao , Zhuang Wei 
Published: July 2019

Trajectory tracking is a problem of emphasis for the mobile robot. In this study, a coordinate transformation method was used to build a kinematic model of the wheeled mobile robot. A traditional proportional-integral-derivative control method was researched and improved by combining it with a neural network. A neural network proportional-integral-derivative trajectory tracking control method was thus designed, and a simulation experiment was performed using Simulink. The results show that in circular trajectory tracking control, the maximum errors of the X axis, Y axis, and θ were approximately 2.1 m, 2.3 m, and 0.4 rad, respectively, and that the system remained stable after running for 10 s. In straight-line trajectory tracking control, the maximum errors of the X axis, Y axis, and θ were approximately −0.8 m, 1.3 m, and 0.3 rad, respectively, and the system remained stable after running for 8 s. The error was relatively small, and the effect of trajectory tracking control was good. The studied method had good performance in terms of wheeled mobile robot trajectory tracking control and is worthy of further promotion and application.
Differential Variation Analysis Enables Detection of Tumor Heterogeneity Using Single-Cell RNA-Sequencing Data
Authors: Davis-Marcisak Emily F. , Sherman Thomas D. , Orugunta Pranay , Stein-O'Brien Genevieve L. , Puram Sidharth V. , Roussos Torres Evanthia T. , Hopkins Alexander C. , Jaffee Elizabeth M. , Favorov Alexander V. , Afsari Bahman , Goff Loyal A. , Fertig Elana J. 
Published: July 2019

Abstract

Tumor heterogeneity provides a complex challenge to cancer treatment and is a critical component of therapeutic response, disease recurrence, and patient survival. Single-cell RNA-sequencing (scRNA-seq) technologies have revealed the prevalence of intratumor and intertumor heterogeneity. Computational techniques are essential to quantify the differences in variation of these profiles between distinct cell types, tumor subtypes, and patients to fully characterize intratumor and intertumor molecular heterogeneity. In this study, we adapted our algorithm for pathway dysregulation, Expression Variation Analysis (EVA), to perform multivariate statistical analyses of differential variation of expression in gene sets for scRNA-seq. EVA has high sensitivity and specificity to detect pathways with true differential heterogeneity in simulated data. EVA was applied to several public domain scRNA-seq tumor datasets to quantify the landscape of tumor heterogeneity in several key applications in cancer genomics such as immunogenicity, metastasis, and cancer subtypes. Immune pathway heterogeneity of hematopoietic cell populations in breast tumors corresponded to the amount of diversity present in the T-cell repertoire of each individual. Cells from head and neck squamous cell carcinoma (HNSCC) primary tumors had significantly more heterogeneity across pathways than cells from metastases, consistent with a model of clonal outgrowth. Moreover, there were dramatic differences in pathway dysregulation across HNSCC basal primary tumors. Within the basal primary tumors, there was increased immune dysregulation in individuals with a high proportion of fibroblasts present in the tumor microenvironment. These results demonstrate the broad utility of EVA to quantify intertumor and intratumor heterogeneity from scRNA-seq data without reliance on low-dimensional visualization.

Significance:
This study presents a robust statistical algorithm for evaluating gene expression heterogeneity within pathways or gene sets in single-cell RNA-seq data
Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk
Authors: Wu Lang , Shu Xiang , Bao Jiandong , Guo Xingyi , Kote-Jarai Zsofia , Haiman Christopher A. , Eeles Rosalind A. , Zheng Wei 
Published: July 2019

AbstractSeveral blood protein biomarkers have been associated with prostate cancer risk. However, most studies assessed only a small number of biomarkers and/or included a small sample size. To identify novel protein biomarkers of prostate cancer risk, we studied 79,194 cases and 61,112 controls of European ancestry, included in the PRACTICAL/ELLIPSE consortia, using genetic instruments of protein quantitative trait loci for 1,478 plasma proteins. A total of 31 proteins were associated with prostate cancer risk including proteins encoded by GSTP1, whose methylation level was shown previously to be associated with prostate cancer risk, and MSMB, SPINT2, IGF2R, and CTSS, which were previously implicated as potential target genes of prostate cancer risk variants identified in genome-wide association studies. A total of 18 proteins inversely correlated and 13 positively correlated with prostate cancer risk. For 28 of the identified proteins, gene somatic changes of short indels, splice site, nonsense, or missense mutations were detected in patients with prostate cancer in The Cancer Genome Atlas. Pathway enrichment analysis showed that relevant genes were significantly enriched in cancer-related pathways. In conclusion, this study identifies 31 candidates of protein biomarkers for prostate cancer risk and provides new insights into the biology and genetics of prostate tumorigenesis.Significance:Integration of genomics and proteomics data identifies biomarkers associated with prostate cancer risk.
Roles and Regulation of Long Noncoding RNAs in Hepatocellular Carcinoma
Authors: Lim Lee Jin , Wong Samuel Y.S. , Huang Feiyang , Lim Sheng , Chong Samuel S. , Ooi London Lucien , Kon Oi Lian , Lee Caroline G. 
Published: July 2019

Abstract
Next-generation sequencing has uncovered thousands of long noncoding RNAs (lncRNA). Many are reported to be aberrantly expressed in various cancers, including hepatocellular carcinoma (HCC), and play key roles in tumorigenesis. This review provides an in-depth discussion of the oncogenic mechanisms reported to be associated with deregulated HCC-associated lncRNAs. Transcriptional expression of lncRNAs in HCC is modulated through transcription factors, or epigenetically by aberrant histone acetylation or DNA methylation, and posttranscriptionally by lncRNA transcript stability modulated by miRNAs and RNA-binding proteins. Seventy-four deregulated lncRNAs have been identified in HCC, of which, 52 are upregulated. This review maps the oncogenic roles of these deregulated lncRNAs by integrating diverse datasets including clinicopathologic features, affected cancer phenotypes, associated miRNA and/or protein-interacting partners as well as modulated gene/protein expression. Notably, 63 deregulated lncRNAs are significantly associated with clinicopathologic features of HCC. Twenty-three deregulated lncRNAs associated with both tumor and metastatic clinical features were also tumorigenic and prometastatic in experimental models of HCC, and eight of these mapped to known cancer pathways. Fifty-two upregulated lncRNAs exhibit oncogenic properties and are associated with prominent hallmarks of cancer, whereas 22 downregulated lncRNAs have tumor-suppressive properties. Aberrantly expressed lncRNAs in HCC exert pleiotropic effects on miRNAs, mRNAs, and proteins. They affect multiple cancer phenotypes by altering miRNA and mRNA expression and stability, as well as through effects on protein expression, degradation, structure, or interactions with transcriptional regulators. Hence, these insights reveal novel lncRNAs as potential biomarkers and may enable the design of precision therapy for HCC.
IL6 Promotes a STAT3-PRL3 Feedforward Loop via SHP2 Repression in Multiple Myeloma
Authors: Chong Phyllis S.Y. , Zhou Jianbiao , Lim Julia S.L. , Hee Yan Ting , Chooi Jing-Yuan , Chung Tae-Hoon , Tan Zea Tuan , Zeng Qi , Waller Daniel D. , Sebag Michael , Chng Wee-Joo 
Published: July 2019

AbstractOverexpression of PRL-3, an oncogenic phosphatase, was identified as a novel cluster in patients with newly diagnosed multiple myeloma. However, the regulation and oncogenic activities of PRL-3 in multiple myeloma warrant further investigation. Here, we report that IL6 activates STAT3, which acts as a direct transcriptional regulator of PRL-3. Upregulation of PRL-3 increased myeloma cell viability and rephosphorylated STAT3 in a biphasic manner through direct interaction and deactivation of SHP2, thus blocking the gp130 (Y759)-mediated repression of STAT3 activity. Abrogation of PRL-3 reduced myeloma cell survival, clonogenicity, and tumorigenesis, and detailed mechanistic studies revealed “deactivation” of effector proteins such as Akt, Erk1/2, Src, STAT1, and STAT3. Furthermore, loss of PRL-3 efficiently abolished nuclear localization of STAT3 and reduced its occupancy on the promoter of target genes c-Myc and Mcl-1, and antiapoptotic genes Bcl2 and Bcl-xL. PRL-3 also played a role in the acquired resistance of myeloma cells to bortezomib, which could be overcome by PRL-3 silencing. Of clinical relevance, STAT3 and PRL-3 expression was positively correlated in five independent cohorts, and the STAT3 activation signature was significantly enriched in patients with high PRL-3 expression. Furthermore, PRL-3 could be used as a biomarker to identify high-risk patients with multiple myeloma that exhibited poor prognosis and inferior outcome even when treated with novel combinational therapeutics (proteasome inhibitors and immunomodulatory imide drugs). Conclusively, our results support a feedforward mechanism between STAT3 and PRL-3 that prolongs prosurvival signaling in multiple myeloma, and suggest targeting PRL-3 as a valid therapeutic opportunity in multiple myeloma.Significance:IL6 promotes STAT3-dependent transcriptional upregulation of PRL-3, which in turn re-phosphorylates STAT3 and aberrantly activates STAT3 target genes, leading to bortezomib resistance in multiple myeloma.
Value of Collaboration among Multi-Domain Experts in Analysis of High-Throughput Genomics Data
Authors: Meerzaman Daoud , Dunn Barbara K. 
Published: July 2019

Abstract
The recent explosion and ease of access to large-scale genomics data is intriguing. However, serious obstacles exist to the optimal management of the entire spectrum from data production in the laboratory through bioinformatic analysis to statistical evaluation and ultimately clinical interpretation. Beyond the multitude of technical issues, what stands out the most is the absence of adequate communication among the specialists in these domains. Successful interdisciplinary collaborations along the genomics pipeline extending from laboratory experiments to bioinformatic analyses to clinical application are notable in large scale, well managed projects such as The Cancer Genome Atlas. However, in certain settings in which the various experts perform their specialized research activities in isolation, the siloed approach to their research contributes to the generation of questionable genomic interpretations. Such situations are particularly concerning when the ultimate endpoint involves genetic/genomic interpretations that are intended for clinical applications. In spite of the fact that clinicians express interest in gaining a better understanding of clinical genomic applications, the lack of communication from upstream experts leaves them with a serious level of discomfort in applying such genomic knowledge to patient care. This discomfort is especially evident among healthcare providers who are not trained as geneticists, in particular primary care physicians. We offer some initiatives that have potential to address this problem, with emphasis on improved and ongoing communication among all the experts in these fields, constituting a comprehensive genomic “pipeline” from laboratory to patient.
Gene Editing of α6 Integrin Inhibits Muscle Invasive Networks and Increases Cell–Cell Biophysical Properties in Prostate Cancer
Authors: Rubenstein Cynthia S. , Gard Jaime M.C. , Wang Mengdie , McGrath Julie E. , Ingabire Nadia , Hinton James P. , Marr Kendra D. , Simpson Skyler J. , Nagle Raymond B. , Miranti Cindy K. , Warfel Noel A. , Garcia Joe G.N. , Arif-Tiwari Hina , Cress Anne E. 
Published: July 2019

Abstract

Human prostate cancer confined to the gland is indolent (low-risk), but tumors outside the capsule are aggressive (high-risk). Extracapsular extension requires invasion within and through a smooth muscle-structured environment. Because integrins respond to biomechanical cues, we used a gene editing approach to determine if a specific region of laminin-binding α6β1 integrin was required for smooth muscle invasion both in vitro and in vivo. Human tissue specimens showed prostate cancer invasion through smooth muscle and tumor coexpression of α6 integrin and E-cadherin in a cell–cell location and α6 integrin in a cell–extracellular matrix (ECM) distribution. Prostate cancer cells expressing α6 integrin (DU145 α6WT) produced a 3D invasive network on laminin-containing Matrigel and invaded into smooth muscle both in vitro and in vivo. In contrast, cells without α6 integrin (DU145 α6KO) and cells expressing an integrin mutant (DU145 α6AA) did not produce invasive networks, could not invade muscle both in vitro and in vivo, and surprisingly formed 3D cohesive clusters. Using electric cell–substrate impedance testing, cohesive clusters had up to a 30-fold increase in normalized resistance at 400 Hz (cell–cell impedance) as compared with the DU145 α6WT cells. In contrast, measurements at 40,000 Hz (cell–ECM coverage) showed that DU145 α6AA cells were two-fold decreased in normalized resistance and were defective in restoring resistance after a 1 μmol/L S1P challenge as compared with the DU145 α6WT cells. The results suggest that gene editing of a specific α6 integrin extracellular region, not required for normal tissue function, can generate a new biophysical cancer phenotype unable to invade the muscle, presenting a new therapeutic strategy for metastasis prevention in prostate cancer.

Significance:
This study shows an innovative strategy to block prostate cancer metastasis and invasion in the muscle through gene editing of a specific α6 integrin extracellular region.
Obesity and Risk for Second Malignant Neoplasms in Childhood Cancer Survivors: A Case–Control Study Utilizing the California Cancer Registry
Authors: Moke Diana J. , Hamilton Ann S. , Chehab Leena , Deapen Dennis , Freyer David R. 
Published: July 2019

Abstract

Background:
Obesity is a known modifiable risk factor associated with adverse outcomes in children with cancer. We sought to determine whether obesity during childhood cancer treatment increases risk for second malignant neoplasms (SMN).

Methods:
In this case–control study, cases (with SMN) and controls (with a single-primary cancer) were selected from the California Cancer Registry who had primary cancer diagnosed &lt;21 years treated at Children's Hospital Los Angeles between 1988 and 2014. Controls were matched 3:1 to cases at the registry level by clinical factors. Medical records were abstracted for cancer treatment exposures, cancer predisposition syndrome, body mass index (BMI), BMI Z-score, and BMI category at diagnosis and end of therapy (EOT).

Results:
A total of 59 cases and 130 controls were included. Median age at primary cancer diagnosis was 6 years, 64.5% were male, median time from primary cancer to SMN was 7.5 years, and 31.7% were obese or overweight. In matched multivariable analyses, there were elevated but nonsignificant associations between SMN and higher BMI Z-score at diagnosis [OR 1.27 (0.99–1.63)] and higher BMI categories at diagnosis [adjusted OR (aOR) overweight, 1.25 (0.55–2.52); aOR obese, 2.51 (1.00–6.29)]. There was a significantly increased risk for SMN among patients who were obese at both diagnosis and EOT [aOR, 4.44 (1.37–14.34)].

Conclusions:
This study suggests that obesity during childhood cancer treatment may be associated with increased risk for SMNs, particularly among those obese throughout therapy.

Impact:
Additional studies to confirm these findings and to develop interventions have the potential to impact SMN development in children with cancer.