Shared decision making for elderly advanced cancer patients
Ontology highlight
ABSTRACT:
DISEASE(S): Advanced Or Recurrent Gastric, Colorectal, And Esophagus Cancer
PROVIDER: 2656567 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
Similar Datasets
Project description:Interventions: using an online decision aid with benefit-harm assessment
Primary outcome(s): Decisional conflict
Study Design: Randomized controlled trial, Open (masking not used), Active, Parallel
| 2444150 | ecrin-mdr-crc
Project description:Interventions: Based on the manual, clinical psychologist, nurses, physicians, or hospital staff as the interventionist will: 1) Explain the Geriatric Assessment (GA) summary to the patient and then discuss the patient’s perception about GA impairments and need for recommended management; then prepare a feedback sheet based on information obtained from the patients, such as aging-related concerns and their interest in the recommendations, 2) Provide communication support using Question Prompt List (QPL), assist patients in organizing and communicating aging-related concerns and intentions for treatment and care to their oncologists; then prepare a feedback sheet including a list of selected questions, 3) Provide feedback on the results of 1) and 2) to their oncologist using a feedback sheet. Interventions will be conducted just prior to the first outpatient visit after randomization. Interventionists are clinical psychologists, nurses, physicians, or hospital staff who have completed training based on the manual in advance. For the 5 months after the initial intervention, interventionists will review and discuss implementation of GA-guided management monthly with the patients and their oncologists to implement management as needed. At 3 months after the initial GA+QPL, GA will be reassessed, and management will be revised if necessary, and feedback on GA+QPL will be provided to patients and oncologists in the same manner as that in the first intervention.
Usual care
Primary outcome(s): Number of conversations about aging-related concerns during consultation at the first outpatient visit after randomization
Study Design: Parallel Randomized
| 2661377 | ecrin-mdr-crc
Project description:Moso bamboo is well known with its rapid growth rate. In order to shed light on the underlying mechanism of growth, we applied Gibberellin (GA) to mimic the fast development process in bamboo and found that exogenous GA can significantly increase the length of internode of moso bamboo. Subsequently, we sequenced the transcriptome by high-through sequencing and identified 5,148 different expressed genes (DEG) and find out 22 genes that take part in GA signaling pathway is significantly differently expressed, including GID1A, GID1B and GAI. From GO analysis, a group of genes related to response hormone stimulus are enriched in up-regulated DEGs and 178 GA-responded genes are involved in other plant hormone signaling pathway, of which genes MYB74 and NCED5 are belong to both two pathways. Besides, clusters of genes about photosynthesis are enriched in down-regulated DEGs. By looking into the content of chlorophyll, we find out that the concentrations of chlorophyll are obviously decreased which verify that photosynthesis do weakened after GA treatment. Through method of slicing by hand, it appears that an increased condensation of lignin after GA treatment. The results imply a functional role of GA in bamboo growth, and maybe major in cell wall formation, and photosynthesis. Differential AS alternative splicing (AS) events upons GA induce suggested that post-transcriptional regulation is involved in the GA response.
2018-06-27 | GSE104596 | GEO
Project description:Background: Grape is highly sensitive to gibberellin (GA), which is crucial during seed and berry development (SBD) either by itself or by interacting with other hormones, such as auxin, Abscisic acid (ABA), and Cytokinin (CK). However, no systematic analysis of GA metabolic and signal transduction (MST) pathway has been undertaken in grapevine. Results: In this study, total endogenous GA3 content significantly decreased during SBD, and a total of 48 known genes in GA metabolic (GAM; 31) and signal transduction (ST; 17) pathways were identified in this process. In the GAM pathway, out of 31 genes, VvGA20ox1-1, VvGA3ox4-1, and VvGA2ox1-1 may be the major factors interacting at the green-berry stage (GBS) accompanied with higher accumulation rate. GA biosynthesis was greater than GA inactivation at GBS, confirming the importance of seeds in GA synthesis. The visible correlation between endogenous GA3 content and gene expression profiles suggested that the transcriptional regulation of GA biosynthesis pathway genes was a key mechanism of GA accumulation at the stone-hardening stage (SHS). Interestingly, we observed a negative feedback regulation between VvGA3oxs-VvGAI1-4, VvGA2oxs-VvGAI1-4, and VvGID1B-VvGAI1-4 in maintaining the balance of GA3 content in berries. Moreover, 11 miRNAs may be involved in the modulation of GA MST pathway by mediating their target genes, such as VvGA3ox, VvGID1B, and VvGAMYB. Many genes in auxin, ABA, and CK MST pathways were further identified and found to have a special pattern in the berry, and the crosstalk between GA and these hormones may modulate the complex process during SBD through the interaction gene network of the multihormone pathway. Lastly, based on the expression characterization of multihormone MST pathway genes, a proposed model of the GA-mediated multihormone regulatory network during SBD was proposed. Conclusions: Our results provided novel insights into GA-mediated regulatory networks during SBD in grape. The complexity of GA-mediated multihormone ST in SBD was also elucidated, thereby providing valuable information for future functional characterizations of specific genes in grape.
2020-07-20 | GSE153169 | GEO
Project description:Many years after the discovery of GID1 as the GA receptor, the belief in the existence of GA-binding protein (GBP) in aleurone cells still persists. Actually, some recent reviews and textbooks still contain information about the possibility of an alternative GA perception mechanism mediated by GBPs. Thus, to finally clarify this issue, we examined the expression of GA-regulated genes using rice embryoless half-seeds of four kinds of GA signaling mutants, each one independently carrying mutated GID1, DELLA, and GA-related F-box, which are all encoded by single genes in rice, allowing for convenient study of the GA perception system. The comprehensive microarray analysis using these rice mutants revealed that all genes tested to be responsive to GA in the wild-type (WT) aleurone cells consistently did not respond to GA in the gid1 or slr1 mutant. All microarray experiments were performed according to the manufacturerM-bM-^@M-^Ys manual. The Feature Extraction software (Agilent Technologies) was used to delineate and measure the Cy3 and Cy5 signal intensities of each spot in the array. The resulting data were normalized using the Variance-stabilizing normalization (VSN) algorithm.
2014-12-19 | E-GEOD-64290 | biostudies-arrayexpress
Project description:Fruit set is the process whereby ovaries develop into fruits after pollination and fertilization. The process is induced by the phytohormone gibberellin (GA) in tomatoes, as determined by the constitutive GA response mutant procera However, the role of GA on the metabolic behavior in fruit-setting ovaries remains largely unknown. This study explored the biochemical mechanisms of fruit set using a network analysis of integrated transcriptome, proteome, metabolome, and enzyme activity data. Our results revealed that fruit set involves the activation of central carbon metabolism, with increased hexoses, hexose phosphates, and downstream metabolites, including intermediates and derivatives of glycolysis, the tricarboxylic acid cycle, and associated organic and amino acids. The network analysis also identified the transcriptional hub gene SlHB15A, that coordinated metabolic activation. Furthermore, a kinetic model of sucrose metabolism predicted that the sucrose cycle had high activity levels in unpollinated ovaries, whereas it was shut down when sugars rapidly accumulated in vacuoles in fruit-setting ovaries, in a time-dependent manner via tonoplastic sugar carriers. Moreover, fruit set at least partly required the activity of fructokinase, which may pull fructose out of the vacuole, and this could feed the downstream pathways. Collectively, our results indicate that GA cascades enhance sink capacities, by up-regulating central metabolic enzyme capacities at both transcriptional and posttranscriptional levels. This leads to increased sucrose uptake and carbon fluxes for the production of the constituents of biomass and energy that are essential for rapid ovary growth during the initiation of fruit set.
2020-09-11 | MTBLS1892 | MetaboLights
Project description:Kin selection may act differently on genes inherited from the two parents (matrigenes and patrigenes), resulting in intragenomic conflict. This conflict can be observed as differential expression of matrigenes and patrigenes, or parent specific gene expression (PSGE). In honey bees (Apis mellifera), intragenomic conflict is hypothesized to occur in multiple social contexts. Previously, we found patrigene expression in reproductive tissues was associated with increased reproductive potential in worker honey bees, consistent with the prediction that patrigenes are selected to promote selfish behavior in this context. Here, we examined brain expression patterns to determine if PSGE is also found in other tissues. As before, the number of transcripts showing patrigene expression bias was significantly greater in the brains of reproductive versus sterile workers, while the number of matrigene-biased transcripts was not significantly different. Twelve transcripts out of the 374 showing PSGE in either tissue showed PSGE in both brain and reproductive tissues; this overlap was significantly greater than expected by chance. However, the majority of transcripts showed PSGE only in one tissue, suggesting the epigenetic mechanisms mediating PSGE show plasticity between tissues. There was no significant overlap between transcripts that showed PSGE and transcripts that were significantly differentially expressed. Weighted gene correlation network analysis identified modules which were significantly enriched in both types of transcripts, suggesting that these genes may influence each other through gene networks. Our results provide further support for the kin selection theory of intragenomic conflict, and provide valuable insights into the mechanisms which may mediate this process.
2021-01-04 | GSE155984 | GEO
Project description:Glatiramer acetate (GA; Copaxone), is a complex mixture of synthetic polypeptides approved for treatment of multiple sclerosis (MS). GA is an altered peptide ligand (APL) of myelin basic protein (MBP), an encephalitic autoantigen implicated in MS. GA induces GA-reactive T cells, which upregulate expression of anti-inflammatory and neurotrophic substances in the CNS. The antigenic sequences in glatiramoids cannot be completely characterized; nevertheless, differences among them can cause toxicity. We conducted microarray analyses to determine whether gene expression by GA-reactive lymphocytes from mouse spleens could differentiate GA from other glatiramoids. Expression of 135 genes was unique to cells reactivated by GA vs by intentionally altered GA and other glatiramoids. Significantly (p<0.01) altered expression of 207 genes was observed by cells reactivated by GA vs purported generic GA. Some APLs of MBP have caused serious adverse effects in MS patients. The influence of altered gene expression on glatiramoid safety warrants further investigation. Glatiramoid samples for SPL cell activation were grouped into four categories: 1) Verified GA, which included GA-RS (22 samples) and GA drug product (GA-DP, 34 samples from 30 batches) manufactured by Teva; 2) Deliberately Modified GA (DM-GA; 9 samples), which included glatiramoids made by Teva that were similar to GA but modified in a variety of ways: prepared with different ingredients (e.g., missing a constituent amino acid); prepared with the same amino acids in the same molar ratio as GA, but with defined amino acid sequences and different molecular weights (referred to as peptide markers TV-35 and TV-66); synthesized by a different process (e.g., changing acetolytic cleavage conditions, alternating polymerization initiator); exposed to destabilizing conditions (e.g., degradation by acid, base, and heat); 3) Unverified Glatiramoids, which included 4 samples, TV-5010 and 3 glatiramoids synthesized to be similar to GA but not manufactured using the Teva-patented manufacturing process; and 4) Unverified Generic GA, which included samples from 2 glatiramoids (M-bM-^@M-^\GA-NM-bM-^@M-^] 11 samples from 5 different batches, and 2 M-bM-^@M-^\GA-CM-bM-^@M-^] samples from a single batch) marketed as generic GA manufactured by companies other than Teva .
2013-08-01 | E-GEOD-40566 | biostudies-arrayexpress
Project description:Small intestinal group 3 innate lymphoid cells (ILC3) from ILC3-conditional BMAL1 knock out mice or littermate control mice were sort-purified for transcriptional analysis
2019-08-28 | GSE135359 | GEO
Project description:Interventions: The study aims to compare the efficacy of an educational pamphlet currently used in the clinical setting to that of the decision aids using two randomised controlled trials. The decision aids will be tested with two different samples: 120 individuals at high risk for HNPCC and 120 members of high-risk breast cancer families who approach one of six familial cancer clinics who have agreed to participate in this study (the familial cancer clinics in NSW: at Prince of Wales, Westmead, St Vincents Hospitals and Hunter Genetics, Newcastle, and in Victoria: at Royal Melbourne Hospital, and the Peter McCallum Cancer Institute). Participants will complete a questionnaire after they have read the decision aid or pamphlet, followed by a second questionnaire after 6 months.
Primary outcome(s): The primary outcome for the study is decisional conflict (measured by the Decisional Conflict Scale). This scale measures uncertainty about choosing among alternatives; modifiable factors contributing to uncertainty, such as being uninformed and unclear about values and feeling unsupported in decision-making, and perceptions of effectiveness of decision-making[Assessed immediately after reading the information materials provided, and in the 6-month follow up questionnaire.]
Study Design: Purpose: Educational / counselling / training; Allocation: Randomised controlled trial; Masking: Blinded (masking used);Assignment: Parallel;Type of endpoint: Efficacy
| 2452387 | ecrin-mdr-crc