HomeNL: Homecare Assistance in Natural Language. An Intelligent Conversational Agent for Hypertensive Patients Management.

International audienceThe prospective home-care management will probably of- fer intelligent conversational assistants for supporting patients at home through natural language interfaces. Homecare assistance in natural lan- guage, HomeNL, is a proof-of-concept dialogue system for the manage- ment of patients with hypertension. It follows up a conversation with a patient in which the patient is able to take the initiative. HomeNL pro- cesses natural language, makes an internal representation of the patients' contributions, interprets sentences by reasoning about their meaning on the basis of a medical-knowledge representation and responds appropri- ately. HomeNL's aim is to provide a laboratory for studying natural language processing (NLP) and intelligent dialogues in clinical domains

The Burden of Structured Self-Monitoring of Blood Glucose on Diabetes-Specific Quality of Life and Locus of Control in Patients with Noninsulin-Treated Type 2 Diabetes: The PRISMA Study

Background: To evaluate whether structured self-monitoring of blood glucose (SMBG) is associated with changes in diabetes-specific quality of life (DSQoL) and locus of control (LOC) in patients with noninsulin-treated type 2 diabetes (T2DM). Study Design and Methods: In this analysis of the PRISMA (Prospective Randomized Trial on Intensive SMBG Management Added Value in Noninsulin-Treated T2DM Patients) Study psychosocial data, we evaluated the impact of 12 months of structured SMBG on the individual domains of DSQoL and LOC questionnaires, including the role of selected confounders. Results: The score for Satisfaction, Impact, and Worry domains (DSQoL) improved when compared with baseline, without significant differences between structured SMBG regimen (intervention group, n = 501) and active control group (n = 523). Scores for Internal, Chance, and Powerful Others domains (LOC) improved compared with baseline, with a significant between-group change in Chance (P = 0.0309). For DSQoL domain score, improvements were associated with higher number of SMBG measurements (P = 0.007), older age (P = 0.013), and male sex (P = 0.0133) for Satisfaction and with male sex (P < 0.0001) for Worry. Concerning LOC domain score, improvements were associated with longer diabetes duration (P = 0.0084) and younger age (P < 0.0001) for Chance and total number of SMBG measurements (P = 0.0036) for Internal, with the intervention group close to being significant (P = 0.06). Conclusions: Our analysis demonstrates that in patients with noninsulin-treated T2DM, structured SMBG is not associated with a deterioration of quality of life and LOC, which is strongly predicted by demographics and diabetes-related variables. These findings should be considered when tailoring educational support to SMBG for these patients

Report from the CVOT Summit 2020: new cardiovascular and renal outcomes

The 6th Cardiovascular Outcome Trial (CVOT) Summit “Cardiovascular and Renal Outcomes 2020” was the first to be held virtually on October 29–30, 2020. As in previous years, this summit served as reference meeting for in-depth discussions on the topic of recently completed and presented major outcome trials. This year, focus was placed on the outcomes of VERTIS-CV, EMPEROR-Reduced, DAPA-CKD, and FIDELIO-DKD. Trial implications for diabetes management and the impact on new treatment algorithms were highlighted for diabetologists, cardiologists, endocrinologists, nephrologists, and general practitioners. Discussion evolved from major outcome trials using SGLT-2 inhibitors for treatment and prevention of heart failure and chronic kidney disease in people with and without diabetes, to additional therapy options for chronic kidney disease with a novel mineralocorticoid receptor antagonist. Furthermore, challenges in diabetes management like COVID-19 and obesity, as well as novel treatment strategies and guidelines, were discussed. The 7th Cardiovascular Outcome Trial Summit will be held virtually on November, 18–19, 2021 (http://www.cvot.org)

Recurrent Auto-Encoder Model for Large-Scale Industrial Sensor Signal Analysis

Recurrent auto-encoder model summarises sequential data through an encoder structure into a fixed-length vector and then reconstructs the original sequence through the decoder structure. The summarised vector can be used to represent time series features. In this paper, we propose relaxing the dimensionality of the decoder output so that it performs partial reconstruction. The fixed-length vector therefore represents features in the selected dimensions only. In addition, we propose using rolling fixed window approach to generate training samples from unbounded time series data. The change of time series features over time can be summarised as a smooth trajectory path. The fixed-length vectors are further analysed using additional visualisation and unsupervised clustering techniques. The proposed method can be applied in large-scale industrial processes for sensors signal analysis purpose, where clusters of the vector representations can reflect the operating states of the industrial system.Comment: Accepted paper at the 19th International Conference on Engineering Applications of Neural Networks (EANN 2018

A formal framework to prove the correctness of model driven engineering composition operators

International audienceCurrent trends in system engineering combine modeling, composition and verification technologies in order to harness their ever growing complexity. Each composition operator dedicated to a different modeling concern should be proven to be property preserving at assembly time. These proofs are usually burdensome with repetitive aspects. Our work targets the factorisation of these aspects relying on primitive generic composition operators used to express more sophisticated language specific ones. These operators are defined for languages expressed with OMG MOF metamodeling technologies. The proof are done with the Coq proof assistant relying on the Coq4MDE framework defined previously. These basic operators, Union and Substitution, are illustrated using the MOF Package Merge as composition operator and the preservation of model conformance as verified property

Unraveling gene regulatory networks from time-resolved gene expression data -- a measures comparison study

Peer reviewedPublisher PD

MiRNA dysregulation underlying common pathways in type 2 diabetes and cancer development. an Italian Association of Medical Oncology (AIOM)/Italian Association of Medical Diabetologists (AMD)/Italian Society of Diabetology (SID)/Italian Society of Endocrinology (SIE)/Italian Society of Pharmacology (SIF) multidisciplinary critical view

Increasing evidence suggests that patients with diabetes, particularly type 2 diabetes (T2D), are characterized by an increased risk of developing different types of cancer, so cancer could be proposed as a new T2D-related complication. On the other hand, cancer may also increase the risk of developing new-onset diabetes, mainly caused by anticancer therapies. Hyperinsulinemia, hyperglycemia, and chronic inflammation typical of T2D could represent possible mechanisms involved in cancer development in diabetic patients. MicroRNAs (miRNAs) are a subset of non-coding RNAs, ⁓22 nucleotides in length, which control the post-transcriptional regulation of gene expression through both translational repression and messenger RNA degradation. Of note, miRNAs have multiple target genes and alteration of their expression has been reported in multiple diseases, including T2D and cancer. Accordingly, specific miRNA-regulated pathways are involved in the pathogenesis of both conditions. In this review, a panel of experts from the Italian Association of Medical Oncology (AIOM), Italian Association of Medical Diabetologists (AMD), Italian Society of Diabetology (SID), Italian Society of Endocrinology (SIE), and Italian Society of Pharmacology (SIF) provide a critical view of the evidence about the involvement of miRNAs in the pathophysiology of both T2D and cancer, trying to identify the shared miRNA signature and pathways able to explain the strong correlation between the two conditions, as well as to envision new common pharmacological approaches

Body size and the risk of biliary tract cancer: a population-based study in China

Though obesity is an established risk factor for gall bladder cancer, its role in cancers of the extrahepatic bile ducts and ampulla of Vater is less clear, as also is the role of abdominal obesity. In a population-based case–control study of biliary tract cancer in Shanghai, China, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for biliary tract cancer in relation to anthropometric measures, including body mass index (BMI) at various ages and waist-to-hip ratio (WHR), adjusting for age, sex, and education. The study included 627 patients with biliary tract cancer (368 gall bladder, 191 bile duct, 68 ampulla of Vater) and 959 healthy subjects randomly selected from the population. A higher BMI at all ages, including early adulthood (ages 20–29 years), and a greater WHR were associated with an increased risk of gall bladder cancer. A high usual adult BMI (⩾25) was associated with a 1.6-fold risk of gall bladder cancer (95% CI 1.2–2.1, P for trend <0.001). Among subjects without gallstones, BMI was also positively associated with gall bladder cancer risk. Regardless of BMI levels, increasing WHR was associated with an excess risk of gall bladder cancer risk, with those having a high BMI (⩾25) and a high WHR (>0.90) having the highest risk of gall bladder cancer (OR=12.6, 95% CI 4.8–33.2), relative to those with a low BMI and WHR. We found no clear risk patterns for cancers of the bile duct and ampulla of Vater. These results suggest that both overall and abdominal obesity, including obesity in early adulthood, are associated with an increased risk of gall bladder cancer. The increasing prevalence of obesity and cholesterol stones in Shanghai seems at least partly responsible for the rising incidence of gall bladder cancer in Shanghai