Weaving healthy behaviors into new technology routines: Designing in (and for) the COVID-19 work-from-home period

Sitting in front of computers has become a major part of our workaday routines, challenging us in maintaining active and healthy lifestyles. This challenge becomes even more salient during this worldwide work-from-home period due to COVID-19. While a wide variety of existing interactive systems have been developed to facilitate health tracking and healthy exercises, relatively little research concerns incorporating healthy behaviors as HCI elements. To maximize pervasive health benefits in users’ technology routines, this workshop sets out to explore a design paradigm that enables users to use lightweight, healthy behaviors to perform daily interactions with computing systems. To navigate this new design space, this workshop calls for interdisciplinary endeavors, synergizing expertise from HCI design, health informatics, persuasive technology, exertion game, and psychology

Pharmacokinetic and Pharmacogenetic Factors Contributing to Platelet Function Recovery After Single Dose of Ticagrelor in Healthy Subjects

Objectives: This study aimed to elucidate the contribution of candidate single nucleotide polymorphisms (SNPs) related to pharmacokinetics on the recovery of platelet function after single dose of ticagrelor was orally administered to healthy Chinese subjects.Methods: The pharmacokinetic profiles of ticagrelor and its metabolite AR-C124910XX (M8), and the platelet aggregation (PA), were assessed after 180 mg of single-dose ticagrelor was orally administered to 51 healthy Chinese subjects. Effects of CYP2C19*2, CYP2C19*3, CYP3A5*3, UGT1A1*6, UGT1A1*28, UGT2B7*2, UGT2B7*3, SLCO1B1 388A>G, and SLCO1B1 521T>C, on the pharmacokinetics of ticagrelor and M8, and platelet function recovery were investigated.Results: The time to recover 50% of the maximum drug effect (RT50) ranging from 36 to 126 h with 46.9% CV had a remarkable individual difference and was positively associated with the half-life (t1/2) of M8 (r = 0.3901, P = 0.0067). The time of peak concentration (Tmax) of ticagrelor for CYP2C19*3 GG homozygotes was significantly higher than that of GA heterozygotes (P = 0.0027, FDR = 0.0243). Decreased peak concentration (Cmax) of M8 was significantly associated with SLCO1B1 388A>G A allele (P = 0.0152, FDR = 0.1368). CYP2C19*2 A was significantly related to decreased Cmax of M8 (P = 0.0455, FDR = 0.2048). While, the influence of these nine SNPs on the recovery of platelet function was not significant.Conclusion: Our study suggests that the elimination of M8 is an important factor in determining the recovery of platelet function. Although CYP2C19 and SLCO1B1 genetic variants were related to the pharmacokinetics of ticagrelor or M8, they did not show a significant effect on the platelet function recovery in this study.Clinical Trial Registration:https://clinicaltrials.gov/ct2/show/NCT03092076, identifier: NCT0309207

Joint population pharmacokinetic modeling of venlafaxine and O-desmethyl venlafaxine in healthy volunteers and patients to evaluate the impact of morbidity and concomitant medication

Introduction: Venlafaxine (VEN) is a widely used dual selective serotonin/noradrenaline reuptake inhibitor indicated for depression and anxiety. It undergoes first-pass metabolism to its active metabolite, O-desmethyl venlafaxine (ODV). The aim of the present study was to develop a joint population pharmacokinetic (PPK) model to characterize their pharmacokinetic characters simultaneously.Methods: Plasma concentrations with demographic and clinical data were derived from a bioequivalence study in 24 healthy subjects and a naturalistic TDM setting containing 127 psychiatric patients. A parent-metabolite PPK modeling was performed with NONMEM software using a non-linear mixed effect modeling approach. Goodness of fit plots and normalized prediction distribution error method were used for model validation.Results and conclusion: Concentrations of VEN and ODV were well described with a one-compartment model incorporating first-pass metabolism. The first-pass metabolism was modeled as a first-order conversion. The morbid state and concomitant amisulpride were identified as two significant covariates affecting the clearance of VEN and ODV, which may account for some of the variations in exposure. This model may contribute to the precision medication in clinical practice and may inspire other drugs with pre-system metabolism

Development and Validation of an HPLC-MS/MS Method for Rapid Simultaneous Determination of Cefprozil Diastereomers in Human Plasma

Background. Both cis- and trans-cefprozil have antimicrobial activity, but their potencies are quite different. It is therefore necessary to develop a sensitive method to simultaneously determine both isomers for pharmacokinetic and bioequivalence studies. Methods. An LC-MS/MS method, using stable isotope-labeled cefprozil as the internal standard, was developed and validated. The analytes were extracted from plasma by protein precipitation and separated on a reverse-phase C18 column using a gradient program consisting of 0.5% formic acid and acetonitrile within 4 min. The mass spectrometry acquisition was performed with multiple reaction monitoring in positive ion mode using the respective [M+H]+ ions, m/z 391.2→114.0 for cefprozil and 395.0→114.5 for cefprozil-D4. Results. The calibration curves were linear over the ranges of 0.025–15 μg/mL for cis-cefprozil and 0.014–1.67 μg/mL for trans-cefprozil. The accuracies for the cis and trans isomers of cefprozil were 93.1% and 103.0%, respectively. The intra- and interassay precisions for the QC samples of the isomers were < 14.3%. The intra- and interassay precisions at the LLOQ were < 16.5%. Conclusions. The method was sensitive and reproducible and was applied in a pilot pharmacokinetic study of healthy volunteers

Research on Gangue Detection Algorithm Based on Cross-Scale Feature Fusion and Dynamic Pruning

The intelligent identification of coal gangue on industrial conveyor belts is a crucial technology for the precise sorting of coal gangue. To address the issues in coal gangue detection algorithms, such as high false negative rates, complex network structures, and substantial model weights, an optimized coal gangue detection algorithm based on YOLOv5s is proposed. In the backbone network, a feature refinement module is employed for feature extraction, enhancing the capability to extract features for coal and gangue. The improved BIFPN structure is employed as the feature pyramid, augmenting the model’s capability for cross-scale feature fusion. In the prediction layer, the ESIOU is utilized as the bounding box regression loss function to rectify the misalignment issue between predicted and actual box angles. This approach expedites the convergence speed of the network while concurrently enhancing the accuracy of coal gangue detection. Channel pruning is implemented on the network to diminish model computational complexity and weight, consequently augmenting detection speed. The experimental results demonstrate that the refined YOLOv5s coal gangue detection algorithm outperforms the original YOLOv5s algorithm, achieving a notable accuracy enhancement of 2.2% to reach 93.8%. Concurrently, a substantial reduction in model weight by 38.8% is observed, resulting in a notable 56.2% increase in inference speed. These advancements meet the detection requirements for scenarios involving mixed coal gangue

Fatigue Life Prediction of Half-Shaft Using the Strain-Life Method

Fatigue life prediction is an important part of the reliability and durability analysis of automobile components. Based on Wang and Brown’s framework, multiaxial random fatigue damage was adopted to predict the fatigue life of half-shaft. The stress analysis of half-shaft was resolved analytically to determine the local stress tensor in the potential area of fracture. The maximum shear strain fatigue damage parameter and the normal stress fatigue damage parameter were evaluated to predict the fatigue life of half-shaft. The results show that the prediction method is reliable and meets the service life and safety requirements

Establishment and Validation of a Liquid Chromatography-Tandem Mass Spectrometry Method for the Determination of Tigecycline in Critically Ill Patients

Utilizing tigecycline-d9 as an internal standard (IS), we establish and validate a simple, effective, and rapid liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the quantitative measurement of tigecycline (TGC) in patient plasma. Acetonitrile was used as a precipitant to process plasma samples by a protein precipitation method. The analyte and IS were separated on an HSS T3 (2.1 × 100 mm, 3.5 μm) chromatographic column using isocratic program with a mobile phase comprising of 80% solvent A (water containing 0.1% formic acid (v/v) with 5 mM ammonium acetate) and 20% solvent B (acetonitrile) with a flow rate of 0.3 mL/min. The mass spectrometer, scanning in multireaction monitoring (MRM) mode and using an electrospray ion source (ESI), operated in the positive-ion mode. The ion pairs used for quantitative analysis were m/z 586.4 ⟶ 513.3 and m/z 595.5 ⟶ 514.3 for TGC and the IS, respectively. The range of the linear calibration curve obtained with this approach was 50–5000 ng/ml. Intra- and interbatch precision for TGC quantitation were less than 7.2%, and the accuracy ranged from 93.4 to 101.8%. The IS-normalized matrix effect was 87 to 104%. Due to its high precision and accuracy, this novel method allows for fast quantitation of TGC with a total analysis time of 2 min. This approach was effectively applied to study the pharmacokinetics of TGC in critically ill adult patients

Integrating industrial design and Geoscience: a survey on data-driven research to promote public health and vitality

With the rapid advance of information communication technologies, unprecedented volumes of environmental and behavioral data have been generated and provided researchers with new pathways to develop strategies and interventions. In digital public health, there has been an emerging interest in promoting vitality based on multidisciplinary research. However, few works have been conducted on facilitating data-related collaboration in vitality research. This paper presents a survey study for the development of a data-driven service system to support multidisciplinary collaboration in vitality-related projects. Our survey received responses from 38 researchers, primarily from Industrial Design and Geoscience. From this survey, we learned both common ground and different research experiences between the two disciplines, regarding the collection, management, and analysis of data. Based on our findings, we proposed a system architecture of a data platform, and specified a set of functions that can assist researchers working from different disciplines in sharing, collection, processing, and analyzing vitality-related research data

Integrating industrial design and Geoscience:a survey on data-driven research to promote public health and vitality

With the rapid advance of information communication technologies, unprecedented volumes of environmental and behavioral data have been generated and provided researchers with new pathways to develop strategies and interventions. In digital public health, there has been an emerging interest in promoting vitality based on multidisciplinary research. However, few works have been conducted on facilitating data-related collaboration in vitality research. This paper presents a survey study for the development of a data-driven service system to support multidisciplinary collaboration in vitality-related projects. Our survey received responses from 38 researchers, primarily from Industrial Design and Geoscience. From this survey, we learned both common ground and different research experiences between the two disciplines, regarding the collection, management, and analysis of data. Based on our findings, we proposed a system architecture of a data platform, and specified a set of functions that can assist researchers working from different disciplines in sharing, collection, processing, and analyzing vitality-related research data