Despite the known heterogeneity of type 2 diabetes and variable response to glucose lowering medications, current evidence on optimal treatment is predominantly based on average effects in clinical ...trials rather than individual-level characteristics. A precision medicine approach based on treatment response would aim to improve on this by identifying predictors of differential drug response for people based on their characteristics and then using this information to select optimal treatment. Recent research has demonstrated robust and clinically relevant differential drug response with all noninsulin treatments after metformin (sulfonylureas, thiazolidinediones, dipeptidyl peptidase 4 DPP-4 inhibitors, glucagon-like peptide 1 GLP-1 receptor agonists, and sodium-glucose cotransporter 2 SGLT2 inhibitors) using routinely available clinical features. This Perspective reviews this current evidence and discusses how differences in drug response could inform selection of optimal type 2 diabetes treatment in the near future. It presents a novel framework for developing and testing precision medicine-based strategies to optimize treatment, harnessing existing routine clinical and trial data sources. This framework was recently applied to demonstrate that "subtype" approaches, in which people are classified into subgroups based on features reflecting underlying pathophysiology, are likely to have less clinical utility compared with approaches that combine the same features as continuous measures in probabilistic "individualized prediction" models.
A number of recent studies have shown that the nonradiative voltage losses in organic solar cells can be suppressed in systems with low energetic offsets between donor and acceptor molecular states, ...but the physical reasons underpinning this remain unclear. Here, we present a systematic study of 18 different donor/acceptor blends to determine the effect that energetic offset has on both radiative and nonradiative recombination of the charge-transfer (CT) state. We find that, for certain blends, low offsets result in hybridization between charge-transfer and lowest donor or acceptor exciton states, which leads to a strong suppression in the nonradiative voltage loss to values as low as 0.23 V associated with an increase in the luminescence of the CT state. Further, we extend a two-state CT-state recombination model to include the interaction between CT and first excited states, which allows us to explain the low nonradiative voltage losses as an increase in the effective CT to ground state oscillator strength due to the intensity borrowing mechanism. We show that low nonradiative voltage losses can be achieved in material combinations with a strong electronic coupling between CT and first excited states and where the lower band gap material has a high oscillator strength for transitions from the excited state to the ground state. Finally, from our model we propose that achieving very low nonradiative voltage losses may come at a cost of higher overall recombination rates, which may help to explain the generally lower FF and EQE of highly hybridized systems.
OBJECTIVES:To measure temporal trends in survival over time in people with severe coronavirus disease 2019 requiring critical care (high dependency unit or ICU) management, and to assess whether ...temporal variation in mortality was explained by changes in patient demographics and comorbidity burden over time.
DESIGN:Retrospective observational cohort; based on data reported to the COVID-19 Hospitalisation in England Surveillance System. The primary outcome was in-hospital 30-day all-cause mortality. Unadjusted survival was estimated by calendar week of admission, and Cox proportional hazards models were used to estimate adjusted survival, controlling for age, sex, ethnicity, major comorbidities, and geographical region.
SETTING:One hundred eight English critical care units.
PATIENTS:All adult (18 yr +) coronavirus disease 2019 specific critical care admissions between March 1, 2020, and June 27, 2020.
INTERVENTIONS:Not applicable.
MEASUREMENTS AND MAIN RESULTS:Twenty-one thousand eighty-two critical care patients (high dependency unit n = 15,367; ICU n = 5,715) were included. Unadjusted survival at 30 days was lowest for people admitted in late March in both high dependency unit (71.6% survival) and ICU (58.0% survival). By the end of June, survival had improved to 92.7% in high dependency unit and 80.4% in ICU. Improvements in survival remained after adjustment for patient characteristics (age, sex, ethnicity, and major comorbidities) and geographical region.
CONCLUSIONS:There has been a substantial improvement in survival amongst people admitted to critical care with coronavirus disease 2019 in England, with markedly higher survival rates in people admitted in May and June compared with those admitted in March and April. Our analysis suggests this improvement is not due to temporal changes in the age, sex, ethnicity, or major comorbidity burden of admitted patients.
A fullerene derivative (α‐bis‐PCBM) is purified from an as‐produced bis‐phenyl‐C61‐butyric acid methyl ester (bis‐60PCBM) isomer mixture by preparative peak‐recycling, high‐performance liquid ...chromatography, and is employed as a templating agent for solution processing of metal halide perovskite films via an antisolvent method. The resulting α‐bis‐PCBM‐containing perovskite solar cells achieve better stability, efficiency, and reproducibility when compared with analogous cells containing PCBM. α‐bis‐PCBM fills the vacancies and grain boundaries of the perovskite film, enhancing the crystallization of perovskites and addressing the issue of slow electron extraction. In addition, α‐bis‐PCBM resists the ingression of moisture and passivates voids or pinholes generated in the hole‐transporting layer. As a result, a power conversion efficiency (PCE) of 20.8% is obtained, compared with 19.9% by PCBM, and is accompanied by excellent stability under heat and simulated sunlight. The PCE of unsealed devices dropped by less than 10% in ambient air (40% RH) after 44 d at 65 °C, and by 4% after 600 h under continuous full‐sun illumination and maximum power point tracking, respectively.
Significantly improved performance of mixed perovskite solar cells, using a facile α‐bis‐PCBM‐containing perovskite growth method during device fabrication, is reported. The newly developed perovskite solar cell exhibits an enhanced power conversion efficiency of 20.8%, along with enhanced stability under heat and illumination.
To describe the relationship between type 2 diabetes and all-cause mortality among adults with coronavirus disease 2019 (COVID-19) in the critical care setting.
This was a nationwide retrospective ...cohort study in people admitted to hospital in England with COVID-19 requiring admission to a high dependency unit (HDU) or intensive care unit (ICU) between 1 March 2020 and 27 July 2020. Cox proportional hazards models were used to estimate 30-day in-hospital all-cause mortality associated with type 2 diabetes, with adjustment for age, sex, ethnicity, obesity, and other major comorbidities (chronic respiratory disease, asthma, chronic heart disease, hypertension, immunosuppression, chronic neurological disease, chronic renal disease, and chronic liver disease).
A total of 19,256 COVID-19-related HDU and ICU admissions were included in the primary analysis, including 13,809 HDU (mean age 70 years) and 5,447 ICU (mean age 58 years) admissions. Of those admitted, 3,524 (18.3%) had type 2 diabetes and 5,077 (26.4%) died during the study period. Patients with type 2 diabetes were at increased risk of death (adjusted hazard ratio aHR 1.23 95% CI 1.14, 1.32), and this result was consistent in HDU and ICU subsets. The relative mortality risk associated with type 2 diabetes decreased with higher age (age 18-49 years aHR 1.50 95% CI 1.05, 2.15, age 50-64 years 1.29 1.10, 1.51, and age ≥65 years 1.18 1.09, 1.29;
value for age-type 2 diabetes interaction = 0.002).
Type 2 diabetes may be an independent prognostic factor for survival in people with severe COVID-19 requiring critical care treatment, and in this setting the risk increase associated with type 2 diabetes is greatest in younger people.
Over the last couple of decades, the advancement in Microelectromechanical System (MEMS) devices is highly demanded for integrating the economically miniaturized sensors with fabricating technology. ...A sensor is a system that detects and responds to multiple physical inputs and converting them into analogue or digital forms. The sensor transforms these variations into a form which can be utilized as a marker to monitor the device variable. MEMS exhibits excellent feasibility in miniaturization sensors due to its small dimension, low power consumption, superior performance, and, batch-fabrication. This article presents the recent developments in standard actuation and sensing mechanisms that can serve MEMS-based devices, which is expected to revolutionize almost many product categories in the current era. The featured principles of actuating, sensing mechanisms and real-life applications have also been discussed. Proper understanding of the actuating and sensing mechanisms for the MEMS-based devices can play a vital role in effective selection for novel and complex application design.
Analogical reasoning is a core facet of higher cognition in humans. Creating analogies as we navigate the environment helps us learn. Analogies involve reframing novel encounters using knowledge of ...familiar, relationally similar contexts stored in memory. When an analogy links a novel encounter with a familiar context, it can aid in problem solving. Reasoning by analogy is a complex process that is mediated by multiple brain regions and mechanisms. Several advanced computational architectures have been developed to simulate how these brain processes give rise to analogical reasoning, like the “learning with inferences and schema ion” architecture and the Companion architecture. To obtain this power to simulate human reasoning, theses architectures assume that various computational “subprocesses” comprise analogical reasoning, such as analogical access, mapping, inference, and schema induction, consistent with the structure‐mapping framework proposed decades ago. However, little is known about how these subprocesses relate to actual brain processes. While some work in neuroscience has linked analogical reasoning to regions of brain prefrontal cortex, more research is needed to investigate the wide array of specific neural hypotheses generated by the computational architectures. In the current article, we review the association between historically important computational architectures of analogy and empirical studies in neuroscience. In particular, we focus on evidence for a frontoparietal brain network underlying analogical reasoning and the degree to which brain mechanisms mirror the computational subprocesses. We also offer a general vantage on the current‐ and future‐states of neuroscience research in this domain and provide some recommendations for future neuroimaging studies.
The handling of missing data is a challenge for inference and regression modelling. A particular challenge is dealing with missing predictor information, particularly when trying to build and make ...predictions from models for use in clinical practice.
We utilise a flexible Bayesian approach for handling missing predictor information in regression models. This provides practitioners with full posterior predictive distributions for both the missing predictor information (conditional on the observed predictors) and the outcome-of-interest. We apply this approach to a previously proposed counterfactual treatment selection model for type 2 diabetes second-line therapies. Our approach combines a regression model and a Dirichlet process mixture model (DPMM), where the former defines the treatment selection model, and the latter provides a flexible way to model the joint distribution of the predictors.
We show that DPMMs can model complex relationships between predictor variables and can provide powerful means of fitting models to incomplete data (under missing-completely-at-random and missing-at-random assumptions). This framework ensures that the posterior distribution for the parameters and the conditional average treatment effect estimates automatically reflect the additional uncertainties associated with missing data due to the hierarchical model structure. We also demonstrate that in the presence of multiple missing predictors, the DPMM model can be used to explore which variable(s), if collected, could provide the most additional information about the likely outcome.
When developing clinical prediction models, DPMMs offer a flexible way to model complex covariate structures and handle missing predictor information. DPMM-based counterfactual prediction models can also provide additional information to support clinical decision-making, including allowing predictions with appropriate uncertainty to be made for individuals with incomplete predictor data.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The cognitive flexibility inventory (CFI) was developed to be a brief self-report measure of the type of cognitive flexibility necessary for individuals to successfully challenge and replace ...maladaptive thoughts with more balanced and adaptive thinking. It was designed to measure three aspects of cognitive flexibility: (a) the tendency to perceive difficult situations as controllable; (b) the ability to perceive multiple alternative explanations for life occurrences and human behavior; and (c) the ability to generate multiple alternative solutions to difficult situations. The two studies presented in this manuscript describe the initial development of the CFI and a 7-week longitudinal study. Results from these studies indicate the CFI has a reliable two-factor structure, excellent internal consistency, and high 7-week test–retest reliability. Preliminary evidence was obtained for the CFI’s convergent construct validity via the CFI’s correlations with other measures of cognitive flexibility (Cognitive Flexibility Scale) and coping (Ways of Coping Checklist-Revised), respectively. Support was also demonstrated for the concurrent construct validity of the CFI via its correlation with the BDI-II. Further research is needed to investigate the reliability and validity of the CFI among clinical populations.
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