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Many data-driven patient risk stratification models have not been evaluated prospectively. We performed and compared the prospective and retrospective evaluations of 2 Clostridioides difficile infection (CDI) risk-prediction models at 2 large academic health centers, and we discuss the models’ robustness to data-set shifts.
Altered DNA methylation in the FK506 binding protein 5 (FKBP5) gene has been shown to regulate stress response, which may serve as a biomarker of depression and a promising candidate for explaining sexual differences. However, there is no consistent conclusion so far.
The present study aimed to test the associations of FKBP5 DNA methylation with depressive symptoms and whether these associations were influenced by sex.
A nested case-control study comprising 87 cases and 151 controls was conducted in South China from January 2019 and December 2019. Peripheral blood for DNA extraction and DNA methylation analysis of FKBP5 gene promoter was collected, and severity of depressive symptoms was assessed at baseline and after one year follow-up.
Compared to healthy controls, lower methylation percentage of FKBP5-12 CpG 1 was observed in adolescents with depressive symptoms after adjusting covariates (case: 0.94 ± 2.00, control: 0.47 ± 0.92; F = 5.41, P = 0.021). In addition, hypomethylation of FKBP5 CpG sites was not an independent risk factor for depressive symptoms after adjustment for environmental stress factors (P > 0.05). No significant sex differences were found in the association of FKBP5 gene methylation with depressive symptoms.
Lower levels of FKBP5 methylation were found in adolescents with depressive symptoms. Our study supported that the epigenetic factors did not act alone in the development of depressive symptoms. Taken together, these findings contribute to a better understanding of complex mechanisms of gene-environment interactions involved in depression.
Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an exciting opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks.
To describe the amount of data collected during a multimodal longitudinal RMT study, in an MDD population.
RADAR-MDD is a multi-centre, prospective observational cohort study. People with a history of MDD were provided with a wrist-worn wearable, and several apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks and cognitive assessments and followed-up for a maximum of 2 years.
A total of 623 individuals with a history of MDD were enrolled in the study with 80% completion rates for primary outcome assessments across all timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. Data availability across all RMT data types varied depending on the source of data and the participant-burden for each data type. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. 110 participants had > 50% data available across all data types, and thus able to contribute to multiparametric analyses.
RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible.
This research examines maternal smoking during pregnancy and risk for poorer executive function in siblings discordant for exposure. Data (N = 173 families) were drawn from the Missouri Mothers and Their Children study, a sample, identified using birth records (years 1998–2005), in which mothers changed smoking behavior between two pregnancies (Child 1 [older sibling]: Mage = 12.99; Child 2 [younger sibling]: Mage = 10.19). A sibling comparison approach was used, providing a robust test for the association between maternal smoking during pregnancy and different aspects of executive function in early-mid adolescence. Results suggested within-family (i.e., potentially causal) associations between maternal smoking during pregnancy and one working memory task (visual working memory) and one response inhibition task (color-word interference), with increased exposure associated with decreased performance. Maternal smoking during pregnancy was not associated with stop-signal reaction time, cognitive flexibility/set-shifting, or auditory working memory. Initial within-family associations between maternal smoking during pregnancy and visual working memory as well as color-word interference were fully attenuated in a model including child and familial covariates. These findings indicate that exposure to maternal smoking during pregnancy may be associated with poorer performance on some, but not all skills assessed; however, familial transmission of risk for low executive function appears more important.
The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.
Organ donation after brain death has been practiced in China since 2003 in the absence of brain death legislation. Similar to international standards, China’s brain death diagnostic criteria include coma, absence of brainstem reflexes, and the lack of spontaneous respiration. The Chinese criteria require that the lack of spontaneous respiration must be verified with an apnea test by disconnecting the ventilator for 8 min to provoke spontaneous respiration. However, we have found publications in Chinese medical journals, in which the donors were declared to be brain dead, yet without an apnea test. The organ procurement procedures started with initiating “intratracheal intubation for mechanical ventilation after brain death,” indicating that a brain death diagnosis was not performed. The purpose of the intubation was not to resuscitate the patient but rather was directly related to facilitating the explantation of organs. Moreover, it was unmistakably stated in two of these publications that the cardiac arrest was induced in these patients without brain death determination by cold St. Thomas cardioplegic solution or other cold myocardial protection solutions. This means that the condition of these donors neither met the criteria of brain death nor that of cardiac death. In other words, the “donor organs” may well have been procured in these cases from living human beings. Thus, brain death definition is abused in China by some individuals for organ harvesting, and a systematic investigation is needed to clarify the situation of organ donation after brain death in China.
The COVID-19 pandemic resulted in millions of deaths worldwide and is considered a significant mass-casualty disaster (MCD). The surge of patients and scarcity of resources negatively impacted hospitals, patients and medical practice. We hypothesized ICUs during this MCD had a higher acuity of illness, and subsequently had increased lengths of stay (LOS), complication rates, death rates and costs of care. The purpose of this study was to investigate those outcomes.
This was a multicenter, retrospective study that compared intensive care admissions in 2020 to those in 2019 to evaluate patient outcomes and cost of care. Data were obtained from the Vizient Clinical Data Base/Resource Manager (Vizient Inc., Irvine, Texas, USA).
Data included the number of ICU admissions, patient outcomes, case mix index and summary of cost reports. Quality outcomes were also collected, and a total of 1304981 patients from 333 hospitals were included. For all medical centers, there was a significant increase in LOS index, ICU LOS, complication rate, case mix index, total cost, and direct cost index.
The MCD caused by COVID-19 was associated with increased adverse outcomes and cost-of-care for ICU patients.
The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.
Background: Canadian neurology residency programs recently transitioned to Competence Based Medical Education (CBME), designed to provide residents with stage-appropriate learning to develop and demonstrate competence. The successful implementation of CBME requires iterative evaluation as the adoption process may differ from the intended design due to systemic or program-specific factors. This study aims to (1) examine the variability in CBME implementation across Canadian neurology residency programs; (2) determine the barriers toward uptake of CBME; and (3) identify the benefits and pitfalls of CBME in neurology residency programs. Methods: A separate national survey was developed for residents and staff neurologists who participated in CBME for at least six months. Surveys were distributed through email, and responses were anonymized. Quantitative data were analyzed by response frequency and mean, where applicable. Free-form responses were analyzed qualitatively. Results: Staff neurologists felt prepared for CBME, but were divided on its fairness and impact on education quality. Residents experienced frequent but not necessarily timely or high-quality feedback. Barriers to implementation included increased paperwork, dissatisfaction with online platforms used to facilitate CBME, and bidirectional burden of initiating evaluations. Conclusions: Staff and residents have expressed unique perspectives on the first iteration of CBME. There remain opportunities for improvement in subsequent iterations.
Ethical decision making has long been recognized as critical for industrial-organizational (I-O) psychologists in the variety of roles they fill in education, research, and practice. Decisions with ethical implications are not always readily apparent and often require consideration of competing concerns. The American Psychological Association (APA) Ethical Principles of Psychologists and Code of Conduct are the principles and standards to which all Society for Industrial and Organizational Psychology (SIOP) members are held accountable, and these principles serve to aid in decision making. To this end, the primary focus of this article is the presentation and application of an integrative ethical decision-making framework rooted in and inspired by empirical, philosophical, and practical considerations of professional ethics. The purpose of this framework is to provide a generalizable model that can be used to identify, evaluate, resolve, and engage in discourse about topics involving ethical issues. To demonstrate the efficacy of this general framework to contexts germane to I-O psychologists, we subsequently present and apply this framework to five scenarios, each involving an ethical situation relevant to academia, practice, or graduate education in I-O psychology. With this article, we hope to stimulate the refinement of this ethical decision-making model, illustrate its application in our profession, and, most importantly, advance conversations about ethical decision making in I-O psychology.
The political connection between the state and firms in the context of China's corporate restructuring has been little explored. Using the clientelist framework and unpacking the incentives of both firms and the state, we analyse political connections as repeated patron–client exchanges where the politically connected firms can help the state fulfil its revenue imperative, serving as a failsafe for local authorities to ensure that upper-level tax quotas are met. Leveraging original surveys of the same Chinese firms over an 11-year period and the variations in their post-restructuring board composition, we find that restructured state-owned enterprises (SOEs) with political connections pay more tax than their assessed amount, independent of profits, in exchange for more preferential access to key inputs and policy opportunities controlled by the state. Examining taxes rather than profits also offers a new interpretation for why China continues to favour its remaining SOEs even when they are less profitable.
The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.
For a common micro-satellite, orbiting in a circular sun-synchronous orbit (SSO) at an altitude between 500 and 600km, the satellite attitude during off-nadir imaging and staring-imaging operations can be up to ±45 degree on roll and pitch angles. During these off-nadir pointing for both multi-trip operation and staring imaging operations, the spacecraft body is commonly subject to high-rate motion. This posts challenges for a spacecraft attitude determination subsystem called Gyro Stellar Inertial Attitude Estimate (GS IAE), which employs gyros and star sensors to maintain the required attitude knowledge, since star trackers will severely degrade attitude estimation accuracies when the spacecraft is subject to high-rate motion. This paper analyses the star motion-induced errors for a typical star tracker, models the star motion-induced errors to assess the performance impact on the attitude estimation accuracy, and investigates the adaptive extended Kalman filter design in the GS IAE while evaluating its effectiveness.
Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.
A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.
Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.
These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.