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Multicenter clinical trials are essential for evaluating interventions but often face significant challenges in study design, site coordination, participant recruitment, and regulatory compliance. To address these issues, the National Institutes of Health’s National Center for Advancing Translational Sciences established the Trial Innovation Network (TIN). The TIN offers a scientific consultation process, providing access to clinical trial and disease experts who provide input and recommendations throughout the trial’s duration, at no cost to investigators. This approach aims to improve trial design, accelerate implementation, foster interdisciplinary teamwork, and spur innovations that enhance multicenter trial quality and efficiency. The TIN leverages resources of the Clinical and Translational Science Awards (CTSA) program, complementing local capabilities at the investigator’s institution. The Initial Consultation process focuses on the study’s scientific premise, design, site development, recruitment and retention strategies, funding feasibility, and other support areas. As of 6/1/2024, the TIN has provided 431 Initial Consultations to increase efficiency and accelerate trial implementation by delivering customized support and tailored recommendations. Across a range of clinical trials, the TIN has developed standardized, streamlined, and adaptable processes. We describe these processes, provide operational metrics, and include a set of lessons learned for consideration by other trial support and innovation networks.
The outer solar system is theoretically predicted to harbour an undiscovered planet, often referred to as Planet Nine. Simulations suggest that its gravitational influence could explain the unusual clustering of minor bodies in the Kuiper Belt. However, no observational evidence for Planet Nine has been found so far, as its predicted orbit lies far beyond Neptune, where it reflects only a faint amount of Sunlight. This work aims to find Planet Nine candidates by taking advantage of two far-infrared all-sky surveys, which are IRAS and AKARI. The epochs of these two surveys were separated by 23 years, which is large enough to detect Planet Nine’s $\sim3'$/year orbital motion. We use a dedicated AKARI Far-Infrared point source list for the purpose of our Planet Nine search — AKARI-FIS Monthly Unconfirmed Source List (AKARI-MUSL), which includes sources detected repeatedly only in hours timescale, but not after months. AKARI-MUSL is more advantageous than the AKARI Bright Source Catalogue (AKARI-BSC) for detecting moving and faint objects like Planet Nine with a twice-deeper flux detection limit. We search for objects that moved slowly between IRAS and AKARI detections given in the catalogues. First, we estimated the expected flux and orbital motion of Planet Nine by assuming its mass, distance, and effective temperature to ensure it can be detected by IRAS and AKARI, then applied the positional and flux selection criteria to narrow down the number of sources from the catalogues. Next, we produced all possible candidate pairs including one IRAS source and one AKARI source whose angular separations were limited between 42′ and $69.6'$, corresponding to the heliocentric distance range of 500 – 700 AU and the mass range of 7 – 17M$_{\oplus}$. There are 13 candidate pairs obtained after the selection criteria. After image inspection, we found one good candidate, of which the IRAS source is absent from the same coordinate in the AKARI image after 23 years and vice versa. However, AKARI and IRAS detections are not enough to determine the full orbit of this candidate. This issue leads to the need for follow-up observations, which will determine the Keplerian motion of our Planet Nine candidate.
An unusual orbital element clustering of Kuiper belt objects (KBOs) has been observed. The most promising dynamic solution is the presence of a giant planet in the outer Solar system, Planet Nine. However, due to its extreme distance, intensive searches in optical have not been successful. We aim to find Planet Nine in the far-infrared, where it has the peak of the black body radiation, using the most sensitive all-sky far-infrared survey to date, AKARI. In contrast to optical searches, where the energy of reflected sunlight decreases by $d^{4}$, thermal radiation in the infrared decreases with the square of the heliocentric distance $d^{2}$. We search for moving objects in the AKARI Single Scan Detection List. We select sources from a promising region suggested by an N-body simulation from Millholland and Laughlin 2017: $30^{\circ}\lt$ R.A. $\lt50^{\circ}$ and $-20^{\circ}\lt$ Dec. $\lt20^{\circ}$. Known sources are excluded by cross-matching AKARI sources with 9 optical and infrared catalogues. Furthermore, we select sources with small background strength to avoid sources in the cirrus. Since Planet Nine is stationary in a timescale of hours but moves on a monthly scale, our primary strategy is to select slowly moving objects that are stationary in 24 h but not in six months, using multiple single scans by AKARI. The selected slowly moving AKARI sources are scrutinised for potential contamination from cosmic rays. Our analysis reveals two possible Planet Nine candidates whose positions and flux are within the theoretical prediction ranges. These candidates warrant further investigation through follow-up observations to confirm the existence and properties of Planet Nine.
Posttraumatic stress disorder (PTSD) has been associated with advanced epigenetic age cross-sectionally, but the association between these variables over time is unclear. This study conducted meta-analyses to test whether new-onset PTSD diagnosis and changes in PTSD symptom severity over time were associated with changes in two metrics of epigenetic aging over two time points.
Methods
We conducted meta-analyses of the association between change in PTSD diagnosis and symptom severity and change in epigenetic age acceleration/deceleration (age-adjusted DNA methylation age residuals as per the Horvath and GrimAge metrics) using data from 7 military and civilian cohorts participating in the Psychiatric Genomics Consortium PTSD Epigenetics Workgroup (total N = 1,367).
Results
Meta-analysis revealed that the interaction between Time 1 (T1) Horvath age residuals and new-onset PTSD over time was significantly associated with Horvath age residuals at T2 (meta β = 0.16, meta p = 0.02, p-adj = 0.03). The interaction between T1 Horvath age residuals and changes in PTSD symptom severity over time was significantly related to Horvath age residuals at T2 (meta β = 0.24, meta p = 0.05). No associations were observed for GrimAge residuals.
Conclusions
Results indicated that individuals who developed new-onset PTSD or showed increased PTSD symptom severity over time evidenced greater epigenetic age acceleration at follow-up than would be expected based on baseline age acceleration. This suggests that PTSD may accelerate biological aging over time and highlights the need for intervention studies to determine if PTSD treatment has a beneficial effect on the aging methylome.
Brown dwarfs are failed stars with very low mass (13–75 Jupiter mass) and an effective temperature lower than 2 500 K. Their mass range is between Jupiter and red dwarfs. Thus, they play a key role in understanding the gap in the mass function between stars and planets. However, due to their faint nature, previous searches are inevitably limited to the solar neighbourhood (20 pc). To improve our knowledge of the low mass part of the initial stellar mass function and the star formation history of the Milky Way, it is crucial to find more distant brown dwarfs. Using James Webb Space Telescope (JWST) COSMOS-Web data, this study seeks to enhance our comprehension of the physical characteristics of brown dwarfs situated at a distance of kpc scale. The exceptional sensitivity of the JWST enables the detection of brown dwarfs that are up to 100 times more distant than those discovered in the earlier all-sky infrared surveys. The large area coverage of the JWST COSMOS-Web survey allows us to find more distant brown dwarfs than earlier JWST studies with smaller area coverages. To capture prominent water absorption features around 2.7 ${\unicode{x03BC}}$m, we apply two colour criteria, $\text{F115W}-\text{F277W}+1\lt\text{F277W}-\text{F444W}$ and $\text{F277W}-\text{F444W}\gt\,0.9$. We then select point sources by CLASS_STAR, FLUX_RADIUS, and SPREAD_MODEL criteria. Faint sources are visually checked to exclude possibly extended sources. We conduct SED fitting and MCMC simulations to determine their physical properties and associated uncertainties. Our search reveals 25 T-dwarf candidates and 2 Y-dwarf candidates, more than any previous JWST brown dwarf searches. They are located from 0.3 to 4 kpc away from the Earth. The spatial number density of 900–1 050 K dwarf is $(2.0\pm0.9) \times10^{-6}\text{ pc}^{-3}$, 1 050–1 200 K dwarf is $(1.2\pm0.7) \times10^{-6}\text{ pc}^{-3}$, and 1 200–1 350 K dwarf is $(4.4\pm1.3) \times10^{-6}\text{ pc}^{-3}$. The cumulative number count of our brown dwarf candidates is consistent with the prediction from a standard double exponential model. Three of our brown dwarf candidates were detected by HST, with transverse velocities $12\pm5$, $12\pm4$, and $17\pm6$ km s$^{-1}$. Along with earlier studies, the JWST has opened a new window of brown dwarf research in the Milky Way thick disk and halo.
Metabolic enzymes are the catalysts that drive the biochemical reactions essential for sustaining life. Many of these enzymes are tightly regulated by feedback mechanisms. To fully understand their roles and modulation, it is crucial to investigate the relationship between their structure, catalytic mechanism, and function. In this perspective, by using three examples from our studies on Mycobacterium tuberculosis (Mtb) isocitrate lyase and related proteins, we highlight how an integrated approach combining structural, activity, and biophysical data provides insights into their biological functions. These examples underscore the importance of employing fast-fail experiments at the early stages of a research project, emphasise the value of complementary techniques in validating findings, and demonstrate how in vitro data combined with chemical, biochemical, and physiological knowledge can lead to a broader understanding of metabolic adaptations in pathogenic bacteria. Finally, we address the unexplored questions in Mtb metabolism and discuss how we expand our approach to include microbiological and bioanalytical techniques to further our understanding. Such an integrated and interdisciplinary strategy has the potential to uncover novel regulatory mechanisms and identify new therapeutic opportunities for the eradication of tuberculosis. The approach can also be broadly applied to investigate other biochemical networks and complex biological systems.
Adolescence is a period marked by highest vulnerability to the onset of depression, with profound implications for adult health. Neuroimaging studies have revealed considerable atrophy in brain structure in these patients with depression. Of particular importance are regions responsible for cognitive control, reward, and self-referential processing. However, the causal structural networks underpinning brain region atrophies in adolescents with depression remain unclear.
Objectives
This study aimed to investigate the temporal course and causal relationships of gray matter atrophy within the brains of adolescents with depression.
Methods
We analyzed T1-weighted structural images using voxel-based morphometry in first-episode adolescent patients with depression (n=80, 22 males; age = 15.57±1.78) and age, gender matched healthy controls (n=82, 25 males; age = 16.11±2.76) to identify the disease stage-specific gray matter abnormalities. Then, with granger causality analysis, we arranged the patients’ illness duration chronologically to construct the causal structural covariance networks that investigated the causal relationships of those atypical structures.
Results
Compared to controls, smaller volumes in ventral medial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), middle cingulate cortex (MCC) and insula areas were identified in patients with less than 1 year illness duration, and further progressed to the subgenual ACC, regions of default, frontoparietal networks in longer duration. Causal network results revealed that dACC, vmPFC, MCC and insula were prominent nodes projecting exerted positive causal effects to regions of the default mode and frontoparietal networks. The dACC, vmPFC and insula also had positive projections to the reward network, which included mainly the thalamus, caudate and putamen, while MCC also exerted a positive causal effect on the insula and thalamus.
Conclusions
These findings revealed the progression of structural atrophy in adolescent patients with depression and demonstrated the causal relationships between regions involving cognitive control, reward and self-referential processes.
There is a relative lack of research, targeted models and tools to manage beaches in estuaries and bays (BEBs). Many estuaries and bays have been highly modified and urbanised, for example port developments and coastal revetments. This paper outlines the complications and opportunities for conserving and managing BEBs in modified estuaries. To do this, we focus on eight diverse case studies from North and South America, Asia, Europe, Africa and Australia combined with the broader global literature. Our key findings are as follows: (1) BEBs are diverse and exist under a great variety of tide and wave conditions that differentiate them from open-coast beaches; (2) BEBs often lack statutory protection and many have already been sacrificed to development; (3) BEBs lack specific management tools and are often managed using tools developed for open-coast beaches; and (4) BEBs have the potential to become important in “nature-based” management solutions. We set the future research agenda for BEBs, which should include broadening research to include greater diversity of BEBs than in the past, standardising monitoring techniques, including the development of global databases using citizen science and developing specific management tools for BEBs. We must recognise BEBs as unique coastal features and develop the required fundamental knowledge and tools to effectively manage them, so they can continue providing their unique ecosystem services.
OBJECTIVES/GOALS: Community and other stakeholder engagement (CSE) is critical for relevant and equitable clinical research, yet implementation poses challenges. This study delineates the perspectives of scientists and diverse stakeholders regarding facilitators and challenges in CSE, its perceived value, and their recommendations for successful CSE. METHODS/STUDY POPULATION: The Tufts CTSI Pilot Studies Program requires applicants to propose a plan for CSE while implementing the award, including which stakeholders (SHs)—community members, clinicians, and others affected by the research--will be involved and at what stages. This qualitative study assessed the experiences of both Principal Investigators (PIs) and SHs engaged in pilot projects from three cohorts of awardees (2019-21). Recruitment targeted one PI and one SH per project. Semi-structured interviews explored their CSE experiences, including facilitators, challenges, meaningfulness, perceived impact, intent to participate in CSE in future studies, as well as recommendations for funders, research support organizations, and investigators. Inductive consensus-based coding and thematic analysis was employed. RESULTS/ANTICIPATED RESULTS: Fourteen PIs from different pilot projects and a SH from five of these projects participated. Almost all PIs (92%) had over six years of experience, but two-thirds (67%) had little or no experience with CSE. Four SHs self-identified as representatives of community organizations and one as a clinician scientist. CSE was a “win-win” for both PIs and SHs, and all PIs intended to involve SHs in other research studies. Three facilitators were identified as fostering effective CSE (e.g., PI access to CSE expertise while conducting the project), while four challenges hindered it (e.g., limits on SH capacity and CSE funding). SHs advised scientists to build authentic, sustained relationships, and PIs and SHs provided three actionable recommendations for funders and research support organizations to deepen and expand CSE. DISCUSSION/SIGNIFICANCE: Perspectives of scientists and SHs engaged in research projects are vital for expanding and sustaining effective CSE in research. Funders and research support organizations can enhance their strategies for CSE integration in clinical and translational research by incorporating these diverse views to ensure the research achieves maximal impact.
Patients with Fontan failure are high-risk candidates for heart transplantation and other advanced therapies. Understanding the outcomes following initial heart failure consultation can help define appropriate timing of referral for advanced heart failure care.
Methods:
This is a survey study of heart failure providers seeing any Fontan patient for initial heart failure care. Part 1 of the survey captured data on clinical characteristics at the time of heart failure consultation, and Part 2, completed 30 days later, captured outcomes (death, transplant evaluation outcome, and other interventions). Patients were classified as “too late” (death or declined for transplant due to being too sick) and/or “care escalation” (ventricular assist device implanted, inotrope initiated, and/or listed for transplant), within 30 days. “Late referral” was defined as those referred too late and/or had care escalation.
Results:
Between 7/2020 and 7/2022, 77 Fontan patients (52% inpatient) had an initial heart failure consultation. Ten per cent were referred too late (6 were too sick for heart transplantation with one subsequent death, and two others died without heart transplantation evaluation, within 30 days), and 36% had care escalation (21 listed ± 5 ventricular assist device implanted ± 6 inotrope initiated). Overall, 42% were late referrals. Heart failure consultation < 1 year after Fontan surgery was strongly associated with late referral (OR 6.2, 95% CI 1.8–21.5, p=0.004).
Conclusions:
Over 40% of Fontan patients seen for an initial heart failure consultation were late referrals, with 10% dying or being declined for transplant within a month of consultation. Earlier referral, particularly for those with heart failure soon after Fontan surgery, should be encouraged.
Excessive and persistent fear of clusters of holes, also known as trypophobia, has been suggested to reflect cortical hyperexcitability and may be associated with mental health risks. No study, however, has yet examined these associations in representative epidemiological samples.
Aims
To examine the prevalence of trypophobia in a population-representative youth sample, its association with mental health and functioning, and its interaction with external stress.
Method
A total of 2065 young people were consecutively recruited from a household-based epidemiological youth mental health study in Hong Kong. Trypophobia, symptoms of anxiety, depression and stress, and exposure to personal stressors were assessed. Logistic regression was used to assess the relationships between trypophobia and mental health. Potential additive and interaction effects of trypophobia and high stress exposure on mental health were also tested.
Results
The prevalence of trypophobia was 17.6%. Trypophobia was significantly associated with severe symptoms of anxiety (odds ratio (OR) = 1.83, 95% CI = 1.32–2.53), depression (OR = 1.78, 95% CI = 1.24–2.56) and stress (OR = 1.68, 95% CI = 1.11–2.53), even when accounting for sociodemographic factors, personal and family psychiatric history, resilience and stress exposure. Dose–response relationships were observed, and trypophobia significantly potentiated the effects of stress exposure on symptom outcomes, particularly for depressive symptoms. Those with trypophobia also showed significantly poorer functioning across domains and poorer health-related quality of life.
Conclusions
Screening for trypophobia in young people may facilitate early risk detection and intervention, particularly among those with recent stress exposure. Nevertheless, the generally small effect sizes suggest that other factors have more prominent roles in determining recent mental health outcomes in population-based samples; these should be explored in future work.
Despite replicated cross-sectional evidence of aberrant levels of peripheral inflammatory markers in individuals with major depressive disorder (MDD), there is limited literature on associations between inflammatory tone and response to sequential pharmacotherapies.
Objectives
To assess associations between plasma levels of pro-inflammatory markers and treatment response to escitalopram and adjunctive aripiprazole in adults with MDD.
Methods
In a 16-week open-label clinical trial, 211 participants with MDD were treated with escitalopram 10– 20 mg daily for 8 weeks. Responders continued on escitalopram while non-responders received adjunctive aripiprazole 2–10 mg daily for 8 weeks. Plasma levels of pro-inflammatory markers – C-reactive protein, Interleukin (IL)-1β, IL-6, IL-17, Interferon gamma (IFN)-Γ, Tumour Necrosis Factor (TNF)-α, and Chemokine C–C motif ligand-2 (CCL-2) - measured at baseline, and after 2, 8 and 16 weeks were included in logistic regression analyses to assess associations between inflammatory markers and treatment response.
Results
Pre-treatment levels of IFN-Γ and CCL-2 were significantly higher in escitalopram non-responders compared to responders. Pre-treatment IFN-Γ and CCL-2 levels were significantly associated with a lower of odds of response to escitalopram at 8 weeks. Increases in CCL-2 levels from weeks 8 to 16 in escitalopram non-responders were significantly associated with higher odds of non-response to adjunctive aripiprazole at week 16.
Conclusions
Pre-treatment levels of IFN-Γ and CCL-2 were predictive of response to escitalopram. Increasing levels of these pro-inflammatory markers may predict non-response to adjunctive aripiprazole. These findings require validation in independent clinical populations.
Colliding collisionless shocks appear in a great variety of astrophysical phenomena and are thought to be possible sources of particle acceleration in the Universe. We have previously investigated particle acceleration induced by single super-critical shocks (whose magnetosonic Mach number is higher than the critical value of 2.7) (Yao et al., Nat. Phys., vol. 17, issue 10, 2021, pp. 1177–1182; Yao et al., Matter Radiat. Extrem., vol. 7, issue 1, 2022, 014402), as well as the collision of two sub-critical shocks (Fazzini et al., Astron. Astrophys., vol. 665, 2022, A87). Here, we propose to make measurements of accelerated particles from interpenetrating super-critical shocks to observe the ‘phase-locking effect’ (Fazzini et al., Astron. Astrophys., vol. 665, 2022, A87) from such an event. This effect is predicted to significantly boost the energy spectrum of the energized ions compared with a single super-critical collisionless shock. We thus anticipate that the results obtained in the proposed experiment could have a significant impact on our understanding of one type of primary source (acceleration of thermal ions as opposed to secondary acceleration mechanisms of already energetic ions) of ion energization of particles in the Universe.
In adults with Clostridioides difficile infection (CDI), higher stool concentrations of toxins A and B are associated with severe baseline disease, CDI-attributable severe outcomes, and recurrence. We evaluated whether toxin concentration predicts these presentations in children with CDI.
Methods:
We conducted a prospective cohort study of inpatients aged 2–17 years with CDI who received treatment. Patients were followed for 40 days after diagnosis for severe outcomes (intensive care unit admission, colectomy, or death, categorized as CDI primarily attributable, CDI contributed, or CDI not contributing) and recurrence. Baseline stool toxin A and B concentrations were measured using ultrasensitive single-molecule array assay, and 12 plasma cytokines were measured when blood was available.
Results:
We enrolled 187 pediatric patients (median age, 9.6 years). Patients with severe baseline disease by IDSA-SHEA criteria (n = 34) had nonsignificantly higher median stool toxin A+B concentration than those without severe disease (n = 122; 3,217.2 vs 473.3 pg/mL; P = .08). Median toxin A+B concentration was nonsignificantly higher in children with a primarily attributed severe outcome (n = 4) versus no severe outcome (n = 148; 19,472.6 vs 429.1 pg/mL; P = .301). Recurrence occurred in 17 (9.4%) of 180 patients. Baseline toxin A+B concentration was significantly higher in patients with versus without recurrence: 4,398.8 versus 280.8 pg/mL (P = .024). Plasma granulocyte colony-stimulating factor concentration was significantly higher in CDI patients versus non-CDI diarrhea controls: 165.5 versus 28.5 pg/mL (P < .001).
Conclusions:
Higher baseline stool toxin concentrations are present in children with CDI recurrence. Toxin quantification should be included in CDI treatment trials to evaluate its use in severity assessment and outcome prediction.
This study assesses governments' long-term non-pharmaceutical interventions upon the coronavirus disease 2019 (COVID-19) pandemic in East Asia. It advances the literature towards a better understanding of when and which control measures are effective. We (1) provide time-varying case fatality ratios and focus on the elderly's mortality and case fatality ratios, (2) measure the correlations between daily new cases (daily new deaths) and each index based on multiple domestic pandemic waves and (3) examine the lead–lag relationship between daily new cases (daily new deaths) and each index via the cross-correlation functions on the pre-whitened series. Our results show that the interventions reduce COVID-19 infections for some periods before the period of the Omicron variant. Moreover, there is no COVID-19 policy lag in Taiwan between daily new confirmed cases and each index. As of March 2022, the case fatality ratios of the elderly group in Japan, Hong Kong and South Korea are 4.69%, 4.72% and 1.48%, respectively, while the case fatality ratio of the elderly group in Taiwan is 25.01%. A government's COVID-19 vaccination distribution and prioritisation policies are pivotal for the elderly group to reduce the number of deaths. Immunising this specific group as best as possible should undoubtedly be a top priority.
Whole-genome sequencing (WGS) has traditionally been used in infection prevention to confirm or refute the presence of an outbreak after it has occurred. Due to decreasing costs of WGS, an increasing number of institutions have been utilizing WGS-based surveillance. Additionally, machine learning or statistical modeling to supplement infection prevention practice have also been used. We systematically reviewed the use of WGS surveillance and machine learning to detect and investigate outbreaks in healthcare settings.
Methods:
We performed a PubMed search using separate terms for WGS surveillance and/or machine-learning technologies for infection prevention through March 15, 2021.
Results:
Of 767 studies returned using the WGS search terms, 42 articles were included for review. Only 2 studies (4.8%) were performed in real time, and 39 (92.9%) studied only 1 pathogen. Nearly all studies (n = 41, 97.6%) found genetic relatedness between some isolates collected. Across all studies, 525 outbreaks were detected among 2,837 related isolates (average, 5.4 isolates per outbreak). Also, 35 studies (83.3%) only utilized geotemporal clustering to identify outbreak transmission routes. Of 21 studies identified using the machine-learning search terms, 4 were included for review. In each study, machine learning aided outbreak investigations by complementing methods to gather epidemiologic data and automating identification of transmission pathways.
Conclusions:
WGS surveillance is an emerging method that can enhance outbreak detection. Machine learning has the potential to identify novel routes of pathogen transmission. Broader incorporation of WGS surveillance into infection prevention practice has the potential to transform the detection and control of healthcare outbreaks.
Young people are most vulnerable to suicidal behaviours but least likely to seek help. A more elaborate study of the intrinsic and extrinsic correlates of suicidal ideation and behaviours particularly amid ongoing population-level stressors and the identification of less stigmatising markers in representative youth populations is essential.
Methods
Participants (n = 2540, aged 15–25) were consecutively recruited from an ongoing large-scale household-based epidemiological youth mental health study in Hong Kong between September 2019 and 2021. Lifetime and 12-month prevalence of suicidal ideation, plan, and attempt were assessed, alongside suicide-related rumination, hopelessness and neuroticism, personal and population-level stressors, family functioning, cognitive ability, lifetime non-suicidal self-harm, 12-month major depressive disorder (MDD), and alcohol use.
Results
The 12-month prevalence of suicidal ideation, ideation-only (no plan or attempt), plan, and attempt was 20.0, 15.4, 4.6, and 1.3%, respectively. Importantly, multivariable logistic regression findings revealed that suicide-related rumination was the only factor associated with all four suicidal outcomes (all p < 0.01). Among those with suicidal ideation (two-stage approach), intrinsic factors, including suicide-related rumination, poorer cognitive ability, and 12-month MDE, were specifically associated with suicide plan, while extrinsic factors, including coronavirus disease 2019 (COVID-19) stressors, poorer family functioning, and personal life stressors, as well as non-suicidal self-harm, were specifically associated with suicide attempt.
Conclusions
Suicide-related rumination, population-level COVID-19 stressors, and poorer family functioning may be important less-stigmatising markers for youth suicidal risks. The respective roles played by not only intrinsic but also extrinsic factors in suicide plan and attempt using a two-stage approach should be considered in future preventative intervention work.
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.
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
Aims
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
Method
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
Results
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Conclusions
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.