Rapid identification and determination of adulteration in medicinal Arnebiae Radix by combining near infrared spectroscopy with chemometrics.

The medicinal Arnebia Radix (AR) is one of widely-used Chinese herbal medicines (CHMs), usually adulterated with non-medicinal species that seriously compromise the quality of AR and affect patients' health. Detection of these adulterants is usually performed by using expensive and time-consuming analytical instruments. In this study, a rapid, non-destructive, and effective method was proposed to identify and determine the adulteration in the medicinal AR by near-infrared (NIR) spectroscopy coupled with chemometrics. 37 batches of medicinal AR samples originated from Arnebia euchroma (Royle) Johnst., 11 batches of non-medicinal AR samples including Onosma paniculatum Bur. et Franch and Arnebia benthamii (Wall. ex G. Don) Johnston, and 72 batches of adulterated AR samples were characterized by NIR spectroscopy. The data driven-soft independent modeling by class analogy (DD-SIMCA) and partial least squares-discriminant analysis (PLS-DA) were separately used to differentiate the authentic from adulterated AR samples. Then the PLS and support vector machine (SVM) were applied to predict the concentration of the adulteration in the adulterated AR samples, respectively. As a result, the classification accuracies of DD-SIMCA and PLS-DA models were 100% for the calibration set, and 96.7% vs. 100% for the prediction set. Moreover, the relative prediction deviation (RPD) values of PLS models reached 11.38 and 7.75 for quantifying two adulterants species, which were obviously superior to the SVM models. It can be concluded that the NIR spectroscopy coupled with chemometrics is feasible to identify the authentic from adulterated AR samples and quantify the adulteration in adulterated AR samples.

Identifying the active ingredients of carbonized Typhae Pollen by spectrum-effect relationship combined with MBPLS, PLS, and SVM algorithms.

Typhae Pollen (TP) and its carbonized product (carbonized Typhae Pollen, CTP), as cut-and-dried herbal drugs, have been widely used in the form of slices in clinical settings. However, the two drugs exhibit a great difference in terms of their clinical efficacy, for TP boasts an effect of removing blood stasis and promoting blood circulation, while CTP typically presents a hemostatic function. Since the active ingredients of CTP, so far, still remain unclear, this study aimed at identifying the active ingredients of CTP by spectrum-effect relationship approach coupled with multi-block partial least squares (MBPLS), partial least squares (PLS), and support vector machine (SVM) algorithms. In this study, the chemical profiles of a series of CTP samples which were stir-fried for different duration (denoted as CTP0∼CTP9) were firstly characterized by UHPLC-QE-Orbitrap MS. Then the hemostatic effect of the CTP samples was evaluated from the perspective of multiple parameters-APTT, PT, TT, FIB, TXB2, 6-keto-PGF1α, PAI-1 and t-PA-using established rat models with functional uterine bleeding. Subsequently, MBPLS, PLS and SVM were combined to perform spectrum-effect relationship analysis to identify the active ingredients of CTP, followed by an in vitro hemostatic bioactivity test for verification. As a result, a total of 77 chemical ingredients were preliminarily identified from the CTP samples, and the variations occurred in these ingredients were also analyzed during the carbonizing process. The study revealed that all the CTP samples, to a varying degree, showed a hemostatic effect, among which CTP6 and CTP7 were superior to the others in terms of the hemostatic effect. The block importance in the projection (BIP) indexes of MBPLS model indicated that flavonoids and organic acids made more contributions to the hemostatic effect of CTP in comparison to other ingredients. Consequently, 9 bioactive ingredients, including quercetin-3-O-glucoside, kaempferol-3-O-rutinoside, quercetin, kaempferol, isorhamnetin, 2-methylenebutanedioic acid, pentanedioic acid, benzoic acid and 3-hydroxybenzoic acid, were further identified as the potential active ingredients based on PLS and SVM models as well as the in vitro verification. This study successfully revealed the bioactive ingredients of CTP associated with its hemostatic effect, and also provided a scientific basis for further understanding the mechanism of TP processing. In addition, it proposed a novel path to identify the active ingredients for Chinese herbal medicines.

Fetal inflammatory response and risk for psychiatric disorders.

Inflammation contributes to numerous neuropsychiatric disorders, especially those that first appear in childhood. Maternal intrauterine environment, including the placenta, has a role in brain development and risk for neuropsychiatric disorders. This study examines the link between fetal inflammatory syndrome (FIRS), which is placental inflammation in the peri-partem period, and neuropsychiatric disorders during childhood.This is a retrospective cohort study using data from electronic medical records over a 19-year period at one women's hospital. The study includes 4851 children born with placentas meeting criteria for and 31,927 controls identified with normal placentas born during the same period. To be diagnosed with FIRS placenta must contain chorionic vasculitis and/or funisitis. Children had to be in study period for at least 5 years. The primary outcome of the study is incidence of neuropsychiatric disorders during childhood. The secondary outcomes were psychiatric medications prescribed, and psychiatric hospitalizations and treatment. Children born to placentas meeting criteria for FIRS were more likely to be diagnosed with neuropsychiatric disorders (OR = 1.21, CI 95% [1.09,1.35]). Specifically, they were more likely to be diagnosed with autism spectrum disorder (OR = 1.35, CI 95% [1.08, 1.67]), ADHD (OR = 1.27, CI 95% [1.07, 1.49]), conduct disorder (OR = 1.50, CI 95% [1.24, 1.81]), PTSD (OR = 2.46. CI 95% [1.21, 5.04]), adjusting for maternal history of psychiatric disorders, intra-partem substance use, and prescriptions of anti-inflammatory drugs. Children born with placental inflammation are at an increased risk to develop neuropsychiatric disorders. This has profound implications for future research, and early detection, monitoring, and treatment in these children.

Clinically stable covid-19 patients presenting to acute unscheduled episodic care venues have increased risk of hospitalization: secondary analysis of a randomized control trial.

BACKGROUND: Assessment for risks associated with acute stable COVID-19 is important to optimize clinical trial enrollment and target patients for scarce therapeutics. To assess whether healthcare system engagement location is an independent predictor of outcomes we performed a secondary analysis of the ACTIV-4B Outpatient Thrombosis Prevention trial. METHODS: A secondary analysis of the ACTIV-4B trial that was conducted at 52 US sites between September 2020 and August 2021. Participants were enrolled through acute unscheduled episodic care (AUEC) enrollment location (emergency department, or urgent care clinic visit) compared to minimal contact (MC) enrollment (electronic contact from test center lists of positive patients).We report the primary composite outcome of cardiopulmonary hospitalizations, symptomatic venous thromboembolism, myocardial infarction, stroke, transient ischemic attack, systemic arterial thromboembolism, or death among stable outpatients stratified by enrollment setting, AUEC versus MC. A propensity score for AUEC enrollment was created, and Cox proportional hazards regression with inverse probability weighting (IPW) was used to compare the primary outcome by enrollment location. RESULTS: Among the 657 ACTIV-4B patients randomized, 533 (81.1%) with known enrollment setting data were included in this analysis, 227 from AUEC settings and 306 from MC settings. In a multivariate logistic regression model, time from COVID test, age, Black race, Hispanic ethnicity, and body mass index were associated with AUEC enrollment. Irrespective of trial treatment allocation, patients enrolled at an AUEC setting were 10-times more likely to suffer from the adjudicated primary outcome, 7.9% vs. 0.7%; p < 0.001, compared with patients enrolled at a MC setting. Upon Cox regression analysis adjustment patients enrolled at an AUEC setting remained at significant risk of the primary composite outcome, HR 3.40 (95% CI 1.46, 7.94). CONCLUSIONS: Patients with clinically stable COVID-19 presenting to an AUEC enrollment setting represent a population at increased risk of arterial and venous thrombosis complications, hospitalization for cardiopulmonary events, or death, when adjusted for other risk factors, compared with patients enrolled at a MC setting. Future outpatient therapeutic trials and clinical therapeutic delivery programs of clinically stable COVID-19 patients may focus on inclusion of higher-risk patient populations from AUEC engagement locations. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04498273.

Defining representativeness of study samples in medical and population health research.

Medical and population health science researchers frequently make ambiguous statements about whether they believe their study sample or results are representative of some (implicit or explicit) target population. This article provides a comprehensive definition of representativeness, with the goal of capturing the different ways in which a study can be representative of a target population. It is proposed that a study is representative if the estimate obtained in the study sample is generalisable to the target population (owing to representative sampling, estimation of stratum specific effects, or quantitative methods to generalise or transport estimates) or the interpretation of the results is generalisable to the target population (based on fundamental scientific premises and substantive background knowledge). This definition is explored in the context of four covid-19 studies, ranging from laboratory science to descriptive epidemiology. All statements regarding representativeness should make clear the way in which the study results generalise, the target population the results are being generalised to, and the assumptions that must hold for that generalisation to be scientifically or statistically justifiable.

Who is trying to lose weight? Trends and prevalence in past-year weight loss attempts among US adults 1999-2018 at the intersection of race/ethnicity, gender, and weight status.

Common stereotypes of those who desire or attempt to lose weight often center on the experience of White, thin women. However, prior studies have neglected how systems of oppression at intersection of race/ethnicity, gender, and weight status may interact to place certain subpopulations at elevated risk. Repeated cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 (n = 53,528), a population-representative sample of US adults, were used to 1) assess trends in past-year weight loss attempts using the Kendall-Mann trend test stratifying by race/ethnicity, gender, and weight status, and 2) estimate the adjusted prevalence of weight loss attempts over the combined 20-year period for combinations of race/ethnicity, gender, and weight status using logistic regression. There were significant monotonic trends from 1999 to 2018 for non-Hispanic Black men (43.8% to 67.8%, FDR adjusted p = .022) with an obese BMI, but not for any other groups. After adjusting for covariates, weight loss attempt prevalence was positively associated with BMI category for all race/ethnicity-gender combinations, although the degree of association differed. These findings underscore the need to use an intersectional lens in weight-related research. Despite limited long-term beneficial health impact, certain population subgroups, particularly Black men with an obese BMI, are increasingly trying to lose weight.

Combining ultra-high-performance liquid chromatography quadruple exactive orbitrap mass spectrometry with chemometrics to identify and verify the blood-activating components of hawthorn.

Hawthorn, one of the widely-used Chinese herbal medicines, has been used to treat blood stasis syndrome in the clinic, but its blood-activating components are unclear. This study combined the ultra-high-performance liquid chromatography-quadruple exactive-orbitrap mass spectrometry with chemometrics to identify the blood-activating components of hawthorn. Different polar fractions of hawthorn aqueous extracts were extracted and mixed to prepare 14 samples. The contents of 25 chemical components for 14 samples were determined by the proposed quantitative method which was validated in terms of linearity, precision, stability, repeatability, and recovery, while the blood-activating effect was evaluated by measuring the whole blood viscosity, plasma viscosity, and plasma fibrinogen levels. Then the partial least squares model was established on the spectrum-effect relationship. The result showed that vitexin-2″-O-rhamnoside, rutin, citric acid, malic acid, gallic acid, and fumaric acid could reduce the whole blood viscosity, plasma viscosity, and plasma fibrinogen levels in blood stasis model rats, and these components were the blood-activating components of hawthorn. This study provided a scientific basis for clarifying the blood-activating components of hawthorn, and the spectrum-effect approach proved to be an effective approach to discovering the bioactive components of Chinese herbal medicines.

Developing the liquid chromatography-mass spectrometry method for simultaneously quantifying five components in rat serums after oral administration of hawthorn aqueous extracts and its application to a pharmacokinetic study.

Hawthorn, one of the widely-used traditional Chinese medicines, has been used to treat dyspepsia, hyperlipidemia, and cardiovascular disease in the clinic. Our previous study revealed that gallic acid, neochlorogenic acid, cryptochlorogenic acid, vitexin, and quercetin were active components of hawthorn. In this study, a simple, precise, and reliable liquid chromatography-mass spectrometry method was developed for the simultaneous quantification of five components in rat serums. The separation was achieved on the Hypersil GOLD C18 column, and the mobile phases consisted of 0.1% acetic acid water and methanol at a flow rate of 0.3 mL/min. The mass spectrometry data acquisition was performed on Q-Extractive-Orbitrap mass spectrometry with an electrospray ionization source in negative ion mode. The proposed liquid chromatography-mass spectrometry method was validated in terms of linearity, intra- and inter-precision, accuracy, recoveries, matrix effects, and stability. Then this newly proposed liquid chromatography-mass spectrometry method was successfully applied to a pharmacokinetic study on rats after oral administration of hawthorn aqueous extracts. This study provided relevant information on the pharmacokinetics of active components of hawthorn and explained the underlying mechanism of their bioactivity.

Use of Machine Learning to Estimate the Per-Protocol Effect of Low-Dose Aspirin on Pregnancy Outcomes: A Secondary Analysis of a Randomized Clinical Trial.

Importance: In randomized clinical trials (RCTs), per-protocol effects may be of interest in the presence of nonadherence with the randomized treatment protocol. Using machine learning in per-protocol effect estimation can help avoid model misspecification owing to strong parametric assumptions, as is common with standard methods (eg, logistic regression). Objectives: To demonstrate the use of ensemble machine learning with augmented inverse probability weighting (AIPW) for per-protocol effect estimation in RCTs and to evaluate the per-protocol effect size of aspirin on pregnancy. Design, Setting, and Participants: This secondary analysis used data from 1227 women in the Effects of Aspirin in Gestation and Reproduction (EAGeR) trial, a multicenter, block-randomized, double-blind, placebo-controlled clinical trial of the effect of daily low-dose aspirin on pregnancy outcomes in women at high risk of pregnancy loss. Participants were recruited at 4 university medical centers in the US from June 15, 2007, to July 15, 2012. Women were followed up for 6 menstrual cycles for attempted pregnancy and 36 weeks of gestation if pregnancy occurred. Follow-up was completed on August 17, 2012. Data analyses were performed on July 9, 2021. Exposures: Daily low-dose (81 mg) aspirin taken at least 5 of 7 days per week for at least 80% of follow-up time relative to placebo. Main Outcomes and Measures: Pregnancy detected using human chorionic gonadotropin (hCG) levels. Results: Among the 1227 women included in the analysis (mean SD age, 28.74 [4.80] years), 1161 (94.6%) were non-Hispanic White and 858 (69.9%) adhered to the protocol. Five machine learning models were combined into 1 meta-algorithm, which was used to construct an AIPW estimator for the per-protocol effect. Compared with adhering to placebo, adherence to the daily low-dose aspirin protocol for at least 5 of 7 days per week was associated with an increase in the probability of hCG-detected pregnancy of 8.0 (95% CI, 2.5-13.6) more hCG-detected pregnancies per 100 women in the sample, which is substantially larger than the estimated intention-to-treat estimate of 4.3 (95% CI, -1.1 to 9.6) more hCG-detected pregnancies per 100 women in the sample. Conclusions and Relevance: These findings suggest that a low-dose aspirin protocol is associated with increased hCG-detected pregnancy in women who adhere to treatment for at least 5 days per week. With the presence of nonadherence, per-protocol treatment effect estimates differ from intention-to-treat estimates in the EAGeR trial. The results of this secondary analysis of clinical trial data suggest that machine learning could be used to estimate per-protocol effects by adjusting for confounders related to nonadherence in a more flexible way than traditional regressions. Trial Registration: ClinicalTrials.gov Identifier: NCT00467363.

Increased burden of cardiovascular risk among youth suicide attempters.

BACKGROUND: Suicide and cardiovascular disease rank among the leading causes of disability and premature mortality worldwide. Young adult suicide attempters are at increased risk of mortality from cardiovascular disease even compared to those with major depressive disorder suggesting an increased burden of cardiovascular risk factors. We compared the cardiovascular risk burden between youth attempters and other high-risk individuals. METHODS: Participants were from the Collaborative Psychiatric Epidemiology Surveys (CPES), a U.S. population-based study, aged 18-30 years [suicide attempt (SA): n = 303; suicidal ideation (SI): n = 451; controls: n = 3671]; and psychiatric inpatients admitted for a SA (n = 38) or SI (n = 40) and healthy controls (n = 37) aged 15-30 years. We computed a cardiovascular risk score and high- and low-risk latent classes based on risk factors of high blood pressure, obesity, and smoking. RESULTS: Suicide attempters showed an increased cardiovascular risk score (CPES: B = 0.43, 95% confidence interval (CI) 0.31-0.54, p < 0.001; inpatient sample: B = 1.61, 95% CI 0.53-2.68, p = 0.004) compared to controls. They were also more likely to be classified in the high cardiovascular risk group (CPES: odds ratio (OR) 3.36, 95% CI 1.67-6.78, p = 0.001; inpatient sample: OR 9.89, 95% CI 1.38-85.39, p = 0.03) compared to those with SI (CPES: OR 1.15, 95% CI 0.55-2.39, p = 0.71; inpatient sample: OR 1.91, 95% CI 0.25-15.00, p = 0.53). CONCLUSIONS: Youth attempters show an increased burden for cardiovascular risk compared to other high-risk individuals in inpatient and population-based samples. Clinicians should pay particular attention to cardiovascular risk factors among suicide attempters in order to reduce their risk for cardiovascular events.

Brain 5-HT1A Receptor PET Binding, Cortisol Responses to Stress, and the Familial Transmission of Suicidal Behavior.

BACKGROUND: The serotonin 1A (5-HT1A) receptor has been implicated in depression and suicidal behavior. Lower resting cortisol levels are associated with higher 5-HT1A receptor binding, and both differentiate suicide attempters with depression. However, it is not clear whether 5-HT1A receptor binding and cortisol responses to stress are related to familial risk and resilience for suicidal behavior. METHODS: [11C]CUMI-101 positron emission tomography imaging to quantify regional brain 5-HT1A receptor binding was conducted in individuals considered to be at high risk for mood disorder or suicidal behavior on the basis of having a first- or second-degree relative(s) with an early onset mood disorder and history of suicidal behavior. These high-risk individuals were subdivided into the following groups: high risk resilient having no mood disorder or suicidal behavior (n = 29); high risk with mood disorder and no suicidal behavior history (n = 31); and high risk with mood disorder and suicidal behavior (n = 25). Groups were compared with healthy volunteers without a family history of mood disorder or suicidal behavior (n = 34). Participants underwent the Trier Social Stress Task (TSST). All participants were free from psychotropic medications at the time of the TSST and PET scanning. RESULTS: We observed no group differences in 5-HT1A receptor binding considering all regions simultaneously, nor did we observe heterogeneity of the effect of group across regions. These results were similar across outcome measures (BPND for all participants and BPp in a subset of the sample) and definitions of regions of interest (ROIs; standard or serotonin system-specific ROIs). We also found no group differences on TSST outcomes. Within the high risk with mood disorder and suicidal behavior group, lower BPp binding (ß = -0.084, SE = 0.038, P = .048) and higher cortisol reactivity to stress (ß = 9.25, 95% CI [3.27,15.23], P = .004) were associated with higher lethality attempts. There were no significant relationships between 5-HT1A binding and cortisol outcomes. CONCLUSIONS: 5-HT1A receptor binding in ROIs was not linked to familial risk or resilience protecting against suicidal behavior or mood disorder although it may be related to lethality of suicide attempt. Future studies are needed to better understand the biological mechanisms implicated in familial risk for suicidal behavior and how hypothalamic-pituitary-adrenal axis function influences such risk.

Opioid use as a proximal risk factor for suicidal behavior in young adults.

INTRODUCTION: There is a concomitant rise in suicide rates with the prevalence of opioids involved in overdose deaths, especially among adolescents and young adults. However, there are limited studies on whether opioid use prospectively predicts suicidal behavior in youth. METHODS: Our sample included 183 psychiatric patients (18-30 years) admitted for a suicide attempt (SA), have current suicidal ideation (SI), and psychiatric controls without ideation or attempt (PC). Suicidal behavior was assessed using the Columbia Suicide Severity Rating Scale. We also recruited a healthy control group (HC; n = 40). Patients and controls were followed over a year. ANOVA, regression, and cox regression were used. RESULTS: Suicide attempt (ß = 0.87, CI [0.1-1.6], p = 0.02) and SI [(ß = 0.75, CI [0.03-1.5], p = 0.04) were significantly more likely than HCs to have used opioids in the past year at baseline. Opioid use was associated with increased anxiety symptoms (ß = 0.75, CI [0.001-1.5], p = 0.05), PTSD symptoms (ß = 3.90, CI [1.1-6.7], p = 0.01), and aggression (ß = 0.02, CI [0.01-0.04], p = 0.02). Opioid use in the month prior to hospitalization predicted SA at 6 months (OR = 1.87, CI [1.06-3.31], p = 0.032). CONCLUSIONS: Opioid use is a proximal predictor for SA. These findings may help clinicians better identify patients at risk for suicidal behavior, allowing for more personalized treatment approaches.

Effect of Antithrombotic Therapy on Clinical Outcomes in Outpatients With Clinically Stable Symptomatic COVID-19: The ACTIV-4B Randomized Clinical Trial.

Importance: Acutely ill inpatients with COVID-19 typically receive antithrombotic therapy, although the risks and benefits of this intervention among outpatients with COVID-19 have not been established. Objective: To assess whether anticoagulant or antiplatelet therapy can safely reduce major adverse cardiopulmonary outcomes among symptomatic but clinically stable outpatients with COVID-19. Design, Setting, and Participants: The ACTIV-4B Outpatient Thrombosis Prevention Trial was designed as a minimal-contact, adaptive, randomized, double-blind, placebo-controlled trial to compare anticoagulant and antiplatelet therapy among 7000 symptomatic but clinically stable outpatients with COVID-19. The trial was conducted at 52 US sites between September 2020 and June 2021; final follow-up was August 5, 2021. Prior to initiating treatment, participants were required to have platelet count greater than 100 000/mm3 and estimated glomerular filtration rate greater than 30 mL/min/1.73 m2. Interventions: Random allocation in a 1:1:1:1 ratio to aspirin (81 mg orally once daily; n = 164), prophylactic-dose apixaban (2.5 mg orally twice daily; n = 165), therapeutic-dose apixaban (5 mg orally twice daily; n = 164), or placebo (n = 164) for 45 days. Main Outcomes and Measures: The primary end point was a composite of all-cause mortality, symptomatic venous or arterial thromboembolism, myocardial infarction, stroke, or hospitalization for cardiovascular or pulmonary cause. The primary analyses for efficacy and bleeding events were limited to participants who took at least 1 dose of trial medication. Results: On June 18, 2021, the trial data and safety monitoring board recommended early termination because of lower than anticipated event rates; at that time, 657 symptomatic outpatients with COVID-19 had been randomized (median age, 54 years [IQR, 46-59]; 59% women). The median times from diagnosis to randomization and from randomization to initiation of study treatment were 7 days and 3 days, respectively. Twenty-two randomized participants (3.3%) were hospitalized for COVID-19 prior to initiating treatment. Among the 558 patients who initiated treatment, the adjudicated primary composite end point occurred in 1 patient (0.7%) in the aspirin group, 1 patient (0.7%) in the 2.5-mg apixaban group, 2 patients (1.4%) in the 5-mg apixaban group, and 1 patient (0.7%) in the placebo group. The risk differences compared with placebo for the primary end point were 0.0% (95% CI not calculable) in the aspirin group, 0.7% (95% CI, -2.1% to 4.1%) in the 2.5-mg apixaban group, and 1.4% (95% CI, -1.5% to 5.0%) in the 5-mg apixaban group. Risk differences compared with placebo for bleeding events were 2.0% (95% CI, -2.7% to 6.8%), 4.5% (95% CI, -0.7% to 10.2%), and 6.9% (95% CI, 1.4% to 12.9%) among participants who initiated therapy in the aspirin, prophylactic apixaban, and therapeutic apixaban groups, respectively, although none were major. Findings inclusive of all randomized patients were similar. Conclusions and Relevance: Among symptomatic clinically stable outpatients with COVID-19, treatment with aspirin or apixaban compared with placebo did not reduce the rate of a composite clinical outcome. However, the study was terminated after enrollment of 9% of participants because of an event rate lower than anticipated. Trial Registration: ClinicalTrials.gov Identifier: NCT04498273.

Collaboration on evidence synthesis in Africa: a network study of growing research capacity.

BACKGROUND: Evidence-based practice in medicine and social policy relies heavily on evidence synthesis. To translate evidence into practical guidelines for low- and middle-income countries, local expertise is essential. The objectives of this study are to assess the change in capacity for conducting evidence synthesis in Africa and to identify key African institutions for regional capacity-building. We take on a network perspective, considering that the position of an institution in the African evidence ecosystem is one constituent of its research capacity. METHODS: We systematically identified 3548 evidence synthesis publications between 2008 and 2019 with at least one author in Africa from the Web of Science Core Collection. These articles involved 3769 institutions. Longitudinal institution-level collaboration network data were constructed based on co-authorship information. We used social network analysis to examine the institutions' connectivity and tendency for intra- and interregional collaboration. We also identified the degree- and betweenness-central African institutions and explored the structure and composition of their local network neighbourhoods. RESULTS: The number of African institutions involved in evidence synthesis has increased substantially over the last decade, from 31 in 2008 to 521 in 2019, and so has the number of evidence synthesis publications with authors in Africa. African institutions in the evidence ecosystem have also become more connected during this period. Although the amount of intercontinental collaboration continues to exceed that of regional collaboration, the tendency for African institutions to collaborate with partners in Africa is increasing. We identified seven institutions-in South Africa, Egypt and Uganda-as central to the collaboration networks between 2008 and 2019, all of whom showed a tendency to collaborate across sectors. CONCLUSION: The development of more regionally based network-building initiatives would help to foster communities of practice and inter-institutional collaboration, strengthening regional research capacity. Moreover, the analysis in this study adds depth beyond a simple bibliometric analysis and illustrates that network analysis could provide a useful tool to evaluate the effectiveness of capacity-building strategies and programmes in the future.

AIPW: An R Package for Augmented Inverse Probability-Weighted Estimation of Average Causal Effects.

An increasing number of recent studies have suggested that doubly robust estimators with cross-fitting should be used when estimating causal effects with machine learning methods. However, not all existing programs that implement doubly robust estimators support machine learning methods and cross-fitting, or provide estimates on multiplicative scales. To address these needs, we developed AIPW, a software package implementing augmented inverse probability weighting (AIPW) estimation of average causal effects in R (R Foundation for Statistical Computing, Vienna, Austria). Key features of the AIPW package include cross-fitting and flexible covariate adjustment for observational studies and randomized controlled trials (RCTs). In this paper, we use a simulated RCT to illustrate implementation of the AIPW estimator. We also perform a simulation study to evaluate the performance of the AIPW package compared with other doubly robust implementations, including CausalGAM, npcausal, tmle, and tmle3. Our simulation showed that the AIPW package yields performance comparable to that of other programs. Furthermore, we also found that cross-fitting substantively decreases the bias and improves the confidence interval coverage for doubly robust estimators fitted with machine learning algorithms. Our findings suggest that the AIPW package can be a useful tool for estimating average causal effects with machine learning methods in RCTs and observational studies.

Early Cortisol and Inflammatory Responses to Parental Cancer and Their Impact on Functional Impairment in Youth.

PURPOSE: Chronic stress is associated with increased risk for maladaptive psychological responses during childhood, adolescence, and young adulthood. Adults exposed to chronic stress during childhood exhibit dysregulation of hypothalamic-pituitary-adrenal (HPA) axis activity and inflammation. There are no studies examining the impact of stress on biological stress responses and functional impairment in adolescents and young adults early after the onset of a stressor. METHODS: The sample consisted of 59 offspring, aged 11-25 years, 33 of parents diagnosed with cancer and 26 controls from families with no cancer or severe chronic illness in parents or siblings. Cancer patients and their families were recruited within an average of 62 days (SD = 35.9) and followed at 6 and 9 months later. Functional impairment was assessed and hair cortisol concentrations (HCC), salivary cortisol, and inflammatory markers were measured. Mixed regression analyses were conducted. RESULTS: The stress group showed higher functional impairment (ß = -5.5, 95% CI (-10.4, -0.06), p = 0.03, d= -0.40) and HCC (ß = 10.5, 95% CI (-5.5, -0.50), p < 0.001, d = 1.43). However, HCC were reduced over time in the stress group (ß= -0.3, 95% CI (-0.04, -0.01), p < 0.001, d = -1.08). Higher total cortisol output was associated with increased functional impairment over time (ß = -3.0, 95% CI (-5.5, -0.5), p = 0.02, d = -0.60). CONCLUSIONS: Parental cancer is associated with early increase in cortisol, which was associated with increased functional impairment in offspring. Clinicians need to assess and monitor psychiatric symptoms and functioning in these offspring early on following parental cancer diagnosis.

The psychiatric sequelae of the COVID-19 pandemic in adolescents, adults, and health care workers.

BACKGROUND: The COVID-19 pandemic is the most serious global public health crisis since the 1918 influenza pandemic. This study is the first to assess its mental health impact across the lifespan in the United States in adolescents, adults, and health care workers. METHODS: We recruited 4909 participants through an online survey advertising on Facebook and Instagram to assess exposure to COVID-19 and psychiatric symptoms from April 27 to July 13. We also recruited through the University of Pittsburgh, University of Pittsburgh Medical Center, and other health care systems around Pittsburgh. The primary outcomes were clinically significant depression, anxiety, and posttraumatic stress disorder (PTSD) symptoms, suicidal ideation or behavior, and grief reactions since COVID-19. RESULTS: Adolescents were significantly more likely to report moderate to severe symptoms of depression (55% vs. 29%; χ2 = 122, df = 1; p < .001), anxiety (48% vs. 29%; χ2 = 73; df = 1; p < .001), PTSD (45% vs. 33%; χ2 = 12; df = 1; p < .001), suicidal ideation or behavior (38% vs. 16%; χ2 = 117; df = 1; p < .001), and sleep problems (69% vs. 57%; χ2 = 26; df = 1; p < .001) compared to adults. The rates of intense grief reactions among those who lost someone to COVID-19 was 55%. Loneliness was the most common predictor across outcomes and higher number of hours spent on social media and exposure to media about COVID-19 predicted depression symptoms and suicidal ideation or behavior in adolescents. CONCLUSIONS: The COVID-19 pandemic is associated with increased rates of clinically significant psychiatric symptoms. Loneliness could put individuals at increased risk for the onset of psychiatric disorders.

Identification of the significant pathways of Banxia Houpu decoction in the treatment of depression based on network pharmacology.

Banxia Houpu decoction (BXHPD) has been used to treat depression in clinical practice for centuries. However, the pharmacological mechanisms of BXHPD still remain unclear. Network Pharmacology (NP) approach was used to explore the potential molecular mechanisms of BXHPD in treating depression. Potential active compounds of BXHPD were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform Database. STRING database was used to build a interaction network between the active compounds and target genes associated with depression. The topological features of nodes were visualized and calculated. Significant pathways and biological functions were identified using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. A total of 44 active compounds were obtained from BXHPD, and 121 potential target genes were considered to be therapeutically relevant. Pathway analysis indicated that MAPK signaling pathway, ErbB signaling pathway, HIF-1 signaling pathway and PI3K-Akt pathway were significant pathways in depression. They were mainly involved in promoting nerve growth and nutrition and alleviating neuroinflammatory conditions. The result provided some potential ways for modern medicine in the treatment of depression.

Signaling networks in inflammatory pathways and risk for suicidal behavior.

BACKGROUND: Suicide is a leading cause of death in the young adult population, with few biological markers identified thus far to be associated with suicidality. Cytokines (including IL-6 and TNFα) may contribute to increased risk for depression and suicidality. Few studies have examined the associations of cytokine mRNA expression with depression and suicidal ideation and behavior. This study examines these associations and whether cytokine signaling networks differentiate suicide attempters (SA), suicide ideators (SI), and healthy controls (HC). METHODS: Cytokine pathway marker (CPM; e.g. cytokines and proteins in cytokine signaling pathways) mRNA gene expression in whole blood was examined in suicide attempters (n = 38), suicide ideators (n = 38), and healthy controls (n = 36). Between-group differences in CPM gene expression were examined. We also examined association of the mRNA of these genes with the severity of depression and suicidal ideation. Novel Gaussian Graphical Model (GGM) techniques were utilized to examine between-network partial correlation differences in cytokine signaling networks relevant to IL-6 and TNFα signaling pathways. RESULTS: The severity of depression symptoms was positively associated with TNFα mRNA levels and negatively associated with IL-10 mRNA levels, but CPM expression was not associated with suicidal ideation severity. There were no between-group differences in CPM markers among healthy controls, SI and SA groups after correcting for multiple comparisons. In network analyses, we found suggestive results of between-group network differences between SI and control groups in gene pairs with IL-6R and STAT3 as common nodes. DISCUSSION: In a cohort of suicide attempters and ideators, TNFα and IL-10 mRNA levels appear to be associated with depressive symptomology, consistent with elevation of pro-inflammatory cytokine production and reduction of anti-inflammatory cytokine production. Additionally, cytokine signaling networks may differentiate suicide ideators from healthy controls based on between-network differences, with differences possibly related to relationships of IL6R or STAT3 with other components of cytokine signaling networks.