Survival Following Diagnosis of HIV-Associated Kaposi Sarcoma Among Adults in East Africa in the "Treat-All" Era.

Background: Despite widespread access to antiretroviral therapy (ART) in the "Treat All" era, HIV-associated Kaposi sarcoma (KS) remains among the most common malignancies in sub-Saharan Africa. Survival after KS diagnosis has historically been poor in Africa, but knowledge whether survival has changed at the population level in the contemporary era has been limited by lack of community-representative surveillance and monitoring systems. Methods: We identified all adult persons living with HIV (PLWH) with a new diagnosis of KS made between 2016 and 2019 during outpatient or inpatient care at prototypical primary care-providing medical facilities in Kenya and Uganda using rapid case ascertainment. Participants were subsequently followed for vital status, including community tracking for those who became lost to follow-up. Findings: Among 411 participants with newly diagnosed KS, 71% were men, median age was 34 (IQR: 30 to 41) years, and 91% had ACTG T1 tumor extent. Over a median follow-up of 7.8 (IQR: 2.4 to 17.9) months, cumulative incidence of death (95% CI) at months 6, 12 and 18 were 34% (30% to 39%), 41% (36% to 46%) and 45% (40% to 51%), respectively. Having the highest number of anatomic sites (11 to 16) harboring KS lesions (hazard ratio 2.2 (95% CI: 1.3-3.8) compared to 1 to 3 sites) and presence of oral KS lesions (hazard ratio 2.2 (95% CI: 1.4-3.3)) were independently associated with higher mortality. Lower hemoglobin and CD4 count as well as higher plasma HIV RNA were also associated with higher mortality. Interpretation: Among PLWH with newly diagnosed KS in East Africa in the "Treat All" era, survival was poor and related to mucocutaneous extent of KS. The findings emphasize the need for better control of KS in Africa, including novel approaches for earlier detection, better linkage to oncologic care, and more potent therapy.

Identifying dose constraints for the parotid ducts to minimize patient-reported xerostomia: Is conventional mean dose sparing of the parotid glands sufficient?

BACKGROUND AND PURPOSE: The aim of this study was to identify dose constraints for the parotid ducts that limit patient-reported xerostomia and estimate whether these constraints are achieved during conventional parotid gland sparing radiation therapy (PGS-RT). METHODS AND MATERIALS: Thirty-eight oropharyngeal squamous cell carcinoma patients were treated prospectively on trial with MRI sialography-guided parotid duct sparing radiation therapy (PDS-RT). PDS-RT explicitly minimizes dose to the parotid ducts in addition to PGS-RT. Parotid duct dose constraints were identified that distinguished patients reporting high and low rates of xerostomia. Atlas-based parotid duct contours were generated on a retrospective cohort of similar patients where the parotid ducts were not contoured nor explicitly spared to estimate the dose received by the parotid ducts during PGS-RT. RESULTS: Patients whose intraglandular parotid ducts or total parotid ducts were planned for a mean dose < 14 Gy and < 12 Gy, respectively, reported significantly (p < 0.01) lower rates of xerostomia at 6 and 12 months post-RT. Patients receiving PDS-RT had average total and intraglandular duct doses of 11.6  and 13.6 Gy, respectively, compared to an estimated 23.8  and 22.1 Gy, for those receiving PGS-RT (p < 0.01). Only 6% (6/108) and 20% (22/108) of patients receiving PGS-RT were estimated to meet the dose constraints for the total ducts and intraglandular ducts, respectively. CONCLUSION: Parotid duct dose thresholds exist that appear to distinguish patients with and without xerostomia. The identified dose thresholds are frequently not met in PGS-RT plans. In addition to reducing the dose to the parotid gland(s), parotid duct sparing may also further reduce xerostomia.

An extension of latent unknown clustering integrating multi-omics data (LUCID) incorporating incomplete omics data.

Motivation: Latent unknown clustering integrating multi-omics data is a novel statistical model designed for multi-omics data analysis. It integrates omics data with exposures and an outcome through a latent cluster, elucidating how exposures influence processes reflected in multi-omics measurements, ultimately affecting an outcome. A significant challenge in multi-omics analysis is the issue of list-wise missingness. To address this, we extend the model to incorporate list-wise missingness within an integrated imputation framework, which can also handle sporadic missingness when necessary. Results: Simulation studies demonstrate that our integrated imputation approach produces consistent and less biased estimates, closely reflecting true underlying values. We applied this model to data from the ISGlobal/ATHLETE "Exposome Data Challenge Event" to explore the association between maternal exposure to hexachlorobenzene and childhood body mass index by integrating incomplete proteomics data from 1301 children. The model successfully estimated proteomics profiles for two clusters representing higher and lower body mass index, characterizing the potential profiles linking prenatal hexachlorobenzene levels and childhood body mass index. Availability and implementation: The proposed methods have been implemented in the R package LUCIDus. The source code is available at https://github.com/USCbiostats/LUCIDus.

Applications of mixture methods in epidemiological studies investigating the health impact of persistent organic pollutants exposures: a scoping review.

BACKGROUND: Persistent organic pollutants (POPs) are environmental chemicals characterized by long half-lives in nature and human bodies, posing significant health risks. The concept of the exposome, encompassing all lifetime environmental exposures, underscores the importance of studying POP as mixtures rather than in isolation. The increasing body of evidence on the health impacts of POP mixtures necessitates the proper application of statistical methods. OBJECTIVES: We aimed to summarize studies on the overall effects of POP mixtures, identify patterns in applications of mixture methods-statistical methods for investigating the association of mixtures-and highlight current challenges in synthesizing epidemiologic evidence of POP mixtures on health effects as illustrated through a case study. METHODS: We conducted a systematic literature search on PubMed and Embase for epidemiological studies published between January 2011 and April 2023. RESULTS: We included 240 studies that met our eligibility criteria. 126 studies focused on per- and polyfluoroalkyl substances (PFAS) mixtures only, while 40 analyzed three or more classes of POPs in mixture analyses. We identified 23 unique mixture methods used to estimate the overall effects of POP mixtures, with Bayesian Kernel Machine Regression (BKMR), a type of response-surface modeling, being the most common. Additionally, 22.9% of studies used a combination of methods, including response-surface modeling, index modeling, dimension reduction, and latent variable models. The most extensively explored health outcome category was body weight and birth sizes (n = 43), and neurological outcomes (n = 41). In the case study of PFAS mixtures and birth weight, 12 studies showed negative associations, while 4 showed null results, and 2 showed positive associations. IMPACT STATEMENT: This scoping review consolidates the existing literature on the overall effects of POP mixtures using statistical methods. By providing a comprehensive overview, our study illuminates the present landscape of knowledge in this field and underscores the methodological hurdles prevalent in epidemiological studies focused on POP mixtures. Through this analysis, we aim to steer future research directions, fostering a more nuanced comprehension of the intricate dynamics involved in assessing the health effects of POP mixtures. Our work stands as a significant contribution to the ongoing exploration of the chemical exposome.

Social reward and nonsocial reward processing across the adult lifespan: An interim multi-echo fMRI and diffusion dataset.

Social relationships change across the lifespan as social networks narrow and motivational priorities shift. These changes may affect, or reflect, differences in how older adults make decisions related to processing social and non-social rewards. While we have shown initial evidence that older adults have a blunted response to some features of social reward, further work in larger samples is needed to replicate our results and probe the extent to which age-related differences translate to real world consequences, such as financial exploitation. To address this gap, we are conducting a 5-year study funded by the National Institute on Aging (NIH R01-AG067011). Over the course of the funding period (2021-2026), this study seeks to: 1) characterize neural responses to social rewards across adulthood; 2) relate those responses to risk for financial exploitation and sociodemographic factors tied to risk; and 3) examine changes in risk for financial exploitation over time in healthy and vulnerable groups of older adults. This paper describes the preliminary release of data for the larger study. Adults (N = 114; 40 male / 70 female / 4 other or non-binary; 21-80 years of age M = 42.78, SD = 17.13) were recruited from the community to undergo multi-echo fMRI while completing tasks that measure brain function during social reward and decision making. Tasks probe neural response to social reward (e.g., peer vs. monetary feedback) and social context and closeness (e.g., sharing a monetary reward with a friend compared to a stranger). Neural response to social decision making is probed via economic trust and ultimatum games. Functional data are complimented by a T1 weighted anatomical scan and multi-shell diffusion-weighted imaging (DWI) to enable tractography and assess neurite orientation dispersion and density. Overall, this dataset has extensive potential for re-use, including leveraging multimodal neuroimaging data, within subject measures of fMRI data from different tasks - data features that are rarely seen in an adult lifespan dataset. Finally, the functional data will allow for developmentally sensitive cross-sectional analyses of differences in brain response to nuanced differences in reward contexts and outcomes (e.g., monetary vs. social; sharing winnings with a friend vs. stranger; stranger vs. computer).

A behavioral dataset of predictive decisions given trends in information across adulthood.

Making early and good predictions is a critical feature of decision making in domains such as investing and predicting the spread of diseases. Past literature indicates that people use recent and longer-term trends to extrapolate future outcomes. Nonetheless, less is known about what differentiates the strategies people use to make better predictions than others. Furthermore, factors underlying predictive judgments could be an important behavioral component in psychosocial research investigating manic-depression, anxiety, and age effects. Additionally, predictive judgments may be moderated based on the experience of living in areas with greater income inequality. To address these issues, we used investment tasks where participants had to predict future outcomes of their investments based on a trend in information. In the task, participants predicted how many tokens a gold mine would produce on the twelfth turn. On each turn, participants could ask for more information at a cost, or make a prediction about whether the gold mine would produce more or less than 100 tokens by the 12th turn. The trend was determined by function type (exponential and inverse exponential functions), whether the function was more linear or curved (growth factors), and good or bad outcomes (final values). This paradigm could help disentangle to what degree people use recent or longer-term information to inform their predictive judgments. We used Qualtrics to conduct this study. We also collected questionnaire data quantifying anxiety, impulsivity, risk attitudes, manic-depressive symptoms, and other psychosocial characteristics. The study was administered to adults with age ranges across the lifespan (N = 360; 225 male, 132 female; 3 nonbinary; mean age: 44.3 years; SD: 15.4 years, min: 18 years, max: 78 years). Additionally, we sampled across areas with high- and low-income inequality, thereby allowing researchers to investigate if value-based decisions are associated with participants' local communities. We outline potential ways to use and reuse this data, including exploring how individual differences are associated with predictive judgments.

Impact of the Coronavirus Disease 2019 Pandemic on Substance Use Disorder Risk Among People Living With Human Immunodeficiency Virus (HIV) Enrolled in HIV Care in the United States: An Interrupted Time Series Analysis.

Background: Rising overdose deaths globally and increased social isolation during the coronavirus disease 2019 (COVID-19) pandemic may have disproportionately impacted people with human immunodeficiency virus (PWH) with substance use disorders (SUD). We examined trends in SUD risk among PWH before and after the COVID-19 shelter-in-place (SIP) mandate. Methods: Data were collected between 2018 and 2022 among PWH enrolled across 8 US sites in the Centers for AIDS Research Network of Integrated Clinical Systems cohort. We evaluated changes in moderate/high SUD risk after SIP using interrupted time series analyses. Results: There were 7126 participants, including 21 741 SUD assessments. The median age was 51 (interquartile range, 39-58) years; 12% identified as Hispanic or Latino/Latina, 46% Black/African American, and 46% White. Moderate/high SUD risk increased continuously after the pandemic's onset, with 43% (95% confidence interval [CI], 40%-46%) endorsing moderate/high SUD risk post-SIP, compared to 24% (95% CI, 22%-26%) pre-SIP (P < .001). There were increases in the use of heroin, methamphetamine, and fentanyl, and decreases in prescription opioids and sedatives post-SIP. Further, there was a decrease in reported substance use treatment post-SIP compared to pre-SIP (P = .025). Conclusions: The rising prevalence of SUD through late 2022 could be related to an increase in isolation and reduced access to substance use and HIV treatment caused by disruptions due to COVID-19. A renewed investment in integrated substance use treatment is vital to address the combined epidemics of substance use and HIV following the COVID-19 pandemic and to support resilience in the face of future disruptions.

Resveratrol: A Multifaceted Guardian against Anxiety and Stress Disorders-An Overview of Experimental Evidence.

The medicinal properties of resveratrol have garnered increasing attention from researchers. Extensive data have been accumulated on its use in treating cardiovascular diseases, immune system disorders, cancer, neurological diseases, and behavioral disorders. The protective mechanisms of resveratrol, particularly in anxiety-related stress disorders, have been well documented. However, less attention has been given to the side effects of resveratrol. This review explores not only the mechanisms underlying the anxiolytic effects of resveratrol but also the mechanisms that may lead to increased anxiety following resveratrol treatment. Understanding these mechanisms is crucial for enhancing the efficacy of resveratrol in managing anxiety disorders associated with stress and PTSD.

First Case of HIV Seroconversion With Integrase Resistance Mutations on Long-Acting Cabotegravir for Prevention in Routine Care.

Background: Long-acting cabotegravir (CAB-LA) is highly effective for HIV prevention, but delayed HIV diagnoses and integrase strand transfer inhibitor (INSTI) resistance were observed in trials. We report the first case in routine clinical care of HIV infection on CAB-LA with INSTI resistance. Methods: The SeroPrEP study enrolls individuals in the United States who acquire HIV on pre-exposure prophylaxis modalities to assess diagnostics, antiretroviral (ARV) drug levels, resistance, and treatment outcomes. Resistance mutations in full-length HIV-1 integrase were identified by single-genome sequencing (SGS). Cabotegravir concentrations in plasma and hair segments were measured by liquid chromatography-tandem mass spectrometry. Results: A 23-year-old gender-nonbinary person, male at birth, restarted CAB-LA 6 months after discontinuation due to losing insurance. Prior to restart, HIV-1 RNA was not detected, but 20 days elapsed before CAB-LA injection. After the second CAB-LA injection, HIV antigen/antibody returned reactive (HIV-1 RNA 451 copies/mL). SGS of plasma HIV-1 RNA identified INSTI mutation Q148R in 2/24 sequences 2 days postdiagnosis; commercial genotype failed amplification. Cabotegravir hair concentration was 0.190 ng/mg 2 weeks prediagnosis; plasma cabotegravir was high (3.37 µg/mL; ∼20× PA-IC90) 14 days postdiagnosis. Viral suppression was maintained for 6 months on darunavir/cobicistat/emtricitabine/tenofovir alafenamide, then switched to doravirine + emtricitabine/tenofovir alafenamide due to nausea. Conclusions: In this first case of HIV infection on CAB-LA with INSTI resistance in routine care, cabotegravir resistance was detected only with a sensitive research assay. Accelerated pathways to minimize time between HIV testing and CAB-LA initiation are needed to optimize acute HIV detection and mitigate resistance risk. Sustained product access regardless of insurance is imperative to reduce HIV infections on CAB-LA.

12.1 terabit/second data center interconnects using O-band coherent transmission with QD-MLL frequency combs.

Most current Data Center Interconnects (DCI) use intensity modulation direct detection (IMDD) configurations due to their low complexity and cost. However, significant scaling challenges allow coherent solutions to become contenders in these short reach applications. We present an O-band coherent optical fiber transmission system based on Quantum Dot-Mode Locked Lasers (QD-MLLs) using two independent free-running comb lasers, one each for the carrier and the Local Oscillator (LO). Using a comb-to-comb configuration, we demonstrate a 10 km single mode fiber, O-band, coherent, heterodyne, 12.1 Tbps system operating at 0.47 Tbps/λ using 26 λs. We used fewer comb lines (26 λs), faster symbol rate (56 GBaud) and higher constellation cardinality (32 QAM) relative to the highest capacity C-band systems reported to date. Through design, analysis, and experimentation, we quantify the optimum comb line spacing for this use case. We compare potential configurations for increasing data center interconnect capacities whilst reducing power consumption, complexity, and cost.

Dilated cardiomyopathy mutation in beta-cardiac myosin enhances actin activation of the power stroke and phosphate release.

Inherited mutations in human beta-cardiac myosin (M2ß) can lead to severe forms of heart failure. The E525K mutation in M2ß is associated with dilated cardiomyopathy (DCM) and was found to stabilize the interacting heads motif (IHM) and autoinhibited super-relaxed (SRX) state in dimeric heavy meromyosin. However, in monomeric M2ß subfragment 1 (S1) we found that E525K enhances (threefold) the maximum steady-state actin-activated ATPase activity (k cat) and decreases (eightfold) the actin concentration at which ATPase is one-half maximal (K ATPase). We also found a twofold to fourfold increase in the actin-activated power stroke and phosphate release rate constants at 30 µM actin, which overall enhanced the duty ratio threefold. Loaded motility assays revealed that the enhanced intrinsic motor activity translates to increased ensemble force in M2ß S1. Glutamate 525, located near the actin binding region in the so-called activation loop, is highly conserved and predicted to form a salt bridge with another conserved residue (lysine 484) in the relay helix. Enhanced sampling molecular dynamics simulations predict that the charge reversal mutation disrupts the E525-K484 salt bridge, inducing conformations with a more flexible relay helix and a wide phosphate release tunnel. Our results highlight a highly conserved allosteric pathway associated with actin activation of the power stroke and phosphate release and suggest an important feature of the autoinhibited IHM is to prevent this region of myosin from interacting with actin. The ability of the E525K mutation to stabilize the IHM likely overrides the enhanced intrinsic motor properties, which may be key to triggering DCM pathogenesis.

Integrating Multi-Omics with environmental data for precision health: A novel analytic framework and case study on prenatal mercury induced childhood fatty liver disease.

BACKGROUND: Precision Health aims to revolutionize disease prevention by leveraging information across multiple omic datasets (multi-omics). However, existing methods generally do not consider personalized environmental risk factors (e.g., environmental pollutants). OBJECTIVE: To develop and apply a precision health framework which combines multiomic integration (including early, intermediate, and late integration, representing sequential stages at which omics layers are combined for modeling) with mediation approaches (including high-dimensional mediation to identify biomarkers, mediation with latent factors to identify pathways, and integrated/quasi-mediation to identify high-risk subpopulations) to identify novel biomarkers of prenatal mercury induced metabolic dysfunction-associated fatty liver disease (MAFLD), elucidate molecular pathways linking prenatal mercury with MAFLD in children, and identify high-risk children based on integrated exposure and multiomics data. METHODS: This prospective cohort study used data from 420 mother-child pairs from the Human Early Life Exposome (HELIX) project. Mercury concentrations were determined in maternal or cord blood from pregnancy. Cytokeratin 18 (CK-18; a MAFLD biomarker) and five omics layers (DNA Methylation, gene transcription, microRNA, proteins, and metabolites) were measured in blood in childhood (age 6-10 years). RESULTS: Each standard deviation increase in prenatal mercury was associated with a 0.11 [95% confidence interval: 0.02-0.21] standard deviation increase in CK-18. High dimensional mediation analysis identified 10 biomarkers linking prenatal mercury and CK-18, including six CpG sites and four transcripts. Mediation with latent factors identified molecular pathways linking mercury and MAFLD, including altered cytokine signaling and hepatic stellate cell activation. Integrated/quasi-mediation identified high risk subgroups of children based on unique combinations of exposure levels, omics profiles (driven by epigenetic markers), and MAFLD. CONCLUSIONS: Prenatal mercury exposure is associated with elevated liver enzymes in childhood, likely through alterations in DNA methylation and gene expression. Our analytic framework can be applied across many different fields and serve as a resource to help guide future precision health investigations.

Spectrin mediates 3D-specific matrix stress-relaxation response in neural stem cell lineage commitment.

While extracellular matrix (ECM) stress relaxation is increasingly appreciated to regulate stem cell fate commitment and other behaviors, much remains unknown about how cells process stress-relaxation cues in tissue-like three-dimensional (3D) geometries versus traditional 2D cell culture. Here, we develop an oligonucleotide-crosslinked hyaluronic acid-based ECM platform with tunable stress relaxation properties capable of use in either 2D or 3D. Strikingly, stress relaxation favors neural stem cell (NSC) neurogenesis in 3D but suppresses it in 2D. RNA sequencing and functional studies implicate the membrane-associated protein spectrin as a key 3D-specific transducer of stress-relaxation cues. Confining stress drives spectrin's recruitment to the F-actin cytoskeleton, where it mechanically reinforces the cortex and potentiates mechanotransductive signaling. Increased spectrin expression is also accompanied by increased expression of the transcription factor EGR1, which we previously showed mediates NSC stiffness-dependent lineage commitment in 3D. Our work highlights spectrin as an important molecular sensor and transducer of 3D stress-relaxation cues.

Machine Learning Identification of Modifiable Predictors of Patient Outcomes After Transcatheter Aortic Valve Replacement.

Background: Transcatheter aortic valve replacement (TAVR) is an important treatment option for patients with severe symptomatic aortic stenosis. It is important to identify predictors of excellent outcomes (good clinical outcomes, more time spent at home) after TAVR that are potentially amenable to improvement. Objectives: The purpose of the study was to use machine learning to identify potentially modifiable predictors of clinically relevant patient-centered outcomes after TAVR. Methods: We used data from 8,332 TAVR cases (January 2016-December 2021) from 21 hospitals to train random forest models with 57 patient characteristics (demographics, comorbidities, surgical risk score, lab values, health status scores) and care process parameters to predict the end point, a composite of parameters that designated an excellent outcome and included no major complications (in-hospital or at 30 days), post-TAVR length of stay of 1 day or less, discharge to home, no readmission, and alive at 30 days. We used recursive feature elimination with cross-validation and Shapley Additive Explanation feature importance to identify parameters with the highest predictive values. Results: The final random forest model retained 29 predictors (15 patient characteristics and 14 care process components); the area under the curve, sensitivity, and specificity were 0.77, 0.67, and 0.73, respectively. Four potentially modifiable predictors with relatively high Shapley Additive Explanation values were identified: type of anesthesia, direct movement to stepdown unit post-TAVR, time between catheterization and TAVR, and preprocedural length of stay. Conclusions: This study identified four potentially modifiable predictors of excellent outcome after TAVR, suggesting that machine learning combined with hospital-level data can inform modifiable components of care, which could support better delivery of care for patients undergoing TAVR.

Prevalence and Correlates of SARS-CoV-2 Vaccine Uptake and Hesitancy Among People With HIV Across the United States.

BACKGROUND: People with HIV (PWH) have higher risk of COVID-19 mortality. SARS-CoV-2 vaccination is highly effective among PWH, although vaccine hesitancy could limit the population-level impact. SETTING: From February 2021 to April 2022, PWH from 8 sites in the Centers for AIDS Research Network of Integrated Clinical Systems completed a vaccine hesitancy instrument as part of routine care. METHODS: Participants were defined as vaccine hesitant if they had not received the SARS-CoV-2 vaccine and would probably/definitely not receive it. We assessed factors associated with SARS-CoV-2 vaccine hesitancy using logistic regression adjusted for demographics, unsuppressed viral load (VL > 200 copies/mL), month, and time on ART; using inverse probability weighting for survey nonresponse. RESULTS: Overall, 3288 PWH with a median age of 55 were included; 18% were female and 94% were virally suppressed. At the time of survey, 27% reported they had not received the SARS-CoV-2 vaccine, and 9% (n = 279) reported vaccine hesitancy. Factors associated with vaccine hesitancy included female sex (adjusted odds ratio [AOR] = 2.3; 95% confidence interval (CI): 1.6-3.2), Black vs. White race (AOR 1.7; 95% CI: 1.2 to 2.4), younger age (AOR 1.4; 95% CI: 1.2 to 1.5), and unsuppressed VL (AOR 1.9; 95% CI: 1.3 to 3.0). CONCLUSION: Overall, over one-quarter of PWH in this multisite cohort were unvaccinated for SARS-CoV-2 when interviewed February 21-April 22. Vaccine hesitancy was reported by approximately 9% of PWH and was higher among women, Black PWH, younger PWH, PWH with unsuppressed VL, and those in the South/Midwest. Renewed efforts are needed to address concerns of PWH about vaccinations against COVID-19 as the pandemic evolves, and vaccines in general, given the potential for future pandemics.

Tranexamic Acid and Pulmonary Complications: A Secondary Analysis of an EAST Multicenter Trial.

BACKGROUND: Anti-inflammatory effects of tranexamic acid (TXA) in reducing trauma endotheliopathy may protect from acute lung injury. Clinical data showing this benefit in trauma patients is lacking. We hypothesized that TXA administration mitigates pulmonary complications in penetrating trauma patients. MATERIALS AND METHODS: This is a post-hoc analysis of a multicenter, prospective, observational study of adults (18+ years) with penetrating torso and/or proximal extremity injury presenting at 25 urban trauma centers. Tranexamic acid administration in the prehospital setting or within three hours of admission was examined. Participants were propensity matched to compare similarly injured patients. The primary outcome was development of pulmonary complication (ARDS and/or pneumonia). RESULTS: A total of 2382 patients were included, and 206 (8.6%) received TXA. Of the 206, 93 (45%) received TXA prehospital and 113 (55%) received it within three hours of hospital admission. Age, sex, and incidence of massive transfusion did not differ. The TXA group was more severely injured, more frequently presented in shock (SBP < 90 mmHg), developed more pulmonary complications, and had lower survival (P < 0.01 for all). After propensity matching, 410 patients remained (205 in each cohort) with no difference in age, sex, or rate of shock. On logistic regression, increased emergency department heart rate was associated with pulmonary complications. Tranexamic acid was not associated with different rate of pulmonary complications or survival on logistic regression. Survival was not different between the groups on logistic regression or propensity score-matched analysis. CONCLUSIONS: Tranexamic acid administration is not protective against pulmonary complications in penetrating trauma patients.

Sexual identity is associated with adverse childhood experiences (ACEs) in US early adolescents.

OBJECTIVE: To determine disparities in adverse childhood experiences (ACEs) by sexual identity in a national cohort of early adolescents. METHODS: We analyzed cross-sectional data from year 2 of the Adolescent Brain Cognitive Development Study (N=10,934, 2018-2020, ages 10-14 years). Disparities in ACE score across lesbian, gay, or bisexual (LGB), not sure, and heterosexual adolescents were assessed using multinomial logistic regression analyses. Logistic regressions estimated the associations between sexual identity and each individual ACE. Analyses were adjusted for potential confounders. RESULTS: In adjusted models, LGB adolescents had higher risk of experiencing 2, 3, or ≥4 ACEs (Relative Risk Ratios [RRR] =1.57, 95% CI 1.01-2.42), 3 (RR=1.78, 95% CI 1.100-2.88), or ≥4 ACEs (RRR=3.20, 95% CI 1.92-5.32), and not sure adolescents had a higher risk of having ≥4 ACEs (RRR=2.17, 95% CI 1.22-3.87), compared to heterosexual adolescents. LGB and not sure adolescents had higher risks of reporting emotional abuse ("yes" OR =4.21, 95% CI 1.84-9.61; "maybe" OR=6.20, 95% CI 2.91-13.19) and parent mental illness ("yes" OR=1.95, 95% CI 1.48-2.57; "maybe" OR=1.63, 95% CI 1.21-2.18) compared to heterosexual adolescents. CONCLUSIONS: LGB adolescents and those questioning their sexual identity were at greater risk of having higher ACE scores, with LGB adolescents experiencing the highest risk of experiencing ACEs. LGB adolescents also had higher odds of reporting emotional and parent mental illness. Recognizing this heightened risk of ACEs in early adolescence is critical for designing clinic and school-based interventions.

Recruitment of Residents to Rural Programs: Early Outcomes From Cohort 1 of the Rural Residency Planning and Development Grants Program.

Background To address rural physician workforce shortages, the Health Resources and Services Administration funded multiple Rural Residency Planning and Development (RRPD) awards, beginning in 2019, to develop rural residency programs in needed specialties. Objective To describe early resident recruitment outcomes of the RRPD grants program. Methods A cross-sectional survey of program directors or administrators of these 25 new rural residency training programs across the United States was administered at RRPD award conclusion in 2022. We performed descriptive analyses of applicant and Match data, including applications and interviews per resident position, positions filled in the main Match vs the Supplemental Offer and Acceptance Program (SOAP), and recruitment of residents from the program's state. Results The 25 Cohort 1 RRPD programs ranged from 2 to 8 residents per year. Most programs (16 of 25, 64.0%) were rural expansion tracks of an urban program. Most programs were sufficiently developed to participate in the 2022 (N=17) or 2023 (N=20) Match; we report on 13 of 17 (76.5%) programs for 2022 and 14 of 20 (70.0%) programs for 2023. Programs completed a median of 14.8 interviews per position. Most positions were filled in the Match (43 of 58, 74.1% in 2022; 45 of 58, 77.6% in 2023); most others were filled in the SOAP. On average, 34.4% of enrolled residents were from the same state as the program (range 0-78.6%). Conclusions The early resident recruitment outcomes of the RRPD model for developing new physician training in rural communities had sufficient recruitment success to support program continuation.

Early biological markers of post-acute sequelae of SARS-CoV-2 infection.

To understand the roles of acute-phase viral dynamics and host immune responses in post-acute sequelae of SARS-CoV-2 infection (PASC), we enrolled 136 participants within 5 days of their first positive SARS-CoV-2 real-time PCR test. Participants self-collected up to 21 nasal specimens within the first 28 days post-symptom onset; interviewer-administered questionnaires and blood samples were collected at enrollment, days 9, 14, 21, 28, and month 4 and 8 post-symptom onset. Defining PASC as the presence of any COVID-associated symptom at their 4-month visit, we compared viral markers (quantity and duration of nasal viral RNA load, infectious viral load, and plasma N-antigen level) and host immune markers (IL-6, IL-10, TNF-α, IFN-α, IFN-γ, MCP, IP-10, and Spike IgG) over the acute period. Compared to those who fully recovered, those reporting PASC demonstrated significantly higher maximum levels of SARS-CoV-2 RNA and N-antigen, burden of RNA and infectious viral shedding, and lower Spike-specific IgG levels within 9 days post-illness onset. No significant differences were identified among a panel of host immune markers. Our results suggest early viral dynamics and the associated host immune responses play a role in the pathogenesis of PASC, highlighting the importance of understanding early biological markers in the natural history of PASC.

Identifying and Quantifying Relative Concentrations of Epimers in Mixtures via Cyclic Ion Mobility Mass Spectrometry: Dexamethasone and Betamethasone as a Case Study.

Epimers can show different biological activities and different pharmacological behaviors; therefore, their separation and analysis are crucial in the drug development process. Due to their similar chemical and physical properties, separation of epimers is challenging. This study demonstrates the application of cyclic ion mobility-mass spectrometry to separate, identify, and quantify dexamethasone and betamethasone in a binary mixture. Cyclic IMS separation of the isolated protonated dimer resulted in three peaks: dexamethasone homodimer, betamethasone homodimer, and their heterodimer. Besides providing improved separation over the protonated monomer, the presence of a heterodimer peak provides additional confirmation of an isomeric mixture. We identified the dexamethasone and betamethasone homodimer peaks by infusing pure solutions of each epimer and measuring each pure homodimer's arrival time. The measured peak areas indicated that the heterodimer is formed at twice the rate of each homodimer and that dexamethasone and betamethasone contribute equally to the heterodimer signal. Using this observation, we could accurately calculate the relative concentrations of each epimer by adding half of the heterodimer peak area to each homodimer peak area. These findings enable the identification and quantification of dexamethasone and betamethasone based on the arrival time distributions of their protonated dimers. This is the first demonstration of accurate relative quantification of epimers by separating charged dimers in the gas phase.