Risk and Protective Factors for COVID-19 Infection among Pregnant Women with Sickle Cell Trait.

Pregnant women and individuals with sickle cell trait (SCT) and underlying comorbidities are both independently more vulnerable to severe illness from coronavirus disease 2019 (COVID-19) compared to nonpregnant women and those without SCT. However, our understanding of the specific factors influencing susceptibility to COVID-19 infection among pregnant women with SCT is currently constrained by limited available data. This study aims to determine the risk and protective factors that influence the likelihood of COVID-19 infection in this population. A retrospective analysis was done among 151 women with SCT in the reproductive age group. Multivariable analysis was performed to determine the various factors affecting COVID-19 infection among pregnant women with SCT. The study found that COVID-19-vaccinated pregnant women with SCT had a 90% lower risk of contracting COVID-19 and were 9 times more likely to have a COVID-19 infection if they had a history of pulmonary conditions such as asthma or chronic obstructive pulmonary disease. The present study further emphasizes the importance of the COVID-19 vaccine in preventing infection and safeguarding the health of pregnant women with SCT, particularly those with underlying comorbidities.

Multicenter Study of Pelvic Nodal Autosegmentation Algorithm of Siemens Healthineers: Comparison of Male Versus Female Pelvis.

Purpose: The autosegmentation algorithm of Siemens Healthineers version VA 30 (AASH) (Siemens Healthineers, Erlangen, Germany) was trained and developed in the male pelvis, with no published data on its usability in the female pelvis. This is the first multi-institutional study to describe and evaluate an artificial intelligence algorithm for autosegmentation of the pelvic nodal region by gender. Methods and Materials: We retrospectively evaluated AASH pelvic nodal autosegmentation in both male and female patients treated at our network of institutions. The automated pelvic nodal contours generated by AASH were evaluated by 1 board-certified radiation oncologist. A 4-point scale was used for each nodal region contour: a score of 4 is clinically usable with minimal edits; a score of 3 requires minor edits (missing nodal contour region, cutting through vessels, or including bowel loops) in 3 or fewer computed tomography slices; a score of 2 requires major edits, as previously defined but in 4 or more computed tomography slices; and a score of 1 requires complete recontouring of the region. Pelvic nodal regions included the right and left side of the common iliac, external iliac, internal iliac, obturator, and midline presacral nodes. In addition, patients were graded based on their lowest nodal contour score. Statistical analysis was performed using Fisher exact tests and Yates-corrected χ2 tests. Results: Fifty-two female and 51 male patients were included in the study, representing a total of 468 and 447 pelvic nodal regions, respectively. Ninety-six percent and 99% of contours required minor edits at most (score of 3 or 4) for female and male patients, respectively (P = .004 using Fisher exact test; P = .007 using Yates correction). No nodal regions had a statistically significant difference in scores between female and male patients. The percentage of patients requiring no more than minor edits was 87% (45 patients) and 92% (47 patients) for female and male patients, respectively (P = .53 using Fisher exact test; P = .55 using Yates correction). Conclusions: AASH pelvic nodal autosegmentation performed very well in both male and female pelvic nodal regions, although with better male pelvic nodal autosegmentation. As autosegmentation becomes more widespread, it may be important to have equal representation from all sexes in training and validation of autosegmentation algorithms.

The functional microclimate of an urban arthropod pest: Urban heat island temperatures in webs of the western black widow spider.

Urbanization alters natural landscapes and creates unique challenges for urban wildlife. Similarly, the Urban Heat Island (UHI) effect can produce significantly elevated temperatures in urban areas, and we have a relatively poor understanding of how this will impact urban biodiversity. In particular, most studies quantify the UHI using broad-scale climate data rather than assessing microclimate temperatures actually experienced by organisms. In addition, studies often fail to address spatial and temporal complexities of the UHI. Here we examine the thermal microclimate and UHI experienced in the web of Western black widow spiders (Latrodectus hesperus), a medically-important, superabundant urban pest species found in cities across the Western region of North America. We do this using replicate urban and desert populations across an entire year to account for seasonal variation in the UHI, both within and between habitats. Our findings reveal a strong nighttime, but no daytime, UHI effect, with urban spider webs being 2-5 °C warmer than desert webs at night. This UHI effect is most prominent during the spring and least prominent in winter, suggesting that the UHI need not be most pronounced when temperatures are most elevated. Urban web temperatures varied among urban sites in the daytime, whereas desert web temperatures varied among desert sites in the nighttime. Finally, web temperature was significantly positively correlated with a spider's boldness, but showed no relationship with voracity towards prey, web size, or body condition. Understanding the complexities of each organism's thermal challenges, the "functional microclimate", is crucial for predicting the impacts of urbanization and climate change on urban biodiversity and ecosystem functioning.

An IMRT planning technique for treating whole breast or chest wall with regional lymph nodes on Halcyon and Ethos.

PURPOSE/OBJECTIVE: Field size limitations on Halcyon and Ethos treatment machines largely preclude use of the conventional monoisocentric three-field technique for breast/chest wall and regional lymph nodes. We present an alternative, IMRT-based planning approach that facilitates treatment on Halcyon and Ethos while preserving plan quality. MATERIALS/METHODS: Eight breast and regional node cases (four left-sided, four right-sided) were planned for an Ethos machine using a 15-17 field IMRT technique. Institutional plan quality metrics for CTV and PTV coverage and OAR sparing were assessed. Five plans (four right-sided, one left-sided) were also planned using a hybrid 3D multisocenter technique. CTV coverage and OAR sparing were compared to the IMRT plans. Eclipse scripting tools were developed to aid in beam placement and plan evaluation through a set of dosimetric scorecards, and both are shared publicly. RESULTS: On average, the IMRT plans achieved breast CTV and PTV coverage at 50 Gy of 97.9% and 95.7%, respectively. Supraclavicular CTV and PTV coverages at 45 Gy were 100% and 95.5%. Axillary lymph node CTV and PTV coverages at 45 Gy were 100% and 97.1%, and IMN CTV coverage at 45 Gy was 99.2%. Mean ipsilateral lung V20 Gy was 19.3%, and average mean heart dose was 1.6 Gy for right-sided cases and 3.0 Gy for left-sided. In comparison to the hybrid 3D plans, IMRT plans achieved higher breast and supraclavicular CTV coverage (99.9% vs. 98.6% and 99.9% vs. 93.4%), higher IMN coverage (99.6% vs. 78.2%), and lower ipsilateral lung V20 Gy (19.6% vs. 28.2%). CONCLUSION: Institutional plan quality benchmarks were achieved for all eight cases using the IMRT-based planning approach. The IMRT-based planning approach offered superior conformity and OAR sparing than a competing hybrid 3D approach.

Comorbidity profiles in older patients last seen by mental health prior to suicide attempt.

OBJECTIVES: Suicide in late life is a public health concern. Determining profiles of psychiatric/medical comorbidity in those who attempt while engaged in mental health services may assist with prevention. We identified comorbidity profiles and their association with utilization, means, and fatality in a national sample who attempted suicide. METHODS: Using latent class analysis, all patients aged ≥ 65 from the Department of Veterans Affairs (VA) healthcare services (2012-2018) last seen in mental health prior to suicide attempt were included. Diagnoses and attempt data were obtained from VA and Center for Medicare & Medicaid Services, VA Suicide Prevention Applications Network, and VA National Mortality Data Repository. RESULTS: 2,269 patients were clustered into three profiles, all with high probability of depression. Profiles included minimal comorbidity (50.4%), high medical comorbidity (28.6%), and high (psychiatric/medical) comorbidity (21.0%). Over half (61.7%) attempted suicide within one week of their visit. The class with highest comorbidity had lowest proportion of fatal attempts, while minimal comorbidity class had highest proportion. CONCLUSIONS: Older patients last seen in mental health prior to suicide attempt were characterized by depression and varying additional comorbidity and attempt-related factors. Findings have implications for risk assessment and intervention in mental health settings, beyond depression.

Control points for design of taxonomic composition in synthetic human gut communities.

Microbial communities offer vast potential across numerous sectors but remain challenging to systematically control. We develop a two-stage approach to guide the taxonomic composition of synthetic microbiomes by precisely manipulating media components and initial species abundances. By combining high-throughput experiments and computational modeling, we demonstrate the ability to predict and design the diversity of a 10-member synthetic human gut community. We reveal that critical environmental factors governing monoculture growth can be leveraged to steer microbial communities to desired states. Furthermore, systematically varied initial abundances drive variation in community assembly and enable inference of pairwise inter-species interactions via a dynamic ecological model. These interactions are overall consistent with conditioned media experiments, demonstrating that specific perturbations to a high-richness community can provide rich information for building dynamic ecological models. This model is subsequently used to design low-richness communities that display low or high temporal taxonomic variability over an extended period. A record of this paper's transparent peer review process is included in the supplemental information.

Review of cone beam computed tomography based online adaptive radiotherapy: current trend and future direction.

Adaptive radiotherapy (ART) was introduced in the late 1990s to improve the accuracy and efficiency of therapy and minimize radiation-induced toxicities. ART combines multiple tools for imaging, assessing the need for adaptation, treatment planning, quality assurance, and has been utilized to monitor inter- or intra-fraction anatomical variations of the target and organs-at-risk (OARs). Ethos™ (Varian Medical Systems, Palo Alto, CA), a cone beam computed tomography (CBCT) based radiotherapy treatment system that uses artificial intelligence (AI) and machine learning to perform ART, was introduced in 2020. Since then, numerous studies have been done to examine the potential benefits of Ethos™ CBCT-guided ART compared to non-adaptive radiotherapy. This review will explore the current trends of Ethos™, including improved CBCT image quality, a feasible clinical workflow, daily automated contouring and treatment planning, and motion management. Nevertheless, evidence of clinical improvements with the use of Ethos™ are limited and is currently under investigation via clinical trials.

Simultaneous detection and quantification of multiple pathogen targets in wastewater.

Wastewater-based epidemiology has emerged as a critical tool for public health surveillance, building on decades of environmental surveillance work for pathogens such as poliovirus. Work to date has been limited to monitoring a single pathogen or small numbers of pathogens in targeted studies; however, few studies consider simultaneous quantitative analysis of a wide variety of pathogens, which could greatly increase the utility of wastewater surveillance. We developed a novel quantitative multi-pathogen surveillance approach (35 pathogen targets including bacteria, viruses, protozoa, and helminths) using TaqMan Array Cards (TAC) and applied the method on concentrated wastewater samples collected at four wastewater treatment plants in Atlanta, GA from February to October of 2020. From sewersheds serving approximately 2 million people, we detected a wide range of targets including many we expected to find in wastewater (e.g., enterotoxigenic E. coli and Giardia in 97% of 29 samples at stable concentrations) as well as unexpected targets including Strongyloides stercoralis (a human threadworm rarely observed in the USA). Other notable detections included SARS-CoV-2, but also several pathogen targets that are not commonly included in wastewater surveillance like Acanthamoeba spp., Balantidium coli, Entamoeba histolytica, astrovirus, norovirus, and sapovirus. Our data suggest broad utility in expanding the scope of enteric pathogen surveillance in wastewaters, with potential for application in a variety of settings where pathogen quantification in fecal waste streams can inform public health surveillance and selection of control measures to limit infections.

Stratospheric Night Sky Imaging Payload for Space Situational Awareness (SSA).

Space situational awareness (SSA) refers to collecting, analyzing, and keeping track of detailed knowledge of resident space objects (RSOs) in the space environment. With the rapidly increasing number of objects in space, the need for SSA grows as well. Traditional methods rely heavily on imaging RSOs from large, narrow field-of-view (FOV), ground-based telescopes. This research outlines the technology demonstration payload, Resident Space Object Near-space Astrometric Research (RSONAR)-a star tracker-like, wide FOV camera combined with commercial off-the-shelf (COTS) hardware to image RSOs from the stratosphere, overcoming the disadvantages of ground-based observations. The hardware components and software algorithm are described and evaluated. The eligibility of the payload for SSA is proven by the image processing algorithms, which detect the RSOs in the images captured during flight and the survival of the COTS components in the near-space environment. The payload features a low-resolution, wide FOV camera coupled with a Field Programmable Gate Array (FPGA)-based platform that houses the altitude and time-based image capture algorithm. The newly developed payload in a 2U-CubeSat form factor was flown as a space-ready payload on the CSA/CNES stratospheric balloon research platform to carry out algorithm and functionality tests in August 2022.

Scorecards: Quantifying Dosimetric Plan Quality in Pancreatic Ductal Adenocarcinoma Stereotactic Body Radiation Therapy.

Purpose: A scoring mechanism called the scorecard that objectively quantifies the dosimetric plan quality of pancreas stereotactic body radiation therapy treatment plans is introduced. Methods and Materials: A retrospective analysis of patients with pancreatic ductal adenocarcinoma receiving stereotactic body radiation therapy at our institution between November 2019 and November 2020 was performed. Ten patients were identified. All patients were treated to 36 Gy in 5 fractions, and organs at risk (OARs) were constrained based on Alliance A021501. The scorecard awarded points for OAR doses lower than those cited in Alliance A021501. A team of 3 treatment planners and 2 radiation oncologists, including a physician resident without plan optimization experience, discussed the relative importance of the goals of the treatment plan and added additional metrics for OARs and plan quality indexes to create a more rigorous scoring mechanism. The scorecard for this study consisted of 42 metrics, each with a unique piecewise linear scoring function which is summed to calculate the total score (maximum possible score of 365). The scorecard-guided plan, the planning and optimization for which were done exclusively by the physician resident with no prior plan optimization experience, was compared with the clinical plan, the planning and optimization for which were done by expert dosimetrists, using the Sign test. Results: Scorecard-guided plans had, on average, higher total scores than those clinically delivered for each patient, averaging 280.1 for plans clinically delivered and 311.7 for plans made using the scorecard (P = .003). Additionally, for most metrics, the average score of each metric across all 10 patients was higher for scorecard-guided plans than for clinically delivered plans. The scorecard guided the planner toward higher coverage, conformality, and OAR sparing. Conclusions: A scorecard tool can help clarify the goals of a treatment plan and provide an objective method for comparing the results of different plans. Our study suggests that a completely novice treatment planner can use a scorecard to create treatment plans with enhanced coverage, conformality, and improved OAR sparing, which may have significant effects on both tumor control and toxicity. These tools, including the scorecard used in this study, have been made freely available.

Methadone Induction for a Patient With Precipitated Withdrawal in the Emergency Department: A Case Report.

In the era of illicit fentanyl, reports on difficulties with buprenorphine inductions for patients with opioid use disorder are emerging. Methadone is the only other approved medication treatment with efficacy similar to buprenorphine but without risks of precipitated withdrawal. Unfortunately, outpatient methadone inductions can take days to weeks to complete, due in part to regulations that limit administration to opioid treatment programs. We describe a patient with opioid use disorder who presented to the emergency department in precipitated withdrawal who completed a same-day methadone induction with next-day dosing at an opioid treatment program as part of an emergency department methadone protocol. As opioid-related deaths rise, emergency department-initiated methadone is feasible for patients with opioid use disorder.

Solvation Environments in Porous Ionic Liquids Determine Selectivity in CO2 Conversion to Cyclic Carbonates.

Porous ionic liquids, which are suspensions of nanoporous particles in ionic liquids that maintain permanent porosity, are effective and selective media for the conversion of styrene oxide into styrene carbonate, absorbing CO2 [Zhou et al. Chem. Commun. 2021, 57, 7922-7925]. Here we elucidate the mechanism of selectivity using polarizable molecular dynamics simulations, which provide a detailed view on the structure of the porous ionic liquid and on the local solvation environments of the reacting species. The porous ionic liquids studied are composed of tetradecyltrihexylphosphonium chloride, or [P66614]Cl, and the ZIF-8 zinc-methylimidazolate metal-organic framework (MOF). The CL&Pol polarizable force field was extended to represent epoxide and cyclic carbonate functional groups, allowing the ionic liquid, the reactants, and the MOF to be all represented by fully flexible, polarizable force fields, providing a detailed description of interactions. The presence of reactant and product molecules leads to changes in the structure of the ionic liquid, revealed by domain analysis. The structure of local solvation environments, namely, the arrangement of charged moieties and CO2 around the epoxide ring of the reactant molecules, clearly indicate ring-opening the reaction mechanism. The MOF acts as a reservoir of CO2 through its free volume. The solute molecules are found in the accessible outer cavities of the MOF, which promotes reaction of the epoxide with CO2 excluding other epoxide molecules, thereby preventing the formation of oligomers, which explains the selectivity toward conversion to cyclic carbonates.

Dose Escalation Patterns of Advanced Therapies in Crohn's Disease and Ulcerative Colitis: A Systematic Literature Review.

INTRODUCTION: Dose escalation is one of the treatment approaches studied and suggested in advanced therapies for Crohn's disease (CD) and ulcerative colitis (UC). This study aimed to identify and characterize the dosing escalation patterns of advanced therapies in CD and UC. METHODS: Two systematic literature reviews (SLRs) were conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE®, Embase®, and Cochrane Library were searched for articles published between January 2011 and October 2021 and limited to non-interventional studies in English language. Congress and bibliographic searches were also conducted. Articles were screened by two independent researchers. Dose escalation patterns were described and summarized considering the regional regulatory label recommendation (in North America [NA] or outside of North America [ONA]). RESULTS: Among 3190 CD and 2116 UC articles identified in the Ovid searches, 100 CD and 54 UC studies were included in the SLR, with more studies conducted ONA. Most studies reported an initial maintenance dose pattern aligned with the lower starting dose per local regulatory label; however, several ONA studies (n = 13 out of 14) reported ustekinumab every 8 weeks as starting maintenance pattern in CD. In ONA studies, the median within-guideline escalation rates in CD and UC were 43% in ustekinumab (CD only), 33% and 32% for vedolizumab; 29% and 39% for adalimumab; and 14% and 10% for infliximab. Evidence regarding dose escalation patterns for tofacitinib, certolizumab pegol, and golimumab was limited. Some dose escalation patterns outside of label recommendations were observed including ustekinumab every 8 weeks to every 4 weeks and vedolizumab every 8 weeks to every 6 weeks. CONCLUSION: Dose escalation strategies are widely documented in the literature. The reported dose escalation patterns and escalation rates vary by region and by CD and UC. Most escalation patterns reported were aligned with regulatory recommendations while some reported more diverse or aggressive dose escalation. PROSPERO REGISTRATION: CRD42021289251.

The Alzheimer's disease-linked protease BACE1 modulates neuronal IL-6 signaling through shedding of the receptor gp130.

BACKGROUND: The protease BACE1 is a major drug target for Alzheimer's disease, but chronic BACE1 inhibition is associated with non-progressive cognitive worsening that may be caused by modulation of unknown physiological BACE1 substrates. METHODS: To identify in vivo-relevant BACE1 substrates, we applied pharmacoproteomics to non-human-primate cerebrospinal fluid (CSF) after acute treatment with BACE inhibitors. RESULTS: Besides SEZ6, the strongest, dose-dependent reduction was observed for the pro-inflammatory cytokine receptor gp130/IL6ST, which we establish as an in vivo BACE1 substrate. Gp130 was also reduced in human CSF from a clinical trial with a BACE inhibitor and in plasma of BACE1-deficient mice. Mechanistically, we demonstrate that BACE1 directly cleaves gp130, thereby attenuating membrane-bound gp130 and increasing soluble gp130 abundance and controlling gp130 function in neuronal IL-6 signaling and neuronal survival upon growth-factor withdrawal. CONCLUSION: BACE1 is a new modulator of gp130 function. The BACE1-cleaved, soluble gp130 may serve as a pharmacodynamic BACE1 activity marker to reduce the occurrence of side effects of chronic BACE1 inhibition in humans.

Outcomes Following Adalimumab Bio-originator to Biosimilar Switch-A Comparison Using Real-world Patient- and Physician-Reported Data in European Countries.

INTRODUCTION: The aim of this work is to compare real-world outcomes of patients with rheumatoid arthritis (RA) receiving adalimumab (ADA) bio-originator (non-switchers) to those who had switched from ADA bio-originator to an ADA biosimilar (switchers) on the basis of the hypothesis that these outcomes would differ. METHODS: Data were drawn from the Adelphi RA Disease Specific Programme™, a point-in-time survey of physicians and their patients in Europe (France, Germany, Italy, Spain, UK) in 2020. Physicians completed a questionnaire for their next ten adult patients with RA, followed by four additional patients who had switched from ADA bio-originator to an ADA biosimilar (switchers). Physician- and patient-reported outcomes (PROs) for switchers and non-switchers were compared by propensity score matching. RESULTS: Three hundred and three rheumatologists provided data for 160 non-switchers and 225 switchers, 140 patients provided data; 51 non-switchers, 89 switchers. According to physician-reported disease activity, non-switchers were more likely to improve on their current ADA treatment than switchers (68%, n = 108 vs. 26%, n = 59 p < 0.001) and less likely to worsen (1%, n = 2 vs. 9%, n = 20; p < 0.01). Physician-reported patient adherence was significantly lower amongst switchers versus non-switchers (0.66 vs. 0.78, respectively; p = 0.04). More non-switchers than switchers were reported by their physicians to be consistent in taking their RA medicine (p < 0.001). Compared with non-switchers, PRO measures indicated quality of life was worse (EQ-5D Visual Analogue Scale: 62.9 vs. 71.9; p < 0.001) and activity impairment was greater (Work Productivity Activity Index: 31.0 vs. 24.4; p = 0.02) for switchers, with trends for poorer health status and greater pain. CONCLUSIONS: Non-medical switching in RA treatment may lead to unforeseen outcomes that should be considered by health decision-makers.

A Paucity of Data on Veterans 65 and Older and Risk of Suicide: A Systematic Review.

Older veterans are vastly underrepresented in studies that shape national suicide prevention strategies. This is of great concern because factors that impact younger veterans may not be as robust in later life. Although younger veterans have higher rate of suicide, the highest counts of death by suicide are in older veterans. However, it remains unclear from the extant literature what factors may influence increased or decreased risk of late-life suicide in veterans. The objective of this systematic review was to identify risk and protective factors related to suicide outcomes (i.e., ideation, attempt, death, or suicide-related behavior [SRB]) among older veterans. Furthermore, it offers data regarding future study directions and hypothesis generation for late-life suicide research and for informing potential intervention and prevention efforts in this area. We searched 4 databases from inception up to May 5, 2022. We screened 2,388 abstracts for inclusion and 508 articles required full text review. The final sample included 19 studies published between 2006 and 2022. We found five domains of factors studied (i.e., neuropsychiatric, social determinants of health, aging stereotypes, residential and supportive housing settings, and multifactorial-neuropsychiatric/mental health and physical health) with more risk factors than protective factors reported. Across the three suicide outcomes only neuropsychiatric factors were consistently identified as risk factors. Neuropsychiatric factors also comprised the largest group of risk factors studied. More innovative targets to consider for intervention and more innovative methods to predict suicide in late-life are needed. There is also continued necessity to design suicide prevention interventions for older veterans given lethality trends.

Posttraumatic stress disorder, suicide, and unintended overdose death in later life: A national cohort study of veterans aged 50 and older.

BACKGROUND/OBJECTIVES: Although studies have shown posttraumatic stress disorder (PTSD) associated with risk of suicide, the relationship in later life, especially for overdose death, remains unclear. Thus, the aim of the current study was to determine associations between PTSD, suicide, and unintended overdose death in mid- to late-life. METHODS: A nationwide cohort study integrating Department of Veterans Affairs' (VA) data, Centers for Medicare & Medicaid Services data, and national cause-specific mortality data. Participants were US veterans aged ≥50 years with PTSD diagnoses at baseline (2012-2013) and were propensity-matched 1:1 with patients without PTSD based on sociodemographics, Charlson Comorbidity Index, and neuropsychiatric disorders (N = 951,018). Information on suicide attempts and unintended death by overdose through December 31, 2017 was provided by the VA's National Suicide Prevention Applications Network (non-fatal attempts) and Mortality Data Repository (death). RESULTS: Veterans with PTSD (N = 475,509) had increased risk of suicide attempt (Hazard Ratio [HR], 1.59; 95% CI, 1.54-1.65; p < 0.001), non-fatal attempt (HR, 1.74; 95% CI, 1.67-1.81; p < 0.001), drug overdose death overall (HR, 1.32; 95% CI, 1.22-1.42; p < 0.001), and suicide overdose death (HR, 1.44; 95% CI, 1.15-1.80; p = 0.002), even after adjusting for sociodemographics, Charlson comorbidity index, and neuropsychiatric disorders. We found increased risk for overdose death by narcotics (HR, 1.30; 95% CI, 1.15-1.46; p < 0.001), antiepileptic/sedative-hypnotics (HR, 1.29; 95% CI, 1.02-1.62; p = 0.032), and for other/unspecified drugs (HR, 1.35; 95% CI, 1.20-1.51; p < 0.001), the last category indicative of polydrug. Results remained robust when examined for unintentional, suicide, and undetermined intent for cause-specific death by other/unspecified drugs. CONCLUSIONS: PTSD persists throughout mid- to late-life with considerable increased risk for non-fatal suicide attempts and suicide overdose death. These findings suggest the importance of drug-monitoring in preventing late-life suicide.

Medical leadership training varies substantially between UK medical schools: Report of the leadership in undergraduate medical education national survey (LUMENS).

BACKGROUND: Doctors are increasingly expected to demonstrate medical leadership and management (MLM) skills. The Faculty of Medical Leadership and Management (FMLM) has published an indicative undergraduate curriculum to guide the development of MLM content at UK medical schools. METHOD: Students from 30 medical schools were surveyed to determine their understanding of MLM teaching at their school. Timetables for 21 schools were searched for MLM-related keywords. Student-reported teaching and timetabled teaching were coded according to predefined themes. Aggregated demographic and postgraduate performance data were obtained through collaboration with the Medical Student Investigators Collaborative (msico.org). RESULTS: Whilst 88% of medical students see MLM teaching as relevant, only 18% believe it is well integrated into their curriculum. MLM content represented ∼2% of timetabled teaching in each 5-year undergraduate medical course. Most of this teaching was dedicated to teamwork, performance/reflection and communication skills. There was minimal association between how much of a topic students believed they were taught, and how much they were actually taught. We found no association between the volume of MLM teaching and performance in postgraduate examinations, trainee career destinations or fitness to practice referrals. CONCLUSION: Our findings demonstrate limited and variable teaching of MLM content. Delivery was independent of broader teaching and assessment factors.

RSOnet: An Image-Processing Framework for a Dual-Purpose Star Tracker as an Opportunistic Space Surveillance Sensor.

A catalogue of over 22,000 objects in Earth's orbit is currently maintained, and that number is expected to double within the next decade. Novel data collection regimes are needed to scale our ability to detect, track, classify and characterize resident space objects in a crowded low Earth orbit. This research presents RSOnet, an image-processing framework for space domain awareness using star trackers. Star trackers are cost-effective, flight proven, and require basic image processing to be used as an attitude-determination sensor. RSOnet is designed to augment the capabilities of a star tracker by becoming an opportunistic space-surveillance sensor. Our research demonstrates that star trackers are a feasible source for RSO detections in LEO by demonstrating the performance of RSOnet on real detections from a star-tracker-like imager in space. RSOnet convolutional-neural-network model architecture, graph-based multi-object classifier and characterization results are described in this paper.