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Fully relativistic particle-in-cell (PIC) simulations are crucial for advancing our knowledge of plasma physics. Modern supercomputers based on graphics processing units (GPUs) offer the potential to perform PIC simulations of unprecedented scale, but require robust and feature-rich codes that can fully leverage their computational resources. In this work, this demand is addressed by adding GPU acceleration to the PIC code Osiris. An overview of the algorithm, which features a CUDA extension to the underlying Fortran architecture, is given. Detailed performance benchmarks for thermal plasmas are presented, which demonstrate excellent weak scaling on NERSC's Perlmutter supercomputer and high levels of absolute performance. The robustness of the code to model a variety of physical systems is demonstrated via simulations of Weibel filamentation and laser-wakefield acceleration run with dynamic load balancing. Finally, measurements and analysis of energy consumption are provided that indicate that the GPU algorithm is up to ${\sim }$14 times faster and $\sim$7 times more energy efficient than the optimized CPU algorithm on a node-to-node basis. The described development addresses the PIC simulation community's computational demands both by contributing a robust and performant GPU-accelerated PIC code and by providing insight into efficient use of GPU hardware.
Autistic people have a high likelihood of developing mental health difficulties but a low chance of receiving effective mental healthcare. Therefore, there is a need to identify and examine strategies to improve mental healthcare for autistic people.
Aims
To identify strategies that have been implemented to improve access, experiences of care and mental health outcomes for autistic adults, and to examine evidence on their acceptability, feasibility and effectiveness.
Method
A co-produced systematic review was conducted. MEDLINE, PsycINFO, CINHAL, medRxiv and PsyArXiv were searched. We included all study designs reporting acceptability or feasibility outcomes and empirical quantitative study designs reporting effectiveness outcomes. Data were synthesised using a narrative approach.
Results
A total of 30 articles were identified. These included 16 studies of adapted mental health interventions, eight studies of service improvements and six studies of bespoke mental health interventions developed for autistic people. There was no conclusive evidence on effectiveness. However, most bespoke and adapted approaches appeared to be feasible and acceptable. Identified adaptations appeared to be acceptable and feasible, including increasing knowledge and detection of autism, providing environmental adjustments and communication accommodations, accommodating individual differences and modifying the structure and content of interventions.
Conclusion
Many identified strategies are feasible and acceptable, and can be readily implemented in services with the potential to make mental healthcare more suitable for autistic people, but important research gaps remain. Future research should address these and investigate a co-produced package of service improvement measures.
Neurobiological and cognitive theories implicate deficits in executive function (EF) as a core facet of both depressive disorders and attention-deficit/hyperactivity disorder (ADHD), but empirical investigations inconsistently support this conclusion. Despite recognition of the likely bi-directional relationship of EF deficits to depression and ADHD, respectively, the extent to which comorbid depression might impact EF in adults remains unclear, considering more of the literature has examined children and adolescents. This study examined performance differences on EF measures in clinically-referred adults diagnosed with ADHD or a non-ADHD primary psychopathological condition in the presence/absence of comorbid depression.
Participants and Methods:
This cross-sectional study included data from 404 adults referred for neuropsychological evaluation at a Midwestern academic medical center. In total, 343 met DSM-5 diagnostic criteria for ADHD (ADHD-all group:164 Predominantly Inattentive presentation [ADHD-I] and 179 Combined presentation [ADHD-C]) and 61 met criteria for a non-ADHD primary psychopathological condition (psychopathology group: 31 mood disorder, 17 anxiety disorder, and 13 posttraumatic stress disorder) when assessed via semi-structured clinical interview. All patients completed the Beck Depression Inventory-Second Edition (BDI-II) and five EF tests: Letter Fluency, Trail Making Test-Part B (Trails-B), Stroop Color and Word Test Color-Word trial (SCWT CW); and WAIS-IV Working Memory Index (WMI). Oneway MANOVAs assessed for significant EF differences between groups with high (BDI-II greater than or equal to 20) or low (BDI-II less than or equal to 19) depressive symptoms.
Results:
When group diagnosis (ADHD-all vs. psychopathology) was examined in the context of high or low depression, a significant difference in EF performance emerged between groups, F(12, 1042.72)=2.44, p<.01, Wilk's A=.93, partial n2=.02, with univariate analyses indicating a significant difference in FAS-T between at least two of the groups (F(3, 397)=3.92 , p< .01, partial n2=.03). Tukey's HSD Test for multiple comparisons found that the mean value of FAS-T was significantly different between the ADHD-high depression and ADHD-low depression groups (p=.046 , 95% CI = [5.81, -.04]) as well as between the ADHD-low depression and psychopathology-high depression groups (p=.05, 95% CI = [-8.89, .00]). A one-way MANOVA examining differences between groups when distinguishing ADHD by subtype revealed a statistically significant difference in EF performance between groups, F(20, 1301)=1.85, p<.05, Wilk's A=.91, partial n2=.02, with univariate analyses indicating a statistically significant difference in FAS-T between at least two of the groups (F(5, 395) = 2.39 , p<.05, partial n2 = .03). However, Tukey's HSD Test for multiple comparisons found that the mean value of FAS-T was not significantly different between any of the groups.
Conclusions:
Overall, results indicate that clinically-referred patients with ADHD perform comparably on tests of EF regardless of the presence or absence of comorbid depression. These findings have implications for conceptualizing EF weaknesses in neuropsychological profiles for individuals with ADHD and suggest examining factors beyond comorbid depression.
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder commonly associated with relative impairments on processing speed, working memory, and/or executive functioning. Anxiety commonly co-occurs with ADHD and may also adversely affect these cognitive functions. Additionally, language status (i.e., monolingualism vs bilingualism) has been shown to affect select cognitive domains across an individual’s lifespan. Yet, few studies have examined the potential effects of the interaction between anxiety and language status on various cognitive domains among people with ADHD. Thus, the current study investigated the effects of the interaction of anxiety and language status on processing speed, working memory, and executive functioning among monolingual and bilingual individuals with ADHD.
Participants and Methods:
The sample comprised of 407 consecutive adult patients diagnosed with ADHD. When asked about their language status, 67% reported to be monolingual (English). The Mean age of individuals was 27.93 (SD = 6.83), mean education of 15.8 years (SD = 2.10), 60% female, racially diverse with 49% Non-Hispanic White, 22% Non-Hispanic Black, 13% Hispanic/Latinx, 9% Asian/Pacific Islander, and 6% other race/ethnicity. Processing speed, working memory, and executive function were measured via the Wechsler Adult Intelligence Scale-Fourth Edition Processing Speed Index, Working Memory Index, and Trail Making Test B, respectively. Anxiety was measured via the Beck Anxiety Inventory (BAI). Three separate linear regression models examined the interaction between anxiety (moderator) and cognition (processing speed, working memory, and executive function) on language. Models included sex/gender and education as covariates with Processing Speed Index and Working Memory Index as the outcomes. Age, sex/gender, and education were used as covariates when Trail Making Test B was the outcome.
Results:
Monolingual and bilingual patients differed in mean age (p < .05) but did not differ in level of anxiety, education, or sex/gender. Overall, anxiety was not associated with processing speed, working memory, and executive function. However, the interaction between anxiety and language status was significantly associated with processing speed (ß = -0.37, p < .05), and executive functioning (ß = 0.82, p < .05). No associations were found when anxiety was added as a moderator for the associations between language and working memory.
Conclusions:
This study found that anxiety moderated the relationship between language status and select cognitive domains (i.e., processing speed and executive functioning) among individuals with ADHD. Specifically, anxiety had a greater association on processing speed and executive functioning performance for bilinguals rather than monolinguals. Future detailed studies are needed to better understand how anxiety modifies the relationship between language and cognitive performance outcomes over time amongst a linguistically diverse sample.
Health literacy is the degree to which an individual is able to attain, process, and understand information, skills, and services required to make informed decisions. Limited health literacy is a risk factor for problems understanding health information and adhering to medical instructions, underuse of preventive services, increased hospitalizations and associated medical costs, and higher mortality rates. Recognizing individuals with reduced health literacy can be difficult given demographic information such as age or years of education do not reliably reflect an individual’s health literacy level. Cross-sectional studies have identified limited health literacy as associated with lower scores on cognitive tests measuring memory, executive function (EF), and processing speed, independent from the influence of demographic variables (e.g., age, race, education). This study assessed the association of objective measures of executive functioning and health literacy when controlling for premorbid estimated intellectual functioning and relevant demographic variables.
Participants and Methods:
A sample of 44 adult patients (20 Male; 24 Female) referred for neuropsychological evaluation for memory complaints who were administered the Test of Premorbid Functioning (TOPF), and multiple measures of EF including the Trail Making Test - Part B (TMT-B), Stroop Color and Word Test (SCWT), and Letter (FAS) and Semantic (Animals) Fluency as part of part of a larger standardized battery. Patients were also administered the Short Assessment of Health Literacy-English (SAHL-E). All included patients had <2 performance validity test failures. The sample was 50% non-Hispanic Black, 31.8% non-Hispanic White, 15.9% Hispanic, 2.3% Asian/Pacific Islander, and 54.5% female. Diagnostically, 50.9% of the sample were cognitively normal, 36.4% had mild cognitive impairment, and 15.9% had dementia. Two multiple regressions were conducted to evaluate (1) the predictive power of EF on the SAHL-E, and (2) the moderating impact of estimated premorbid IQ and demographics via the TOPF on the relationship between EF and SAHL-E.
Results:
The first regression was not significant (p=.168) with FAS as the only independent predictor of SAHL-E performance (ß=.387, p<.05). The overall model was significant with the addition of the TOPF (p<.001). FAS accounted for 29% (ß=.336, p<.05) of the variance in SAHL-E when controlling for TOPF and other measures of EF.
Conclusions:
These results indicate that novel generativity is a significant predictor of health literacy beyond the influence of estimated premorbid intelligence and demographic factors. Importantly, these findings suggest that broadly speaking EF abilities have minimal impact on health literacy, although reduced verbal generativity to letter cues is associated with reduced health literacy. Identification of at-risk populations such as individuals with limited health literacy is clinically important and can make way for early intervention. Health information targeted at this at-risk population should go beyond vocabulary and more specifically reduce the burden on verbal fluency.
Health numeracy is the understanding and application of information conveyed with numbers, tables and graphs, and probabilities in order to effectively manage one's own healthcare. Health numeracy is a vital aspect of communicating with healthcare providers and participating in one's own medical decision making, which is especially important in aging populations. Current literature indicates that assessing and establishing one's health numeracy abilities is among the first steps in providing necessary resources and accommodating patients' individual needs. Additionally, older adults with diffuse cognitive impairment often have issues with facets of executive functioning; however, the extant literature does not discuss the role of executive functioning in relation to health numeracy in this population. The purpose of this study was to explore the relationship between performance on tasks of executive functioning and objectively-measured health numeracy abilities in older adult patients.
Participants and Methods:
This study included a sample of 42 older adult patients referred for neuropsychological evaluation for memory complaints who were administered the Test of Premorbid Functioning (TOPF), Trail Making Test - Part B (TMT-B), and Stroop Color and Word Test (SCWT Color Word Interference [CWI]) as part of a larger standardized battery. Patients were also administered the Numerical Understand in Medicine Instrument - Short Form (NUMI-SF). All included patients had <2 performance validity test failures. The sample was racially diverse (47.6% Black, 35.7% White, 14.3% Hispanic, 2.4% Asian) and 54.8% female. Average age was 62.95 (SD= 8.6) and average education was 14.1 (SD=2.7). Diagnostically, 47.6% of the sample were cognitively normal, 33.3% had mild cognitive impairment, and 19.0% had dementia. Average NUMI-SF score was 4.79 (SD= 1.7). Two multiple regressions were conducted to evaluate the extent to which executive functioning, as measured by the TMT-B and SCWT CWI predicted NUMI-SF, and the additive predictive power of premorbid IQ and demographics via the TOPF on the relationship between executive functioning and NUMI-SF.
Results:
The first regression, which measured the relationship between the TMT-B and SCWT CWI upon NUMI-SF scores, was not significant (p=.616). The model was significant with the addition of the TOPF (ß=.595, p<.001) and TOPF alone predicted ∼60% of the variance in NUMI-SF score, while TMT-B and SCWT CWI remained non-significant.
Conclusions:
These results indicate that common measures of executive functioning are not reliable predictors of health literacy with or without the moderating of premorbid intellectual functioning taken into consideration. This suggests that health numeracy is likely to be minimally affected by deficits in executive functioning and rather may be better accounted for by premorbid intellectual functioning and/or other sociodemographic factors (e.g. socioeconomic status, education quality, occupation). Future studies will benefit from elucidating the contributions of other social determinant factors on predicting health numeracy.
Individuals with chronic pain frequently report diminished cognitive functioning. Prior cross-sectional studies have demonstrated strong associations between chronic pain and neurocognitive impairment, most notably in memory, attention, processing speed, and executive functioning. However, there is a paucity of research evaluating visual learning and memory abilities in this population. Further, while current practice standards advocate for the use of performance validity tests (PVTs) to assess the credibility of neuropsychological test performance, they have infrequently been incorporated into studies examining chronic pain samples, despite a higher observed rate of noncredible performance in the literature. This study aimed to compare visual learning and memory performance between a mixed neuropsychiatric (MNP) group and a chronic pain group in a validity-controlled sample.
Participants and Methods:
The study consisted of 371 adults referred for outpatient neuropsychological evaluation. Between groups, various PVTs were administered, which included, at minimum, one freestanding and four embedded PVTs. All patients were administered the Brief Visuospatial Memory Test-Revised (BVMT-R) as part of a comprehensive neuropsychological evaluation. Only patients classified as valid performers (<1 PVT fails; n=295) were included in the analyses (Pain: n=109; MNP: n=186). The overall sample was 69% female and racially diverse (22% non-Hispanic Black, 43% non-Hispanic White, 30% Hispanic, 3% Asian/Pacific Islander, and 2% other race/ethnicities), with a mean age of 46.8 (SD=14.8) and mean education of 13.7 years (SD=2.7). Independent samples t-tests were performed to investigate the differences in visual learning and memory abilities between the chronic pain and MNP groups.
Results:
Chi-square analyses revealed significant differences between the pain and MNP groups on race, with more non-Hispanic White and Hispanic patients represented in the MNP group. There were also modest group differences in age and education. For the chronic pain group, patients scored lower on both BVMT-R Total T-Score (mean difference = 9.65T, p<.001) and BVMT Delayed Recall T-Score (mean difference = 8.97T, p<.001). The effect size was robust for both for Total T-Score (d = 0.682) and Delayed Recall T-Score (d = 0.632). In contrast, the difference in BVMT Recognition Discriminability was not statistically significant.
Conclusions:
This study demonstrated significant differences in performance between mixed neuropsychiatric and chronic pain patients. Preliminary evidence indicated that chronic pain patients displayed lower visual mediated encoding and retrieval performance, although their recognition is comparable. Although the nature of this study was targeted toward visual learning and retrieval, it is likely that the known impact of chronic pain on attention, working memory, and processing speed accounts for this relationship. Future studies will benefit from further elucidating these potential mechanisms and better inform clinical decision-making and neuropsychological testing performance in patients with chronic pain.
Awareness of risk factors associated with any form of impairment is critical for formulating optimal prevention and treatment planning. Millions worldwide suffer from some form of cognitive impairment, with the highest rates amongst Black and Hispanic populations. The latter have also been found to achieve lower scores on standardized neurocognitive testing than other racial/ethnic groups. Understanding the socio-demographic risk factors that lead to this discrepancy in neurocognitive functioning across racial groups is crucial. Adverse childhood experiences (ACEs), are one aspect of social determinants of health. ACES have been linked to a greater risk of future memory impairment, such as dementia. Moreover, higher instances of ACEs have been found amongst racial minorities. Considering the current literature, the purpose of this exploratory research is to better understand how social determinants, more specifically, ACEs, may play a role in the development of cognitive impairment.
Participants and Methods:
This cross-sectional study included data from an urban, public Midwestern academic medical center. There was a total of 64 adult clinical patients that were referred for a neuropsychological evaluation. All patients were administered a standardized neurocognitive battery that included the Montreal Cognitive Assessment (MoCA) as well as a 10-item ACE questionnaire, which measures levels of adverse childhood experiences. The sample was 73% Black and 27% White. The average age was 66 (SD=8.6) and average education was 12.6 years (SD=3.4). A two-way ANOVA was conducted to evaluate the interaction of racial identity (White; Black) and ACE score on MoCA total score. An ACE score >4 was categorized as “high”; ACE <4 was categorized as “low.”
Results:
There was not a significant interaction of race and ACE group on MoCA score (p=.929) nor a significant main effect of ACE score (p=.541). Interestingly, there was a significant main effect of Race on MoCA (p=.029). White patients had an average MoCA score of 21.82 (sd=4.77). Black patients had an average MoCA score of 17.54 (sd=5.91).
Conclusions:
Overall, Black patients demonstrated statistically lower scores on the MoCA than White patients. There was no significant difference on MoCA score between races when also accounting for ACE scores. Given this study’s findings, one’s level of adverse childhood experiences does not appear to impact one’s cognitive ability later in life. There is a significant difference in cognitive ability between races, specifically Black and White people, which suggests there may be social determinants other than childhood experiences to be explored that influence cognitive impairment.
Understanding healthcare information is an important aspect in managing one’s own needs and navigating a complex healthcare system. Health numeracy and literacy reflect the ability to understand and apply information conveyed numerically (i.e., graphs, statistics, proportions, etc.) and written/verbally (i.e., treatment instructions, appointments, diagnostic results) to communicate with healthcare providers, understand one’s medical condition(s) and treatment plan, and participate in informed medical decision-making. Cognitive impairment has been shown to impact one’s ability to understand complex medical information. The purpose of this study is to explore the relationship between the degree of cognitive impairment and one’s ability to perform on measures of health numeracy and literacy.
Participants and Methods:
This cross-sectional study included data from 38 adult clinical patients referred for neuropsychological evaluation for primary memory complaints at an urban, public Midwestern academic medical center. All patients were administered a standardized neurocognitive battery that included the Montreal Cognitive Assessment (MoCA), as well as measures of both health numeracy (Numeracy Understanding of Medicine Instrument-Short Version [NUMI-SF]) and health literacy (Short Assessment of Health Literacy-English [SAHL-E]). The sample was 58% female and 60% Black/40% White. Mean age was 65 (SD=9.4) and mean education was 14.4 years (SD=2.5). The sample was further split into three groups based on cognitive diagnosis determined by comprehensive neuropsychological assessment (i.e., No Diagnosis [34%]; Mild Cognitive Impairment [MCI; 29%]; Dementia [34%]).Groups were well matched and did not statistically differ in premorbid intellectual functioning (F=1.96, p=.157; No Diagnosis, M=100, SD=7.92; MCI, M=99, SD=8.87; Dementia, M=94, SD=7.72) ANOVAs were conducted to evaluate differences between clinical groups on the MoCA, NUMI-SF, and SAHL-E. Multiple regressions were then conducted to determine the association of MoCA scores with NUMI-SF and SAHL-E performance.
Results:
As expected, the Dementia group performed significantly below both the No Diagnosis and MCI groups on the MoCA (F=19.92, p<.001) with a large effect (ηp2=.540). Significant differences were also found on the NUM-SF (F=5.90, p>.05) and on the SAHL-E (F=6.20, p>.05) with large effects (ηp2=.258 and ηp2=.267, respectively). Regression found that MoCA performance did not predict performance on the NUMI-SF and SAHL-E in the No Diagnosis group (F=2.30, p=.809) or the MCI group (F=1.31, p=.321). Conversely, the MoCA significantly predicted performance on the NUMI-SF and SAHL-E for the Dementia (F=15.59, p=.001) group.
Conclusions:
Degree of cognitive impairment is associated with understanding of health numeracy and literacy information, with patients diagnosed with dementia performing most poorly on these measures. Patients with normal cognitive functioning demonstrated a significantly better understanding of health numeracy and health literacy. This study supports the notion that as cognitive functioning diminishes, incremental support is necessary for patients to understand medical information pertaining to their continued care and medical decision-making, particularly as it relates to both numerical and written information.
Social connections have a significant impact on health across age groups, including older adults. Loneliness and social isolation are known risk factors for Alzheimer’s disease and related dementias (ADRD). Yet, we did not find a review focused on meta-analyses and systematic reviews of studies that had examined associations of social connections with cognitive decline and trials of technology-based and other social interventions to enhance social connections in people with ADRD.
Study design:
We conducted a scoping review of 11 meta-analyses and systematic reviews of social connections as possible determinants of cognitive decline in older adults with or at risk of developing ADRD. We also examined eight systematic reviews of technology-based and other social interventions in persons with ADRD.
Study results:
The strongest evidence for an association of social connections with lower risk of cognitive decline was related to social engagement and social activities. There was also evidence linking social network size to cognitive function or cognitive decline, but it was not consistently significant. A number of, though not all, studies reported a significant association of marital status with risk of ADRD. Surprisingly, evidence showing that social support reduces the risk of ADRD was weak. To varying degrees, technology-based and other social interventions designed to reduce loneliness in people with ADRD improved social connections and activities as well as quality of life but had no significant impact on cognition. We discuss strengths and limitations of the studies included.
Conclusions:
Social engagement and social activities seem to be the most consistent components of social connections for improving cognitive health among individuals with or at risk for ADRD. Socially focused technology-based and other social interventions aid in improving social activities and connections and deserve more research.
We present detailed characterization of laser-driven fusion and neutron production ($\sim {10}^5$/second) using 8 mJ, 40 fs laser pulses on a thin (<1 μm) D${}_2$O liquid sheet employing a measurement suite. At relativistic intensity ($\sim 5\times {10}^{18}$ W/cm${}^2$) and high repetition rate (1 kHz), the system produces deuterium–deuterium (D-D) fusion, allowing for consistent neutron generation. Evidence of D-D fusion neutron production is verified by a measurement suite with three independent detection systems: an EJ-309 organic scintillator with pulse-shape discrimination, a ${}^3\mathrm{He}$ proportional counter and a set of 36 bubble detectors. Time-of-flight analysis of the scintillator data shows the energy of the produced neutrons to be consistent with 2.45 MeV. Particle-in-cell simulations using the WarpX code support significant neutron production from D-D fusion events in the laser–target interaction region. This high-repetition-rate laser-driven neutron source could provide a low-cost, on-demand test bed for radiation hardening and imaging applications.
Since the initial publication of A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals in 2008, the prevention of healthcare-associated infections (HAIs) has continued to be a national priority. Progress in healthcare epidemiology, infection prevention, antimicrobial stewardship, and implementation science research has led to improvements in our understanding of effective strategies for HAI prevention. Despite these advances, HAIs continue to affect ∼1 of every 31 hospitalized patients,1 leading to substantial morbidity, mortality, and excess healthcare expenditures,1 and persistent gaps remain between what is recommended and what is practiced.
The widespread impact of the coronavirus disease 2019 (COVID-19) pandemic on HAI outcomes2 in acute-care hospitals has further highlighted the essential role of infection prevention programs and the critical importance of prioritizing efforts that can be sustained even in the face of resource requirements from COVID-19 and future infectious diseases crises.3
The Compendium: 2022 Updates document provides acute-care hospitals with up-to-date, practical expert guidance to assist in prioritizing and implementing HAI prevention efforts. It is the product of a highly collaborative effort led by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Disease Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of organizations and societies with content expertise, including the Centers for Disease Control and Prevention (CDC), the Pediatric Infectious Disease Society (PIDS), the Society for Critical Care Medicine (SCCM), the Society for Hospital Medicine (SHM), the Surgical Infection Society (SIS), and others.
Prior trials suggest that intravenous racemic ketamine is a highly effective for treatment-resistant depression (TRD), but phase 3 trials of racemic ketamine are needed.
Aims
To assess the acute efficacy and safety of a 4-week course of subcutaneous racemic ketamine in participants with TRD. Trial registration: ACTRN12616001096448 at www.anzctr.org.au.
Method
This phase 3, double-blind, randomised, active-controlled multicentre trial was conducted at seven mood disorders centres in Australia and New Zealand. Participants received twice-weekly subcutaneous racemic ketamine or midazolam for 4 weeks. Initially, the trial tested fixed-dose ketamine 0.5 mg/kg versus midazolam 0.025 mg/kg (cohort 1). Dosing was revised, after a Data Safety Monitoring Board recommendation, to flexible-dose ketamine 0.5–0.9 mg/kg or midazolam 0.025–0.045 mg/kg, with response-guided dosing increments (cohort 2). The primary outcome was remission (Montgomery-Åsberg Rating Scale for Depression score ≤10) at the end of week 4.
Results
The final analysis (those who received at least one treatment) comprised 68 in cohort 1 (fixed-dose), 106 in cohort 2 (flexible-dose). Ketamine was more efficacious than midazolam in cohort 2 (remission rate 19.6% v. 2.0%; OR = 12.1, 95% CI 2.1–69.2, P = 0.005), but not different in cohort 1 (remission rate 6.3% v. 8.8%; OR = 1.3, 95% CI 0.2–8.2, P = 0.76). Ketamine was well tolerated. Acute adverse effects (psychotomimetic, blood pressure increases) resolved within 2 h.
Conclusions
Adequately dosed subcutaneous racemic ketamine was efficacious and safe in treating TRD over a 4-week treatment period. The subcutaneous route is practical and feasible.
With the increase in hectares planted to auxin-resistant cotton, the number of preplant, at-plant, and postplant applications of dicamba and 2,4-D choline to aid in the control of troublesome broadleaf weeds, including glyphosate-resistant Palmer amaranth, has increased. More dicamba and 2,4-D choline applications mean an increased risk of off-target movement. Field studies were conducted in 2019 to 2021 at the Texas Tech University New Deal Research Farm to evaluate dicamba-resistant cotton response to various rates of 2,4-D choline when applied at four growth stages (first square [FS] + 2 wk, first bloom [FB], FB + 2 wk, and FB + 4 wk). Applications of 2,4-D choline were applied at 1,060 (1X), 106 (1/10X), 21 (1/50X), 10.6 (1/100X), 2.1 (1/500X), and 1.06 (1/1000X) g ae ha−1 to Deltapine 1822 XF cotton. Relative to the nontreated control, yield losses were observed in all years at FS + 2 wk and FB from rates of 2,4-D choline ≥ 1/100X. At the FB + 4 wk application, only the 1X rate of 2,4-D choline resulted in a yield reduction in all three years. Micronaire, fiber length, and uniformity were negatively influenced by the 1/10X and 1X rates of 2,4-D choline at various timings in 2019, 2020, and 2021. In addition, short fiber content, neps, and seed coat neps increased where micronaire, fiber length, and uniformity were negatively impacted.
Deep Springs Valley (DSV) is a hydrologically isolated valley between the White and Inyo mountains that is commonly excluded from regional paleohydrology and paleoclimatology. Previous studies showed that uplift of Deep Springs ridge (informal name) by the Deep Springs fault defeated streams crossing DSV and hydrologically isolated the valley sometime after eruption of the Pleistocene Bishop Tuff (0.772 Ma). Here, we present tephrochronology and clast counts that reaffirms interruption of the Pliocene–Pleistocene hydrology and formation of DSV during the Pleistocene. Paleontology and infrared stimulated luminescence (IRSL) dates indicate a freshwater lake inundated Deep Springs Valley from ca. 83–61 ka or during Late Pleistocene Marine Isotope Stages 5a (MIS 5a; ca. 82 ka peak) and 4 (MIS 4; ca. 71–57 ka). The age of pluvial Deep Springs Lake coincides with pluvial lakes in Owens Valley and Columbus Salt Marsh and documents greater effective precipitation in southwestern North America during MIS 5a and MIS 4. In addition, we hypothesize that Deep Springs Lake was a balanced-fill lake that overflowed into Eureka Valley via the Soldier Pass wind gap during MIS 5a and MIS 4. DSV hydrology has implications for dispersal and endemism of the Deep Springs black toad (Anaxyrus exsul).
The superposition of data sets with internal parametric self-similarity is a longstanding and widespread technique for the analysis of many types of experimental data across the physical sciences. Typically, this superposition is performed manually, or recently through the application of one of a few automated algorithms. However, these methods are often heuristic in nature, are prone to user bias via manual data shifting or parameterization, and lack a native framework for handling uncertainty in both the data and the resulting model of the superposed data. In this work, we develop a data-driven, nonparametric method for superposing experimental data with arbitrary coordinate transformations, which employs Gaussian process regression to learn statistical models that describe the data, and then uses maximum a posteriori estimation to optimally superpose the data sets. This statistical framework is robust to experimental noise and automatically produces uncertainty estimates for the learned coordinate transformations. Moreover, it is distinguished from black-box machine learning in its interpretability—specifically, it produces a model that may itself be interrogated to gain insight into the system under study. We demonstrate these salient features of our method through its application to four representative data sets characterizing the mechanics of soft materials. In every case, our method replicates results obtained using other approaches, but with reduced bias and the addition of uncertainty estimates. This method enables a standardized, statistical treatment of self-similar data across many fields, producing interpretable data-driven models that may inform applications such as materials classification, design, and discovery.