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Recent excavations by the Ancient Southwest Texas Project of Texas State University sampled a previously undocumented Younger Dryas component from Eagle Cave in the Lower Pecos Canyonlands of Texas. This stratified assemblage consists of bison (Bison antiquus) bones in association with lithic artifacts and a hearth. Bayesian modeling yields an age of 12,660–12,480 cal BP, and analyses indicate behaviors associated with the processing of a juvenile bison and the manufacture and maintenance of lithic tools. This article presents spatial, faunal, macrobotanical, chronometric, geoarchaeological, and lithic analyses relating to the Younger Dryas component within Eagle Cave. The identification of the Younger Dryas occupation in Eagle Cave should encourage archaeologists to revisit previously excavated rockshelter sites in the Lower Pecos and beyond to evaluate deposits for unrecognized, older occupations.
Despite innovative treatments, the impairment in real-life functioning in subjects with schizophrenia (SCZ) remains an unmet need in the care of these patients. Recently, real-life functioning in SCZ was associated with abnormalities in different electrophysiological indices. It is still not clear whether this relationship is mediated by other variables, and how the combination of different EEG abnormalities influences the complex outcome of schizophrenia.
The purpose of the study was to find EEG patterns which can predict the outcome of schizophrenia and identify recovered patients.
Illness-related and functioning-related variables were measured in 61 SCZ at baseline and after four-years follow-up. EEGs were recorded at the baseline in resting-state condition and during two auditory tasks. We performed Sparse Partial Least Square (SPLS) Regression, using EEG features, age and illness duration to predict clinical and functional features at baseline and follow up. Through a Linear Support Vector Machine (Linear SVM) we used electrophysiological and clinical scores derived from SPLS regression, in order to classify recovered patients at follow-up.
We found one significant latent variable (p<0.01) capturing correlations between independent and dependent variables at follow-up (RHO=0.56). Among individual predictors, age and illness-duration showed the highest scores; however, the score for the combination of the EEG features was higher than all other predictors. Within dependent variables, negative symptoms showed the strongest correlation with predictors. Scores resulting from SPLS Regression classified recovered patients with 90.1% of accuracy.
A combination of electrophysiological markers, age and illness-duration might predict clinical and functional outcome of schizophrenia after 4 years of follow-up.
Different electrophysiological indices have been investigated to identify diagnostic and prognostic markers of schizophrenia (SCZ). However, these indices have limited use in clinical practice, since both specificity and association with illness outcome remain unclear. In recent years, machine learning techniques, through the combination of multidimensional data, have been used to better characterize SCZ and to predict illness course.
The aim of the present study is to identify multimodal electrophysiological biomarkers that could be used in clinical practice in order to improve precision in diagnosis and prognosis of SCZ.
Illness-related and functioning-related variables were measured at baseline in 113 subjects with SCZ and 57 healthy controls (HC), and after four-year follow-up in 61 SCZ. EEGs were recorded at baseline in resting-state condition and during two auditory tasks (MMN-P3a and N100-P3b). Through a Linear Support Vector Machine, using EEG data as predictors, four models were generated in order to classify SCZ and HC. Then, we combined unimodal classifiers’ scores through a stacking procedure. Pearson’s correlations between classifiers score with illness-related and functioning-related variables, at baseline and follow-up, were performed.
Each EEG model produced significant classification (p < 0.05). Global classifier discriminated SCZ from HC with accuracy of 75.4% (p < 0.01). A significant correlation (r=0.40, p=0.002) between the global classifier scores with negative symptoms at follow-up was found. Within negative symptoms, blunted affect showed the strongest correlation.
Abnormalities in electrophysiological indices might be considered trait markers of schizophrenia. Our results suggest that multimodal electrophysiological markers might have prognostic value for negative symptoms.
Ensuring equitable access to health care is a widely agreed-upon goal in medicine, yet access to care is a multidimensional concept that is difficult to measure. Although frameworks exist to evaluate access to care generally, the concept of “access to genomic medicine” is largely unexplored and a clear framework for studying and addressing major dimensions is lacking.
Comprised of seven clinical genomic research projects, the Clinical Sequencing Evidence-Generating Research consortium (CSER) presented opportunities to examine access to genomic medicine across diverse contexts. CSER emphasized engaging historically underrepresented and/or underserved populations. We used descriptive analysis of CSER participant survey data and qualitative case studies to explore anticipated and encountered access barriers and interventions to address them.
CSER’s enrolled population was largely lower income and racially and ethnically diverse, with many Spanish-preferring individuals. In surveys, less than a fifth (18.7%) of participants reported experiencing barriers to care. However, CSER project case studies revealed a more nuanced picture that highlighted the blurred boundary between access to genomic research and clinical care. Drawing on insights from CSER, we build on an existing framework to characterize the concept and dimensions of access to genomic medicine along with associated measures and improvement strategies.
Our findings support adopting a broad conceptualization of access to care encompassing multiple dimensions, using mixed methods to study access issues, and investing in innovative improvement strategies. This conceptualization may inform clinical translation of other cutting-edge technologies and contribute to the promotion of equitable, effective, and efficient access to genomic medicine.
This chapter provides several examples of how artificial intelligence–based technologies are changing human rights practice, from detecting abuses to dealing with their aftermath. It especially focuses on three critical issues where the field of psychology can address a spectrum of human rights needs. The first is the psychological impact of the application of AI within society, specifically the positive and negative impacts of its use within humanitarian and human rights work. The second is the risk of its application perpetuating bias and discrimination. The third is the spread of disinformation and the manipulation of public opinion. While the chapter touches on all three issues, it particularly focuses on the third because of the central role disinformation is currently playing in everything from democratic governance to daily life. For each of these issues, the chapter summarizes how psychological research might provide critical insights for mitigating harm. The chapter closes with priority considerations for minimizing the negative effects of AI on human rights.
Successful management of an event where health-care needs exceed regional health-care capacity requires coordinated strategies for scarce resource allocation. Publications for rapid development, training, and coordination of regional hospital triage teams to manage the allocation of scarce resources during coronavirus disease 2019 (COVID-19) are lacking. Over a period of 3 weeks, over 100 clinicians, ethicists, leaders, and public health authorities convened virtually to achieve consensus on how best to save the most lives possible and share resources. This is referred to as population-based crisis management. The rapid regionalization of 22 acute care hospitals across 4500 square miles in the midst of a pandemic with a shifting regulatory landscape was challenging, but overcome by mutual trust, transparency, and confidence in the public health authority. Because many cities are facing COVID-19 surges, we share a process for successful rapid formation of health-care care coalitions, Crisis Standard of Care, and training of Triage Teams. Incorporation of continuous process improvement and methods for communication is essential for successful implementation. Use of our regional health-care coalition communications, incident command system, and the crisis care committee helped mitigate crisis care in the San Diego and Imperial County region as COVID-19 cases surged and scarce resource collaborative decisions were required.
Substance use disorders are highly prevalent among people with schizophrenia. Dually diagnosed patients present with unfavorable course and poor long-term outcomes. Integrated, motivation-based treatment for both disorders in the same setting is considered the treatment of choice. However, integrated treatment programs are not readily available and effect sizes of the programs are modest.
To evaluate an integrated psychosocial treatment program for people with schizophrenia and substance use disorders in the setting of a community psychiatric hospital.
100 in-patients with schizophrenia and substance use disorders were randomized to Integrated Treatment (IT) or Treatment as usual (TAU). The IT group was initially treated in a specialized open ward; upon discharge they were offered treatment in a specialized out-patient program of the hospital. The TAU group was initially treated in another non-specialized open ward; upon discharge they were offered treatment in the non-specialized out-patient unit of the hospital. TAU included pharmacotherapy, medical treatment, supportive psychotherapy and further aids by nursing staff and social workers. IT included all elements of TAU plus manualized group therapy with motivational interviewing, psychoeducation and cognitive-behavioral approaches. Assessments were performed at baseline and after 3, 6 and 12 months.
The IT group had slightly less drop-outs in the follow-up period (non-significant). The IT group was more satisfied with treatment and they developed a higher motivation to reduce substance use. Both groups succeeded in reducing substance use during follow-up, whereas the IT group did slightly better (non-significant).
Negative symptoms are a core feature of schizophrenia but their pathophysiology remains elusive. They cluster in a motivation-related domain, including apathy, anhedonia, asociality and in an expression-related domain, including alogia and blunted affect.
Our aim was to investigate the different neurobiological underpinnings of the two domains using the brain electrical microstates (MS), which reflect global patterns of functional connectivity with high temporal resolution.
We recorded multichannel resting EEGs in 142 schizophrenia patients (SCZ) and in 64 healthy controls (HC), recruited to the Italian network for research on psychoses study. Four microstates (MS) classes were computed from resting EEG data using the K-Mean clustering algorithm. Pearson's coefficient was used to investigate correlations of microstates measures with negative symptom domains, assessed by the Brief Negative Symptoms Scale (BNSS).
SCZ, in comparison to HC, showed increased contribution and duration of MS-C. Only the avolition domain of BNSS correlated with the contribution and occurrence of MS-A. Within the same domain, anticipatory anhedonia, apathy and asociality, but not consummatory anhedonia, were positively correlated with contribution and occurrence of microstate A. Asociality was also negatively correlated with contribution and occurrence of MS-D.
Our findings support different neurobiological underpinnings of the negative symptom domains, avolition and expressive deficit. Furthermore, our results lend support to the hypothesis that only anticipatory anhedonia is linked to the avolition domain of the negative symptoms. Mixed results in the literature concerning the presence of MS-A and D abnormalities in schizophrenia might be related to the syndrome heterogeneity.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
In subjects with schizophrenia (SCZ), the disorganization factor was found to be a strong predictor of real-life functioning. “Conceptual disorganization” (P2), “difficulties in abstract thinking” (N5) and “poor attention” (G11) are considered core aspects of the disorganization factor, as assessed by PANSS. The overlap of these items with neurocognitive functions is debated and should be further investigated.
Within the Italian network for research on psychoses study, electrophysiological and neurocognitive correlates of the disorganization factor and its component items were investigated.
Resting state EEGs were recorded in 145 stabilized SCZ and 69 matched healthy controls (HC). Spectral amplitude (SAmp) was averaged in nine frequency bands. MATRICS consensus cognitive battery (MCCB) was used for neurocognitive assessment. Band SAmp differences and correlations with psychopathology and MCCB scores were explored by global randomization statistics.
SCZ showed increased delta, theta, and beta1 and decreased alpha2 SAmp. A negative correlation between alpha1 and disorganization was observed in SCZ. At the item level, only N5 showed this correlation. MCCB neurocognitive composite was associated with P2 and N5 but not with alpha1 SAmp.
Our findings suggest an heterogeneity of the disorganization dimension and a partial overlap with neurocognitive domains. The N5, “difficulties in abstract thinking”, had a unique association with alpha1 SAmp, which is thought to be involved in the formation of conceptual maps.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Since the year 2000, Greenland ice sheet mass loss has been dominated by a decrease in surface mass balance rather than an increase in solid ice discharge. Southeast Greenland is an important region to understand how high accumulation rates can offset increasing Greenland ice sheet meltwater runoff. To that end, we derive a new 9-year long dataset (2009–17) of accumulation rates in Southeast Greenland using NASA Operation IceBridge snow radar. Our accumulation dataset derived from internal layers focuses on high elevations (1500–3000 m) because at lower elevations meltwater percolation obscured internal layer structure. The uncertainty of the radar-derived accumulation rates is 11% [using Firn Densification Model (FDM) density profiles] and the average accumulation rate ranges from 0.5 to 1.2 m w.e. With our observations spanning almost a decade, we find large inter-annual variability, but no significant trend. Accumulation rates are compared with output from two regional climate models (RCMs), MAR and RACMO2. This comparison shows that the models are underestimating accumulation in Southeast Greenland and the models misrepresent spatial heterogeneity due to an orographically forced bias in snowfall near the coast. Our dataset is useful to fill in temporal and spatial data gaps, and to evaluate RCMs where few in situ measurements are available.
Disaster Medicine (DM) education for Emergency Medicine (EM) residents is highly variable due to time constraints, competing priorities, and program expertise. The investigators’ aim was to define and prioritize DM core competencies for EM residency programs through consensus opinion of experts and EM professional organization representatives.
Investigators utilized a modified Delphi methodology to generate a recommended, prioritized core curriculum of 40 DM educational topics for EM residencies.
The DM topics recommended and outlined for inclusion in EM residency training included: patient triage in disasters, surge capacity, introduction to disaster nomenclature, blast injuries, hospital disaster mitigation, preparedness, planning and response, hospital response to chemical mass-casualty incident (MCI), decontamination indications and issues, trauma MCI, disaster exercises and training, biological agents, personal protective equipment, and hospital response to radiation MCI.
This expert-consensus-driven, prioritized ranking of DM topics may serve as the core curriculum for US EM residency programs.
Meaningful participant engagement has been identified as a key contributor to the success of efforts to share data via a “Medical Information Commons” (MIC). We present findings from expert stakeholder interviews aimed at understanding barriers to engagement and the appropriate role of MIC participants. Although most interviewees supported engagement, they distinguished between individual versus collective forms. They also noted challenges including representation and perceived inefficiency, prompting reflection on political aspects of engagement and efficiency concerns.
Drawing on a landscape analysis of existing data-sharing initiatives, in-depth interviews with expert stakeholders, and public deliberations with community advisory panels across the U.S., we describe features of the evolving medical information commons (MIC). We identify participant-centricity and trustworthiness as the most important features of an MIC and discuss the implications for those seeking to create a sustainable, useful, and widely available collection of linked resources for research and other purposes.
This paper describes a model of electron energization and cyclotron-maser emission applicable to astrophysical magnetized collisionless shocks. It is motivated by the work of Begelman, Ergun and Rees [Astrophys. J. 625, 51 (2005)] who argued that the cyclotron-maser instability occurs in localized magnetized collisionless shocks such as those expected in blazar jets. We report on recent research carried out to investigate electron acceleration at collisionless shocks and maser radiation associated with the accelerated electrons. We describe how electrons accelerated by lower-hybrid waves at collisionless shocks generate cyclotron-maser radiation when the accelerated electrons move into regions of stronger magnetic fields. The electrons are accelerated along the magnetic field and magnetically compressed leading to the formation of an electron velocity distribution having a horseshoe shape due to conservation of the electron magnetic moment. Under certain conditions the horseshoe electron velocity distribution function is unstable to the cyclotron-maser instability [Bingham and Cairns, Phys. Plasmas 7, 3089 (2000); Melrose, Rev. Mod. Plasma Phys. 1, 5 (2017)].
Objectives: The objective of this study was to evaluate the feasibility and implementation of a standardized medically supervised concussion protocol established between a city-wide AAA hockey league and a multi-disciplinary concussion program. Methods: We conducted a retrospective review of injury surveillance, clinical and healthcare utilization data from all athletes evaluated and managed through the Winnipeg AAA Hockey concussion protocol during the 2016-2017 season. We also conducted post-season email surveys of head coaches and parents responsible for athletes who competed in the same season. Results: During the 2016-2017 season, 28 athletes were evaluated through the medically supervised concussion protocol, with two athletes undergoing evaluation for repeat injuries (a total of 30 suspected injuries and consultations). In all, 96.7% of the athletes managed through the concussion protocol were captured by the league-designated Concussion Protocol Coordinator and 100% of eligible athletes underwent complete medical follow-up and clearance to return to full hockey activities. Although 90% of responding head coaches and 91% of parents were aware of the concussion protocol, survey results suggest that some athletes who sustained suspected concussions were not managed through the protocol. Head coaches and parents also indicated that athlete education and communication between medical and sport stakeholders were other elements of the concussion protocol that could be improved. Conclusion: Successful implementation of a medically supervised concussion protocol for youth hockey requires clear communication between sport stakeholders and timely access to multi-disciplinary experts in traumatic brain and spine injuries. Standardized concussion protocols for youth sports may benefit from periodic evaluations by sport stakeholders and incorporation of national guideline best practices and resources.
Taking a cultural approach to understanding attributional processes provides new insights into how people make attributions within different cultural environments. First, it provides new insights by demonstrating cultural differences (i.e., the “what”). Second, it provides new insights by thoroughly examining when and why these cultural differences occur – which provides insight into the attributional process as it occurs in the East and West (i.e., the “why”). If instructors wish to emphasize culture even more strongly, they can include a discussion of the value of cross-cultural research not only to understanding others but also for understanding one’s own culture. Indeed, a cross-cultural approach helps students appreciate the subjectivity of attributions by emphasizing that attributions convey just as much about our own cultural orientation and ways of thinking about the world as they do other people’s behavior.
Returning genomic research results to family members raises complex questions. Genomic research on life-limiting conditions such as cancer, and research involving storage and reanalysis of data and specimens long into the future, makes these questions pressing. This author group, funded by an NIH grant, published consensus recommendations presenting a framework. This follow-up paper offers concrete guidance and tools for implementation. The group collected and analyzed relevant documents and guidance, including tools from the Clinical Sequencing Exploratory Research (CSER) Consortium. The authors then negotiated a consensus toolkit of processes and documents. That toolkit offers sample consent and notification documents plus decision flow-charts to address return of results to family of living and deceased participants, in adult and pediatric research. Core concerns are eliciting participant preferences on sharing results with family and on choice of a representative to make decisions about sharing after participant death.
The physics of compressible turbulence in high energy density (HED) plasmas is an unchartered experimental area. Simulations of compressible and radiative flows relevant for astrophysics rely mainly on subscale parameters. Therefore, we plan to perform turbulent hydrodynamics experiments in HED plasmas (TurboHEDP) in order to improve our understanding of such important phenomena for interest in both communities: laser plasma physics and astrophysics. We will focus on the physics of supernovae remnants which are complex structures subject to fluid instabilities such as the Rayleigh–Taylor and Kelvin–Helmholtz instabilities. The advent of megajoule laser facilities, like the National Ignition Facility and the Laser Megajoule, creates novel opportunities in laboratory astrophysics, as it provides unique platforms to study turbulent mixing flows in HED plasmas. Indeed, the physics requires accelerating targets over larger distances and longer time periods than previously achieved. In a preparatory phase, scaling from experiments at lower laser energies is used to guarantee the performance of future MJ experiments. This subscale experiments allow us to develop experimental skills and numerical tools in this new field of research, and are stepping stones to achieve our objectives on larger laser facilities. We review first in this paper recent advances in high energy density experiments devoted to laboratory astrophysics. Then we describe the necessary steps forward to commission an experimental platform devoted to turbulent hydrodynamics on a megajoule laser facility. Recent novel experimental results acquired on LULI2000, as well as supporting radiative hydrodynamics simulations, are presented. Together with the development of LiF detectors as transformative X-ray diagnostics, these preliminary results are promising on the way to achieve micrometric spatial resolution in turbulent HED physics experiments in the near future.
In this paper, we present a model characterizing the interaction of a radiative shock (RS) with a solid material, as described in a recent paper (Koenig et al., Phys. Plasmas, 24, 082707 (2017)), the new model is then related to recent experiments performed on the GEKKO XII laser facility. The RS generated in a xenon gas cell propagates towards a solid obstacle that is ablated by radiation coming from the shock front and the radiative precursor, mimicking processes occurring in astrophysical phenomena. The model presented here calculates the dynamics of the obstacle expansion, which depends on several parameters, notably the geometry and the temperature of the shock. All parameters required for the model have been obtained from experiments. Good agreement between experimental data and the model is found when spherical geometry is taken into account. As a consequence, this model is a useful and easy tool to infer parameters from experimental data (such as the shock temperature), and also to design future experiments.