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The stars of the Milky Way carry the chemical history of our Galaxy in their atmospheres as they journey through its vast expanse. Like barcodes, we can extract the chemical fingerprints of stars from high-resolution spectroscopy. The fourth data release (DR4) of the Galactic Archaeology with HERMES (GALAH) Survey, based on a decade of observations, provides the chemical abundances of up to 32 elements for 917 588 stars that also have exquisite astrometric data from the Gaia satellite. For the first time, these elements include life-essential nitrogen to complement carbon, and oxygen as well as more measurements of rare-earth elements critical to modern-life electronics, offering unparalleled insights into the chemical composition of the Milky Way. For this release, we use neural networks to simultaneously fit stellar parameters and abundances across the whole wavelength range, leveraging synthetic grids computed with Spectroscopy Made Easy. These grids account for atomic line formation in non-local thermodynamic equilibrium for 14 elements. In a two-iteration process, we first fit stellar labels to all 1 085 520 spectra, then co-add repeated observations and refine these labels using astrometric data from Gaia and 2MASS photometry, improving the accuracy and precision of stellar parameters and abundances. Our validation thoroughly assesses the reliability of spectroscopic measurements and highlights key caveats. GALAH DR4 represents yet another milestone in Galactic archaeology, combining detailed chemical compositions from multiple nucleosynthetic channels with kinematic information and age estimates. The resulting dataset, covering nearly a million stars, opens new avenues for understanding not only the chemical and dynamical history of the Milky Way but also the broader questions of the origin of elements and the evolution of planets, stars, and galaxies.
This Element examines various aspects of the demarcation problem: finding a distinction between science and pseudoscience. Section 1 introduces issues surrounding pseudoscience in the recent literature. Popper's falsificationism is presented in Section 2, alongside some of its early critics, such as Thomas Kuhn and Imre Lakatos. It is followed in Section 3 by the notable criticism of the Popperian program by Larry Laudan that put the issue out of fashion for decades. Section 4 explores recent multi-criteria approaches that seek to define pseudoscience not only along a single criterion, but by considering the diversity and historical dimension of science. Section 5 introduces the problem of values (the 'new demarcation problem') and addresses how we can use values in the problem of pseudoscience. Finally, Section 6 concludes by emphasizing the need for an attitude-oriented approach over a rigid, method-based demarcation, recognizing scientific practice's evolving and multifaceted nature.
Research participants” feedback about their participation experiences offers critical insights for improving programs. A shared Empowering the Participant Voice (EPV) infrastructure enabled a multiorganization collaborative to collect, analyze, and act on participants’ feedback using validated participant-centered measures.
Methods:
A consortium of academic research organizations with Clinical and Translational Science Awards (CTSA) programs administered the Research Participant Perception Survey (RPPS) to active or recent research participants. Local response data also aggregated into a Consortium database, facilitating analysis of feedback overall and for subgroups.
Results:
From February 2022 to June 2024, participating organizations sent surveys to 28,096 participants and received 5045 responses (18%). Respondents were 60% female, 80% White, 13% Black, 2% Asian, and 6% Latino/x. Most respondents (85–95%) felt respected and listened to by study staff; 68% gave their overall experience the top rating. Only 60% felt fully prepared by the consent process. Consent, feeling valued, language assistance, age, study demands, and other factors were significantly associated with overall experience ratings. 63% of participants said that receiving a summary of the study results would be very important to joining a future study. Intersite scores differed significantly for some measures; initiatives piloted in response to local findings raised experience scores.
Conclusion:
RPPS results from 5045 participants from seven CTSAs provide a valuable evidence base for evaluating participants’ research experiences and using participant feedback to improve research programs. Analyses revealed opportunities for improving research practices. Sites piloting local change initiatives based on RPPS findings demonstrated measurable positive impact.
Coronavirus disease-2019 precipitated the rapid deployment of novel therapeutics, which led to operational and logistical challenges for healthcare organizations. Four health systems participated in a qualitative study to abstract lessons learned, challenges, and promising practices from implementing neutralizing monoclonal antibody (nMAb) treatment programs. Lessons are summarized under three themes that serve as critical building blocks for health systems to rapidly deploy novel therapeutics during a pandemic: (1) clinical workflows, (2) data infrastructure and platforms, and (3) governance and policy. Health systems must be sufficiently agile to quickly scale programs and resources in times of uncertainty. Real-time monitoring of programs, policies, and processes can help support better planning and improve program effectiveness. The lessons and promising practices shared in this study can be applied by health systems for distribution of novel therapeutics beyond nMAbs and toward future pandemics and public health emergencies.
Autism Spectrum Disorders (ASDs) are a group of severe developmental and neuropsychiatric disorders usually apparent by the age of three. Autism, referred to as autism spectrum disorder in the 11th revision of the International Classification of Diseases (ICD-11), is a neurodevelopmental condition characterised by persistent deficits in social interaction and social communication, as well as a range of restricted, repetitive behaviours (World Health Organization 2018). The onset of autism is in the developmental period (0–18 years of age), though for some autistic persons the symptoms may manifest later in life, at a time of increased social demands (World Health Organization 2018). In addition to the aforementioned core autistic features, many autistic people have associated symptoms, including hypo- or hypersensitivities to sensory stimuli, difficulties describing their emotional state (alexithymia), and problems with gross motor co-ordination The chapter will discuss the interface between autism spectrum disorder and intellectual disability and the potential management of the disorder. It will also cover the gender variations in presentation.
Aggression is often defined with reference to the intended consequences of an act exhibited by a person, or as any behaviour exhibited by a person where they intentionally acted to cause harm to another. Behaviours which cause harm but without associated intent tend not to be defined as aggression. Some people with intellectual disability may engage in behaviours with intent to cause harm to another, while for others, especially those with severe to profound intellectual disability, an absence of intent may exist. Aggressive behaviour exhibited by people with intellectual disability can take the form of verbal threats, physical aggression directed towards others including punching, kicking, slapping and biting, amongst other behaviours, as well as property damage and destruction. Aggressive behaviour can cause serious harm to others which may be life-threatening and result in social exclusion and a reduced quality of life. This chapter provides an overview of severe aggression and self-injurious behaviour relevant to people with disorders of intellectual development, and focuses on the evidence base for the various challenging behaviours and whether there is benefit from medication or alternative approaches.
In response to the COVID-19 pandemic, we rapidly implemented a plasma coordination center, within two months, to support transfusion for two outpatient randomized controlled trials. The center design was based on an investigational drug services model and a Food and Drug Administration-compliant database to manage blood product inventory and trial safety.
Methods:
A core investigational team adapted a cloud-based platform to randomize patient assignments and track inventory distribution of control plasma and high-titer COVID-19 convalescent plasma of different blood groups from 29 donor collection centers directly to blood banks serving 26 transfusion sites.
Results:
We performed 1,351 transfusions in 16 months. The transparency of the digital inventory at each site was critical to facilitate qualification, randomization, and overnight shipments of blood group-compatible plasma for transfusions into trial participants. While inventory challenges were heightened with COVID-19 convalescent plasma, the cloud-based system, and the flexible approach of the plasma coordination center staff across the blood bank network enabled decentralized procurement and distribution of investigational products to maintain inventory thresholds and overcome local supply chain restraints at the sites.
Conclusion:
The rapid creation of a plasma coordination center for outpatient transfusions is infrequent in the academic setting. Distributing more than 3,100 plasma units to blood banks charged with managing investigational inventory across the U.S. in a decentralized manner posed operational and regulatory challenges while providing opportunities for the plasma coordination center to contribute to research of global importance. This program can serve as a template in subsequent public health emergencies.
This position paper by the international IMMERSE consortium reviews the evidence of a digital mental health solution based on Experience Sampling Methodology (ESM) for advancing person-centered mental health care and outlines a research agenda for implementing innovative digital mental health tools into routine clinical practice. ESM is a structured diary technique recording real-time self-report data about the current mental state using a mobile application. We will review how ESM may contribute to (1) service user engagement and empowerment, (2) self-management and recovery, (3) goal direction in clinical assessment and management of care, and (4) shared decision-making. However, despite the evidence demonstrating the value of ESM-based approaches in enhancing person-centered mental health care, it is hardly integrated into clinical practice. Therefore, we propose a global research agenda for implementing ESM in routine mental health care addressing six key challenges: (1) the motivation and ability of service users to adhere to the ESM monitoring, reporting and feedback, (2) the motivation and competence of clinicians in routine healthcare delivery settings to integrate ESM in the workflow, (3) the technical requirements and (4) governance requirements for integrating these data in the clinical workflow, (5) the financial and competence related resources related to IT-infrastructure and clinician time, and (6) implementation studies that build the evidence-base. While focused on ESM, the research agenda holds broader implications for implementing digital innovations in mental health. This paper calls for a shift in focus from developing new digital interventions to overcoming implementation barriers, essential for achieving a true transformation toward person-centered care in mental health.
In 2010, Turaev introduced knotoids as a variation on knots that replaces the embedding of a circle with the embedding of a closed interval with two endpoints which here we call poles. We define generalised knotoids to allow arbitrarily many poles, intervals and circles, each pole corresponding to any number of interval endpoints, including zero. This theory subsumes a variety of other related topological objects and introduces some particularly interesting new cases. We explore various analogs of knotoid invariants, including height, index polynomials, bracket polynomials and hyperbolicity. We further generalise to knotoidal graphs, which are a natural extension of spatial graphs that allow both poles and vertices.
Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence.
Aims
The aim of this study was to generate an experts’ consensus on how the medical regulatory method used for assessing safety could best be adapted for DMHIs.
Method
An online Delphi study containing three rounds was conducted with an international panel of 20 experts with experience/knowledge in the field of UK digital mental health.
Results
Sixty-four items were generated, of which 41 achieved consensus (64%). Consensus emerged around ten recommendations, falling into five main themes: Enhancing the quality of adverse events data in DMHIs; Re-defining serious adverse events for DMHIs; Reassessing short-term symptom deterioration in psychological interventions as a therapeutic risk; Maximising the benefit of the Yellow Card Scheme; and Developing a harmonised approach for assessing the safety of psychological interventions in general.
Conclusion
The implementation of the recommendations provided by this consensus could improve the assessment of safety of DMHIs, making them more effective in detecting and mitigating risk.
How was trust created and reinforced between the inhabitants of medieval and early modern cities? And how did the social foundations of trusting relationships change over time? Current research highlights the role of kinship, neighbourhood, and associations, particularly guilds, in creating ‘relationships of trust’ and social capital in the face of high levels of migration, mortality, and economic volatility, but tells us little about their relative importance or how they developed. We uncover a profound shift in the contribution of family and guilds to trust networks among the middling and elite of one of Europe's major cities, London, over three centuries, from the 1330s to the 1680s. We examine almost 15,000 networks of sureties created to secure orphans’ inheritances to measure the presence of trusting relationships connected by guild membership, family, and place. We uncover a profound increase in the role of kinship – a re-embedding of trust within the family – and a decline of the importance of shared guild membership in connecting Londoners who secured orphans’ inheritances together. These developments indicate a profound transformation in the social fabric of urban society.
Design hackathons offer a unique research opportunity to study time-pressured collaborative design. At the same time, research on design hackathons faces unique methodological challenges, prompting the exploration of new research approaches. This paper proposes a new data-collection framework that leverages a virtual format of hackathon events and enables a deeper insight into hackathon dynamics. The framework applicability is presented through a case study of the IDEA challenge hackathon, in which different intrusive and non-intrusive data collection approaches were used.
Recent measurements of inertial particles in isotropic turbulence (Hammond & Meng, J. Fluid Mech., vol. 921, 2021, A16) revealed surprising extreme clustering of particles at near-contact separations $(r)$, whereby the radial distribution function, $g(r)$, grows from $O(10)$ to $O(10^3)$ with a $(r/a)^{-6}$ scaling (where $a$ is the particle radius), and a surprising upturn of the mean inward particle-pair relative velocity (MIRV). Hydrodynamic interactions (HIs) were proposed to explain the extreme clustering, but despite predicting the correct scaling $(r/a)^{-6}$, the HI theory underpredicted $g(r)$ by at least two orders of magnitude (Bragg et al., J. Fluid Mech., vol. 933, 2022, A31). To further understand the extreme clustering phenomenon and the relevance of HI, we characterize $g(r)$ and particle-pair kinematics for Stokes numbers $0.07 \leq St \leq 3.68$ in a homogeneous isotropic turbulence chamber using three-dimensional (3-D) particle tracking resolved to near–contact. A drift–diffusion equation governing $g(r)$ is presented to investigate the kinematic mechanisms of particle pairs. Measurements in all 24 conditions show that when $r/a\lessapprox 20$, extreme clustering consistently occurs, scaling as $g(r) \sim (r/a)^{-k}$ with $4.5 \leq k \leq 7.6$, which increases with $St$. Here $g(r)$ varies with $St$, particle size, density and polydispersity in ways that HI cannot explain. The extreme clustering region features an inward drift contributed by particle-pair turbophoresis and an inward radial relative acceleration. The latter indicates an interparticle attractive force at these separations that HI also cannot explain. The MIRV turns upward when approaching the extreme clustering region, opposite to direct numerical simulation predictions. These observations further support our previous assessment that extreme clustering arises from particle–particle interactions, but HI is not the main mechanism.
Empowering the Participant Voice (EPV) is an NCATS-funded six-CTSA collaboration to develop, demonstrate, and disseminate a low-cost infrastructure for collecting timely feedback from research participants, fostering trust, and providing data for improving clinical translational research. EPV leverages the validated Research Participant Perception Survey (RPPS) and the popular REDCap electronic data-capture platform. This report describes the development of infrastructure designed to overcome identified institutional barriers to routinely collecting participant feedback using RPPS and demonstration use cases. Sites engaged local stakeholders iteratively, incorporating feedback about anticipated value and potential concerns into project design. The team defined common standards and operations, developed software, and produced a detailed planning and implementation Guide. By May 2023, 2,575 participants diverse in age, race, ethnicity, and sex had responded to approximately 13,850 survey invitations (18.6%); 29% of responses included free-text comments. EPV infrastructure enabled sites to routinely access local and multi-site research participant experience data on an interactive analytics dashboard. The EPV learning collaborative continues to test initiatives to improve survey reach and optimize infrastructure and process. Broad uptake of EPV will expand the evidence base, enable hypothesis generation, and drive research-on-research locally and nationally to enhance the clinical research enterprise.
Therapeutics targeting frontotemporal dementia (FTD) are entering clinical trials. There are challenges to conducting these studies, including the relative rarity of the disease. Remote assessment tools could increase access to clinical research and pave the way for decentralized clinical trials. We developed the ALLFTD Mobile App, a smartphone application that includes assessments of cognition, speech/language, and motor functioning. The objectives were to determine the feasibility and acceptability of collecting remote smartphone data in a multicenter FTD research study and evaluate the reliability and validity of the smartphone cognitive and motor measures.
Participants and Methods:
A diagnostically mixed sample of 207 participants with FTD or from familial FTD kindreds (CDR®+NACC-FTLD=0 [n=91]; CDR®+NACC-FTLD=0.5 [n=39]; CDR®+NACC-FTLD>1 [n=39]; unknown [n=38]) were asked to remotely complete a battery of tests on their smartphones three times over two weeks. Measures included five executive functioning (EF) tests, an adaptive memory test, and participant experience surveys. A subset completed smartphone tests of balance at home (n=31) and a finger tapping test (FTT) in the clinic (n=11). We analyzed adherence (percentage of available measures that were completed) and user experience. We evaluated Spearman-Brown split-half reliability (100 iterations) using the first available assessment for each participant. We assessed test-retest reliability across all available assessments by estimating intraclass correlation coefficients (ICC). To investigate construct validity, we fit regression models testing the association of the smartphone measures with gold-standard neuropsychological outcomes (UDS3-EF composite [Staffaroni et al., 2021], CVLT3-Brief Form [CVLT3-BF] Immediate Recall, mechanical FTT), measures of disease severity (CDR®+NACC-FTLD Box Score & Progressive Supranuclear Palsy Rating Scale [PSPRS]), and regional gray matter volumes (cognitive tests only).
Results:
Participants completed 70% of tasks. Most reported that the instructions were understandable (93%), considered the time commitment acceptable (97%), and were willing to complete additional assessments (98%). Split-half reliability was excellent for the executive functioning (r’s=0.93-0.99) and good for the memory test (r=0.78). Test-retest reliabilities ranged from acceptable to excellent for cognitive tasks (ICC: 0.70-0.96) and were excellent for the balance (ICC=0.97) and good for FTT (ICC=0.89). Smartphone EF measures were strongly associated with the UDS3-EF composite (ß's=0.6-0.8, all p<.001), and the memory test was strongly correlated with total immediate recall on the CVLT3-BF (ß=0.7, p<.001). Smartphone FTT was associated with mechanical FTT (ß=0.9, p=.02), and greater acceleration on the balance test was associated with more motor features (ß=0.6, p=0.02). Worse performance on all cognitive tests was associated with greater disease severity (ß's=0.5-0.7, all p<.001). Poorer performance on the smartphone EF tasks was associated with smaller frontoparietal/subcortical volume (ß's=0.4-0.6, all p<.015) and worse memory scores with smaller hippocampal volume (ß=0.5, p<.001).
Conclusions:
These results suggest remote digital data collection of cognitive and motor functioning in FTD research is feasible and acceptable. These findings also support the reliability and validity of unsupervised ALLFTD Mobile App cognitive tests and provide preliminary support for the motor measures, although further study in larger samples is required.
Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.
Participants and Methods:
Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.
Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.
Results:
We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).
Conclusions:
This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.
Epilepsy is a chronic neurological disease, and surgery is a common treatment option for persons who do not respond to medication. Neuropsychology plays an important role in the epilepsy presurgical workup, characterizing the cognitive functioning of patients with epilepsy as well as assisting in the determination of which hemisphere seizures originate in the brain through testing of different cognitive functions. NeuroQuant is a relatively newer software that analyzes clinical neuroimaging to quantify brain volume. The objective of this study was to determine if changes in left versus right total hippocampal volume predicted changes in verbal versus nonverbal memory performance.
Participants and Methods:
Cognitive performance and NeuroQuant bilateral hippocampal volume were examined in a cross-sectional sample of 37 patients with epilepsy. All patients had undergone a comprehensive presurgical neuropsychological evaluation as well as magnetic resonance imaging (MRI) and these results were analyzed using a series of linear regression analyses.
Results:
Total left hippocampal volume was a significant predictor of delayed verbal free recall (RAVLT F(1, 31) = 4.79, p< .036, RA2 = 0.13, and ß=.37, p<.036). Even when controlling for the effects of biological sex, education, and depression, left hippocampal volume remained a significant predictor (ß=.42, p<.025). Total left hippocampal volume did not predict other verbal memory scores. Total right hippocampal volume was a significant predictor of delayed nonverbal figure recall (RCFT F(1, 31)= 6.46, p<.016), RA2 = .17 and ß=.42) p<.016). When controlling for the effects of biological sex, education, and depression, right hippocampal volume remained a significant predictor (ß=.404, p<.026). Total right hippocampal volume did not predict other nonverbal memory scores.
Conclusions:
These findings validate prior research demonstrating the importance of the left hippocampus in verbal memory and right hippocampus in nonverbal memory. Findings also demonstrate the clinical utility of neuropsychological evaluation in determining laterality in the epilepsy presurgical workup process, as well as support NeuroQuants’ inclusion as an additional consideration in that process.
Hippocampal pathology is a consistent feature in persons with temporal lobe epilepsy (TLE) and a strong biomarker of memory impairment. Histopathological studies have identified selective patterns of cell loss across hippocampal subfields in TLE, the most common being cellular loss in the cornu ammonis 1 (CA1) and dentage gyrus (DG). Structural neuroimaging provides a non-invasive method to understand hippocampal pathology, but traditionally only at a whole-hippocampal level. However, recent methodological advances have enabled the non-invasive quantification of subfield pathology in patients, enabling potential integration into clinical workflow. In this study, we characterize patterns of hippocampal subfield atrophy in patients with TLE and examine the associations between subfield atrophy and clinical characteristics.
Participants and Methods:
High-resolution T2 and T1-weighted MRI were collected from 31 participants (14 left TLE; 6 right TLE; 11 healthy controls [HC], aged 18-61 years). Reconstructions of hippocampal subfields and estimates of their volumes were derived using the Automated Segmentation of Hippocampal Subfields (ASHS) pipeline. Total hippocampal volume was calculated by combining estimates of the subfields CA1-3, DG, and subiculum. To control for variations in head size, all volume estimates were divided by estimates of total brain volume. To assess disease effects on hippocampal atrophy, hippocampi were recoded as either ipsilateral or contralateral to the side of seizure focus. Two sample t-tests at a whole-hippocampus level were used to test for ipsilateral and contralateral volume loss in patients relative to HC. To assess whether we replicated the selective histopathological patterns of subfield atrophy, we carried out mixed-effects ANOVA, coding for an interaction between diagnostic group and hippocampal subfield. Finally, to assess effects of disease load, non-parametric correlations were performed between subfield volume and age of first seizure and duration of illness.
Results:
Patients had significantly smaller total ipsilateral hippocampal volume compared with HC (d=1.23, p<.005). Contralateral hippocampus did not significantly differ between TLE and HC. Examining individual subfields for the ipsilateral hemisphere revealed significant main-effects for group (F(1, 29)=8.2, p<0.01), subfields (F(4, 115)=550.5, p<0.005), and their interaction (F(4, 115)=8.1, p<0.001). Post-hoc tests revealed that TLE had significantly smaller volume in the ipsilateral CA1 (d=-2.0, p<0.001) and DG (d = -1.4, p<0.005). Longer duration of illness was associated with smaller volume of ipsilateral CA2 (p=-0.492, p<0.05) and larger volume of contralateral whole-hippocampus (p=0.689, p<0.001), CA1 (p=0.614, p < 0.005), and DG (p=0.450, p<0.05).
Conclusions:
Histopathological characterization after surgery has revealed important associations between hippocampal subfield cell loss and memory impairments in patients with TLE. Here we demonstrate that non-invasive neuroimaging can detect a pattern of subfield atrophy in TLE (i.e., CA1/DG) that matches the most common form of histopathologically-observed hippocampal sclerosis in TLE (HS Type 1) and has been linked directly to both verbal and visuospatial memory impairment. Finally, we found evidence that longer disease duration is associated with larger contralateral hippocampal volume, driven by increases in CA1 and DG. This may reflect subfield-specific functional reorganization to the unaffected brain tissue, a compensatory effect which may have important implications for patient function and successful treatment outcomes.
Acute cognitive complications following COVID-19 infection have been appreciated in a subset of patients since the early months of the global pandemic. Emerging data reveal that some patients go on to experience cognitive improvement, whereas others may experience further cognitive decline. We aimed to assess trajectories and predictors of cognitive change in a sample of post-COVID-19 patients.
Participants and Methods:
This prospective cohort study assessed longitudinal cognitive change in adults receiving care for COVID-19 in the Johns Hopkins Post-Acute COVID-19 Team (JH PACT) clinic. Participants self-administered the Digital Automated Neurobehavioral Assessment (DANA) battery of seven cognitive tests and a performance-based measure of cognitive fatigue on up to six occasions over six weeks. Improvement or decline between the first and last assessment was defined as change of >1 standard deviation of the baseline mean of each outcome. Potential predictors of change included demographic features (age, sex, race/ethnicity, education), COVID-19 illness characteristics (hospitalization or ICU stay, months since symptom onset), and comorbid disease burden. Analyses included measures of central tendency, independent samples t-tests, and chi-square tests of independence.
Results:
Of the 36 enrolled participants, 29 (81%) completed at least one DANA assessment (M = 4.7 assessments, SD = 1.8). Those completing at least three assessments (n = 24, 66.7%) were included in the present analyses (71% female; 58% white; M age = 54 years, SD = 10.9; M education = 14.6 years, SD = 2.4; M months since COVID-19 symptom onset at recruitment = 9.8, SD = 4.7; M comorbidities = 2.8, SD = 2.0). Fatigue was the most frequently improved outcome measure, with 41.7% of participants scoring >1 standard deviation above the baseline mean fatigue score at their final assessment. Among cognitive outcomes, the greatest frequency of improvement was observed on tests assessing rapid spatial processing (37.5%), processing speed (33.3%), and memory (33.3%). There were no consistent predictors of improvement, but several subtest-specific findings emerged. Specifically, (a) more comorbidities were positively associated with rate of fatigue reduction (p = .04), (b) longer duration since COVID-19 illness was positively associated with rates of memory improvement (p = .02), (c) older age, male sex, and more comorbidities were positively associated with rate of improvement in reaction time (ps < .05), and (d) more assessments completed was positively associated with rates of improvements in working memory (ps < .05). Response inhibition (12.5%), simple reaction times (16.7%), and working memory (16.7%) showed the lowest rates of improvement over time. Declines in cognition were infrequent, with 4.2 - 8.3% (n = 1 to 2) declining on measures of procedural reaction time, spatial processing, inhibitory control, or working memory.
Conclusions:
At an average of >9 months following acute COVID-19 illness, we observed longitudinal improvements in cognitive fatigue as well as processing speed, memory, and spatial reasoning. Consistent predictors of recovery were not identified, although age, sex, comorbid conditions, and time since illness predicted rates of improvement in select domains. Further analyses with a larger sample size and more stringent analyses are needed to confirm and extend these findings.