Sustaining attention in affective contexts during adolescence: age-related differences and association with elevated symptoms of depression and anxiety.

Sustained attention, a key cognitive skill that improves during childhood and adolescence, tends to be worse in some emotional and behavioural disorders. Sustained attention is typically studied in non-affective task contexts; here, we used a novel task to index performance in affective versus neutral contexts across adolescence (N = 465; ages 11-18). We asked whether: (i) performance would be worse in negative versus neutral task contexts; (ii) performance would improve with age; (iii) affective interference would be greater in younger adolescents; (iv) adolescents at risk for depression and higher in anxiety would show overall worse performance; and (v) would show differential performance in negative contexts. Results indicated that participants performed more poorly in negative contexts and showed age-related performance improvements. Those at risk of depression performed more poorly than those at lower risk. However, there was no difference between groups as a result of affective context. For anxiety there was no difference in performance as a function of severity. However, those with higher anxiety showed less variance in their reaction times to negative stimuli than those with lower anxiety. One interpretation is that moderate levels of emotional arousal associated with anxiety make individuals less susceptible to the distracting effects of negative stimuli.

Locality error free effective core potentials for 3d transition metal elements developed for the diffusion Monte Carlo method.

Pseudopotential locality errors have hampered the applications of the diffusion Monte Carlo (DMC) method in materials containing transition metals, in particular oxides. We have developed locality error free effective core potentials, pseudo-Hamiltonians, for transition metals ranging from Cr to Zn. We have modified a procedure published by some of us in Bennett et al. [J. Chem. Theory Comput. 18, 828 (2022)]. We carefully optimized our pseudo-Hamiltonians and achieved transferability errors comparable to the best semilocal pseudopotentials used with DMC but without incurring in locality errors. Our pseudo-Hamiltonian set (named OPH23) bears the potential to significantly improve the accuracy of many-body-first-principles calculations in fundamental science research of complex materials involving transition metals.

Management of minimal and overt hepatic encephalopathy with branched-chain amino acids: a review of the evidence.

Hepatic encephalopathy (HE) is a challenging complication of liver disease that is associated with substantial morbidity and mortality. Branched-chain amino acid (BCAA) supplementation in the management of HE is a debated topic. This narrative review aims to provide an up-to-date review of the topic and includes studies featuring patients with hepatocellular carcinoma. A review of the literature was performed using the online databases MEDLINE and EMBASE for studies between 2002 and December 2022. Keywords 'branched-chain amino acids', 'liver cirrhosis' and 'hepatic encephalopathy' were used. Studies were assessed for inclusion and exclusion criteria. Of 1045 citations, 8 studies met the inclusion criteria. The main outcomes reported for HE was changed in minimal HE (MHE) (n = 4) and/or incidence of overt HE (OHE) (n = 7). Two of the 4 studies reporting on MHE had improvement in psychometric testing in the BCAA group, but there was no change in the incidence of OHE in any of the 7 papers in the BCAA group. There were few adverse effects of BCAA supplementation. This review found weak evidence for BCAA supplementation for MHE, and no evidence for BCAAs for OHE. However, given the relative paucity and methodological heterogeneity of the current research, there is scope for future studies to examine the effects of varying timing, dosage, and frequency of BCAAs on outcomes such as HE. Importantly, research is also needed to examine BCAAs in conjunction with standard therapies for HE such as rifaximin and/or lactulose.

Chronic disease multimorbidity and substance use among African American men: veteran-non-veteran differences.

OBJECTIVES: The purpose of the study was to explore the extent to which prior military service may moderate the relationship between chronic disease multimorbidity and substance use among African American men in the United States. DESIGN: Data for this cross-sectional study was downloaded from the 2016 -2019 United States (US) National Survey on Drug Use and Health. We estimated three survey-weighted multivariable logistic regression models, where use of each of the following substances served as the dependent variables: illicit drugs, opioids, and tobacco. Differences in these outcomes were examined along two primary independent variables: veteran status and multimorbidity (and an interaction term for these variables). We also controlled for the following covariates: age, education, income, rurality, criminal behavior, and religiosity. RESULTS: From the 37,203,237 (weighted N) African American men in the sample, approximately 17% reported prior military service. Veterans with ≥ 2 chronic diseases had higher rates of illicit drug use (aOR = 1.37, 95% CI = 1.01, 1.87; 32% vs. 28%) than non-veterans with ≥ 2 chronic diseases. Non-veterans with one chronic disease had higher rates of tobacco use (aOR = 0.80, 95% CI = 0.69, 0.93; 29% vs. 26%) and opioid misuse (aOR = 0.49, 95% CI = 0.36, 0.67; 29% vs. 18%) than veterans with one chronic disease. DISCUSSION: Chronic disease multi-morbidity appears to be a context in which African American veterans may be at greater risk for certain undesirable health behaviors than African American non-veterans and at lower risk for others. This may be due to exposure to trauma, difficulty accessing care, socio-environmental factors, and co-occurring mental health conditions. These complex interactions may contribute to higher rates of SUDs among African American veterans compared to African American non-veterans.

Leveraging technology in public-private partnerships: a model to address public health inequities.

Long-standing inequities in healthcare access and outcomes exist for underserved populations. Public-private partnerships (PPPs) are where the government and a private entity jointly invest in the provision of public services. Using examples from the Health Equity Consortium (HEC), we describe how technology was used to facilitate collaborations between public and private entities to address health misinformation, reduce vaccine hesitancy, and increase access to primary care services across various underserved communities during the COVID-19 pandemic. We call out four enablers of effective collaboration within the HEC-led PPP model, including: 1. Establishing trust in the population to be served 2. Enabling bidirectional flow of data and information 3. Mutual value creation and 4. Applying analytics and AI to help solve complex problems. Continued evaluation and improvements to the HEC-led PPP model are needed to address post-COVID-19 sustainability.

Decision Considerations and Strategies for Lip Surgery in Patients with Cleft lip/Palate: A Qualitative Study.

Objective: To qualitatively assess surgeons decision making for lip surgery in patients with cleft lip/palate (CL/P). Design: Prospective, non-randomized, clinical trial. Setting: Clinical data institutional laboratory setting. Patients Participants: The study included both patient and surgeon participants recruited from four craniofacial centers. The patient participants were babies with a CL/P requiring primary lip repair surgery (n=16) and adolescents with repaired CL/P who may require secondary lip revision surgery (n=32). The surgeon participants (n=8) were experienced in cleft care. Facial imaging data that included 2D images, 3D images, videos, and objective 3D visual modelling of facial movements were collected from each patient, and compiled as a collage termed the Standardized Assessment for Facial Surgery (SAFS) for systematic viewing by the surgeons. Interventions: The SAFS served as the intervention. Each surgeon viewed the SAFS for six distinct patients (two babies and four adolescents) and provided a list of surgical problems and goals. Then an in-depth-interview (IDI) was conducted with each surgeon to explore their decision-making processes. IDIs were conducted either in person or virtually, recorded, and then transcribed for qualitative statistical analyses using the Grounded Theory Method. Results: Rich narratives/themes emerged that included timing of the surgery; risks/limitations and benefits of surgery; patient/family goals; planning for muscle repair and scarring; multiplicity of surgeries and their impact; and availability of resources. For diagnoses/treatments, surgeons agreed, and level of surgical experience was not a factor. Conclusions: The themes provided important information to populate a checklist of considerations to serve as a guide for clinicians.

The BLV App Arcade: a new curated repository and evaluation rubric for mobile applications supporting blindness and low vision.

PURPOSE: Visual impairment-related disabilities have become increasingly pervasive. Current reports estimate a total of 36 million persons with blindness and 217 million persons with moderate to severe visual impairment worldwide. Assistive technologies (AT), including text-to-speech software, navigational/spatial guides, and object recognition tools have the capacity to improve the lives of people with blindness and low vision. However, access to such AT is constrained by high costs and implementation barriers. More recently, expansive growth in mobile computing has enabled many technologies to be translated into mobile applications. As a result, a marketplace of accessibility apps has become available, yet no framework exists to facilitate navigation of this voluminous space. MATERIALS AND METHODS: We developed the BLV (Blind and Low Vision) App Arcade: a fun, engaging, and searchable curated repository of app AT broken down into 11 categories spanning a wide variety of themes from entertainment to navigation. Additionally, a standardized evaluation metric was formalized to assess each app in five key dimensions: reputability, privacy, data sharing, effectiveness, and ease of use/accessibility. In this paper, we describe the methodological approaches, considerations, and metrics used to find, store and score mobile applications. CONCLUSION: The development of a comprehensive and standardized database of apps with a scoring rubric has the potential to increase access to reputable tools for the visually impaired community, especially for those in low- and middle-income demographics, who may have access to mobile devices but otherwise have limited access to more expensive technologies or services.

A wide array of assistive mobile applications now serve as low cost, convenient, and effective alternatives to standard tools in the rehabilitation domain.Given an extensive (and growing) marketplace of assistive apps, we highlight the importance of developing standardized evaluation frameworks that serve to assess the merit, functionality, and accessibility of tools in respective rehabilitation fields.To provide an introduction to a novel resource accessible to the public to exhibit verified and reliable assistive apps for the visually impaired community, especially for those in low- and middle-income demographics who may not have access to common technologies and services.

Racial and Ethnic Disparities in Geographic Access to Autism Resources Across the US.

Importance: While research has identified racial and ethnic disparities in access to autism services, the size, extent, and specific locations of these access gaps have not yet been characterized on a national scale. Mapping comprehensive national listings of autism health care services together with the prevalence of autistic children of various races and ethnicities and evaluating geographic regions defined by localized commuting patterns may help to identify areas within the US where families who belong to minoritized racial and ethnic groups have disproportionally lower access to services. Objective: To evaluate differences in access to autism health care services among autistic children of various races and ethnicities within precisely defined geographic regions encompassing all serviceable areas within the US. Design, Setting, and Participants: This population-based cross-sectional study was conducted from October 5, 2021, to June 3, 2022, and involved 530 965 autistic children in kindergarten through grade 12. Core-based statistical areas (CBSAs; defined as areas containing a city and its surrounding commuter region), the Civil Rights Data Collection (CRDC) data set, and 51 071 autism resources (collected from October 1, 2015, to December 18, 2022) geographically distributed into 912 CBSAs were combined and analyzed to understand variation in access to autism health care services among autistic children of different races and ethnicities. Six racial and ethnic categories (American Indian or Alaska Native, Asian, Black or African American, Hispanic or Latino, Native Hawaiian or other Pacific Islander, and White) assigned by the US Department of Education were included in the analysis. Main Outcomes and Measures: A regularized least-squares regression analysis was used to measure differences in nationwide resource allocation between racial and ethnic groups. The number of autism resources allocated per autistic child was estimated based on the child's racial and ethnic group. To evaluate how the CBSA population size may have altered the results, the least-squares regression analysis was run on CBSAs divided into metropolitan (>50 000 inhabitants) and micropolitan (10 000-50 000 inhabitants) groups. A Mann-Whitney U test was used to compare the model estimated ratio of autism resources to autistic children among specific racial and ethnic groups comprising the proportions of autistic children in each CBSA. Results: Among 530 965 autistic children aged 5 to 18 years, 83.9% were male and 16.1% were female; 0.7% of children were American Indian or Alaska Native, 5.9% were Asian, 14.3% were Black or African American, 22.9% were Hispanic or Latino, 0.2% were Native Hawaiian or other Pacific Islander, 51.7% were White, and 4.2% were of 2 or more races and/or ethnicities. At a national scale, American Indian or Alaska Native autistic children (ß = 0; 95% CI, 0-0; P = .01) and Hispanic autistic children (ß = 0.02; 95% CI, 0-0.06; P = .02) had significant disparities in access to autism resources in comparison with White autistic children. When evaluating the proportion of autistic children in each racial and ethnic group, areas in which Black autistic children (>50% of the population: ß = 0.05; <50% of the population: ß = 0.07; P = .002) or Hispanic autistic children (>50% of the population: ß = 0.04; <50% of the population: ß = 0.07; P < .001) comprised greater than 50% of the total population of autistic children had significantly fewer resources than areas in which Black or Hispanic autistic children comprised less than 50% of the total population. Comparing metropolitan vs micropolitan CBSAs revealed that in micropolitan CBSAs, Black autistic children (ß = 0; 95% CI, 0-0; P < .001) and Hispanic autistic children (ß = 0; 95% CI, 0-0.02; P < .001) had the greatest disparities in access to autism resources compared with White autistic children. In metropolitan CBSAs, American Indian or Alaska Native autistic children (ß = 0; 95% CI, 0-0; P = .005) and Hispanic autistic children (ß = 0.01; 95% CI, 0-0.06; P = .02) had the greatest disparities compared with White autistic children. Conclusions and Relevance: In this study, autistic children from several minoritized racial and ethnic groups, including Black and Hispanic autistic children, had access to significantly fewer autism resources than White autistic children in the US. This study pinpointed the specific geographic regions with the greatest disparities, where increases in the number and types of treatment options are warranted. These findings suggest that a prioritized response strategy to address these racial and ethnic disparities is needed.

A new generation of effective core potentials from correlated and spin-orbit calculations: Selected heavy elements.

We introduce new correlation consistent effective core potentials (ccECPs) for the elements I, Te, Bi, Ag, Au, Pd, Ir, Mo, and W with 4d, 5d, 6s, and 6p valence spaces. These ccECPs are given as a sum of spin-orbit averaged relativistic effective potential (AREP) and effective spin-orbit (SO) terms. The construction involves several steps with increasing refinements from more simple to fully correlated methods. The optimizations are carried out with objective functions that include weighted many-body atomic spectra, norm-conservation criteria, and SO splittings. Transferability tests involve molecular binding curves of corresponding hydride and oxide dimers. The constructed ccECPs are systematically better and in a few cases on par with previous effective core potential (ECP) tables on all tested criteria and provide a significant increase in accuracy for valence-only calculations with these elements. Our study confirms the importance of the AREP part in determining the overall quality of the ECP even in the presence of sizable spin-orbit effects. The subsequent quantum Monte Carlo calculations point out the importance of accurate trial wave functions that, in some cases (mid-series transition elements), require treatment well beyond a single-reference.

Detection of repeat expansions in large next generation DNA and RNA sequencing data without alignment.

Bioinformatic methods for detecting short tandem repeat expansions in short-read sequencing have identified new repeat expansions in humans, but require alignment information to identify repetitive motif enrichment at genomic locations. We present superSTR, an ultrafast method that does not require alignment. superSTR is used to process whole-genome and whole-exome sequencing data, and perform the first STR analysis of the UK Biobank, efficiently screening and identifying known and potential disease-associated STRs in the exomes of 49,953 biobank participants. We demonstrate the first bioinformatic screening of RNA sequencing data to detect repeat expansions in humans and mouse models of ataxia and dystrophy.

The impact of mindfulness training in early adolescence on affective executive control, and on later mental health during the COVID-19 pandemic: a randomised controlled trial.

BACKGROUND: Previous research suggests that mindfulness training (MT) appears effective at improving mental health in young people. MT is proposed to work through improving executive control in affectively laden contexts. However, it is unclear whether MT improves such control in young people. MT appears to mitigate mental health difficulties during periods of stress, but any mitigating effects against COVID-related difficulties remain unexamined. OBJECTIVE: To evaluate whether MT (intervention) versus psychoeducation (Psy-Ed; control), implemented in after-school classes: (1) Improves affective executive control; and/or (2) Mitigates negative mental health impacts from the COVID-19 pandemic. METHODS: A parallel randomised controlled trial (RCT) was conducted (Registration: https://osf.io/d6y9q/; Funding: Wellcome (WT104908/Z/14/Z, WT107496/Z/15/Z)). 460 students aged 11-16 years were recruited and randomised 1:1 to either MT (N=235) or Psy-Ed (N=225) and assessed preintervention and postintervention on experimental tasks and self-report inventories of affective executive control. The RCT was then extended to evaluate protective functions of MT on mental health assessed after the first UK COVID-19 lockdown. FINDINGS: Results provided no evidence that the version of MT used here improved affective executive control after training or mitigated negative consequences on mental health of the COVID-19 pandemic relative to Psy-Ed. No adverse events were reported. CONCLUSIONS: There is no evidence that MT improves affective control or downstream mental health of young people during stressful periods. CLINICAL IMPLICATIONS: We need to identify interventions that can enhance affective control and thereby young people's mental health.

A Structured Intervention to Support Early Palliative Care Conversations for Oncology Patients - A Qualitative Feasibility Study.

AIMS: For patients with advanced cancer, early access to palliative care can have numerous psychosocial and disease management benefits. However, it can be difficult for clinicians to initiate these initial conversations about palliative care. The aim of the present study was to beta test an intervention to facilitate timely conversations about palliative care between patients and clinicians. MATERIALS AND METHODS: The study reported forms one stage of a complex intervention development study following Medical Research Council guidance for developing complex interventions. Feasibility was explored from patient and clinician perspectives in an oncology outpatient setting. RESULTS: Sixteen patients and 18 clinicians participated. Three phases of the intervention were assessed through patient and clinician interviews. The analysis produced three themes in each phase: (i) Preparation (patient preparedness; healthcare professionals' perspectives on palliative care; administration, data and communication); (ii) STEP consultation (defining perspectives on palliative care; how palliative care fits with the current treatment plan; permission to explore future care); (iii) Outcomes (changes in perspective and approaches to coping; opening the door to future conversations; referrals and involvement of palliative services). CONCLUSIONS: The STEP intervention generated important early conversations about end-of-life care that may otherwise not have occurred. No patients regretted having the STEP consultation, which resulted in palliative care referrals for some. Others felt better informed about the support services available and better able to have further conversations. Participating clinicians found the structured conversation guide useful, as it acted as a prompt for areas to cover, as well as providing an explicit way to open discussion about difficult topics.

Context-dependent variation in persistence of host populations in the face of disease.

Research Highlight: Valenzuela-Sánchez, A., Azat, C., Cunningham, A. A., Delgado, S., Bacigalupe, L. D., Beltrand, J., Serrano, J. M., Sentenac, H., Haddow, N., Toledo, V., Schmidt, B. R., & Cayuela, H. (2022). Interpopulation differences in male reproductive effort drive the population dynamics of a host exposed to an emerging fungal pathogen. Journal of Animal Ecology, 00, 1- 12. https://doi.org/10.1111/1365-2656.13603. Understanding the nuances of population persistence in the face of a stressor can help predict extinction risk and guide conservation actions. However, the exact mechanisms driving population stability may not always be known. In this paper, Valenzuela-Sánchez et al. (2022) integrate long-term mark-recapture data, focal measurements of reproductive effort, a population matrix model and inferences on life-history variation to reveal differences in demographic response to disease in a susceptible frog species (Rhinoderma darwinii). Valenzuela-Sánchez et al. found that demographic compensation via recruitment explained the positive population growth rate in their high disease prevalence population whereas the low disease prevalence population did not compensate and thus had decreasing population growth. Compensatory recruitment was likely due to the high probability of males brooding, and the high number of brooded larvae in the high prevalence population compared to low prevalence and disease-free populations. Valenzuela-Sánchez et al. also document faster generation times in the high prevalence population, which may indicate a faster life history that may be contributing to the population's ability to compensate for reduced survival. Lastly, the authors find a positive relationship between disease prevalence and the proportion of juveniles in a given population that suggest that there may be a threshold for disease prevalence that triggers increased reproductive effort. Altogether, their study provides novel support for increased reproductive effort as the pathway for compensatory recruitment leading to increasing population growth despite strong negative effects of disease on adult survival. Their results also caution the overgeneralization of the effects of stressors (e.g. disease) on population dynamics, where context-dependent responses may differ among host populations of a given species.

Multiplexed CRISPR-based microfluidic platform for clinical testing of respiratory viruses and identification of SARS-CoV-2 variants.

The coronavirus disease 2019 (COVID-19) pandemic has demonstrated a clear need for high-throughput, multiplexed and sensitive assays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory viruses and their emerging variants. Here, we present a cost-effective virus and variant detection platform, called microfluidic Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (mCARMEN), which combines CRISPR-based diagnostics and microfluidics with a streamlined workflow for clinical use. We developed the mCARMEN respiratory virus panel to test for up to 21 viruses, including SARS-CoV-2, other coronaviruses and both influenza strains, and demonstrated its diagnostic-grade performance on 525 patient specimens in an academic setting and 166 specimens in a clinical setting. We further developed an mCARMEN panel to enable the identification of 6 SARS-CoV-2 variant lineages, including Delta and Omicron, and evaluated it on 2,088 patient specimens with near-perfect concordance to sequencing-based variant classification. Lastly, we implemented a combined Cas13 and Cas12 approach that enables quantitative measurement of SARS-CoV-2 and influenza A viral copies in samples. The mCARMEN platform enables high-throughput surveillance of multiple viruses and variants simultaneously, enabling rapid detection of SARS-CoV-2 variants.

A combined first principles study of the structural, magnetic, and phonon properties of monolayer CrI3.

The first magnetic 2D material discovered, monolayer (ML) CrI3, is particularly fascinating due to its ground state ferromagnetism. However, because ML materials are difficult to probe experimentally, much remains unresolved about ML CrI3's structural, electronic, and magnetic properties. Here, we leverage Density Functional Theory (DFT) and high-accuracy Diffusion Monte Carlo (DMC) simulations to predict lattice parameters, magnetic moments, and spin-phonon and spin-lattice coupling of ML CrI3. We exploit a recently developed surrogate Hessian DMC line search technique to determine CrI3's ML geometry with DMC accuracy, yielding lattice parameters in good agreement with recently published STM measurements-an accomplishment given the ∼10% variability in previous DFT-derived estimates depending upon the functional. Strikingly, we find that previous DFT predictions of ML CrI3's magnetic spin moments are correct on average across a unit cell but miss critical local spatial fluctuations in the spin density revealed by more accurate DMC. DMC predicts that magnetic moments in ML CrI3 are 3.62 µB per chromium and -0.145 µB per iodine, both larger than previous DFT predictions. The large disparate moments together with the large spin-orbit coupling of CrI3's I-p orbital suggest a ligand superexchange-dominated magnetic anisotropy in ML CrI3, corroborating recent observations of magnons in its 2D limit. We also find that ML CrI3 exhibits a substantial spin-phonon coupling of ∼3.32 cm-1. Our work, thus, establishes many of ML CrI3's key properties, while also continuing to demonstrate the pivotal role that DMC can assume in the study of magnetic and other 2D materials.

High Accuracy Transition Metal Effective Cores for the Many-Body Diffusion Monte Carlo Method.

Practical applications of the real-space diffusion Monte Carlo (DMC) method require the removal of core electrons, where currently localization approximations of semilocal potentials are generally used in the projector. Accurate calculations of complex solids and large molecules demand minimizing the impact of approximated atomic cores. Prior works have shown that the errors from such approximations can be sizable in both finite and periodic systems. In this work, we show that a class of differential pseudopotentials, known as pseudo-Hamiltonians, can be constructed for the 3d transition metal atoms, entirely removing the need for any localization scheme in the DMC projector. As a proof of principle, we demonstrate the approach for the case of Co. In order to minimize errors in the pseudo-Hamiltonian at the many-body level, we generalize the recently proposed correlation-consistent pseudopotential generation scheme to successively close semilocal representations of the differential potentials. Our generation scheme successfully produces potentials tailored specifically for real space projector quantum Monte Carlo methods with low error at the many-body level, i.e., with many-body scattering properties very close to relativistic all-electron results. In particular, we show that the agreement with respect to atomic and molecular quantities reach chemical accuracy in many cases─on par with the most accurate semilocal pseudopotentials available. Further, our pseudo-Hamiltonian generation scheme utilizes standard quantum chemistry codes designed only to work with semilocal pseudopotentials, enabling straightforward generation of pseudo-Hamiltonians for additional elements in future works.

Fear of memory loss predicts increased memory failures and lower quality of life in older adults: preliminary findings from a fear-avoidance of memory loss (FAM) scale.

BACKGROUND: Few studies have measured the impact of dementia-related fear on daily functioning, despite its clinical relevance. Our aim was to determine the relationship between fear-avoidance of memory loss, perceived memory failures and self-reported quality of life in a community based sample of older adults using a novel fear of memory loss (FAM) scale. METHODS: Sixty-seven older adults (59-81 years) completed a 23-item self-report scale designed to capture multi-faceted components of fear of memory loss, known as the FAM scale. Perceived memory failures were measured using the Memory Failures Scale (MFS) and quality of life was assessed using the Older Person's Quality of Life scale (OPQOL-35). Participants also completed the Wechsler Memory Scale (WMS-IV) as a measure of objective memory performance and the Depression, Anxiety and Stress Scales (DASS) and the Geriatric Anxiety Inventory (GAI) as measures of general anxiety. RESULTS: The FAM scale demonstrated strong internal consistency (Cronbach's α = .82) and concurrent validity with the GAI (r = .47). Three latent factors were observed: (1) fear-avoidance, (2) problematic beliefs and (3) affective resilience. After adjusting for objective memory performance and general anxiety, higher fear-avoidance significantly predicted increased perceived memory failures (p = .014) and reduced quality of life (p = .033). CONCLUSIONS: Fear of memory loss predicts increased perceived memory failures and lower self-reported quality of life in a community sample of older adults. Based on these findings, we propose a preliminary fear-avoidance model that explains the development and maintenance of dementia-related functional disability in terms of psychological processes.

Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows.

The global spread and continued evolution of SARS-CoV-2 has driven an unprecedented surge in viral genomic surveillance. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine laboratory processes and results. This challenge will increase with the expanding global production of sequences across a variety of laboratories for epidemiological and clinical interpretation, as well as for genomic surveillance of emerging diseases in future outbreaks. We present SDSI + AmpSeq, an approach that uses 96 synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination throughout the sequencing workflow. We apply SDSIs to the ARTIC Consortium's amplicon design, demonstrate their utility and efficiency in a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases and validate them across 6,676 diagnostic samples at multiple laboratories. We establish that SDSI + AmpSeq provides increased confidence in genomic data by detecting and correcting for relatively common, yet previously unobserved modes of error, including spillover and sample swaps, without impacting genome recovery.