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One mechanism proposed to explain high species diversity in tropical systems is strong negative conspecific density dependence (CDD), which reduces recruitment of juveniles in proximity to conspecific adult plants. Although evidence shows that plant-specific soil pathogens can drive negative CDD, trees also form key mutualisms with mycorrhizal fungi, which may counteract these effects. Across 43 large-scale forest plots worldwide, we tested whether ectomycorrhizal tree species exhibit weaker negative CDD than arbuscular mycorrhizal tree species. We further tested for conmycorrhizal density dependence (CMDD) to test for benefit from shared mutualists. We found that the strength of CDD varies systematically with mycorrhizal type, with ectomycorrhizal tree species exhibiting higher sapling densities with increasing adult densities than arbuscular mycorrhizal tree species. Moreover, we found evidence of positive CMDD for tree species of both mycorrhizal types. Collectively, these findings indicate that mycorrhizal interactions likely play a foundational role in global forest diversity patterns and structure.

Abstract Sharing neuroimaging datasets enables reproducibility, education, tool development, and new discoveries. Neuroimaging from many studies are publicly available, providing a glimpse into progressive disorders and human development. In contrast, few stroke studies are shared, and these datasets lack longitudinal sampling of functional imaging, diffusion imaging, as well as the behavioral and demographic data that encourage novel applications. This is surprising, as stroke is a leading cause of disability, and acquiring brain imaging is considered standard of care. The first release of the Aphasia Recovery Cohort includes imaging data, demographics and behavioral measures from 230 chronic stroke survivors who experienced aphasia. We also share scripts to illustrate how the imaging data can predict impairment. In conclusion, recent advances in machine learning thrive on large, diverse datasets. Clinical data sharing can contribute to improvements in automated detection of brain injury, identification of white matter hyperintensities, measures of brain health, and prognostic abilities to guide care.

Abstract The heart produces bioelectrical signals, which can be measured as an electrocardiogram (ECG) for the detection of rhythm disturbances. Rapid and precise detection of these arrhythmias is crucial for their termination by closed‐looped therapeutic interventions to counteract detrimental effects. However, there is a current lack of such systems tailored for experimental cardiovascular applications. This hampers not only in‐depth mechanistic studies but also translational testing of new therapeutic strategies, especially in an untethered manner in awake animal models. To break new ground, recent advances to develop a non‐invasive AI‐supported heart rhythm monitoring system for untethered automated arrhythmia detection in a continuous manner is combined. This system is housed in a lightweight jacket for mobile use and includes an on‐skin ECG sensor, a low‐power microprocessor unit, a massive data storage unit, and a power‐management system. By implementing a novel hybrid algorithm based on so‐called heart rate (R‐R) variability and a case‐specific AI model, 100% sensitivity and 95% specificity is achieved in detecting atrial arrhythmias within 2 s upon initiation in adult rats. Thereby, the novel system sets the stage for advanced mechanistic studies and therapeutic testing, including closed‐loop applications aiming for the termination of a broad range of atrial arrhythmias.

BACKGROUND: Aphasia therapy is an effective approach to improve language function in chronic aphasia. However, it remains unclear what prognostic factors facilitate therapy response at the individual level. Here, we utilized data from the POLAR (Predicting Outcomes of Language Rehabilitation in Aphasia) trial to (a) determine therapy-induced change in confrontation naming and long-term maintenance of naming gains and (b) examine the extent to which aphasia severity, age, education, time postonset, and cognitive reserve predict naming gains at 1 week, 1 month, and 6 months posttherapy. METHOD: A total of 107 participants with chronic (≥ 12 months poststroke) aphasia underwent extensive case history, cognitive-linguistic testing, and a neuroimaging workup prior to receiving 6 weeks of impairment-based language therapy. Therapy-induced change in naming performance (measured as raw change on the 175-item Philadelphia Naming Test [PNT]) was assessed 1 week after therapy and at follow-up time points 1 month and 6 months after therapy completion. Change in naming performance over time was evaluated using paired t tests, and linear mixed-effects models were constructed to examine the association between prognostic factors and therapy outcomes. RESULTS: Naming performance was improved by 5.9 PNT items (Cohens d = 0.56, p < .001) 1 week after therapy and by 6.4 (d = 0.66, p < .001) and 7.5 (d = 0.65, p < .001) PNT items at 1 month and 6 months after therapy completion, respectively. Aphasia severity emerged as the strongest predictor of naming improvement recovery across time points; mild (ß = 5.85-9.02) and moderate (ß = 9.65-11.54) impairment predicted better recovery than severe (ß = 1.31-3.37) and very severe (ß = 0.20-0.32) aphasia. Age was an emergent prognostic factor for recovery 1 month (ß = -0.14) and 6 months (ß = -0.20) after therapy, and time postonset (ß = -0.05) was associated with retention of naming gains at 6 months posttherapy. CONCLUSIONS: These results suggest that therapy-induced naming improvement is predictable based on several easily measurable prognostic factors. Broadly speaking, these results suggest that prognostication procedures in aphasia therapy can be improved and indicate that personalization of therapy is a realistic goal in the near future. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.22141829.

Transcranial ultrasonic stimulation (TUS) is rapidly emerging as a promising non-invasive neuromodulation technique. TUS is already well-established in animal models, providing foundations to now optimize neuromodulatory efficacy for human applications. Across multiple studies, one promising protocol, pulsed at 1000 Hz, has consistently resulted in motor cortical inhibition in humans (Fomenko et al., 2020). At the same time, a parallel research line has highlighted the potentially confounding influence of peripheral auditory stimulation arising from TUS pulsing at audible frequencies. In this study, we disentangle direct neuromodulatory and indirect auditory contributions to motor inhibitory effects of TUS. To this end, we include tightly matched control conditions across four experiments, one preregistered, conducted independently at three institutions. We employed a combined transcranial ultrasonic and magnetic stimulation paradigm, where TMS-elicited motor-evoked potentials (MEPs) served as an index of corticospinal excitability. First, we replicated motor inhibitory effects of TUS but showed through both tight controls and manipulation of stimulation intensity, duration, and auditory masking conditions that this inhibition was driven by peripheral auditory stimulation, not direct neuromodulation. Furthermore, we consider neuromodulation beyond driving overall excitation/inhibition and show preliminary evidence of how TUS might interact with ongoing neural dynamics instead. Primarily, this study highlights the substantial shortcomings in accounting for the auditory confound in prior TUS-TMS work where only a flip-over sham and no active control was used. The field must critically reevaluate previous findings given the demonstrated impact of peripheral confounds. Furthermore, rigorous experimental design via (in)active control conditions is required to make substantiated claims in future TUS studies. Only when direct effects are disentangled from those driven by peripheral confounds can TUS fully realize its potential for research and clinical applications.

Objective Diabetes patients can draw on an increasing number of eHealth apps to support them in the self-management of their disease. While studies so far have focused on patients with type 1 diabetes, we explored how patients with type 2 diabetes mellitus (T2DM) integrate eHealth apps into their practices aimed at managing and coping with the disease, which aspects were considered particularly valuable and which challenges users encountered. Methods Semi-structured interviews and focus group sessions were conducted to explore how patients cope with T2DM in their daily lives and their attitude towards eHealth. In a further step, four eHealth apps were tested by patients and their expectations and experiences studied by way of qualitative interviews and focus groups. Results The analysis showed that the study participants valued in particular the possibility to use eHealth apps to sense and gain a better understanding of their own body, to learn about specific responses of their body to nutrition and physical activity, and to support changes in daily routines and lifestyle. Key challenges encountered related to difficulties in interpreting the data, matching the data to other bodily sensations, getting overly occupied with the disease and difficulties in integrating the apps into personal, family, and care practices. Conclusion Under certain conditions, eHealth can play an important role for patients in developing a nuanced, personal understanding of their body and coping with T2DM. A prerequisite is that eHealth needs to be fitted into the specific practices of users, and patients desire a strong role by their care professionals in providing support in interpretation of data.

Background & Aims: Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) can co-exist in AIH-PBC, requiring combined treatment with immunosuppression and ursodeoxycholic acid (UDCA). The Paris criteria are commonly used to identify these patients; however, the optimal diagnostic criteria are unknown. We aimed to evaluate the use and clinical relevance of both Paris and Zhang criteria. Methods: Eighty-three patients with a clinical suspicion of AIH-PBC who were treated with combination therapy were included. Histology was re-evaluated. Characteristics and long-term outcomes were retrospectively compared to patients with AIH and PBC. Results: Seventeen (24%) patients treated with combination therapy fulfilled the Paris criteria. Fifty-two patients (70%) fulfilled the Zhang criteria. Patients who met Paris and Zhang criteria more often had inflammation and fibrosis on histology compared to patients only meeting the Zhang criteria. Ten-year liver transplant (LT)-free survival was 87.3% (95% CI 78.9–95.7%) in patients with AIH-PBC. This did not differ in patients in or outside the Paris or Zhang criteria (p = 0.46 and p = 0.40, respectively) or from AIH (p = 0.086). LT-free survival was significantly lower in patients with PBC and severe hepatic inflammation – not receiving immunosuppression – compared to those with AIH-PBC (65%; 95% CI 52.2–77.8% vs. 87%; 95% CI 83.2–90.8%; hazard ratio 0.52; p = 0.043). Conclusions: In this study, patients with AIH-PBC outside Paris or Zhang criteria were frequently labeled as having AIH-PBC and were successfully treated with combination therapy with similar outcomes. LT-free survival was worse in patients with PBC and hepatic inflammation than in those treated as having AIH-PBC. More patients may benefit from combination therapy. Impact and implications: This study demonstrated that patients with AIH-PBC variant syndrome treated with combined therapy consisting of immunosuppressants and ursodeoxycholic acid often do not fulfill the Paris criteria. They do however have comparable response to therapy and long-term outcomes as patients who do fulfill the diagnostic criteria. Additionally, patients with PBC and additional signs of hepatic inflammation have poorer long-term outcomes compared to patients treated as having AIH-PBC. These results implicate that a larger group of patients with features of both AIH and PBC may benefit from combined treatment. With our results, we call for improved consensus among experts in the field on the diagnosis and management of AIH-PBC variant syndrome.

BACKGROUND: The non-selective serotonin 2A (5-HT2A) receptor agonist lysergic acid diethylamide (LSD) holds promise as a treatment for some psychiatric disorders. Psychedelic drugs such as LSD have been suggested to have therapeutic actions through their effects on learning. The behavioural effects of LSD in humans, however, remain incompletely understood. Here we examined how LSD affects probabilistic reversal learning (PRL) in healthy humans. METHODS: Healthy volunteers received intravenous LSD (75 μg in 10 mL saline) or placebo (10 mL saline) in a within-subjects design and completed a PRL task. Participants had to learn through trial and error which of three stimuli was rewarded most of the time, and these contingencies switched in a reversal phase. Computational models of reinforcement learning (RL) were fitted to the behavioural data to assess how LSD affected the updating (learning rates) and deployment of value representations (reinforcement sensitivity) during choice, as well as stimulus stickiness (choice repetition irrespective of reinforcement history). RESULTS: Raw data measures assessing sensitivity to immediate feedback (win-stay and lose-shift probabilities) were unaffected, whereas LSD increased the impact of the strength of initial learning on perseveration. Computational modelling revealed that the most pronounced effect of LSD was the enhancement of the reward learning rate. The punishment learning rate was also elevated. Stimulus stickiness was decreased by LSD, reflecting heightened exploration. Reinforcement sensitivity differed by phase. CONCLUSIONS: Increased RL rates suggest LSD induced a state of heightened plasticity. These results indicate a potential mechanism through which revision of maladaptive associations could occur in the clinical application of LSD.

PURPOSE: We present a 20-item naming test, the Severity-Calibrated Aphasia Naming Test (SCANT), that can serve as a proxy measure for an aphasia severity scale that is derived from a thorough test battery of connected speech production, single-word production, speech repetition, and auditory verbal comprehension. METHOD: We use lasso regression and cross-validation to identify an optimal subset from a set of 174 pictures to be named for prediction of aphasia severity, based on data from 200 participants with left-hemisphere stroke who were quasirandomly selected to represent the full impairment scale. Data from 20 healthy controls (i.e., participant caretakers/spouses) were also analyzed. We examine interrater reliability, test-retest reliability, sensitivity and specificity to the presence of aphasia, sensitivity to therapy gains, and external validity (i.e., correlation with aphasia severity measures) for the SCANT. RESULTS: The SCANT has extremely high interrater reliability, and it is sensitive and specific to the presence of aphasia. We demonstrate the superiority of predictions based on the SCANT over those based on the full set of naming items. We estimate a 15% reduction in power when using the SCANT score versus the full test batterys aphasia severity score as an outcome measure; for example, to maintain the same power to detect a significant group average change in aphasia severity, a study with 25 participants using the full test battery to measure treatment effectiveness would require 30 participants if the SCANT were to be used as the testing instrument instead. CONCLUSION: We provide a linear model to convert SCANT scores to aphasia severity scores, and we identify a change score cutoff of four SCANT items to obtain a high degree of confidence based on test-retest SCANT data and the modeled relation between SCANT and aphasia severity scores. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.21476871.

Abstract Background To diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease. Methods We performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels

Abstract Actions are biased by the outcomes they can produce: Humans are more likely to show action under reward prospect, but hold back under punishment prospect. Such motivational biases derive not only from biased response selection, but also from biased learning: humans tend to attribute rewards to their own actions, but are reluctant to attribute punishments to having held back. The neural origin of these biases is unclear. Specifically, it remains open whether motivational biases arise primarily from the architecture of subcortical regions or also reflect cortical influences, the latter being typically associated with increased behavioral flexibility and control beyond stereotyped behaviors. Simultaneous EEG-fMRI allowed us to track which regions encoded biased prediction errors in which order. Biased prediction errors occurred in cortical regions (dorsal anterior and posterior cingulate cortices) before subcortical regions (striatum). These results highlight that biased learning is not a mere feature of the basal ganglia, but arises through prefrontal cortical contributions, revealing motivational biases to be a potentially flexible, sophisticated mechanism.

BackgroundThere is a need to develop and coordinate dementia care plans that use assistive technology for vulnerable groups such as immigrant populations. However, immigrant populations are seldom included in various stages of the development and implementation of assistive technology, which does not optimize technology acceptance. ObjectiveThis study aims to gain an in-depth understanding of the acceptance of a digital personal assistant, called Anne4Care, by older adult immigrants living with dementia in their own homes. MethodsThis study used a qualitative descriptive research design with naturalistic inquiry. A total of 13 older adults participated in this study. The participants were invited for 2 interviews. After an introduction of Anne4Care, the first interview examined the lives and needs of participants, their expectations, and previous experiences with assistive technology in daily life. Four months later, the second interview sought to understand facilitators and barriers, suggestions for modifications, and the role of health care professionals. Three semistructured interviews were conducted with health care professionals to examine the roles and challenges they experienced in the use and implementation of Anne4Care. Content analysis, using NVivo11, was performed on all transcripts. ResultsAll 13 participants had an immigration background. There were 10 male and 3 female participants, with ages ranging from 52 to 83 years. Participants were diagnosed with an early-stage form of dementia or acquired brain injury. None of the older adult participants knew or used digital assistive technology at the beginning. They obtained assistance from health care professionals and family caregivers who explained and set up the technology. Four themes were found to be critical aspects of the acceptance of the digital personal assistant Anne4Care: (1) use of Anne4Care, (2) positive aspects of Anne4Care, (3) challenges with Anne4Care, and (4) expectations. Assistance at first increased the burden on health care professionals and families. After the initial effort, most health care professionals and families experienced that Anne4Care reduced their tasks and stress. Contributions of Anne4Care included companionship, help with daily tasks, and opportunities to communicate in multiple languages. On the other hand, some participants expressed anxiety toward the use of Anne4Care. Furthermore, the platform required an internet connection at home and Anne4Care could not be used outside the home. ConclusionsAlthough older adult immigrants living with dementia had no previous experience with digital assistive technology specifically, the acceptance of the digital personal assistant, called Anne4Care, by older adult immigrants living with dementia was rather high. The digital assistant can be further developed to allow for interactive conversations and for use outside of one’s home. Participation of end users during various stages of the development, refinement, and implementation of health technology innovations is of utmost importance to maximize technology acceptance.

Abstract One mechanism proposed to explain high species diversity in tropical systems is strong negative conspecific density dependence (CDD), which reduces recruitment of juveniles in proximity to conspecific adult plants. Although evidence shows that plant-specific soil pathogens can drive negative CDD, trees also form key mutualisms with mycorrhizal fungi, which may counteract these effects. Across 43 large-scale forest plots worldwide, we tested whether ectomycorrhizal tree species exhibit weaker negative CDD than arbuscular mycorrhizal tree species. We further tested for conmycorrhizal density dependence (CMDD) to test for benefit from shared mutualists. We found that the strength of CDD varies systematically with mycorrhizal type, with ectomycorrhizal tree species exhibiting higher sapling densities with increasing adult densities than arbuscular mycorrhizal tree species. Moreover, we found evidence of positive CMDD for tree species of both mycorrhizal types. Collectively, these findings indicate that mycorrhizal interactions likely play a foundational role in global forest diversity patterns and structure.

Discourse is a fundamentally important aspect of communication, and discourse production provides a wealth of information about linguistic ability. Aphasia commonly affects, in multiple ways, the ability to produce discourse. Comprehensive aphasia assessments such as the Western Aphasia Battery-Revised (WAB-R) are time- and resource-intensive. We examined whether discourse measures can be used to estimate WAB-R Aphasia Quotient (AQ), and whether this can serve as an ecologically valid, less resource-intensive measure. We used features extracted from discourse tasks using three AphasiaBank prompts involving expositional (picture description), story narrative, and procedural discourse. These features were used to train a machine learning model to predict the WAB-R AQ. We also compared and supplemented the model with lesion location information from structural neuroimaging. We found that discourse-based models could estimate AQ well, and that they outperformed models based on lesion features. Addition of lesion features to the discourse features did not improve the performance of the discourse model substantially. Inspection of the most informative discourse features revealed that different prompt types taxed different aspects of language. These findings suggest that discourse can be used to estimate aphasia severity, and provide insight into the linguistic content elicited by different types of discourse prompts.

Tris (1-chloro-2-propyl) phosphate (TCIPP) is one of the major organophosphate flame retardants present in the indoor and outdoor environment. Knowledge of biotransformation pathways is important to elucidate potential bioavailability and toxicity of TCIPP and to identify relevant biomarkers. This study aimed to identify TCIPP metabolites through in vitro human metabolism assays and finally to confirm these findings in urine samples from an occupationally exposed population to propose new biomarkers to accurately monitor exposure to TCIPP.TCIPP was incubated with human liver microsomes and human liver cytosol to identify Phase I and Phase II metabolites, by liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Using a suspect-screening approach, the established biomarkers bis (1-chloro-2-propyl) hydrogen phosphate (BCIPP) and 1-hydroxy-2-propyl bis (1-chloro-2-propyl) phosphate (BCIPHIPP) were identified. In addition, carboxyethyl bis (1-chloro-2-propyl) phosphate (TCIPP-M1), bis (1-chloropropan-2-yl) (-oxopropan-2-yl) phosphate (TCIPP-M2) and 1-chloro-3-hydroxypropan-2-yl bis (1-chloropropan-2-yl) phosphate (TCIPP-M3) were identified. TCIPP-M2, an intermediate product, was not reported before in literature. In urine samples, apart from BCIPP and BCIPHIPP, TCIPP-M1 and TCIPP-M3 were identified for the first time. Interestingly, BCIPP showed the lowest detection frequency, likely due to the poor sensitivity for this compound. Therefore, TCIPP-M1 and TCIPP-M3 could serve as potential additional biomarkers to more efficiently monitor TCIPP exposure in humans.

Exposure to organophosphate flame retardants and plasticizers (PFRs) increases the risk of asthma and allergies. However, little is known about its association with type 2 inflammation (T2) biomarkers used in the management of allergies. The study investigated associations among urinary PFR metabolite concentrations, allergic symptoms, and T2 biomarkers. The data and samples were collected between 2017 and 2020, including school children (n = 427) aged 9–12 years living in Sapporo City, Japan, among the participants of “The Hokkaido Study on Environment and Children’s Health.” Thirteen urinary PFR metabolites were measured by LC-MS/MS. Allergic symptoms were assessed using the International Study of Asthma and Allergies in Childhood questionnaire. For T2 biomarkers, the peripheral blood eosinophil counts, fraction of exhaled nitric oxide level (FeNO), and serum total immunoglobulin E level were measured. Multiple logistic regression analysis, quantile-based g-computation (qg-computation), and Bayesian kernel machine regression (BKMR) were used to examine the associations between the health outcomes of the individual PFRs and the PFR mixtures. The highest concentration of PFR was Σtris(1-chloro-isopropyl) phosphates (ΣTCIPP) (Median:1.20 nmol/L). Tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) was significantly associated with a high odds ratio (OR, 95%CI:1.36, 1.07–1.72) for wheeze. TDCIPP (OR, 95%CI:1.19, 1.02–1.38), Σtriphenyl phosphate (ΣTPHP) (OR, 95%CI:1.81, 1.40–2.37), and Σtris(2-butoxyethyl) phosphate (ΣTBOEP) (OR, 95%:1.40, 1.13–1.74) were significantly associated with increased odds of FeNO (≥35 ppb). ΣTPHP (OR, 95%CI:1.44, 1.15–1.83) was significantly associated with high eosinophil counts (≥300/μL). For the PFR mixtures, a one-quartile increase in all PFRs (OR, 95%CI:1.48, 1.18–1.86) was significantly associated with high FeNO (≥35 ppb) in the qg-computation model. The PFR mixture was positively associated with high FeNO (≥35 ppb) and eosinophil counts (≥300/μL) in the BKMR models. These results may suggest that exposure to PFRs increases the probability of asthma, allergies, and T2 inflammation.

Humans and other animals can learn and exploit repeating patterns that occur within their environments. These learned patterns can be used to form expectations about future sensory events. Several influential predictive coding models have been proposed to explain how learned expectations influence the activity of stimulus-selective neurons in the visual system. These models specify reductions in neural response measures when expectations are fulfilled (termed expectation suppression) and increases following surprising sensory events. However, there is currently scant evidence for expectation suppression in the visual system when confounding factors are taken into account. Effects of surprise have been observed in blood oxygen level dependent (BOLD) signals, but not when using electrophysiological measures. To provide a strong test for expectation suppression and surprise effects we performed a predictive cueing experiment while recording electroencephalographic (EEG) data. Participants (n=48) learned cue-face associations during a training session and were then exposed to these cue-face pairs in a subsequent experiment. Using univariate analyses of face-evoked event-related potentials (ERPs) we did not observe any differences across expected (90% probability), neutral (50%) and surprising (10%) face conditions. Across these comparisons, Bayes factors consistently favoured the null hypothesis throughout the time-course of the stimulus-evoked response. When using multivariate pattern analysis we did not observe above-chance classification of expected and surprising face-evoked ERPs. By contrast, we found robust within- and across-trial stimulus repetition effects. Our findings do not support predictive coding-based accounts that specify reduced prediction error signalling when perceptual expectations are fulfilled. They instead highlight the utility of other types of predictive processing models that describe expectation-related phenomena in the visual system without recourse to prediction error signalling.

Abstract Background Interdisciplinary collaboration between healthcare providers with regard to consultation, transfer and advice in terminal care is both important and challenging. The use of video communication in terminal care is low while in first-line healthcare it has the potential to improve quality of care, as it allows healthcare providers to assess the clinical situation in real time and determine collectively what care is needed. The aim of the present study is to explore the intention to use video communication by healthcare providers in interprofessional terminal care and predictors herein. Methods In this cross-sectional study, an online survey was used to explore the intention to use video communication. The survey was sent to first-line healthcare providers involved in terminal care (at home, in hospices and/ or nursing homes) and consisted of 39 questions regarding demographics, experience with video communication and constructs of intention to use (i.e. Outcome expectancy, Effort expectancy, Attitude, Social influence, Facilitating conditions, Anxiety, Self-efficacy and Personal innovativeness) based on the Unified Theory of Acceptance and Use of Technology and Diffusion of Innovation Theory. Descriptive statistics were used to analyze demographics and experiences with video communication. A multiple linear regression analysis was performed to give insight in the intention to use video communication and predictors herein. Results 90 respondents were included in the analysis.65 (72%) respondents had experience with video communication within their profession, although only 15 respondents (17%) used it in terminal care. In general, healthcare providers intended to use video communication in terminal care (Mean (M) = 3.6; Standard Deviation (SD) = .88). The regression model was significant (F = 9.809, p-value

Abstract Pathogenic variants in the OPN1LW/OPN1MW gene cluster are causal for a range of mild to severe visual impairments with color deficiencies. The widely utilized short-read next-generation sequencing (NGS) is inappropriate for the analysis of the OPN1LW/OPN1MW gene cluster and many patients with pathogenic variants stay underdiagnosed. A diagnostic genetic assay was developed for the OPN1LW/OPN1MW gene cluster, consisting of copy number analysis via multiplex ligation-dependent probe amplification and sequence analysis via long-read circular consensus sequencing. Performance was determined on 50 clinical samples referred for genetic confirmation of the clinical diagnosis (n = 43) or carrier status analysis (n = 7). A broad range of pathogenic haplotypes were detected, including deletions, hybrid genes, single variants and combinations of variants. The developed genetic assay for the OPN1LW/OPN1MW gene cluster is a diagnostic test that can detect both structural and nucleotide variants with a straightforward analysis, improving diagnostic care of patients with visual impairment.