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Augmented reality (AR), mixed reality (MR), and virtual reality devices are enabling technologies that may facilitate effective communication in healthcare between those with information and knowledge (clinician/specialist; expert; educator) and those seeking understanding and insight (patient/family; non-expert; learner). Investigators initiated an exploratory program to enable the study of AR/MR use-cases in acute care clinical and instructional settings. Academic clinician educators, computer scientists, and diagnostic imaging specialists conducted a proof-of-concept project to 1) implement a core holoimaging pipeline infrastructure and open-access repository at the study institution, and 2) use novel AR/MR techniques on off-the-shelf devices with holoimages generated by the infrastructure to demonstrate their potential role in the instructive communication of complex medical information. The study team successfully developed a medical holoimaging infrastructure methodology to identify, retrieve, and manipulate real patients' de-identified computed tomography and magnetic resonance imagesets for rendering, packaging, transfer, and display of modular holoimages onto AR/MR headset devices and connected displays. Holoimages containing key segmentations of cervical and thoracic anatomic structures and pathology were overlaid and registered onto physical task trainers for simulation-based \"blind insertion\" invasive procedural training. During the session, learners experienced and used task-relevant anatomic holoimages for central venous catheter and tube thoracostomy insertion training with enhanced visual cues and haptic feedback. Direct instructor access into the learner's AR/MR headset view of the task trainer was achieved for visual-axis interactive instructional guidance. Investigators implemented a core holoimaging pipeline infrastructure and modular open-access repository to generate and enable access to modular holoimages during exploratory pilot stage applications for invasive procedure training that featured innovative AR/MR techniques on off-the-shelf headset devices.

Objectives Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients. Methods An artificial intelligence (AI) system in a time-to-event analysis framework was developed to integrate chest CT and clinical data for risk prediction of future deterioration to critical illness in patients with COVID-19. Results A multi-institutional international cohort of 1,051 patients with RT-PCR confirmed COVID-19 and chest CT was included in this study. Of them, 282 patients developed critical illness, which was defined as requiring ICU admission and/or mechanical ventilation and/or reaching death during their hospital stay. The AI system achieved a C-index of 0.80 for predicting individual COVID-19 patients’ to critical illness. The AI system successfully stratified the patients into high-risk and low-risk groups with distinct progression risks ( p < 0.0001). Conclusions Using CT imaging and clinical data, the AI system successfully predicted time to critical illness for individual patients and identified patients with high risk. AI has the potential to accurately triage patients and facilitate personalized treatment. Key Point • AI system can predict time to critical illness for patients with COVID-19 by using CT imaging and clinical data.

Pulmonary artery endothelial cells (PAECs) from patients with pulmonary arterial hypertension (PAH) exhibit heterogeneous responses to their mechanical microenvironment. PAH is characterized by pulmonary artery stiffening and vascular remodeling. In this study, the researchers investigated the mechanosensing properties of PAECs obtained from living patients with PAH. They hypothesized that the mechanical properties of the substrate may influence PAH EC characteristics and correlate with clinical disease severity. PAECs were cultured on substrates with varying stiffness and their morphology and migration were analyzed. The results showed that PAECs from different PAH subtypes exhibited distinct responses to substrate stiffness. The stiffness at which cells demonstrated maximum speed correlated with clinical features such as pulmonary vascular resistance and 6-minute walk distance. These findings suggest that PAEC phenotype can be assessed based on their response to the mechanical microenvironment and may provide insights into the heterogeneity of PAH. Further studies are needed to validate these observations and understand the underlying molecular mechanisms.

Stereotactic electroencephalography (SEEG) is an increasingly utilized method for invasive monitoring in patients with medically intractable epilepsy. Yet, the lack of standardization for labeling electrodes hinders communication among clinicians. A rational clustering of contacts based on anatomy rather than arbitrary physical leads may help clinical neurophysiologists interpret seizure networks. We identified SEEG electrodes on post‐implant CTs and registered them to preoperative MRIs segmented according to an anatomical atlas. Individual contacts were automatically assigned to anatomical areas independent of lead. These contacts were then organized using a hierarchical anatomical schema for display and interpretation. Bipolar‐referenced signal cross‐correlations were used to compare the similarity of grouped signals within a conventional montage versus this anatomical montage. As a result, we developed a hierarchical organization for SEEG contacts using well‐accepted, free software that is based solely on their post‐implant anatomical location. When applied to three example SEEG cases for epilepsy, clusters of contacts that were anatomically related collapsed into standardized groups. Qualitatively, seizure events organized using this framework were better visually clustered compared to conventional schemes. Quantitatively, signals grouped by anatomical region were more similar to each other than electrode‐based groups as measured by Pearson correlation. Further, we uploaded visualizations of SEEG reconstructions into the electronic medical record, rendering them durably useful given the interpretable electrode labels. In conclusion, we demonstrate a standardized, anatomically grounded approach to the organization of SEEG neuroimaging and electrophysiology data that may enable improved communication among and across surgical epilepsy teams and promote a clearer view of individual seizure networks. We developed a hierarchical organization for SEEG contacts using well‐accepted, free software that is based solely on their post‐implant anatomical location. Qualitatively, seizure events organized using this framework were better visually clustered compared to conventional schemes. Quantitatively, signals grouped by anatomical region were more similar to each other than electrode‐based groups as measured by Pearson correlation.

Background Delirium occurs frequently in patients with stroke, but the role of preexisting neural substrates in delirium pathogenesis remains unclear. We sought to explore associations between acute and chronic neural substrates of delirium in patients with intracerebral hemorrhage (ICH). Methods Using data from a single-center ICH registry, we identified consecutive patients with acute nontraumatic ICH and available magnetic resonance imaging scans. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria were used to classify each patient as delirious or nondelirious during their hospitalization. Magnetic resonance imaging scans were processed and analyzed using semiautomated software, with volumetric measurement of acute ICH volume as well as white matter hyperintensity volume (WMHV) and gray and white matter volumes from the contralateral hemisphere. We tested associations between WMHV and incident delirium using multivariable regression models, and then determined the predictive accuracy of these neuroimaging models via area under the curve (AUC) analysis. Results Of 139 patients in our cohort (mean [standard deviation] age 67.3 [17.3] years, 53% male), 58 (42%) patients experienced delirium. In our primary analyses, WMHV was significantly associated with delirium after adjusting for ICH features (odds ratio 1.56 per 10 cm 3 , 95% confidence interval 1.13–2.13), and this association was strengthened after further adjustment for segmented brain volume in patients with high-resolution scans (odds ratio 1.89 per 10 cm 3 , 95% confidence interval 1.24–2.86). Neuroimaging-based models predicted delirium with high accuracy (AUC 0.81), especially in patients with Glasgow Coma Scale score > 13 (AUC 0.85) and smaller ICH (AUC 0.91). Conclusions Chronic white matter disease is independently associated with delirium in patients with acute ICH, and neuroimaging biomarkers may have utility in predicting delirium occurrence.

When interacting with infants, humans often alter their speech and song in ways thought to support communication. Theories of human child-rearing, informed by data on vocal signalling across species, predict that such alterations should appear globally. Here, we show acoustic differences between infant-directed and adult-directed vocalizations across cultures. We collected 1,615 recordings of infant- and adult-directed speech and song produced by 410 people in 21 urban, rural and small-scale societies. Infant-directedness was reliably classified from acoustic features only, with acoustic profiles of infant-directedness differing across language and music but in consistent fashions. We then studied listener sensitivity to these acoustic features. We played the recordings to 51,065 people from 187 countries, recruited via an English-language website, who guessed whether each vocalization was infant-directed. Their intuitions were more accurate than chance, predictable in part by common sets of acoustic features and robust to the effects of linguistic relatedness between vocalizer and listener. These findings inform hypotheses of the psychological functions and evolution of human communication.Across 21 societies, people alter their speech and song when interacting with infants. These infant-directed vocalizations are recognized by listeners. This suggests that forms of human vocalizations may be shaped by their functions.

Across taxa, the forms of vocal signals are shaped by their functions. In humans, a salient context of vocal signaling is infant care, as human infants are altricial. Humans often produce \"parent-ese\", speech and song for infants that differ acoustically from ordinary speech and song, in fashions that are thought to support parent-infant communication and infant language learning; modulate infant affect; or credibly signal information to infants. These theories predict a universal form-function link in infant-directed vocalizations, with consistent differentiation between infant-directed and adult-directed vocalizations across cultures. Some evidence supports this prediction, but the limited generalizability of individual ethnographic reports and laboratory experiments and small stimulus sets, along with intriguing reports of counterexamples, leave the question open. Here, we show that infant-directed speech and song are robustly differentiable from their adult-directed counterparts, within voices and across cultures. We built a corpus of 1615 recordings of infant- and adult-directed singing and speech produced by 410 people living in 21 urban, rural, and small-scale societies and played the recordings to 45,745 people recruited online from many countries. We asked them to guess whether or not each vocalization was, in fact, infant-directed. The patterns of inferences of these naive listeners, supported by acoustic analyses and predictive modelling, demonstrate acoustic cues to infant-directedness that are cross-culturally robust. The cues to infant-directedness differ across language and music, however, informing hypotheses of the psychological functions and evolution of both. Competing Interest Statement The authors have declared no competing interest. Footnotes * corrections to author spellings and affiliations * https://doi.org/10.5281/zenodo.5525161 * https://github.com/themusiclab/infant-speech-song * https://themusiclab.org/quizzes/ids

To assess the potential benefit of digital health interventions (DHIs) on cardiovascular disease (CVD) outcomes (CVD events, all-cause mortality, hospitalizations) and risk factors compared with non-DHIs. We conducted a systematic search of PubMed, MEDLINE, EMBASE, Web of Science, Ovid, CINHAL, ERIC, PsychINFO, Cochrane, and Cochrane Central Register of Controlled Trials for articles published from January 1, 1990, through January 21, 2014. Included studies examined any element of DHI (telemedicine, Web-based strategies, e-mail, mobile phones, mobile applications, text messaging, and monitoring sensors) and CVD outcomes or risk factors. Two reviewers independently evaluated study quality utilizing a modified version of the Cochrane Collaboration risk assessment tool. Authors extracted CVD outcomes and risk factors for CVD such as weight, body mass index, blood pressure, and lipid levels from 51 full-text articles that met validity and inclusion criteria. Digital health interventions significantly reduced CVD outcomes (relative risk, 0.61; 95% CI, 0.46-0.80; P<.001; I2=22%). Concomitant reductions in weight (−2.77 lb [95% CI, −4.49 to −1.05 lb]; P<.002; I2=97%) and body mass index (−0.17 kg/m2 [95% CI, −0.32 kg/m2 to −0.01 kg/m2]; P=.03; I2=97%) but not blood pressure (−1.18 mm Hg [95% CI, −2.93 mm Hg to 0.57 mm Hg]; P=.19; I2=100%) were found in these DHI trials compared with usual care. In the 6 studies reporting Framingham risk score, 10-year risk percentages were also significantly improved (−1.24%; 95% CI, −1.73% to −0.76%; P<.001; I2=94%). Results were limited by heterogeneity not fully explained by study population (primary or secondary prevention) or DHI modality. Overall, these aggregations of data provide evidence that DHIs can reduce CVD outcomes and have a positive impact on risk factors for CVD.

Personalized exoskeleton assistance provides users with the largest improvements in walking speed 1 and energy economy 2 – 4 but requires lengthy tests under unnatural laboratory conditions. Here we show that exoskeleton optimization can be performed rapidly and under real-world conditions. We designed a portable ankle exoskeleton based on insights from tests with a versatile laboratory testbed. We developed a data-driven method for optimizing exoskeleton assistance outdoors using wearable sensors and found that it was equally effective as laboratory methods, but identified optimal parameters four times faster. We performed real-world optimization using data collected during many short bouts of walking at varying speeds. Assistance optimized during one hour of naturalistic walking in a public setting increased self-selected speed by 9 ± 4% and reduced the energy used to travel a given distance by 17 ± 5% compared with normal shoes. This assistance reduced metabolic energy consumption by 23 ± 8% when participants walked on a treadmill at a standard speed of 1.5 m s −1 . Human movements encode information that can be used to personalize assistive devices and enhance performance. A portable ankle exoskeleton uses a data-driven method and wearable sensors to adapt to the user as they walk in a natural setting.

A central role for nature-based solution is to identify optimal management practices to address environmental challenges, including carbon sequestration and biodiversity conservation. Inorganic fertilization increases plant aboveground biomass but often causes a tradeoff with plant diversity loss. It remains unclear, however, whether organic fertilization, as a potential nature-based solution, could alter this tradeoff by increasing aboveground biomass without plant diversity loss. Here we compile data from 537 experiments on organic and inorganic fertilization across grasslands and croplands worldwide to evaluate the responses of aboveground biomass, plant diversity, and soil organic carbon (SOC). Both organic and inorganic fertilization increase aboveground biomass by 56% and 42% relative to ambient, respectively. However, only inorganic fertilization decreases plant diversity, while organic fertilization increases plant diversity in grasslands with greater soil water content. Moreover, organic fertilization increases SOC in grasslands by 19% and 15% relative to ambient and inorganic fertilization, respectively. The positive effect of organic fertilization on SOC increases with increasing mean annual temperature in grasslands, a pattern not observed in croplands. Collectively, our findings highlight organic fertilization as a potential nature-based solution that can increase two ecosystem services of grasslands, forage production, and soil carbon storage, without a tradeoff in plant diversity loss. Inorganic fertilization reduces plant biodiversity. Here, the authors conduct a global meta-analysis on the use of organic and inorganic fertilizer in croplands and grasslands, showing that while both fertilizers increase plant biomass, only organic fertilizer increases biodiversity.