Impact of drone-specific dispatch instructions on the safety and efficacy of drone-delivered emergency medical treatments: A randomized simulation pilot study.

Introduction: Medical drones have potential for improving the response times to out-of-hospital emergencies. However, widespread adoption is hindered by unanswered questions surrounding medical dispatch and bystander safety. This study evaluated the impact of novel drone-specific dispatch instructions (DSDI) on bystanders' ability to interact effectively with a medical drone and provide prompt, safe, and high-quality treatment in a simulated emergency scenario. We hypothesized DSDI would improve bystanders' performance and facilitate safer bystander-drone interactions. Methods: Twenty-four volunteers were randomized to receive either DSDI and standard Medical Priority Dispatch (MPD) instructions or MPD alone in a simulated out-of-hospital cardiac arrest (OHCA) or pediatric anaphylaxis.,3 Participants in the DSDI group received detailed instructions on locating and interacting with the drone and its enclosed medical kit. The simulations were video recorded. Participants completed a semi-structured interview and survey. Results: The addition of DSDI did not lead to statistically significant changes to the overall time to provide care in either the anaphylaxis or OHCA simulations. However, DSDI did have an impact on bystander safety. In the MPD only group, 50% (6/12) of participants ignored the audio and visual safety cues from the drone instead of waiting for it to be declared safe compared to no DSDI participants ignoring these safety cues. Conclusions: All participants successfully provided patient care. However, this study indicates that DSDI may be useful to ensure bystander safety and should be incorporated in the continued development of emergency medical drones.

Bystander interaction with a novel multipurpose medical drone: A simulation trial.

Intro: Medical drones are an emerging technology which may facilitate rapid treatment in time-sensitive emergencies. However, drones rely on lay rescuers, whose interactions with multipurpose medical drones have not been studied, and the optimal drone design remains unclear. Methods: We conducted 24 simulations of adult out-of-hospital cardiac arrest (OHCA) and pediatric anaphylaxis with a prototype drone equipped with spoken and visual cues and a multipurpose medical kit. 24 layperson volunteers encountered one of the two scenarios and were supported through administering treatment by a simulated 911 dispatcher. Bystander-drone interactions were evaluated via a convergent parallel mixed methods approach using surveys, video event review, and semi-structured interviews. Results: 83% (20/24) of participants voiced comfort interacting with the drone. 96% (23/24) were interested in future interaction. Participants appreciated the drone's spoken instructions but found visual cues confusing. Participants retrieved the medical kit from the drone in a mean of 5 seconds (range 2-14) of drone contact; 79% (19/24) found this step easy or very easy. The medical kit's layered design caused difficulty in retrieving appropriate equipment. Participants expressed a wide range of reactions to the unique drone design. Conclusions: Laypeople can effectively and comfortably interact with a medical drone with a novel design. Feedback on design elements will result in further refinements and valuable insights for other drone designers. A multipurpose medical kit created more challenges and indicates the need for further refinement to facilitate use of the equipment.

The genetic status and rescue measure for a geographically isolated population of Amur tigers.

The Amur tiger is currently confronted with challenges of anthropogenic development, leading to its population becoming fragmented into two geographically isolated groups: smaller and larger ones. Small and isolated populations frequently face a greater extinction risk, yet the small tiger population's genetic status and survival potential have not been assessed. Here, a total of 210 samples of suspected Amur tiger feces were collected from this small population, and the genetic background and population survival potentials were assessed by using 14 microsatellite loci. Our results demonstrated that the mean number of alleles in all loci was 3.7 and expected heterozygosity was 0.6, indicating a comparatively lower level of population genetic diversity compared to previously reported studies on other subspecies. The genetic estimates of effective population size (Ne) and the Ne/N ratio were merely 7.6 and 0.152, respectively, representing lower values in comparison to the Amur tiger population in Sikhote-Alin (the larger group). However, multiple methods have indicated the possibility of genetic divergence within our isolated population under study. Meanwhile, the maximum kinship recorded was 0.441, and the mean inbreeding coefficient stood at 0.0868, both of which are higher than those observed in other endangered species, such as the African lion and the grey wolf. Additionally, we have identified a significant risk of future extinction if the lethal equivalents were to reach 6.26, which is higher than that of other large carnivores. Further, our simulation results indicated that an increase in the number of breeding females would enhance the prospects of this population. In summary, our findings provide a critical theoretical basis for further bailout strategies concerning Amur tigers.

Combination of facial and nose features of Amur tigers to determine age.

We found that the area of black round or irregular-shaped spots on the tiger's nose increased with age, indicating a positive relationship between age and nose features. We used the deep learning model to train the facial and nose image features to identify the age of Amur tigers, using a combination of classification and prediction methods to achieve age determination with an accuracy of 87.81%.

Myeloid-derived suppressor cell mitochondrial fitness governs chemotherapeutic efficacy in hematologic malignancies.

Myeloid derived suppressor cells (MDSCs) are key regulators of immune responses and correlate with poor outcomes in hematologic malignancies. Here, we identify that MDSC mitochondrial fitness controls the efficacy of doxorubicin chemotherapy in a preclinical lymphoma model. Mechanistically, we show that triggering STAT3 signaling via ß2-adrenergic receptor (ß2-AR) activation leads to improved MDSC function through metabolic reprograming, marked by sustained mitochondrial respiration and higher ATP generation which reduces AMPK signaling, altering energy metabolism. Furthermore, induced STAT3 signaling in MDSCs enhances glutamine consumption via the TCA cycle. Metabolized glutamine generates itaconate which downregulates mitochondrial reactive oxygen species via regulation of Nrf2 and the oxidative stress response, enhancing MDSC survival. Using ß2-AR blockade, we target the STAT3 pathway and ATP and itaconate metabolism, disrupting ATP generation by the electron transport chain and decreasing itaconate generation causing diminished MDSC mitochondrial fitness. This disruption increases the response to doxorubicin and could be tested clinically.

A Cluster of Neuroinvasive Adenovirus Infections on a College Campus: Case Series.

INTRODUCTION: We present six adenovirus cases that emerged from a cluster of respiratory illnesses within a college population. Two patients required intensive care with complicated hospital courses and experienced residual symptoms. Four additional patients were evaluated in the emergency department (ED) with two additional diagnoses of neuroinvasive disease. These cases represent the first known occurrences of neuroinvasive adenovirus infections in healthy adults. CASE SERIES: An individual presented to the ED with fever, altered mental status, and seizures after being found unresponsive in his apartment. His presentation was concerning for significant central nervous system pathology. Shortly after his arrival, a second individual presented with similar symptoms. Both required intubation and admission to a critical care setting. Over a 24-hour period, four additional individuals presented to the ED with moderate severity symptoms. All six individuals tested positive for adenovirus in their respiratory secretions. A provisional diagnosis of neuroinvasive adenovirus was made after consultation with infectious diseases. CONCLUSION: This cluster of cases appears to represent the first known reported diagnosis of neuroinvasive adenovirus in healthy young individuals. Our cases were also unique in demonstrating a significant spectrum of disease severity. Over 80 individuals in the broader college community ultimately tested positive for adenovirus in respiratory samples. As respiratory viruses continue to challenge our healthcare systems, new spectrums of disease are being discovered. We believe clinicians should be aware of the potential severity of neuroinvasive adenovirus disease.

A Novel Workflow to Create a Checkpoint Inhibitor Pneumonitis Patient Registry.

Background Despite being a groundbreaking cancer therapy, immune checkpoint inhibitors (ICI) can lead to potentially life-threatening toxicity with checkpoint inhibitor pneumonitis (CIP). While treatable, it is easy for clinicians to miss the symptoms of CIP, which can lead to a delay in diagnosis and worsening respiratory function. There is no consensus approach to systematically identifying patients at risk of developing CIP. Thus, we sought to create a workflow that could inform patient selection for ICI therapy based on previously reported risk factors for CIP development. Materials and methods We retrospectively identified 250 patients with lung cancer treated with at least one dose of an ICI over 20 months. Data were collected on comorbidities, cancer type and stage, performance status, ICI cycles, biomarkers, prior curative treatment, diagnostic evaluation, antibiotics, steroids, progression, and survival. A single-blinded radiologist characterized radiographic patterns of suspected CIP cases. Results Among 97 patients who received steroids while admitted to the hospital, 12 (6%) had at least one sign or symptom suggestive of CIP. Chronic obstructive pulmonary disease and non-small cell lung cancer subtypes correlated with suspicion of having CIP. CIP was confirmed in five patients (42%) and ruled out (mimics) in seven (58%). Median times until symptoms were 17 months and one month for confirmed and mimic cases, respectively. The median time to confirm or exclude CIP was 5 ± 4 days. Most suspected cases underwent thoracic imaging, blood cultures, and empiric antibiotics. Radiographic patterns in suspected cases included ground glass opacities, organizing pneumonia, acute interstitial pneumonia/acute respiratory distress syndrome, bronchiolitis, radiation recall pneumonitis, hypersensitivity pneumonitis, and post-radiation fibrotic changes. Conclusions CIP mimics are common in clinical practice; therefore, it is reasonable to empirically treat suspected cases with shorter courses of steroids until diagnostic clarity is achieved. This proof-of-concept study demonstrates that this novel workflow can identify the true incidence of CIP, inform treatment decisions, and lead to the development of implementation studies to improve patient care directly.

Current summary of the evidence in drone-based emergency medical services care.

Interventions for many medical emergencies including cardiac arrests, strokes, drug overdoses, seizures, and trauma, are critically time-dependent, with faster intervention leading to improved patient outcomes. Consequently, a major focus of emergency medical services (EMS) systems and prehospital medicine has been improving the time until medical intervention in these time-sensitive emergencies, often by reducing the time required to deliver critical medical supplies to the scene of the emergency. Medical indications for using unmanned aerial vehicles, or drones, are rapidly expanding, including the delivery of time-sensitive medical supplies. To date, the drone-based delivery of a variety of time-critical medical supplies has been evaluated, generating promising data suggesting that drones can improve the time interval to intervention through the rapid delivery of automatic external defibrillators (AEDs), naloxone, antiepileptics, and blood products. Furthermore, the improvement in the time until intervention offered by drones in out-of-hospital emergencies is likely to improve patient outcomes in time-dependent medical emergencies. However, barriers and knowledge gaps remain that must be addressed. Further research demonstrating functionality in real-world scenarios, as well as research that integrates drones into the existing EMS structure will be necessary before drones can reach their full potential. The primary aim of this review is to summarize the current evidence in drone-based Emergency Medical Services Care to help identify future research directions.

Confounder-corrected T1 mapping in the liver through simultaneous estimation of T1 , PDFF, R 2 * , and B 1 + in a single breath-hold acquisition.

PURPOSE: Quantitative volumetric T1 mapping in the liver has the potential to aid in the detection, diagnosis, and quantification of liver fibrosis, inflammation, and spatially resolved liver function. However, accurate measurement of hepatic T1 is confounded by the presence of fat and inhomogeneous B 1 + $$ {B}_1^{+} $$ excitation. Furthermore, scan time constraints related to respiratory motion require tradeoffs of reduced volumetric coverage and/or increased acquisition time. This work presents a novel 3D acquisition and estimation method for confounder-corrected T1 measurement over the entire liver within a single breath-hold through simultaneous estimation of T1 , fat and B 1 + $$ {B}_1^{+} $$ . THEORY AND METHODS: The proposed method combines chemical shift encoded MRI and variable flip angle MRI with a B 1 + $$ {B}_1^{+} $$ mapping technique to enable confounder-corrected T1 mapping. The method was evaluated theoretically and demonstrated in both phantom and in vivo acquisitions at 1.5 and 3.0T. At 1.5T, the method was evaluated both pre- and post- contrast enhancement in healthy volunteers. RESULTS: The proposed method demonstrated excellent linear agreement with reference inversion-recovery spin-echo based T1 in phantom acquisitions at both 1.5 and 3.0T, with minimal bias (5.2 and 45 ms, respectively) over T1 ranging from 200-1200 ms. In vivo results were in general agreement with reference saturation-recovery based 2D T1 maps (SMART1 Map, GE Healthcare). CONCLUSION: The proposed 3D T1 mapping method accounts for fat and B 1 + $$ {B}_1^{+} $$ confounders through simultaneous estimation of T1 , B 1 + $$ {B}_1^{+} $$ , PDFF and R 2 * $$ {R}_2^{\ast } $$ . It demonstrates strong linear agreement with reference T1 measurements, with low bias and high precision, and can achieve full liver coverage in a single breath-hold.

Impacts of top predators and humans on the mammal communities of recovering temperate forest regions.

Top predators are important drivers in shaping ecological community structure via top-down effects. However, the ecological consequences and mechanisms of top predator loss under accelerated human impacts have rarely been quantitatively assessed due to the limited availability of long-term community data. With increases in top predator populations in northern China over the past two decades, forests with varying densities of top predators and humans provide an opportunity to study their ecological effects on mammal communities. We hypothesized a priori of conceptual models and tested these using structural equation models (SEMs) with multi-year camera trap data, aiming to reveal the underlying independent ecological effects of top predators (tigers, bears, and leopards) and humans on mammal communities. We used random forest models and correlations among species pairs to validate results. We found that top predator reduction could be related to augmented populations of large ungulates ("large ungulate release") and mesopredators ("mesopredator release"), consistent with observations of mammal communities in other ecosystems. Additionally, top predator reduction could be related to reduced small mammal abundance. Hierarchical SEMs identified three bottom-up pathways from forest quality to human activities, large ungulates, and some small mammals, and five top-down pathways from human activities and top predators to some small mammals, large ungulates, and mesopredators. Furthermore, our results suggest that humans showed predominant top-down effects on multiple functional groups, partially replacing the role of top predators, rather than be mediated by them; effects of humans and top predators appeared largely independent. Effects of humans on top predators were non-significant. This study provides novel insights into the effects of top predators and humans as super-predators on mammal communities in forest ecosystems and presents cues of bottom-up effects that can be translated into actionable management plans for improving forest quality, thereby supporting top predator recovery and work/life activities of local people.

Individual automatic detection and identification of big cats with the combination of different body parts.

The development of facial recognition technology has become an increasingly powerful tool in wild animal individual recognition. In this paper, we develop an automatic detection and recognition method with the combinations of body features of big cats based on the deep convolutional neural network (CNN). We collected dataset including 12 244 images from 47 individual Amur tigers (Panthera tigris altaica) at the Siberian Tiger Park by mobile phones and digital camera and 1940 images and videos of 12 individual wild Amur leopard (Panthera pardus orientalis) by infrared cameras. First, the single shot multibox detector algorithm is used to perform the automatic detection process of feature regions in each image. For the different feature regions of the image, like face stripe or spots, CNNs and multi-layer perceptron models were applied to automatically identify tiger and leopard individuals, independently. Our results show that the identification accuracy of Amur tiger can reach up to 93.27% for face front, 93.33% for right body stripe, and 93.46% for left body stripe. Furthermore, the combination of right face, left body stripe, and right body stripe achieves the highest accuracy rate, up to 95.55%. Consequently, the combination of different body parts can improve the individual identification accuracy. However, it is not the higher the number of body parts, the higher the accuracy rate. The combination model with 3 body parts has the highest accuracy. The identification accuracy of Amur leopard can reach up to 86.90% for face front, 89.13% for left body spots, and 88.33% for right body spots. The accuracy of different body parts combination is lower than the independent part. For wild Amur leopard, the combination of face with body spot part is not helpful for the improvement of identification accuracy. The most effective identification part is still the independent left or right body spot part. It can be applied in long-term monitoring of big cats, including big data analysis for animal behavior, and be helpful for the individual identification of other wildlife species.

Topological supermodes in photonic crystal fiber.

Topological states enable robust transport within disorder-rich media through integer invariants inextricably tied to the transmission of light, sound, or electrons. However, the challenge remains to exploit topological protection in a length-scalable platform such as optical fiber. We demonstrate, through both modeling and experiment, optical fiber that hosts topological supermodes across multiple light-guiding cores. We directly measure the photonic winding number invariant characterizing the bulk and observe topological guidance of visible light over meter length scales. Furthermore, the mechanical flexibility of fiber allows us to reversibly reconfigure the topological state. As the fiber is bent, we find that the edge states first lose their localization and then become relocalized because of disorder. We envision fiber as a scalable platform to explore and exploit topological effects in photonic networks.

Temporal activity patterns of North China leopards and their prey in response to moonlight and habitat factors.

The nocturnal activities of predators and prey are influenced by several factors, including physiological adaptations, habitat quality and, we suspect, corresponds to changes in brightness of moonlight according to moon phase. In this study, we used a dataset from 102 camera traps to explore which factors are related to the activity pattern of North China leopards (Panthera pardus japonensis) in Shanxi Tieqiaoshan Provincial Nature Reserve (TPNR), China. We found that nocturnal activities of leopards were irregular during four different lunar phases, and while not strictly lunar philic or lunar phobic, their temporal activity was highest during the brighter moon phases (especially the last quarter) and lower during the new moon phase. On the contrary, roe deer (Capreolus pygargus) exhibited lunar philic activity, while wild boar (Sus scrofa) and tolai hare (Lepus tolai) were evidently lunar phobic, with high and low temporal activity during the full moon, respectively. In terms of temporal overlap, there was positive overlap between leopards and their prey species, including roe deer and tolai hare, while leopard activity did not dip to the same low level of wild boar during the full moon phase. Human activities also more influenced the temporal activity of leopards and wild boar than other species investigated. Generally, our results suggested that besides moonlight risk index (MRI), cloud cover and season have diverse effects on leopard and prey nocturnal activity. Finally, distinct daytime and nighttime habitats were identified, with leopards, wild boar, and tolai hare all using lower elevations at night and higher elevations during the day, while leopards and roe deer were closer to secondary roads during the day than at night.

Circadian Rhythm Disruption Increases Tumor Growth Rate and Accumulation of Myeloid-Derived Suppressor Cells.

Circadian rhythm disruption is implicated in the initiation and progression of many diseases, including cancer. External stimuli, such as sunlight, serve to synchronize physiological processes and cellular functions to a 24-h cycle. The immune system is controlled by circadian rhythms, and perturbation of these rhythms can potentially alter the immune response to infections and tumors. The effect of circadian rhythm disruption on the immune response to tumors remains unclear. Specifically, the effects of circadian disruption (CD) on immunosuppressive cell types within the tumor, such as myeloid-derived suppressor cells (MDSCs), are unknown. In this study, a shifting lighting schedule is used to disrupt the circadian rhythm of mice. After acclimation to lighting schedules, mice are inoculated with 4T1 or B16-F10 tumors. Tumor growth is increased in mice housed under circadian disrupting lighting conditions compared to standard lighting conditions. Analysis of immune populations within the spleen and tumor shows an increased accumulation of MDSCs within these tissues, suggesting that MDSC mediated immunosuppression plays a role in the enhanced tumor growth caused by circadian disruption. This paves the way for future studies of the effects of CD on immunosuppression in cancer.

Addressing concomitant gradient phase errors in time-interleaved chemical shift-encoded MRI fat fraction and R2 * mapping with a pass-specific phase fitting method.

PURPOSE: Concomitant gradients induce phase errors that increase quadratically with distance from isocenter. This work proposes a complex-based fitting method that addresses concomitant gradient phase errors in chemical shift encoded (CSE) MRI estimation of proton density fat fraction (PDFF) and R2 * through joint estimation of pass-specific phase terms. This method is applicable to time-interleaved multi-echo gradient-echo acquisitions (i.e., multi-pass acquisitions) and does not require prior knowledge of gradient waveforms typically needed to address concomitant gradient phase errors. THEORY AND METHODS: A CSE-MRI spoiled gradient echo signal model, with pass-specific phase terms, is introduced for non-linear least squares estimation of PDFF and R2 * in the presence of concomitant gradient phase errors. Cramér-Rao lower bound analysis was used to determine noise performance tradeoffs of the proposed fitting method, which was then validated in both phantom and in vivo experiments. RESULTS: The proposed fitting method removed PDFF and R2 * estimation errors up to 12% and 10 s-1 , respectively, at ±12 cm off isocenter (S/I) in a water phantom. In healthy volunteers, PDFF and R2 * bias was reduced by ~10% (12 cm off-isocenter) and ~30 s-1 (16 cm off-isocenter), respectively. An evaluation in 29 clinical liver datasets demonstrated reduced PDFF bias and variability (8.4% improvement in the coefficient of variation), even with the imaging volume centered at isocenter. CONCLUSION: Concomitant gradient induced phase errors in multi-pass CSE-MRI acquisitions can result in PDFF and R2 * estimation biases away from isocenter. The proposed fitting method enables accurate PDFF and R2 * quantification in the presence of concomitant gradient phase errors without knowledge of imaging gradient waveforms.

Behavioral-psychological motivations encoded in the vocal repertoire of captive Amur tiger (Panthera tigris altaica) cubs.

BACKGROUND: The Amur tiger (Panthera tigris altaica) is the largest and one of the most endangered cats in the world. In wild and captive cats, communication is mainly dependent on olfaction. However, vocal communication also plays a key role between mother and cubs during the breeding period. How cubs express their physiological and psychological needs to their mother and companions by using acoustic signals is little known and mainly hindered by the difficult process of data collection. Here, we quantitatively summarized the vocal repertoire and behavioral contexts of captive Amur tiger cubs. The aim of the present work was to investigate the behavioral motivations of cub calls by considering influential factors of age, sex, and rearing experiences. RESULTS: The 5335 high-quality calls from 65 tiger cubs were classified into nine call types (Ar-1, Ar-2, Er, eee, Chuff, Growl, Hiss, Haer, and Roar) produced in seven behavioral contexts. Except for Er, eight of the nine call types were context-specific, related to Play (Ar-2, eee, and Roar), Isolation (Ar-1), Offensive Context (Haer, Growl, and Hiss), and a friendly context (Chuff). CONCLUSIONS: The results suggest that cubs are not quiet, but instead they express rich information by emitting various call types, which are probably crucial for survival in the wild. We herein provide the first detailed spectrogram classification to indicate vocal repertoires of calls and their coding with respect to behavioral contexts in Amur tiger cubs, and we pave the steps for revealing their social communication system, which can be applied for conservation of populations. These insights can help tiger managers or keepers to improve the rearing conditions by understanding the feline cubs' inner status and needs by monitoring their vocal information expressions and exchanges.

CRISPAltRations: a validated cloud-based approach for interrogation of double-strand break repair mediated by CRISPR genome editing.

CRISPR systems enable targeted genome editing in a wide variety of organisms by introducing single- or double-strand DNA breaks, which are repaired using endogenous molecular pathways. Characterization of on- and off-target editing events from CRISPR proteins can be evaluated using targeted genome resequencing. We characterized DNA repair fingerprints that result from non-homologous end joining (NHEJ) after double-stranded breaks (DSBs) were introduced by Cas9 or Cas12a for >500 paired treatment/control experiments. We found that building biological understanding of the repair into a novel analysis tool (CRISPAltRations) improved the quality of the results. We validated our software using simulated, targeted amplicon sequencing data (11 guide RNAs [gRNAs] and 603 on- and off-target locations) and demonstrated that CRISPAltRations outperforms other publicly available software tools in accurately annotating CRISPR-associated indels and homology-directed repair (HDR) events. We enable non-bioinformaticians to use CRISPAltRations by developing a web-accessible, cloud-hosted deployment, which allows rapid batch processing of samples in a graphical user interface (GUI) and complies with HIPAA security standards. By ensuring that our software is thoroughly tested, version controlled, and supported with a user interface (UI), we enable resequencing analysis of CRISPR genome editing experiments to researchers no matter their skill in bioinformatics.