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Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Abstract Philips Visual Patient Avatar is an innovative approach to patient monitoring. Computer-based simulation studies have shown that it can improve diagnostic accuracy and confidence while reducing perceived workload. Following its integration into clinical practice, we conducted a single-centre qualitative study at the University Hospital Zurich to explore the views of anaesthesia, post-anaesthesia and intensive care providers on their experience with the technology. We used an online survey to assess its contributions in different clinical situations. We analysed the data thematically to identify key themes. Of the 510 healthcare providers contacted, 131 (25.7%) completed the survey and 154 comments were collected. Key themes included the detection of specific vital sign changes, focusing on temperature and oxygen saturation (41.9%, 34/81 comments in the operating room; 38.6%, 17/44 comments in the intensive care unit; 10.3%, 3/29 comments in the post-anaesthesia care unit). Additionally, the technology was perceived to support daily routines and situational awareness (28.4%, 23/81 comments in the OR; 9.1%, 4/44 comments in the ICU; 10.3%, 3/29 comments in the PACU). The study provides early, but strong evidence that the Philips Visual Patient Avatar assists healthcare providers in specific clinical situations in the perioperative and critical care settings.

The Morris Water Maze (MWM) is the most commonly used assay for evaluating learning and memory in laboratory mice. Despite its widespread use, contemporary reviews have highlighted substantial methodological variation in experimental protocols and that the associated testing procedures are acutely (each trial) and chronically (testing across days) stressful; stress impairs attention, memory consolidation and the retrieval of learned information. Moreover, the interpretation of behavior within the MWM is often difficult because of wall hugging, non-spatial swim strategies, floating, and jumping off the escape platform. Together, these issues may compromise the reproducibility, generalizability, and predictability of experimental results, as well as animal welfare. To address these issues, and as an initial proof-of-principle, we first narrowed the spatial dimensions of the MWM by using a T-insert, which constrained and reduced the overall length of time/distance that the animal must swim in order to navigate to the escape platform, thus reducing stress and off-task behavior. Given the robust performance observed across spatial acquisition (learning and memory) as well as during reversal learning (executive function), we further reduced (by 43%) the overall distance and time that the animal must swim in order to find the escape platform in a bespoke standalone Water T-Maze (WTM). We show, across five experiments, procedural refinements to our protocol and demonstrate robust, reliable and reproducible indicators of learning, memory and executive functioning in a task that is also significantly more efficient (3 days of testing within the WTM vs. 11 days of testing within the MWM). Taken together, our WTM apparatus and protocol are a significant improvement over other water-based apparatuses and protocols for evaluating learning, memory, and executive functioning in laboratory mice.

Human noroviruses (HuNoVs) are a major cause of diarrheal disease, yet critical aspects of their biology, including cellular tropism, remain unclear. Although research has traditionally focused on the intestinal epithelium, the hypothesis that HuNoV infects macrophages has been recurrently discussed and is investigated here using a zebrafish larval model. Through single-cell RNA sequencing of dissected zebrafish intestines, we unbiasedly identified macrophages as host cells for HuNoV replication, with all three open reading frames mapped to individual macrophages. Notably, HuNoV preferentially infects actively phagocytosing inflammatory macrophages. HuNoV capsid proteins and double-stranded RNA colocalized within intestinal macrophages of infected zebrafish larvae, and the negative-strand RNA intermediate was detected within FACS-sorted macrophages. Flow cytometry confirmed viral replication within these macrophages, constituting approximately 23% of HuNoV’s host cells. Identifying macrophages as host cells prompts a reevaluation of their role in HuNoV pathogenesis, offering new directions for understanding and controlling this infection.

Abstract Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Abstract Spectrum power analysis in the low frequency oscillations (LFO) region of functional near infrared spectroscopy (fNIRS) is a promising method to deliver information about brain activation and therefore might be used for prognostication in patients with disorders of consciousness in the neurocritical care unit alongside with established methods. In this study, we measure the cortical hemodynamic response measured by fNIRS in the LFO region following auditory and somatosensory stimulation in healthy subjects. The significant hemodynamic reaction in the contralateral hemisphere correlation with the physiologic electric response suggests neurovascular coupling. In addition, we investigate power spectrum changes in steady state measurements of cerebral death patients and healthy subjects in the LFO region, the frequency of the heartbeat and respiration. The spectral power within the LFO region was lower in the patients with cerebral death compared to the healthy subjects, whereas there were no differences in spectral power for physiological activities such as heartbeat and respiration rate. This finding indicates the cerebral origin of our low frequency measurements. Therefore, LFO measurements are a potential method to detect brain activation in patients with disorders of consciousness and cerebral death. However, further studies in patients are needed to investigate its potential clinical use.

This case study examines the adaptation of an existing online, asynchronous faculty development resource at the University of New Mexico to support the unanticipated need for all instructors to teach remotely starting in spring 2020, due to the COVID-19 pandemic. The course--entitled Evidence-Based Practices for Teaching Online (EBPTO)--was previously utilized to support instructor transitions to distance education by applying constructivist principles to the development of evidence-based online teaching practices. The course was adapted to address institutional and instructor needs as a result of the pandemic, including increasing facilitation resources. The largest EBPTO cohort, with 117 participants, began in June 2020. Data were collected through a reflective journal administered at the mid-point and an end-of-course survey. Analysis of the reflective journal provided insight into participants' learning experience in terms of key "takeaways," LMS tools that they had the opportunity to practice, and "lingering questions" that they had. The top 3 takeaways were the usefulness of course mapping, the usefulness of backwards design, and the deepening familiarity with LMS tools. Results from the end-of-course survey showed positive feedback from participants regarding perceived achievement of the course learning objectives, even after scaling the course to accommodate the large number of instructors moving to remote instruction.

Abstract Despite significant progress in the medical field, there is still a pressing need for minimal‐invasive tools to assist with decision‐making, especially in cases of polytrauma. Our team explored the potential of serum‐derived large extracellular vesicles, so called microparticles/microvesicles/ectosomes, to serve as a supportive tool in decision‐making in polytrauma situations. We focused on whether monocyte derived large EVs may differentiate between polytrauma patients with internal organ injury (ISS > 15) and those without. Thus, we compared our EV data to soluble biomarkers such as tumour necrosis factor alpha (TNF alpha) and Interleukin‐8 (IL‐8). From the blood of 25 healthy and 26 patients with polytrauma large EVs were isolated, purified, and characterized. TNF alpha and IL‐8 levels were quantified. We found that levels of these monocyte derived large EVs were significantly higher in polytrauma patients with internal organ damage and correlated with the ISS. Interestingly, we also observed a decline in AnnV+CD14+ large EVs during normal recovery after trauma. Thus, inflammatory serological markers as TNF alpha and as IL‐8 demonstrated an inability to discriminate between polytrauma patients with or without internal organ damage, such as spleen, kidney, or liver lacerations/ruptures. However, TNF and IL‐8 levels were elevated in polytrauma cases overall when contrasted with healthy non‐traumatic controls. These findings suggest that delving deeper into the potential of AnnV+ large EVs derived from monocytes could highly beneficial in the managment of polytrauma, potentially surpassing the efficacy of commonly used serum markers.

In March 2020, at the onset of the coronavirus disease 2019 (COVID-19) pandemic in the United States, the Southern California Extracorporeal Membrane Oxygenation (ECMO) Consortium was formed. The consortium included physicians and coordinators from the 4 ECMO centers in San Diego County. Guidelines were created to ensure that ECMO was delivered equitably and in a resource effective manner across the county during the pandemic. A biomedical ethicist reviewed the guidelines to ensure ECMO use would provide maximal community benefit of this limited resource. The San Diego County Health and Human Services Agency further incorporated the guidelines into its plans for the allocation of scarce resources. The consortium held weekly video conferences to review countywide ECMO capacity (including census and staffing), share data, and discuss clinical practices and difficult cases. Equipment exchanges between ECMO centers maximized regional capacity. From March 1 to November 30, 2020, consortium participants placed 97 patients on ECMO. No eligible patients were denied ECMO due to lack of resources or capacity. The Southern California ECMO Consortium may serve as a model for other communities seeking to optimize ECMO resources during the current COVID-19 or future pandemics.

Abstract The circadian clock is a molecular timekeeper, present from cyanobacteria to mammals, that coordinates internal physiology with the external environment. The clock has a 24-h period however development proceeds with its own timing, raising the question of how these interact. Using the intestine of Drosophila melanogaster as a model for organ development, we track how and when the circadian clock emerges in specific cell types. We find that the circadian clock begins abruptly in the adult intestine and gradually synchronizes to the environment after intestinal development is complete. This delayed start occurs because individual cells at earlier stages lack the complete circadian clock gene network. As the intestine develops, the circadian clock is first consolidated in intestinal stem cells with changes in Ecdysone and Hnf4 signalling influencing the transcriptional activity of Clk/cyc to drive the expression of tim, Pdp1, and vri. In the mature intestine, stem cell lineage commitment transiently disrupts clock activity in differentiating progeny, mirroring early developmental clock-less transitions. Our data show that clock function and differentiation are incompatible and provide a paradigm for studying circadian clocks in development and stem cell lineages.

Delayed cerebral ischemia (DCI) occurs in up to one third of patients suffering from aneurysmal subarachnoid hemorrhage (aSAH). Untreated, it leads to secondary cerebral infarctions and is frequently associated with death or severe disability. After aneurysm rupture, erythrocytes in the subarachnoid space lyse and liberate free hemoglobin (Hb), a key driver for the development of DCI. Hemoglobin in the cerebrospinal fluid (CSF-Hb) can be analyzed through a two-step procedure of centrifugation to exclude intact erythrocytes and subsequent spectrophotometric quantification. This analysis can only be done in specialized laboratories but not at the bedside in the intensive care unit. This limits the number of tests done, increases the variability of the results and restricts accuracy. Bedside measurements of CSF-Hb as a biomarker with a point of care diagnostic test system would allow for a continuous monitoring for the risk of DCI in the individual patient. In this study, a microfluidic chip was explored that allows to continuously separate blood particles from CSF or plasma based on acoustophoresis. An in vitro test bench was developed to test in-line measurements with the developed microfluidic chip and a spectrometer. The proof of principle for a continuous particle separation device has been established with diluted blood and CSF samples from animals and aSAH patients, respectively. Processing 1 mL of blood in our microfluidic device was achieved within around 70 min demonstrating only minor deviations from the gold standard centrifugation (7% average error of patient samples), while saving several hours of processing time and additionally the reduction of deviations in the results due to manual labor.