Qualitative evaluation of a molecular point-of-care testing study for influenza in UK primary care.

BACKGROUND: Influenza contributes to the surge in winter infections and the consequent winter pressures on the health service. Molecular point-of-care testing(POCT) for influenza might improve patient management by providing rapid and accurate clinical diagnosis to inform the timely initiation of antiviral therapy and reduce unnecessary admissions and antibiotics use. AIM: To explore factors that influence the adoption or non-adoption of POCT in English general practices and provide insights to enable its integration into routine practice workflows. DESIGN & SETTING: A qualitative implementation evaluation was conducted in ten general practices within the English national sentinel network (Oxford-RCGP Research and Surveillance Centre), from April to July 2023. METHOD: Using the nonadoption, abandonment, scale-up, spread, and sustainability framework, data collection and analysis were conducted across ten practices. We made ethnographic observations of the POCT workflow and surveyed the practice staff for their perspectives on POCT implementation. Data were analysed using a mix of descriptive statistics, graphical modelling techniques and framework approach. RESULTS: Ethnographic observations identified two modes of POCT integration into practice workflow: 1) clinician POCT workflow - typically involving batch testing due to time constraints, 2) research nurse/healthcare assistant POCT workflow - characterised by immediate testing of individual patients. Survey indicated that most primary care staff considered the POCT training offered was sufficient, and these practices were ready for change and had the capacity and resources to integrate POCT in workflows. CONCLUSION: General practices should demonstrate flexibility in the workflow and workforce they deploy to integrate POCT into routine clinical workflow.

Degron-Based bioPROTACs for Controlling Signaling in CAR T Cells.

Chimeric antigen receptor (CAR) T cells have made a tremendous impact in the clinic, but potent signaling through the CAR can be detrimental to treatment safety and efficacy. The use of protein degradation to control CAR signaling can address these issues in preclinical models. Existing strategies for regulating CAR stability rely on small molecules to induce systemic degradation. In contrast to small molecule regulation, genetic circuits offer a more precise method to control CAR signaling in an autonomous cell-by-cell fashion. Here, we describe a programmable protein degradation tool that adopts the framework of bioPROTACs, heterobifunctional proteins that are composed of a target recognition domain fused to a domain that recruits the endogenous ubiquitin proteasome system. We develop novel bioPROTACs that utilize a compact four-residue degron and demonstrate degradation of cytosolic and membrane protein targets using either a nanobody or synthetic leucine zipper as a protein binder. Our bioPROTACs exhibit potent degradation of CARs and can inhibit CAR signaling in primary human T cells. We demonstrate the utility of our bioPROTACs by constructing a genetic circuit to degrade the tyrosine kinase ZAP70 in response to recognition of a specific membrane-bound antigen. This circuit can disrupt CAR T cell signaling only in the presence of a specific cell population. These results suggest that bioPROTACs are powerful tools for expanding the CAR T cell engineering toolbox.

Predictors of Extended Length of Stay Following Open Reduction and Internal Fixation for Proximal Humerus Fractures.

Purpose: An extended length of stay following open reduction and internal fixation (ORIF) for proximal humerus fractures (PHFs) is associated with increased patient morbidity and health care costs. The primary purpose of this study was to identify risk factors for an extended length of stay following ORIF for PHF. Methods: All patients who underwent ORIF for PHF between 2015 and 2021 were queried from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database. Patient demographics, comorbid conditions, and postoperative complications within 30 days of procedure were collected. Extended length of stay (eLOS) was defined by ≥ 3 days from operation to discharge. Multivariate logistic regression was employed to identify predictors of eLOS following ORIF. Results: Characteristics of patients significantly associated with eLOS included age ≥ 75 years (p < .001), male gender (p < 0.001), body mass index (BMI) < 18.5 (P = .001), American Society of Anesthesiologists (ASA) classification ≥ 3 (P < .001), dependent functional status (P < .001), noninsulin-dependent diabetes (P = .037), insulin-dependent diabetes (P < .001), chronic obstructive pulmonary disease (P < .001), congestive heart failure (CHF) (P < .001), hypertension (P < 0.001), dialysis (P < .013), disseminated cancer (P < 0.001), chronic steroid use (P = .004), and bleeding disorder (P < .001). Independent predictors of eLOS were age ≥ 75 years (OR = 2.69; P < .001), BMI < 18.5 (OR = 1.70; P = .016), ASA ≥ 3 (OR = 2.70; P < .001), dependent functional status (OR = 2.30; P < .001), CHF (OR = 3.57; P < .001), disseminated cancer (OR = 7.62; P < .001), and bleeding disorder (OR = 2.68; P < .001). Conclusion: Age ≥ 75, BMI < 18.5, ASA ≥ 3, functional dependence, CHF, disseminated cancer, and bleeding disorder were independently associated with eLOS. Clinical Relevance: Assessing specific patient factors prior to ORIF for PHF can assist in managing perioperative risks and decreasing expenses related to eLOS. Level of Evidence: Prognosis III.

Predicting operative outcomes of total shoulder arthroplasty using the model for end-stage liver disease score.

Background: The aim of this study was to assess the efficacy of the Model for End-Stage Liver Disease (MELD) score in predicting postoperative complications following total shoulder arthroplasty (TSA). Methods: The American College of Surgeons National Surgical Quality Improvement database was queried for all patients who underwent TSA between 2015 and 2019. The study population was subsequently classified into two categories: those with a MELD score ≥ 10 and those with a MELD score < 10. A total of 5265 patients undergoing TSA between 2015 and 2019 were included in this study. Among these, 4690 (89.1%) patients had a MELD score ≥ 10, while 575 (10.9%) patients had a MELD score < 10. Postoperative complications within 30 days of the TSA were collected. Multivariate logistic regression analysis was conducted to explore the correlation between a MELD score ≥ 10 and postoperative complications. The anchor based optimal cutoff was calculated by receiver operating characteristic analysis to determine the MELD score cutoff that most accurately predicts a specific complication. Youden's index (J) determined the optimal cutoff point calculation for the maximum sensitivity and specificity; these were deemed to be "acceptable" if the area under curve (AUC) was greater than 0.7 and "excellent" if greater than 0.8. Results: Multivariate regression analysis found a MELD score ≥ 10 to be independently associated with higher rates of reoperation (OR, 2.08; P = .013), cardiac complications (OR, 3.37; P = .030), renal complications (OR, 7.72; P = .020), bleeding transfusions (OR, 3.23; P < .001), and nonhome discharge (OR, 1.75; P < .001). The receiver operating characteristic analysis showed that AUC for a MELD score cutoff of 7.61 as a predictor of renal complications was 0.87 (excellent) with sensitivity of 100.0% and specificity of 70.0%. AUC for a MELD score cutoff of 7.76 as a predictor of mortality was 0.76 (acceptable) with sensitivity of 81.8% and specificity of 71.0%. Conclusion: A MELD score ≥ 10 was correlated with high rates of reoperation, cardiac complications, renal complications, bleeding transfusions, and nonhome discharge following TSA. MELD score cutoffs of 7.61 and 7.76 were effective in predicting renal complications and mortality, respectively.

Cumulative effect of chronic dehydration and age on postoperative complications after total shoulder arthroplasty.

Background: Dehydration is a modifiable risk factor that should be optimized prior to all surgical procedures. The aim of this study was to determine the effects of dehydration on postoperative complications following total shoulder arthroplasty (TSA). Methods: The American College of Surgeons National Surgical Quality Improvement database was queried for all patients who underwent TSA between 2015 and 2019 and a total of 16,993 patients were included in this study. The study population was subsequently classified into 3 categories: 8498 (50.0%) nondehydrated patients with blood urea nitrogen/creatinine (BUN/Cr) < 20, 4908 (28.9%) moderately dehydrated patients with 20 ≤ BUN/Cr ≤ 25, and 3587 (21.1%) severely dehydrated patients with 25 < BUN/Cr. A subgroup analysis involving only elderly patients aged > 65 years and normalized gender-adjusted Cr values was also performed. Postoperative complications within 30 days of the TSA were collected. Multivariate logistic regression analysis was conducted to explore the correlation between dehydration and postoperative complications. Results: Adjusted multivariate logistic regression analysis showed that the severely dehydrated cohort had a greater risk of postoperative transfusion, mortality, nonhome discharge, and increased length of stay (all P < .05). The moderately dehydrated cohort had a greater risk of wound dehiscence (P = .044). Among the elderly, severely dehydrated patients had a greater risk of cardiac complications, postoperative transfusion, mortality, nonhome discharge, and increased length of stay (all P < .05). Finally, the elderly moderately dehydrated cohort had a greater risk of postoperative transfusion and nonhome discharge (all P < .05). Conclusion: BUN/Cr ratio is an important preoperative diagnostic tool to identify at-risk dehydrated patients. Providers should optimize dehydration to prevent complications, decrease costs, and improve discharge planning.

Preoperative Dehydration Is an Underrecognized Modifiable Risk Factor in Total Hip Arthroplasty.

Dehydration is an overlooked modifiable risk factor that should be optimized prior to elective total hip arthroplasty (THA) to reduce postoperative complications and inpatient costs. All primary THA from 2005 - 2019 were queried from the National Surgical Quality Improvement Program database, and patients were compared based on dehydration status: blood urea nitrogen (BUN): creatinine ratio (Cr) (BUN/Cr) < 20 (nondehydrated), 20 ≤ BUN/Cr ≤ 25 (moderately dehydrated), 25 < BUN/Cr (severely dehydrated). A subgroup analysis involving only elderly patients > 65 years and normalized gender-adjusted Cr values was also performed. The analysis included 212,452 patients who underwent THA. Adjusted multivariate logistic regression analysis showed that the severely dehydrated cohort had a greater risk of overall complications, postoperative anemia requiring transfusion, nonhome discharge, and increased length of stay (all p < 0.01). Among the elderly, dehydrated patients had a greater risk of postoperative transfusion, cardiac complications, and nonhome discharge (all p < 0.01). BUN/Cr > 20 is an important preoperative diagnostic tool to identify at-risk dehydrated patients. Providers should optimize dehydration to prevent complications, decrease costs, and improve discharge planning. (Journal of Surgical Orthopaedic Advances 33(1):017-025, 2024).

Where Does Auto-Segmentation for Brain Metastases Radiosurgery Stand Today?

Detection and segmentation of brain metastases (BMs) play a pivotal role in diagnosis, treatment planning, and follow-up evaluations for effective BM management. Given the rising prevalence of BM cases and its predominantly multiple onsets, automated segmentation is becoming necessary in stereotactic radiosurgery. It not only alleviates the clinician's manual workload and improves clinical workflow efficiency but also ensures treatment safety, ultimately improving patient care. Recent strides in machine learning, particularly in deep learning (DL), have revolutionized medical image segmentation, achieving state-of-the-art results. This review aims to analyze auto-segmentation strategies, characterize the utilized data, and assess the performance of cutting-edge BM segmentation methodologies. Additionally, we delve into the challenges confronting BM segmentation and share insights gleaned from our algorithmic and clinical implementation experiences.

The National Sleep Research Resource: making data findable, accessible, interoperable, reusable and promoting sleep science.

This paper presents a comprehensive overview of the National Sleep Research Resource (NSRR), a National Heart Lung and Blood Institute-supported repository developed to share data from clinical studies focused on the evaluation of sleep disorders. The NSRR addresses challenges presented by the heterogeneity of sleep-related data, leveraging innovative strategies to optimize the quality and accessibility of available datasets. It provides authorized users with secure centralized access to a large quantity of sleep-related data including polysomnography, actigraphy, demographics, patient-reported outcomes, and other data. In developing the NSRR, we have implemented data processing protocols that ensure de-identification and compliance with FAIR (Findable, Accessible, Interoperable, Reusable) principles. Heterogeneity stemming from intrinsic variation in the collection, annotation, definition, and interpretation of data has proven to be one of the primary obstacles to efficient sharing of datasets. Approaches employed by the NSRR to address this heterogeneity include (1) development of standardized sleep terminologies utilizing a compositional coding scheme, (2) specification of comprehensive metadata, (3) harmonization of commonly used variables, and (3) computational tools developed to standardize signal processing. We have also leveraged external resources to engineer a domain-specific approach to data harmonization. We describe the scope of data within the NSRR, its role in promoting sleep and circadian research through data sharing, and harmonization of large datasets and analytical tools. Finally, we identify opportunities for approaches for the field of sleep medicine to further support data standardization and sharing.

Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024.

BACKGROUND: Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. OBJECTIVE: We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. METHODS: Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. RESULTS: We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. CONCLUSIONS: The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.

An Optimized Langendorff-free Method for Isolation and Characterization of Primary Adult Cardiomyocytes.

Isolation of adult mouse cardiomyocytes is an essential technique for advancing our understanding of cardiac physiology and pathology, and for developing therapeutic strategies to improve cardiac health. Traditionally, cardiomyocytes are isolated from adult mouse hearts using the Langendorff perfusion method in which the heart is excised, cannulated, and retrogradely perfused through the aorta. While this method is highly effective for isolating cardiomyocytes, it requires specialized equipment and technical expertise. To address the challenges of the Langendorff perfusion method, researchers have developed a Langendorff-free technique for isolating cardiomyocytes. This Langendorff-free technique involves anterograde perfusion through the coronary vasculature by clamping the aorta and intraventricular injection. This method simplifies the experimental setup by eliminating the need for specialized equipment and cannulation of the heart. Here, we introduce an updated Langendorff-free method for isolating adult mice cardiomyocytes that builds on the Langendorff-free protocols developed previously. In this method, the aorta is clamped in situ, and the heart is perfused using a peristaltic pump, water bath, and an injection needle. This simplicity makes cardiomyocyte isolation more accessible for researchers who are new to cardiomyocyte isolation or are working with limited resources. In this report, we provide a step-by-step description of our optimized protocol. In addition, we present example studies of analyzing mitochondrial structural and functional characteristics in isolated cardiomyocytes treated with and without the acute inflammatory stimuli lipopolysaccharide (LPS).

Motion correction of 3D dynamic contrast-enhanced ultrasound imaging without anatomical B-Mode images: Pilot evaluation in eight patients.

BACKGROUND: Dynamic contrast-enhanced ultrasound (DCE-US) is highly susceptible to motion artifacts arising from patient movement, respiration, and operator handling and experience. Motion artifacts can be especially problematic in the context of perfusion quantification. In conventional 2D DCE-US, motion correction (MC) algorithms take advantage of accompanying side-by-side anatomical B-Mode images that contain time-stable features. However, current commercial models of 3D DCE-US do not provide side-by-side B-Mode images, which makes MC challenging. PURPOSE: This work introduces a novel MC algorithm for 3D DCE-US and assesses its efficacy when handling clinical data sets. METHODS: In brief, the algorithm uses a pyramidal approach whereby short temporal windows consisting of three consecutive frames are created to perform local registrations, which are then registered to a master reference derived from a weighted average of all frames. We applied the algorithm to imaging studies from eight patients with metastatic lesions in the liver and assessed improvements in original versus motion corrected 3D DCE-US cine using: (i) frame-to-frame volumetric overlap of segmented lesions, (ii) normalized correlation coefficient (NCC) between frames (similarity analysis), and (iii) sum of squared errors (SSE), root-mean-squared error (RMSE), and r-squared (R2) quality-of-fit from fitted time-intensity curves (TIC) extracted from a segmented lesion. RESULTS: We noted improvements in frame-to-frame lesion overlap across all patients, from 68% ± 13% without correction to 83% ± 3% with MC (p = 0.023). Frame-to-frame similarity as assessed by NCC also improved on two different sets of time points from 0.694 ± 0.057 (original cine) to 0.862 ± 0.049 (corresponding MC cine) and 0.723 ± 0.066 to 0.886 ± 0.036 (p ≤ 0.001 for both). TIC analysis displayed a significant decrease in RMSE (p = 0.018) and a significant increase in R2 goodness-of-fit (p = 0.029) for the patient cohort. CONCLUSIONS: Overall, results suggest decreases in 3D DCE-US motion after applying the proposed algorithm.

Degron-based bioPROTACs for controlling signaling in CAR T cells.

Chimeric antigen receptor (CAR) T cells have made a tremendous impact in the clinic, but potent signaling through the CAR can be detrimental to treatment safety and efficacy. The use of protein degradation to control CAR signaling can address these issues in pre-clinical models. Existing strategies for regulating CAR stability rely on small molecules to induce systemic degradation. In contrast to small molecule regulation, genetic circuits offer a more precise method to control CAR signaling in an autonomous, cell-by-cell fashion. Here, we describe a programmable protein degradation tool that adopts the framework of bioPROTACs, heterobifunctional proteins that are composed of a target recognition domain fused to a domain that recruits the endogenous ubiquitin proteasome system. We develop novel bioPROTACs that utilize a compact four residue degron and demonstrate degradation of cytosolic and membrane protein targets using either a nanobody or synthetic leucine zipper as a protein binder. Our bioPROTACs exhibit potent degradation of CARs and can inhibit CAR signaling in primary human T cells. We demonstrate the utility of our bioPROTACs by constructing a genetic circuit to degrade the tyrosine kinase ZAP70 in response to recognition of a specific membrane-bound antigen. This circuit is able to disrupt CAR T cell signaling only in the presence of a specific cell population. These results suggest that bioPROTACs are a powerful tool for expanding the cell engineering toolbox for CAR T cells.

GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.

Hundreds of inbred mouse strains and intercross populations have been used to characterize the function of genetic variants that contribute to disease. Thousands of disease-relevant traits have been characterized in mice and made publicly available. New strains and populations including consomics, the collaborative cross, expanded BXD, and inbred wild-derived strains add to existing complex disease mouse models, mapping populations, and sensitized backgrounds for engineered mutations. The genome sequences of inbred strains, along with dense genotypes from others, enable integrated analysis of trait-variant associations across populations, but these analyses are hampered by the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense variant resource by harmonizing multiple data sets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extendable to other model organisms. The result is a web- and programmatically accessible data service called GenomeMUSter, comprising single-nucleotide variants covering 657 strains at 106.8 million segregating sites. Interoperation with phenotype databases, analytic tools, and other resources enable a wealth of applications, including multitrait, multipopulation meta-analysis. We show this in cross-species comparisons of type 2 diabetes and substance use disorder meta-analyses, leveraging mouse data to characterize the likely role of human variant effects in disease. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU: 2023.

RATIONALE: Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care hospitals have implemented systems aimed at detecting and responding to such patients. OBJECTIVES: To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients. PANEL DESIGN: The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based Clinical Practice Guidelines. METHODS: We generated actionable questions using the Population, Intervention, Control, and Outcomes (PICO) format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation Approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs). RESULTS: The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among unselected patients. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system. CONCLUSIONS: The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

Executive Summary: Society of Critical Care Medicine Guidelines on Recognizing and Responding to Clinical Deterioration Outside the ICU.

RATIONALE: Clinical deterioration of patients hospitalized outside the ICU is a source of potentially reversible morbidity and mortality. To address this, some acute care facilities have implemented systems aimed at detecting and responding to such patients. OBJECTIVES: To provide evidence-based recommendations for hospital clinicians and administrators to optimize recognition and response to clinical deterioration in non-ICU patients. PANEL DESIGN: The 25-member panel included representatives from medicine, nursing, respiratory therapy, pharmacy, patient/family partners, and clinician-methodologists with expertise in developing evidence-based clinical practice guidelines. METHODS: We generated actionable questions using the Population, Intervention, Control, and Outcomes format and performed a systematic review of the literature to identify and synthesize the best available evidence. We used the Grading of Recommendations Assessment, Development, and Evaluation approach to determine certainty in the evidence and to formulate recommendations and good practice statements (GPSs). RESULTS: The panel issued 10 statements on recognizing and responding to non-ICU patients with critical illness. Healthcare personnel and institutions should ensure that all vital sign acquisition is timely and accurate (GPS). We make no recommendation on the use of continuous vital sign monitoring among "unselected" patients due to the absence of data regarding the benefit and the potential harms of false positive alarms, the risk of alarm fatigue, and cost. We suggest focused education for bedside clinicians in signs of clinical deterioration, and we also suggest that patient/family/care partners' concerns be included in decisions to obtain additional opinions and help (both conditional recommendations). We recommend hospital-wide deployment of a rapid response team or medical emergency team (RRT/MET) with explicit activation criteria (strong recommendation). We make no recommendation about RRT/MET professional composition or inclusion of palliative care members on the responding team but suggest that the skill set of responders should include eliciting patients' goals of care (conditional recommendation). Finally, quality improvement processes should be part of a rapid response system (GPS). CONCLUSIONS: The panel provided guidance to inform clinicians and administrators on effective processes to improve the care of patients at-risk for developing critical illness outside the ICU.

De novo-designed minibinders expand the synthetic biology sensing repertoire.

Synthetic and chimeric receptors capable of recognizing and responding to user-defined antigens have enabled "smart" therapeutics based on engineered cells. These cell engineering tools depend on antigen sensors which are most often derived from antibodies. Advances in the de novo design of proteins have enabled the design of protein binders with the potential to target epitopes with unique properties and faster production timelines compared to antibodies. Building upon our previous work combining a de novo-designed minibinder of the Spike protein of SARS-CoV-2 with the synthetic receptor synNotch (SARSNotch), we investigated whether minibinders can be readily adapted to a diversity of cell engineering tools. We show that the Spike minibinder LCB1 easily generalizes to a next-generation proteolytic receptor SNIPR that performs similarly to our previously reported SARSNotch. LCB1-SNIPR successfully enables the detection of live SARS-CoV-2, an improvement over SARSNotch which can only detect cell-expressed Spike. To test the generalizability of minibinders to diverse applications, we tested LCB1 as an antigen sensor for a chimeric antigen receptor (CAR). LCB1-CAR enabled CD8+ T cells to cytotoxically target Spike-expressing cells. Our findings suggest that minibinders represent a novel class of antigen sensors that have the potential to dramatically expand the sensing repertoire of cell engineering tools.

Validation of oxygen saturations measured in the community by emergency medical services as a marker of clinical deterioration in patients with confirmed COVID-19: a retrospective cohort study.

OBJECTIVES: To evaluate oxygen saturation and vital signs measured in the community by emergency medical services (EMS) as clinical markers of COVID-19-positive patient deterioration. DESIGN: A retrospective data analysis. SETTING: Patients were conveyed by EMS to two hospitals in Hampshire, UK, between 1 March 2020 and 31 July 2020. PARTICIPANTS: A total of 1080 patients aged ≥18 years with a COVID-19 diagnosis were conveyed by EMS to the hospital. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary study outcome was admission to the intensive care unit (ICU) within 30 days of conveyance, with a secondary outcome representing mortality within 30 days of conveyance. Receiver operating characteristic (ROC) analysis was performed to evaluate, in a retrospective fashion, the efficacy of different variables in predicting patient outcomes. RESULTS: Vital signs measured by EMS staff at the first point of contact in the community correlated with patient 30-day ICU admission and mortality. Oxygen saturation was comparably predictive of 30-day ICU admission (area under ROC (AUROC) 0.753; 95% CI 0.668 to 0.826) to the National Early Warning Score 2 (AUROC 0.731; 95% CI 0.655 to 0.800), followed by temperature (AUROC 0.720; 95% CI 0.640 to 0.793) and respiration rate (AUROC 0.672; 95% CI 0.586 to 0.756). CONCLUSIONS: Initial oxygen saturation measurements (on air) for confirmed COVID-19 patients conveyed by EMS correlated with short-term patient outcomes, demonstrating an AUROC of 0.753 (95% CI 0.668 to 0.826) in predicting 30-day ICU admission. We found that the threshold of 93% oxygen saturation is prognostic of adverse events and of value for clinician decision-making with sensitivity (74.2% CI 0.642 to 0.840) and specificity (70.6% CI 0.678 to 0.734).

Targeting IDH2R140Q and other neoantigens in acute myeloid leukemia.

ABSTRACT: For patients with high-risk or relapsed/refractory acute myeloid leukemia (AML), allogeneic stem cell transplantation (allo-HSCT) and the graft-versus-leukemia effect mediated by donor T cells, offer the best chance of long-term remission. However, the concurrent transfer of alloreactive T cells can lead to graft-versus-host disease that is associated with transplant-related morbidity and mortality. Furthermore, ∼60% of patients will ultimately relapse after allo-HSCT, thus, underscoring the need for novel therapeutic strategies that are safe and effective. In this study, we explored the feasibility of immunotherapeutically targeting neoantigens, which arise from recurrent nonsynonymous mutations in AML and thus represent attractive targets because they are exclusively present on the tumor. Focusing on 14 recurrent driver mutations across 8 genes found in AML, we investigated their immunogenicity in 23 individuals with diverse HLA profiles. We demonstrate the immunogenicity of AML neoantigens, with 17 of 23 (74%) reactive donors screened mounting a response. The most immunodominant neoantigens were IDH2R140Q (n = 11 of 17 responders), IDH1R132H (n = 7 of 17), and FLT3D835Y (n = 6 of 17). In-depth studies of IDH2R140Q-specific T cells revealed the presence of reactive CD4+ and CD8+ T cells capable of recognizing distinct mutant-specific epitopes restricted to different HLA alleles. These neo-T cells could selectively recognize and kill HLA-matched AML targets endogenously expressing IDH2R140Q both in vitro and in vivo. Overall, our findings support the clinical translation of neoantigen-specific T cells to treat relapsed/refractory AML.

Nasoseptal Flap to Repair Large Maxillary Sinus Floor Defects.

This case highlights the successful use of a large nasoseptal flap to repair a large maxillary sinus floor defect. Surgeons can therefore rely on this flap for repairing maxillary sinus floor defects of most sizes and locations. Laryngoscope, 134:87-91, 2024.

Mechanical loading of joint modulates T cells in lymph nodes to regulate osteoarthritis.

OBJECTIVE: The crosstalk of joint pathology with local lymph nodes in osteoarthritis (OA) is poorly understood. We characterized the change in T cells in lymph nodes following load-induced OA and established the association of the presence and migration of T cells to the onset and progression of OA. METHODS: We used an in vivo model of OA to induce mechanical load-induced joint damage. After cyclic tibial compression of mice, we analyzed lymph nodes for T cells using flow cytometry and joint pathology using histology and microcomputed tomography. The role of T-cell migration and the presence of T-cell type was examined using T-cell receptor (TCR)α-/- mice and an immunomodulatory drug, Sphingosine-1-phosphate (S1P) receptor inhibitor-treated mice, respectively. RESULTS: We demonstrated a significant increase in T-cell populations in local lymph nodes in response to joint injury in 10, 16, and 26-week-old mice, and as a function of load duration, 1, 2, and 6 weeks. T-cell expression of inflammatory cytokine markers increased in the local lymph nodes and was associated with load-induced OA progression in the mouse knee. Joint loading in TCRα-/- mice reduced both cartilage degeneration (Osteoarthritis Research Society International (OARSI) scores: TCRα 0.568, 0.981-0.329 confidence interval (CI); wild type (WT) 1.328, 2.353-0.749 CI) and osteophyte formation. Inhibition of T-cell egress from lymph nodes attenuated load-induced cartilage degradation (OARSI scores: Fingolimod: 0.509, 1.821-0.142 CI; Saline 1.210, 1.932-0.758 CI) and decreased localization of T cells in the synovium. CONCLUSIONS: These results establish the association of lymph node-resident T cells in joint damage and suggest that the S1P receptor modulators and T-cell immunotherapies could be used to treat OA.