In the Murine and Bovine Maternal Mammary Gland Signal Transducer and Activator of Transcription 3 is Activated in Clusters of Epithelial Cells around the Day of Birth.

Signal transducers and activators of transcription (STAT) proteins regulate mammary development. Here we investigate the expression of phosphorylated STAT3 (pSTAT3) in the mouse and cow around the day of birth. We present localised colocation analysis, applicable to other mammary studies requiring identification of spatially congregated events. We demonstrate that pSTAT3-positive events are multifocally clustered in a non-random and statistically significant fashion. Arginase-1 expressing cells, consistent with macrophages, exhibit distinct clustering within the periparturient mammary gland. These findings represent a new facet of mammary STAT3 biology, and point to the presence of mammary sub-microenvironments.

Bronchogenic cyst: a rare cause of palpitations and atrial fibrillation.

Bronchogenic cysts are rare congenital lesions found primarily in the mediastinum. Most patients are asymptomatic and can be treated with minimally invasive resection. We present a case of a middle-aged patient who presented to a district general hospital with palpitations and shortness of breath. She underwent a computerised tomographic pulmonary angiogram that showed a likely bronchogenic cyst and was subsequently transferred to our hospital. She developed atrial fibrillation during admission requiring therapy with beta-blockers and digoxin. Cardiac MRI revealed a large cyst posterior to the left atrium, a moderate circumferential pericardial effusion and bilateral pleural effusions. There was significant left atrial compression. The patient underwent surgical removal of the cyst and was discharged. She returned to the hospital within a week with palpitations and was treated with intravenous antibiotics for sepsis. She was discharged a week later and remained clinically stable.

Distinct lung cell signatures define the temporal evolution of diffuse alveolar damage in fatal COVID-19.

BACKGROUND: Lung damage in severe COVID-19 is highly heterogeneous however studies with dedicated spatial distinction of discrete temporal phases of diffuse alveolar damage (DAD) and alternate lung injury patterns are lacking. Existing studies have also not accounted for progressive airspace obliteration in cellularity estimates. We used an imaging mass cytometry (IMC) analysis with an airspace correction step to more accurately identify the cellular immune response that underpins the heterogeneity of severe COVID-19 lung disease. METHODS: Lung tissue was obtained at post-mortem from severe COVID-19 deaths. Pathologist-selected regions of interest (ROIs) were chosen by light microscopy representing the patho-evolutionary spectrum of DAD and alternate disease phenotypes were selected for comparison. Architecturally normal SARS-CoV-2-positive lung tissue and tissue from SARS-CoV-2-negative donors served as controls. ROIs were stained for 40 cellular protein markers and ablated using IMC before segmented cells were classified. Cell populations corrected by ROI airspace and their spatial relationships were compared across lung injury patterns. FINDINGS: Forty patients (32M:8F, age: 22-98), 345 ROIs and >900k single cells were analysed. DAD progression was marked by airspace obliteration and significant increases in mononuclear phagocytes (MnPs), T and B lymphocytes and significant decreases in alveolar epithelial and endothelial cells. Neutrophil populations proved stable overall although several interferon-responding subsets demonstrated expansion. Spatial analysis revealed immune cell interactions occur prior to microscopically appreciable tissue injury. INTERPRETATION: The immunopathogenesis of severe DAD in COVID-19 lung disease is characterised by sustained increases in MnPs and lymphocytes with key interactions occurring even prior to lung injury is established. FUNDING: UK Research and Innovation/Medical Research Council through the UK Coronavirus Immunology Consortium, Barbour Foundation, General Sir John Monash Foundation, Newcastle University, JGW Patterson Foundation, Wellcome Trust.

Pericardial Fluid Analysis in Diagnosis and Prognosis of Patients Who Underwent Pericardiocentesis.

In this study, we aimed to examine the diagnostic yield of pericardial fluid biochemistry and cytology and their prognostic significance in patients with percutaneously drained pericardial effusions, with and without malignancy. This is a single-center, retrospective study of patients who underwent pericardiocentesis between 2010 and 2020. Data were extracted from electronic patient records, including procedural information, underlying diagnosis, and laboratory results. Patients were grouped into those with and without underlying malignancy. A Cox proportional hazards model was used to analyze the association of variables with mortality. The study included 179 patients; 50% had an underlying malignancy. There were no significant differences in pericardial fluid protein and lactate dehydrogenase between the 2 groups. Diagnostic yield from pericardial fluid analysis was greater in the malignant group (32% vs 11%, p = 0.002); 72% of newly diagnosed malignancies had positive fluid cytology. The 1-year survival was 86% and 33% in nonmalignant and malignant groups, respectively (p <0.001). Of 17 patients who died within the nonmalignant group, idiopathic effusions were the largest group (n = 6). In malignancy, lower pericardial fluid protein and higher serum C-reactive protein were associated with increased risk of mortality. In conclusion, pericardial fluid biochemistry has limited value in determining the etiology of pericardial effusions; fluid cytology is the most important diagnostic test. Mortality in malignant pericardial effusions may be associated with lower pericardial fluid protein levels and a higher serum C-reactive protein. Nonmalignant pericardial effusions do not have a benign prognosis and close follow-up is required.

Dinaciclib as an effective pan-cyclin dependent kinase inhibitor in platinum resistant ovarian cancer.

Background: Ovarian cancer (OC) is amongst the most lethal of common cancers in women. Lacking in specific symptoms in the early stages, OC is predominantly diagnosed late when the disease has undergone metastatic spread and chemotherapy is relied on to prolong life. Platinum-based therapies are preferred and although many tumors respond initially, the emergence of platinum-resistance occurs in the majority of cases after which prognosis is very poor. Upregulation of DNA damage pathways is a common feature of platinum resistance in OC with cyclin dependent kinases (CDKs) serving as key regulators of this process and suggesting that CDK inhibitors (CDKis) could be effective tools in the treatment of platinum resistant and refractory OC. Aim: The aim of this study was to evaluate the efficacy of CDKis in platinum resistant OC models and serve as a predictor of potential clinical utility. Methods: The efficacy of CDKi, dinaciclib, was determined in wildtype and platinum resistant cell line pairs representing different OC subtypes. In addition, dinaciclib was evaluated in primary cells isolated from platinum-sensitive and platinum-refractory tumors to increase the clinical relevance of the study. Results and conclusions: Dinaciclib proved highly efficacious in OC cell lines and primary cells, which were over a thousand-fold more sensitive to the CDKi than to cisplatin. Furthermore, cisplatin resistance in these cells did not influence sensitivity to dinaciclib and the two drugs combined additively in both platinum-sensitive and platinum-resistant OC cells suggesting a potential role for pan-CDKis (CDKis targeting multiple CDKs), such as dinaciclib, in the treatment of advanced and platinum-resistant OC.

Highlighting the hidden dangers of a 'weak' opioid: Deaths following use of dihydrocodeine in England (2001-2020).

BACKGROUND: Dihydrocodeine (DHC) is considered a 'weak' opioid, but there is evidence of its increasing misuse in overdose deaths. This research aims to analyse trends in DHC-related deaths in England relevant to source and dose of DHC, and decedent demographics. METHODS: Cases from England reported to the National Programme on Substance Abuse Deaths (NPSAD) where DHC was identified at post-mortem and/or implicated in death between 2001 and 2020 were extracted for analysis. RESULTS: 2071 DHC-related deaths were identified. The greatest number of deaths involved illicitly obtained DHC and a significant increase in these deaths was recorded over time (r = 0.5, p = 0.03). However, there was a concurrent decline in the implication rate of DHC in causing death (r = -0.6, p < 0.01). Fatalities were primarily due to accidental overdose (64.8%) and misuse was highly prevalent in combination with additional central nervous system depressants (95.3%), namely illicit heroin/morphine and diazepam. In contrast, when DHC was obtained over-the-counter (OTC) suicide mortality accounted for almost half of the deaths (42.5%). Differences in polysubstance use were also identified, with less heroin/morphine and benzodiazepine co-detection, but increased OTC codeine co-detection. CONCLUSIONS: DHC misuse in England is increasing. The pharmacological consideration of DHC as a 'weak' opioid may be misinterpreted by users, leading to accidental overdosing. There is an urgent need to understand increasing polypharmacy in overdose deaths. Additionally, suicides involving DHC is a potential cause for concern and a review of OTC opioid-paracetamol preparations is necessary to determine whether the benefits of these medications continue to outweigh the risks of intentional overdose.

Developing ovine mammary terminal duct lobular units have a dynamic mucosal and stromal immune microenvironment.

The human breast and ovine mammary gland undergo striking levels of postnatal development, leading to formation of terminal duct lobular units (TDLUs). Here we interrogate aspects of sheep TDLU growth as a model of breast development and to increase understanding of ovine mammogenesis. The distributions of epithelial nuclear Ki67 positivity differ significantly between younger and older lambs. Ki67 expression is polarised to the leading edge of the developing TDLUs. Intraepithelial ductal macrophages exhibit periodicity and considerably increased density in lambs approaching puberty. Stromal macrophages are more abundant centrally than peripherally. Intraepithelial T lymphocytes are more numerous in older lambs. Stromal hotspots of Ki67 expression colocalize with immune cell aggregates that exhibit distinct organisation consistent with tertiary lymphoid structures. The lamb mammary gland thus exhibits a dynamic mucosal and stromal immune microenvironment and constitutes a valuable model system that provides new insights into postnatal breast development.

Dinaciclib, a Bimodal Agent Effective against Endometrial Cancer.

Endometrial cancer (EC) is the sixth most prevalent female cancer globally and although high rates of success are achieved when diagnosed at an early stage, the 5-year survival rate for cancers diagnosed at Stages II-IV is below 50%. Improving patient outcomes will necessitate the introduction of novel therapies to the clinic. Pan-cyclin-dependent kinase inhibitors (CDKis) have been explored as therapies for a range of cancers due to their ability to simultaneously target multiple key cellular processes, such as cell cycle progression, transcription, and DNA repair. Few studies, however, have reported on their potential for the treatment of EC. Herein, we examined the effects of the pan-CDKi dinaciclib in primary cells isolated directly from tumors and EC cell lines. Dinaciclib was shown to elicit a bimodal action in EC cell lines, disrupting both cell cycle progression and phosphorylation of the RNA polymerase carboxy terminal domain, with a concomitant reduction in Bcl-2 expression. Furthermore, the therapeutic potential of combining dinaciclib and cisplatin was explored, with the drugs demonstrating synergy at specific doses in Type I and Type II EC cell lines. Together, these results highlight the potential of dinaciclib for use as an effective EC therapy.

Data Driven Cell Cycle Model to Quantify the Efficacy of Cancer Therapeutics Targeting Specific Cell-Cycle Phases From Flow Cytometry Results.

Many chemotherapeutic drugs target cell processes in specific cell cycle phases. Determining the specific phases targeted is key to understanding drug mechanism of action and efficacy against specific cancer types. Flow cytometry experiments, combined with cell cycle phase and division round specific staining, can be used to quantify the current cell cycle phase and number of mitotic events of each cell within a population. However, quantification of cell interphase times and the efficacy of cytotoxic drugs targeting specific cell cycle phases cannot be determined directly. We present a data driven computational cell population model for interpreting experimental results, where in-silico populations are initialized to match observable results from experimental populations. A two-stage approach is used to determine the efficacy of cytotoxic drugs in blocking cell-cycle phase transitions. In the first stage, our model is fitted to experimental multi-parameter flow cytometry results from untreated cell populations to identify parameters defining probability density functions for phase transitions. In the second stage, we introduce a blocking routine to the model which blocks a percentage of attempted transitions between cell-cycle phases due to therapeutic treatment. The resulting model closely matches the percentage of cells from experiment in each cell-cycle phase and division round. From untreated cell populations, interphase and intermitotic times can be inferred. We then identify the specific cell-cycle phases that cytotoxic compounds target and quantify the percentages of cell transitions that are blocked compared with the untreated population, which will lead to improved understanding of drug efficacy and mechanism of action.

Objective assessment of stored blood quality by deep learning.

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we demonstrate the use of label-free imaging flow cytometry and deep learning to characterize RBC lesions. Using brightfield images, a trained neural network achieved 76.7% agreement with experts in classifying seven clinically relevant RBC morphologies associated with storage lesions, comparable to 82.5% agreement between different experts. Given that human observation and classification may not optimally discern RBC quality, we went further and eliminated subjective human annotation in the training step by training a weakly supervised neural network using only storage duration times. The feature space extracted by this network revealed a chronological progression of morphological changes that better predicted blood quality, as measured by physiological hemolytic assay readouts, than the conventional expert-assessed morphology classification system. With further training and clinical testing across multiple sites, protocols, and instruments, deep learning and label-free imaging flow cytometry might be used to routinely and objectively assess RBC storage lesions. This would automate a complex protocol, minimize laboratory sample handling and preparation, and reduce the impact of procedural errors and discrepancies between facilities and blood donors. The chronology-based machine-learning approach may also improve upon humans' assessment of morphological changes in other biomedically important progressions, such as differentiation and metastasis.

Label-Free Leukemia Monitoring by Computer Vision.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While there are a number of well-recognized prognostic biomarkers at diagnosis, the most powerful independent prognostic factor is the response of the leukemia to induction chemotherapy (Campana and Pui: Blood 129 (2017) 1913-1918). Given the potential for machine learning to improve precision medicine, we tested its capacity to monitor disease in children undergoing ALL treatment. Diagnostic and on-treatment bone marrow samples were labeled with an ALL-discriminating antibody combination and analyzed by imaging flow cytometry. Ignoring the fluorescent markers and using only features extracted from bright-field and dark-field cell images, a deep learning model was able to identify ALL cells at an accuracy of >88%. This antibody-free, single cell method is cheap, quick, and could be adapted to a simple, laser-free cytometer to allow automated, point-of-care testing to detect slow early responders. Adaptation to other types of leukemia is feasible, which would revolutionize residual disease monitoring. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Label-Free Identification of White Blood Cells Using Machine Learning.

White blood cell (WBC) differential counting is an established clinical routine to assess patient immune system status. Fluorescent markers and a flow cytometer are required for the current state-of-the-art method for determining WBC differential counts. However, this process requires several sample preparation steps and may adversely disturb the cells. We present a novel label-free approach using an imaging flow cytometer and machine learning algorithms, where live, unstained WBCs were classified. It achieved an average F1-score of 97% and two subtypes of WBCs, B and T lymphocytes, were distinguished from each other with an average F1-score of 78%, a task previously considered impossible for unlabeled samples. We provide an open-source workflow to carry out the procedure. We validated the WBC analysis with unstained samples from 85 donors. The presented method enables robust and highly accurate identification of WBCs, minimizing the disturbance to the cells and leaving marker channels free to answer other biological questions. It also opens the door to employing machine learning for liquid biopsy, here, using the rich information in cell morphology for a wide range of diagnostics of primary blood. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Trauma Hemostasis and Oxygenation Research Network position paper on the role of hypotensive resuscitation as part of remote damage control resuscitation.

The Trauma Hemostasis and Oxygenation Research (THOR) Network has developed a consensus statement on the role of permissive hypotension in remote damage control resuscitation (RDCR). A summary of the evidence on permissive hypotension follows the THOR Network position on the topic. In RDCR, the burden of time in the care of the patients suffering from noncompressible hemorrhage affects outcomes. Despite the lack of published evidence, and based on clinical experience and expertise, it is the THOR Network's opinion that the increase in prehospital time leads to an increased burden of shock, which poses a greater risk to the patient than the risk of rebleeding due to slightly increased blood pressure, especially when blood products are available as part of prehospital resuscitation.The THOR Network's consensus statement is, "In a casualty with life-threatening hemorrhage, shock should be reversed as soon as possible using a blood-based HR fluid. Whole blood is preferred to blood components. As a part of this HR, the initial systolic blood pressure target should be 100 mm Hg. In RDCR, it is vital for higher echelon care providers to receive a casualty with sufficient physiologic reserve to survive definitive surgical hemostasis and aggressive resuscitation. The combined use of blood-based resuscitation and limiting systolic blood pressure is believed to be effective in promoting hemostasis and reversing shock".

Diagnostic Potential of Imaging Flow Cytometry.

Imaging flow cytometry (IFC) captures multichannel images of hundreds of thousands of single cells within minutes. IFC is seeing a paradigm shift from low- to high-information-content analysis, driven partly by deep learning algorithms. We predict a wealth of applications with potential translation into clinical practice.

REBOA at Role 2 Afloat: resuscitative endovascular balloon occlusion of the aorta as a bridge to damage control surgery in the military maritime setting.

Role 2 Afloat provides a damage control resuscitation and surgery facility in support of maritime, littoral and aviation operations. Resuscitative endovascular balloon occlusion of the aorta (REBOA) offers a rapid, effective solution to exsanguinating haemorrhage from pelvic and non-compressible torso haemorrhage. It should be considered when the patient presents in a peri-arrest state, if surgery is likely to be delayed, or where the single operating table is occupied by another case. This paper will outline the data in support of endovascular haemorrhage control, describe the technique and explore how REBOA could be delivered using equipment currently available in the Royal Navy Role 2 Afloat equipment module. Also discussed are potential future directions in endovascular resuscitation.

Safety and efficacy of ozanezumab in patients with amyotrophic lateral sclerosis: a randomised, double-blind, placebo-controlled, phase 2 trial.

BACKGROUND: Neurite outgrowth inhibitor A (Nogo-A) is thought to have a role in the pathophysiology of amyotrophic lateral sclerosis (ALS). A monoclonal antibody against Nogo-A showed a positive effect in the SOD1G93A mouse model of ALS, and a humanised form of this antibody (ozanezumab) was well tolerated in a first-in-human trial. Therefore, we aimed to assess the safety and efficacy of ozanezumab in patients with ALS. METHODS: This randomised, double-blind, placebo-controlled, phase 2 trial was done in 34 centres in 11 countries. Patients aged 18-80 years with a diagnosis of familial or sporadic ALS were randomly assigned (1:1), centrally according to a computer-generated allocation schedule, to receive ozanezumab (15 mg/kg) or placebo as intravenous infusions over 1 h every 2 weeks for 46 weeks, followed by assessments at week 48 and week 60. Patients and study personnel were masked to treatment assignment. The primary outcome was a joint-rank analysis of function (ALS Functional Rating Scale-Revised) and overall survival, analysed at 48 weeks in all patients who received at least one dose of study drug. This study is registered with ClinicalTrials.gov, number NCT01753076, and with GSK-ClinicalStudyRegister.com, NOG112264, and is completed. FINDINGS: Between Dec 20, 2012, and Nov 1, 2013, we recruited 307 patients, of whom 303 were randomly assigned to receive placebo (n=151) or ozanezumab (n=152). The adjusted mean of the joint-rank score was -14·9 (SE 13·5) for the ozanezumab group and 15·0 (13·6) for the placebo group, with a least squares mean difference of -30·0 (95% CI -67·9 to 7·9; p=0·12). Overall, reported adverse events, serious adverse events, and adverse events leading to permanent discontinuation of study drug or withdrawal from study were similar between the treatment groups, except for dyspepsia (ten [7%] in the ozanezumab group vs four [3%] in the placebo group), depression (11 [7%] vs five [3%]), and diarrhoea (25 [16%] vs 12 [8%]). Respiratory failure was the most common serious adverse event (12 [8%] vs seven [5%]). At week 60, the number of deaths was higher in the ozanezumab group (20 [13%]) than in the placebo group (16 [11%]), mainly as a result of respiratory failure (ten [7%] vs five [3%]). Two deaths were considered related to the study drug (bladder transitional cell carcinoma in the ozanezumab group and cerebrovascular accident in the placebo group). INTERPRETATION: Ozanezumab did not show efficacy compared with placebo in patients with ALS. Therefore, Nogo-A does not seem to be an effective therapeutic target in ALS. FUNDING: GlaxoSmithKline.

Generation of an in vitro 3D PDAC stroma rich spheroid model.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a prominent desmoplastic/stromal reaction, which contributes to the poor clinical outcome of this disease. Therefore, greater understanding of the stroma development and tumor-stroma interactions is highly required. Pancreatic stellate cells (PSC) are myofibroblast-like cells located in exocrine areas of the pancreas, which as a result of inflammation produced by PDAC migrate and accumulate in the tumor mass, secreting extracellular matrix components and producing the dense PDAC stroma. Currently, only a few orthotopic or ectopic animal tumor models, where PDAC cells are injected into the pancreas or subcutaneous tissue layer, or genetically engineered animals offer tumors that encompass some stromal component. Herein, we report generation of a simple 3D PDAC in vitro micro-tumor model without an addition of external extracellular matrix, which encompasses a rich, dense and active stromal compartment. We have achieved this in vitro model by incorporating PSCs into 3D PDAC cell culture using a modified hanging drop method. It is now known that PSCs are the principal source of fibrosis in the stroma and interact closely with cancer cells to create a tumor facilitatory environment that stimulates local and distant tumor growth. The 3D micro-stroma models are highly reproducible with excellent uniformity, which can be used for PDAC-stroma interaction analysis and high throughput automated drug-screening assays. Additionally, the increased expression of collagenous regions means that molecular based perfusion and cytostaticity of gemcitabine is decreased in our Pancreatic adenocarcinoma stroma spheroids (PDAC-SS) model when compared to spheroids grown without PSCs. We believe this model will allow an improved knowledge of PDAC biology and has the potential to provide an insight into pathways that may be therapeutically targeted to inhibit PSC activation, thereby inhibiting the development of fibrosis in PDAC and interrupting PSC-PDAC cell interactions so as to inhibit cancer progression.

A New Imaging Platform for Visualizing Biological Effects of Non-Invasive Radiofrequency Electric-Field Cancer Hyperthermia.

Herein, we present a novel imaging platform to study the biological effects of non-invasive radiofrequency (RF) electric field cancer hyperthermia. This system allows for real-time in vivo intravital microscopy (IVM) imaging of radiofrequency-induced biological alterations such as changes in vessel structure and drug perfusion. Our results indicate that the IVM system is able to handle exposure to high-power electric-fields without inducing significant hardware damage or imaging artifacts. Furthermore, short durations of low-power (< 200 W) radiofrequency exposure increased transport and perfusion of fluorescent tracers into the tumors at temperatures below 41°C. Vessel deformations and blood coagulation were seen for tumor temperatures around 44°C. These results highlight the use of our integrated IVM-RF imaging platform as a powerful new tool to visualize the dynamics and interplay between radiofrequency energy and biological tissues, organs, and tumors.

Radiofrequency treatment alters cancer cell phenotype.

The importance of evaluating physical cues in cancer research is gradually being realized. Assessment of cancer cell physical appearance, or phenotype, may provide information on changes in cellular behavior, including migratory or communicative changes. These characteristics are intrinsically different between malignant and non-malignant cells and change in response to therapy or in the progression of the disease. Here, we report that pancreatic cancer cell phenotype was altered in response to a physical method for cancer therapy, a non-invasive radiofrequency (RF) treatment, which is currently being developed for human trials. We provide a battery of tests to explore these phenotype characteristics. Our data show that cell topography, morphology, motility, adhesion and division change as a result of the treatment. These may have consequences for tissue architecture, for diffusion of anti-cancer therapeutics and cancer cell susceptibility within the tumor. Clear phenotypical differences were observed between cancerous and normal cells in both their untreated states and in their response to RF therapy. We also report, for the first time, a transfer of microsized particles through tunneling nanotubes, which were produced by cancer cells in response to RF therapy. Additionally, we provide evidence that various sub-populations of cancer cells heterogeneously respond to RF treatment.