Deep learning-based characterization of neutrophil activation phenotypes in ex vivo human Candida blood infections.

Early identification of human pathogens is crucial for the effective treatment of bloodstream infections to prevent sepsis. Since pathogens that are present in small numbers are usually difficult to detect directly, we hypothesize that the behavior of the immune cells that are present in large numbers may provide indirect evidence about the causative pathogen of the infection. We previously applied time-lapse microscopy to observe that neutrophils isolated from human whole-blood samples, which had been infected with the human-pathogenic fungus Candida albicans or C. glabrata, indeed exhibited a characteristic morphodynamic behavior. Tracking the neutrophil movement and shape dynamics over time, combined with machine learning approach, the accuracy for the differentiation between the two Candida species was about 75%. In this study, the focus is on improving the classification accuracy of the Candida species using advanced deep learning methods. We implemented (i) gated recurrent unit (GRU) networks and transformer-based networks for video data, and (ii) convolutional neural networks (CNNs) for individual frames of the time-lapse microscopy data. While the GRU and transformer-based approaches yielded promising results with 96% and 100% accuracy, respectively, the classification based on videos proved to be very time-consuming and required several hours. In contrast, the CNN model for individual microscopy frames yielded results within minutes, and, utilizing a majority-vote technique, achieved 100% accuracy both in identifying the pathogen-free blood samples and in distinguishing between the Candida species. The applied CNN demonstrates the potential for automatically differentiating bloodstream Candida infections with high accuracy and efficiency. We further analysed the results of the CNN using explainable artificial intelligence (XAI) techniques to understand the critical features and patterns, thereby shedding light on potential key morphodynamic characteristics of neutrophils in response to different Candida species. This approach could provide new insights into host-pathogen interactions and may facilitate the development of rapid, automated diagnostic tools for differentiating fungal species in blood samples.

Disparities in surgical health service delivery and outcomes for indigenous children.

BACKGROUND: Evidence of health disparities for Indigenous children requiring surgical care is lacking. We present a systematic review of the literature examining possible disparities in surgical care and outcomes for pediatric patients of Indigenous ethnicity. DATA SOURCES: PubMed, Cochrane, MEDLINE, gray literature. METHODS: Literature review, using PubMed, Cochrane, MEDLINE, and gray literature was conducted to identify articles published more than 2010-2020 examining children's surgical health service delivery (epidemiology, access, operations provided) and outcomes for pediatric patients of Indigenous ethnicity compared with others. Extracted data included study design, setting, participant race/ethnicity, operations examined, and surgical outcomes. Article quality was assessed using the Newcastle-Ottawa Scales. RESULTS: From 411 abstracts, 125 articles were reviewed and 33 included for data abstraction. These were cohort and cross-sectional studies investigating a wide range of patient populations and procedures across the United States, Canada, Australia, and New Zealand. Articles were organized naturally by theme into birth malformations (15 articles), trauma (6 articles), pediatric general surgery/appendicitis (5 articles), pediatric otolaryngology (6 articles), and renal transplant (1 article) surgery. Four articles also described access and resource utilization related to inpatient care. Notable disparities observed included apparent increased prevalence of gastroschisis, rates of traumatic fatality, non accidental injury, and self harm among North American Indigenous children. CONCLUSIONS: Indigenous children appear to be vulnerable to a number of health and treatment outcome disparities related to conditions treated by surgeons. Surgeons are thus uniquely poised to act in identifying and eliminating Indigenous ethnicity-based pediatric health disparities.

Automated characterisation of neutrophil activation phenotypes in ex vivo human Candida blood infections.

Rapid identification of pathogens is required for early diagnosis and treatment of life-threatening bloodstream infections in humans. This requirement is driving the current developments of molecular diagnostic tools identifying pathogens from human whole blood after successful isolation and cultivation. An alternative approach is to determine pathogen-specific signatures from human host immune cells that have been exposed to pathogens. We hypothesise that activated immune cells, such as neutrophils, may exhibit a characteristic behaviour - for instance in terms of their speed, dynamic cell morphology - that allows (i) identifying the type of pathogen indirectly and (ii) providing information on therapeutic efficacy. In this feasibility study, we propose a method for the quantitative assessment of static and morphodynamic features of neutrophils based on label-free time-lapse imaging data. We investigate neutrophil activation phenotypes after confrontation with fungal pathogens and isolation from a human whole-blood assay. In particular, we applied a machine learning supported approach to time-lapse microscopy data from different infection scenarios and were able to distinguish between Candida albicans and C. glabrata infection scenarios with test accuracies well above 75%, and to identify pathogen-free samples with accuracy reaching 100%. These results significantly exceed the test accuracies achieved using state-of-the-art deep neural networks to classify neutrophils by their morphodynamics.

Perinatal Outcomes of Twin Gestations with and without Gestational Diabetes Mellitus.

OBJECTIVE: Existing data suggest that obstetric outcomes for individuals with twin gestations, who have gestational diabetes mellitus (GDM), may be comparable to those who do not have GDM, yet studies are limited by small sample sizes. The aim of this study was to examine differences in maternal and neonatal outcomes of individuals with twin gestations based on presence of GDM. METHODS: This was a population-based retrospective cohort study of individuals giving birth to twins in the United States between 2012 and 2014. Inclusion criteria were live births (≥24 weeks) and available information on GDM status; individuals with pregestational diabetes were excluded. Participants were categorized as either having had or not had GDM. Multivariable logistic regression was utilized to assess the independent association of GDM with adverse maternal outcomes, whereas generalized estimating equation models were used to estimate associations with neonatal outcomes to account for clustering. RESULTS: Of 173,196 individuals meeting inclusion criteria, 13,194 (7.6%) had GDM. Individuals with GDM were more likely to be older, identify as Hispanic or Asian race and ethnicity, married, college educated, privately insured, and obese than those without GDM. After adjusting for potential confounding variables, those with GDM were more likely to have hypertensive disorders (18.0 vs. 10.2%) and undergo cesarean delivery (51.2 vs. 47.3%). Neonates born to individuals with GDM were more likely to require mechanical ventilation for greater than 6 hours (6.5 vs. 5.6%) and experience neonatal intensive care unit (NICU) admission (41.1 vs. 36.2%), but were less likely to be low birth weight or have small for gestational age status (16.2 vs. 19.5%). Findings were confirmed in a sensitivity analysis of neonates born at 32 weeks of gestation or greater. CONCLUSION: Odds of poor obstetric and neonatal outcomes are increased for individuals with twin gestations complicated by GDM. KEY POINTS: · Individuals with GDM and twin gestation have higher odds of developing hypertensive disorders during pregnancy and of undergoing cesarean delivery.. · Neonates of such pregnancies are less likely to be low birth weight or small for gestational age.. · Neonates of pregnancies complicated by GDM and twin gestation are more likely to require mechanical ventilation and experience NICU admission..

A Retrospective Cohort Study of Optimal Contrast for Successful Intussusception Reduction: Institutional Practices Matter.

BACKGROUND: The first-line treatment for intussusception is radiologic reduction with either air-contrast enema (AE) or liquid-contrast enema (LE). The purpose of this study was to explore relationships between self-reported institutional AE or LE intussusception reduction preferences and rates of operative intervention and bowel resection. METHODS: Pediatric Health Information System (PHIS) hospitals were contacted to assess institutional enema practices for intussusception. A retrospective study using 2009-2018 PHIS data was conducted for patients aged 0-5 y to evaluate outcomes. Chi-squared tests were used to test for differences in the distribution of surgical patients by hospital management approach. RESULTS: Of the 45 hospitals, 20 (44%) exclusively used AE, 4 (9%) exclusively used LE, and 21 (46%) used a mixed practice. Of 24,688 patients identified from PHIS, 13,231 (54%) were at exclusive AE/LE hospitals and 11,457 (46%) were at mixed practice hospitals. Patients at AE/LE hospitals underwent operative procedures at lower rates than at mixed practice hospitals (14.8% versus 16.5%, P< 0.001) and were more likely to undergo bowel resection (31.1% versus 27.1%, P= 0.02). CONCLUSIONS: Practice variation exists in hospital-level approaches to radiologic reduction of intussusception and mixed practices may impact outcomes.

Elevated testosterone on immunoassay in a patient with metastatic prostate cancer following androgen deprivation therapy and bilateral orchiectomy.

We present the case of an 83-year-old man with metastatic prostate cancer who had testosterone levels reading above castration range despite appropriate medical and surgical castration. Mass spectrometry was performed to confirm presence of testosterone, but no testosterone was detected. The elevated testosterone as measured by standard immunoassay was postulated to be secondary to heterophile antibodies in the patient's serum. This report highlights the need for a high index of suspicion for interference in testosterone immunoassays when levels remain mildly elevated. Mass spectrometry may provide a more reliable method by which to detect testosterone concentration prior to escalation of care.

Identification of Images of COVID-19 from Chest X-rays Using Deep Learning: Comparing COGNEX VisionPro Deep Learning 1.0™ Software with Open Source Convolutional Neural Networks.

The novel Coronavirus, COVID-19, pandemic is being considered the most crucial health calamity of the century. Many organizations have come together during this crisis and created various Deep Learning models for the effective diagnosis of COVID-19 from chest radiography images. For example, The University of Waterloo, along with Darwin AI-a start-up spin-off of this department, has designed the Deep Learning model 'COVID-Net' and created a dataset called 'COVIDx' consisting of 13,975 images across 13,870 patient cases. In this study, COGNEX's Deep Learning Software, VisionPro Deep Learning™,  is used to classify these Chest X-rays from the COVIDx dataset. The results are compared with the results of COVID-Net and various other state-of-the-art Deep Learning models from the open-source community. Deep Learning tools are often referred to as black boxes because humans cannot interpret how or why a model is classifying an image into a particular class. This problem is addressed by testing VisionPro Deep Learning with two settings, first, by selecting the entire image as the Region of Interest (ROI), and second, by segmenting the lungs in the first step, and then doing the classification step on the segmented lungs only, instead of using the entire image. VisionPro Deep Learning results: on the entire image as the ROI it achieves an overall F score of 94.0%, and on the segmented lungs, it gets an F score of 95.3%, which is better than COVID-Net and other state-of-the-art open-source Deep Learning models.

To wrap or not to wrap: A retrospective review of circumcision dressing and post-procedural bleeding.

INTRODUCTION: Bleeding is an infrequent, but important, complication after circumcision. Our aim was to examine postoperative bleeding events after circumcision comparing patients managed with a circumferential wrap to ointment alone. METHODS: Boys ≤18 years of age who underwent circumcision at a tertiary children's hospital were retrospectively reviewed between 2017 and 2018. Postoperative bleeding was defined by phone calls, clinic or Emergency Department visits, or return to the operating room. Outcomes were examined by univariate association and multivariable modeling. RESULTS: Of 681 boys undergoing circumcision, 503 (74%) patients received a wrap dressing and 178 (26%) only ointment. There were 28 (4%) patients who had a postoperative bleeding event: 14/503 (2.7%) among wrap dressings and 14/178 (7.8%) among ointment alone (p < 0.01). The majority of events were phone calls related to bleeding (75%). Univariate analysis demonstrated no association between postoperative bleeding and surgeon specialty (p = 0.72), age at circumcision (p = 0.44) or technique type (p = 0.09). After controlling for age, technique type, and surgeon specialty, dressing type remained significantly associated with postoperative bleeding (OR = 2.81, p < 0.01). CONCLUSION: This single-center, retrospective review found circumferential wrap dressings are associated with a decrease in bleeding events after circumcision. LEVEL OF EVIDENCE: III - retrospective case-control study.

Tau Pathology Drives Dementia Risk-Associated Gene Networks toward Chronic Inflammatory States and Immunosuppression.

To understand how neural-immune-associated genes and pathways contribute to neurodegenerative disease pathophysiology, we performed a systematic functional genomic analysis in purified microglia and bulk tissue from mouse and human AD, FTD, and PSP. We uncover a complex temporal trajectory of microglial-immune pathways involving the type 1 interferon response associated with tau pathology in the early stages, followed by later signatures of partial immune suppression and, subsequently, the type 2 interferon response. We find that genetic risk for dementias shows disease-specific patterns of pathway enrichment. We identify drivers of two gene co-expression modules conserved from mouse to human, representing competing arms of microglial-immune activation (NAct) and suppression (NSupp) in neurodegeneration. We validate our findings by using chemogenetics, experimental perturbation data, and single-cell sequencing in post-mortem brains. Our results refine the understanding of stage- and disease-specific microglial responses, implicate microglial viral defense pathways in dementia pathophysiology, and highlight therapeutic windows.

Identification of evolutionarily conserved gene networks mediating neurodegenerative dementia.

Identifying the mechanisms through which genetic risk causes dementia is an imperative for new therapeutic development. Here, we apply a multistage, systems biology approach to elucidate the disease mechanisms in frontotemporal dementia. We identify two gene coexpression modules that are preserved in mice harboring mutations in MAPT, GRN and other dementia mutations on diverse genetic backgrounds. We bridge the species divide via integration with proteomic and transcriptomic data from the human brain to identify evolutionarily conserved, disease-relevant networks. We find that overexpression of miR-203, a hub of a putative regulatory microRNA (miRNA) module, recapitulates mRNA coexpression patterns associated with disease state and induces neuronal cell death, establishing this miRNA as a regulator of neurodegeneration. Using a database of drug-mediated gene expression changes, we identify small molecules that can normalize the disease-associated modules and validate this experimentally. Our results highlight the utility of an integrative, cross-species network approach to drug discovery.