Comparison of Ultrasound Parameters and Clinical Parameters in Airway Assessment for Prediction of Difficult Laryngoscopy and Intubation: An Observational Study.

Background and objective The primary responsibility of the anesthesiologist is to provide adequate oxygenation and ventilation to the patient by securing the airway. Prediction of Cormack-Lehane (CL) grading preoperatively helps patients' airway management during anesthesia induction, particularly in difficult intubations. Our study aims to evaluate airway assessment modalities using ultrasound and conventional clinical screening methods for predicting difficult laryngoscopy and intubation. Materials and methods This prospective observational study was conducted on 100 patients aged between 18 and 70 years belonging to ASA classes I, II, and III scheduled for elective surgery requiring general anesthesia under endotracheal intubation was included in the study. Patients who needed rapid sequence induction and had a history of difficult intubation, obese patients with a body mass index (BMI) of more than 40, patients with notable swelling in the neck region (thyroid), pregnant patients, and patients with maxillofacial anomalies were excluded from the study. Clinical parameters such as body mass index, neck circumference, modified Mallampati grading, thyromental distance, and ultrasound parameters such as anterior neck soft tissue thickness at the level of the thyrohyoid membrane (ANS-TM) and anterior neck soft tissue thickness at the level of vocal cord (ANS-VC) were obtained preoperatively. After intubation, the CL grading was noted and categorized into two groups: easy (classes 1 and 2) and difficult (classes 3 and 4). Descriptive statistics included frequency and percentage for categorical variables and mean±standard deviation for continuous variables. The chi-square test was applied to find the relationship between easy and difficult laryngoscopy when compared with the outcome for categorical variables. A P value of less than 0.05 was considered significant throughout the study. The receiver operating characteristics curve (ROC curve) was used to determine the sensitivity and specificity to predict the outcomes. Results Ultrasound-guided measurements of ANS-TM and ANS-VC are independent predictors of difficult laryngoscopy compared with clinical screening tests. Of the two parameters, we found that ANS-TM has a better diagnostic value for predicting a difficult airway with an area under the ROC curve (AUC) of 91% compared with ANS-VC, which has an AUC of 84%. Of the clinical parameters, the modified Mallampati grading has an AUC of 81%, leading to better diagnostic value in the prediction of a difficult airway. Conclusion Our study demonstrated that ANS-TM and ANS-VC are independent predictors of a difficult airway. ANS-TM has a better correlation with CL grading. Clinical screening tests should be combined with ultrasound measurements to aid in the better prediction of difficult laryngoscopy.

Prostanoid receptors in hyperfiltration-mediated glomerular injury: Novel agonists and antagonists reveal opposing roles for EP2 and EP4 receptors.

Increased fluid-flow shear stress (FFSS) contributes to hyperfiltration-induced podocyte and glomerular injury resulting in progression of chronic kidney disease (CKD). We reported that increased FFSS in vitro and in vivo upregulates PGE2 receptor EP2 (but not EP4 expression), COX2-PGE2 -EP2 axis, and EP2-linked Akt-GSK3ß-ß-catenin signaling pathway in podocytes. To understand and use the disparities between PGE2 receptors, specific agonists, and antagonists of EP2 and EP4 were used to assess phosphorylation of Akt, GSK3ß and ß-catenin in podocytes using Western blotting, glomerular filtration barrier function using in vitro albumin permeability (Palb ) assay, and mitigation of hyperfiltration-induced injury in unilaterally nephrectomized (UNX) mice at 1 and 6 months. Results show an increase in Palb by PGE2 , EP2 agonist (EP2AGO ) and EP4 antagonist (EP4ANT ), but not by EP2 antagonist (EP2ANT ) or EP4 agonist (EP4AGO ). Pretreatment with EP2ANT blocked the effect of PGE2 or EP2AGO on Palb . Modulation of EP2 and EP4 also induced opposite effects on phosphorylation of Akt and ß-Catenin. Individual agonists or antagonists of EP2 or EP4 did not induce significant improvement in albuminuria in UNX mice. However, treatment with a combination EP2ANT + EP4AGO for 1 or 6 months caused a robust decrease in albuminuria. EP2ANT + EP4AGO combination did not impact adaptive hypertrophy or increased serum creatinine. Observed differences between expression of EP2 and EP4 on the glomerular barrier highlight these receptors as potential targets for intervention. Safe and effective mitigating effect of EP2ANT + EP4AGO presents a novel opportunity to delay the progression of hyperfiltration-associated CKD as seen in transplant donors.

Transcription Factor ß-Catenin Plays a Key Role in Fluid Flow Shear Stress-Mediated Glomerular Injury in Solitary Kidney.

Increased fluid flow shear stress (FFSS) in solitary kidney alters podocyte function in vivo. FFSS-treated cultured podocytes show upregulated AKT-GSK3ß-ß-catenin signaling. The present study was undertaken to confirm (i) the activation of ß-catenin signaling in podocytes in vivo using unilaterally nephrectomized (UNX) TOPGAL mice with the ß-galactosidase reporter gene for ß-catenin activation, (ii) ß-catenin translocation in FFSS-treated mouse podocytes, and (iii) ß-catenin signaling using publicly available data from UNX mice. The UNX of TOPGAL mice resulted in glomerular hypertrophy and increased the mesangial matrix consistent with hemodynamic adaptation. Uninephrectomized TOPGAL mice showed an increased ß-galactosidase expression at 4 weeks but not at 12 weeks, as assessed using immunofluorescence microscopy (p < 0.001 at 4 weeks; p = 0.16 at 12 weeks) and X-gal staining (p = 0.008 at 4 weeks; p = 0.65 at 12 weeks). Immunofluorescence microscopy showed a significant increase in phospho-ß-catenin (Ser552, p = 0.005) at 4 weeks but not at 12 weeks (p = 0.935) following UNX, and the levels of phospho-ß-catenin (Ser675) did not change. In vitro FFSS caused a sustained increase in the nuclear translocation of phospho-ß-catenin (Ser552) but not phospho-ß-catenin (Ser675) in podocytes. The bioinformatic analysis of the GEO dataset, #GSE53996, also identified ß-catenin as a key upstream regulator. We conclude that transcription factor ß-catenin mediates FFSS-induced podocyte (glomerular) injury in solitary kidney.

A mouse model of prenatal exposure to Interleukin-6 to study the developmental origin of health and disease.

Systemic inflammation in pregnant obese women is associated with 1.5- to 2-fold increase in serum Interleukin-6 (IL-6) and newborns with lower kidney/body weight ratio but the role of IL-6 in increased susceptibility to chronic kidney (CKD) in adult progeny is not known. Since IL-6 crosses the placental barrier, we administered recombinant IL-6 (10 pg/g) to pregnant mice starting at mid-gestation yielded newborns with lower body (p < 0.001) and kidney (p < 0.001) weights. Histomorphometry indicated decreased nephrogenic zone width (p = 0.039) with increased numbers of mature glomeruli (p = 0.002) and pre-tubular aggregates (p = 0.041). Accelerated maturation in IL-6 newborns was suggested by early expression of podocyte-specific protein podocin in glomeruli, increased 5-methyl-cytosine (LC-MS analysis for CpG DNA methylation) and altered expression of certain genes of cell-cycle and apoptosis (RT-qPCR array-analysis). Western blotting showed upregulated pJAK2/pSTAT3. Thus, treating dams with IL-6 as a surrogate provides newborns to study effects of maternal systemic inflammation on future susceptibility to CKD in adulthood.

MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge.

Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public.

Unmasking the immune microecology of ductal carcinoma in situ with deep learning.

Despite increasing evidence supporting the clinical relevance of tumour infiltrating lymphocytes (TILs) in invasive breast cancer, TIL spatial variability within ductal carcinoma in situ (DCIS) samples and its association with progression are not well understood. To characterise tissue spatial architecture and the microenvironment of DCIS, we designed and validated a new deep learning pipeline, UNMaSk. Following automated detection of individual DCIS ducts using a new method IM-Net, we applied spatial tessellation to create virtual boundaries for each duct. To study local TIL infiltration for each duct, DRDIN was developed for mapping the distribution of TILs. In a dataset comprising grade 2-3 pure DCIS and DCIS adjacent to invasive cancer (adjacent DCIS), we found that pure DCIS cases had more TILs compared to adjacent DCIS. However, the colocalisation of TILs with DCIS ducts was significantly lower in pure DCIS compared to adjacent DCIS, which may suggest a more inflamed tissue ecology local to DCIS ducts in adjacent DCIS cases. Our study demonstrates that technological developments in deep convolutional neural networks and digital pathology can enable an automated morphological and microenvironmental analysis of DCIS, providing a new way to study differential immune ecology for individual ducts and identify new markers of progression.

Proliferation Tumour Marker Network (PTM-NET) for the identification of tumour region in Ki67 stained breast cancer whole slide images.

Uncontrolled proliferation is a hallmark of cancer and can be assessed by labelling breast tissue using immunohistochemistry for Ki67, a protein associated with cell proliferation. Accurate measurement of Ki67-positive tumour nuclei is of critical importance, but requires annotation of the tumour regions by a pathologist. This manual annotation process is highly subjective, time-consuming and subject to inter- and intra-annotator experience. To address this challenge, we have developed Proliferation Tumour Marker Network (PTM-NET), a deep learning model that objectively annotates the tumour regions in Ki67-labelled breast cancer digital pathology images using a convolution neural network. Our custom designed deep learning model was trained on 45 immunohistochemical Ki67-labelled whole slide images to classify tumour and non-tumour regions and was validated on 45 whole slide images from two different sources that were stained using different protocols. Our results show a Dice coefficient of 0.74, positive predictive value of 70% and negative predictive value of 88.3% against the manual ground truth annotation for the combined dataset. There were minimal differences between the images from different sources and the model was further tested in oestrogen receptor and progesterone receptor-labelled images. Finally, using an extension of the model, we could identify possible hotspot regions of high proliferation within the tumour. In the future, this approach could be useful in identifying tumour regions in biopsy samples and tissue microarray images.

Ameloblastic fibrodentinoma presenting as a false gingival enlargement in the maxillary anterior region.

Ameloblastic fibrodentinoma is a rare benign mixed odontogenic neoplasm usually occurring in the first two decades of life. It is more common in males and the most common site of occurrence is in the mandibular premolar molar area. This report presents a case of ameloblastic fibrodentinoma in a 12-year-old boy in the maxillary anterior region, a less common site for the occurrence of ameloblastic fibrodentinoma. A 12-year-old boy presented with a midline diastema in 11 and 21 region and a swelling in the palatal aspect of 11 and 12. Intraoral periapical radiograph showed the presence of rarefaction of bone on the mesial aspect of the cervical and middle third of the root of 11. Excision biopsy was done. The specimen was processed and stained with hematoxylin and eosin. Microscopic examination showed islands, chords and strands of odontogenic epithelium in a primitive ectomesenchyme resembling dental papilla. The odontogenic epithelium exhibited peripheral ameloblast-like and central stellate reticulum-like cells. The presence of dentinoid material was seen adjacent to the odontogenic epithelium in some foci. The lesion was diagnosed as ameloblastic fibrodentinoma.

Primary non-Hodgkin's lymphoma of the mandible.

Primary non-Hodgkins's lymphoma is a very uncommon lesion, accounting for 0.6% in jaws. As the lesions frequently resemble other disease such as chronic osteomyelitis, odontogenic or any secondary neoplasms, further evaluation and histopathologic examination allow early identification for appropriate treatment. The purpose of this case report is to describe a rare case of non-Hodgkin's lymphoma of the mandible, explore the diagnosis and workup based on immunohistochemistry.