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Background: Proteinuria is a major indicator of hypertensive disorder of pregnancy. The gold standard for diagnosis of significant proteinuria is based on a 24hour urine collection which is cumbersome, time-consuming, and inconvenient to patients. A need, therefore, exists for a rapid, valid, and accurate test to identify significant urinary proteinuria. Methods: We conducted an observational cross-sectional hospital-based study wherein a total of 150 pregnant women who met the criteria of preeclampsia were taken. Spot urine samples for calculating the urine P/C ratio were taken immediately before 24hr urine collection. Correlation between 24hour urine protein and spot PCR was then determined by Pearson’s correlation coefficient(r). Results: The correlation coefficient (r) between 24hr urine protein and spot PCR was found to be 0.734 (n=150) which was highly significant with p

The COX/prostaglandin (COX/PG) pathway plays a role in cancer pathogenesis via the production of prostaglandin E2 (PGE2). In breast cancer, the expression patterns of the COX/PG pathway enzymes involved in PGE2 synthesis are not well defined.Using the Cancer Genome Atlas data, we analyzed the expression patterns of cyclooxygenases, COX1 (PTGS1) and COX2 (PTGS2), and four downstream enzymes of the COX/prostaglandin pathway - PTGS3 (PTGDS), PTGES1, PTGES2 and PTGES3 - in invasive breast cancer. The Clinical Proteomic Tumor Analysis Consortium database was used to determine the expression of these six genes at the protein level. Existing single-cell RNA sequencing data were used to evaluate the expression of the six COX/PG genes in luminal and basal epithelial cells from normal breast tissues. Cox regression Kaplan-Meier adjusted survival analyses were performed to evaluate the association of COX/PG pathway genes in overall survival using the TCGA data. Finally, we utilized the Tumor Immune Estimation Resource to correlate the expression of these six COX/PG genes with tumor infiltrating immune cell number.COX1, COX2 and PTGES3 were significantly upregulated at the protein level in breast cancer compared to normal tissues (P0.005). However, only PTGES3 expression was elevated at both the mRNA and protein level in breast cancer (P0.0005). PTGES3 is the most highly expressed enzymes within the COX/PG pathway in both luminal and basal epithelial cells in normal breast tissues. Using Cox Regression Kaplan-Meier survival analysis, PTGES3 expression had a significant inverse prognostic association with breast cancer survival [HR1.43, P = 0.0057]. Elevated PTGES3 expression within the tumor microenvironment significantly correlated with CD8+ T cell abundance, suggesting a possible immunomodulatory role of PTGES3 in the tumor microenvironment.PTGES3, a terminal synthetase in the COX/prostaglandin pathway, is a putative prognostic marker in breast cancer.

Narrative medicine describes the application of story to medical education and practice. Although it has been implemented successfully in many medical schools as a part of undergraduate medical education, applications to the residency environment have been relatively limited. There are virtually no data concerning the adoption of narrative medicine within surgical residencies. This paper provides a brief introduction to the formal discipline of narrative medicine. We further discuss how storytelling is already used in surgical education and summarize the literature on applications of narrative medicine to residents in other specialties. The relevance of narrative medicine to the ACGME core competencies is explored. We conclude with specific suggestions for implementation of narrative medicine within surgical residency programs.

The intrahepatic milieu is inhospitable to intraportal islet allografts1–3, limiting their applicability for the treatment of type 1 diabetes. Although the subcutaneous space represents an alternate, safe and easily accessible site for pancreatic islet transplantation, lack of neovascularization and the resulting hypoxic cell death have largely limited the longevity of graft survival and function and pose a barrier to the widespread adoption of islet transplantation in the clinic. Here we report the successful subcutaneous transplantation of pancreatic islets admixed with a device-free islet viability matrix, resulting in long-term euglycaemia in diverse immune-competent and immuno-incompetent animal models. We validate sustained normoglycaemia afforded by our transplantation methodology using murine, porcine and human pancreatic islets, and also demonstrate its efficacy in a non-human primate model of syngeneic islet transplantation. Transplantation of the islet–islet viability matrix mixture in the subcutaneous space represents a simple, safe and reproducible method, paving the way for a new therapeutic paradigm for type 1 diabetes. Yu et al. report a preparation that enables transplantation of pancreatic islets underneath the skin and achieves long-term euglycaemia in several preclinical models of type 1 diabetes, thus providing a simple method that might enable a more widespread adoption of islet transplantation in the clinic.

In this article, we propose a nonparametric graphical test based on optimal matching, for assessing the equality of multiple unknown multivariate probability distributions. Our procedure pools the data from the different classes to create a graph based on the minimum non-bipartite matching, and then utilizes the number of edges connecting data points from different classes to examine the closeness between the distributions. The proposed test is exactly distribution-free (the null distribution does not depend on the distribution of the data) and can be efficiently applied to multivariate as well as non-Euclidean data, whenever the inter-point distances are well-defined. We show that the test is universally consistent, and prove a distributional limit theorem for the test statistic under general alternatives. Through simulation studies, we demonstrate its superior performance against other common and well-known multisample tests. The method is applied to single cell transcriptomics data obtained from the peripheral blood, cancer tissue, and tumor-adjacent normal tissue of human subjects with hepatocellular carcinoma and non-small-cell lung cancer. Our method unveils patterns in how biochemical metabolic pathways are altered across immune cells in a cancer setting, depending on the tissue location. All of the methods described herein are implemented in the R package multicross. Supplementary materials for this article are available online.

Despite new immunotherapies aimed at B and T cells, plasma cells and their lifelong antibody secretion constitute a major immune barrier to long-term graft survival. In this mini-review, we survey the recent advances that have been made in the biology and immunometabolism of long-lived plasma cells, and outline aspects of plasma cell function that can be exploited for clinical benefit in recipients of solid organ transplants. A handful of ongoing studies are already targeting plasma cells to achieve desensitization and reduce the alloantibody burden in individuals posttransplant. In reviewing the recent strides made in our understanding of the molecular basis of plasma cell survival, we will place our discussions in the context of existing preclinical and clinical studies.

Amyand’s hernia, an incarcerated appendix inside an inguinal hernia, accounts for

Unchecked hyperadiposity causes systemic metabolic perturbations and subclinical chronic inflammation, promoting hormone receptor positive (HR+) breast cancer. Murine models of high-fat diet-induced obesity have shown alterations in proteins involved in fatty acid binding and mitochondrial beta-oxidation, including enoyl-CoA hydratase short chain 1 (ECHS1), which promote increased uptake of fatty acids by primary tumor cells. This creates a metabolic tug of war between tumor and immune cells in the tumor microenvironment, thereby depriving cytotoxic immune cells of the metabolic reprogramming for anti-tumor functionality. Nonetheless, metabolic gene expression changes in breast tumor microenvironment of obese individuals remain elusive. We hypothesize that increased expression of ECHS1 leads to immune dysregulation in breast tumor microenvironment and increases risk of cancer progression. Proteomic and genomic expression and survival characteristics of ECHS1 in invasive breast cancer was explored in The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium. We the modeled the effects of ECHS1 expression on immune infiltration in the tumor microenvironment using a regression framework. We also performed single cell RNA sequencing analysis for differential expression of ECHS1 in various human breast cells. Additionally, expression level of ECHS1 was validated in silico in adipose tissue to elucidate increased immune dysregulation and risk of progression of breast carcinoma in obese individuals. We found a significantly increased expression of ECHS1 at both RNA and protein levels in HR+ breast cancer (p Collectively, our observations support the hypothesis that preferential uptake of free fatty acid through increased expression of ECHS1 in HR+ breast cancer impairs cytotoxic and anti-tumor effects of CD8+ T cells in the tumor microenvironment. Immune dysregulation is further amplified in obese individuals given increased levels of adipose cells and higher ECHS1 expression. Altogether, ECHS1 is a putative biomarker and potential therapeutic target as its downregulation may improve survival in obese patients with HR+ breast cancer. Citation Format: Tina Bharani, Divyansh Agarwal, Estefania Roldan-Vasquez, Jessalyn Ubellacker, Ted A. James. ECHS1 mediates metabolic disruption in hormone receptor-positive breast tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1270.

With advances in single cell RNA sequencing (scRNAseq), accurate detection of perturbed pathways between conditions or cell types of interest becomes a critical analytical step. The ability to model alterations in a set of genes corresponding of a biological function is particularly useful when comparing cells between healthy and tumor tissues. Yet, few tools exist to detect changes in the multivariate distribution of genes corresponding to a given pathway. We developed a novel, graph-based statistical framework based on optimal matching for testing differential distribution of biological pathways in scRNAseq. We applied our method to data generated from >4,000 T cells isolated from six individuals with hepatocellular carcinoma (HCC). The T cell populations were purified from three tissue locations: peripheral blood, tumor-infiltrating immune cells (TIICs), and normal tissue adjacent to the tumor. We examined the distribution of gene sets that belong to a particular metabolic pathway across T cell subtypes to address the following questions: (1) Which pathways have a similar distribution across T cell subtypes in a given tissue? (2) Are there pathways that have a stable distribution across T cell subtypes in a normal/healthy tissue, but a perturbed distribution in HCC? (3) For pathways that have a disparate distribution across the T cell subtypes, which subtypes show the most distinct distribution? Of the 86 metabolic pathways compared, 41, 63 and 76 metabolic pathways were indistinguishable across T cell subtypes in the tumor, peripheral blood and adjacent normal tissues, respectively. We observed that most metabolic pathways do not show evidence for dissimilar distribution across cell types, suggesting that T cell subtypes might be more similar than previously appreciated in terms of how they regulate their basic metabolic machinery. Further, for each pair of tissue locations, we computed the overlap in perturbed pathways, and found that the concordance was substantially higher for blood and adjacent normal, than what either of these tissues had with the tumor tissue. Interestingly, five metabolic pathways were differentially distributed across the T cell subtypes in each tissue examined in HCC: glycolysis, purine metabolism, glycosphingolipid biosynthesis, pyruvate metabolism, and glycerophospholipid metabolism. Our model also found that CD4+ regulatory T cells were the strongest contributors, driving the differential distribution of these pathways between T cell subtypes in HCC. Altogether, our approach allows for a systems level characterization of pathway activity across multiple cell types with a variety of applications in single cell pathway analysis in oncology. Our work here also highlights unexpected regulatory mechanisms of regulatory T cells that might play in role in the immunobiology of HCC. Citation Format: Divyansh Agarwal, Tina Bharani, Somabha Mukherjee. Graph-based pathway analysis of T cell populations in hepatocellular carcinoma reveals novel metabolic regulators of tumor-infiltration lymphocyte activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2042.

Neurodevelopmental impairment is common in survivors of congenital diaphragmatic hernia (CDH). Altered cerebral perfusion in utero may contribute to abnormal brain development in CDH patients.5 fetal lambs with surgical left-CDH and 5 controls underwent transuterine cranial Doppler and contrast enhanced ultrasound (CEUS). Global and regional perfusion metrics were obtained. Biometric and perfusion data were compared between groups via nonparametric Mann Whitney U test and Spearman's rank order correlation.No significant differences in cerebral Doppler measurements were identified between groups. By CEUS, CDH animals demonstrated significantly decreased global brain perfusion and increased transit time. With focal regions-of-interest (ROIs), there was a tendency towards decreased perfusion in the central/thalamic region in CDH but not in the peripheral brain parenchyma. Transit time was significantly increased in both ROIs in CDH, whereas flux rate was decreased in the central/thalamic region but not the peripheral brain parenchyma. Biometric CDH severity was correlated to perfusion deficit. There was no difference in cardiomyocyte histology.The fetal lamb model of CDH shows altered cerebral perfusion as measured by CEUS, correlating to disease severity. This suggests a physiological abnormality in fetal cerebrovascular perfusion that may contribute to abnormal brain development and neurodevelopmental impairment in survivors.

The human brain is energetically expensive, yet the key factors governing its heterogeneous energy distributions across cortical regions to support its diversity of functions remain unexplored. Here, we built up a 3D digital cortical energy atlas based on the energetic costs of all neuropil activities into a high-resolution stereological map of the human cortex with cellular and synaptic densities derived, respectively, from ex vivo histological staining and in vivo PET imaging. The atlas was validated with PET-measured glucose oxidation at the voxel level. A 3D cortical activity map was calculated to predict the heterogeneous activity rates across all cortical regions, which revealed that resting brain is indeed active with heterogeneous neuronal activity rates averaging around 1.2 Hz, comprising around 70% of the glucose oxidation of the cortex. Additionally, synaptic density dominates spatial patterns of energetics, suggesting that the cortical energetics rely heavily on the distribution of synaptic connections. Recent evidence from functional imaging studies suggests that some cortical areas act as hubs (i.e., interconnecting distinct and functionally active regions). An inverse allometric relationship was observed between hub metabolic rates versus hub volumes. Hubs with smaller volumes have higher synapse density, metabolic rate, and activity rates compared to nonhubs. The open-source BrainEnergyAtlas provides a granular framework for exploring revealing design principles in energy-constrained human cortical circuits across multiple spatial scales.