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ObjectiveWe aimed to discover computationally-derived phenotypes of opioid-related patient presentations to the emergency department (ED) via clinical notes and structured electronic health record (EHR) data.MethodsThis was a retrospective study of ED visits from 2013-2020 across ten sites within a regional healthcare network. We derived phenotypes from visits for patients 18 years of age with at least one prior or current documentation of an opioid-related diagnosis. Natural language processing was used to extract clinical entities from notes, which were combined with structured data within the EHR to create a set of features. We performed Latent Dirichlet allocation to identify topics within these features. Groups of patient presentations with similar attributes were identified by cluster analysis.ResultsIn total 82,577 ED visits met inclusion criteria. The 30 topics discovered ranged from those related to substance use disorder, chronic conditions, mental health, and medical management. Clustering on these topics identified nine unique cohorts with one-year survivals ranging from 84.2-96.8%, rates of one-year ED returns from 9-34%, rates of one-year opioid event 10-17%, rates of medications for opioid use disorder from 17-43%, and a median Carlson comorbidity index of 2-8. Two cohorts of phenotypes were identified related to chronic substance use disorder, or acute overdose.ConclusionsOur results indicate distinct phenotypic clusters with varying patient-oriented outcomes which provide future targets better allocation of resources and therapeutics. This highlights the heterogeneity of the overall population, and the need to develop targeted interventions for each population.

Organoids are novelin vitromodels to study intercellular crosstalk between the different types of cells in the pathophysiology of disease. To better understand the underlying mechanisms driving the progression of primary sclerosing cholangitis (PSC), we developed scaffold-free multi-cellular 3D cholangiocyte organoids (3D-CHO) using ‘primary’ liver cell lines derived from normal and PSC patients. Human liver samples from healthy donors and late-stage PSC patients were used to isolate ‘primary’ cholangiocytes (EPCAM+/CK-19+), liver endothelial cells (LECs, CD31+), and hepatic stellate cells (HSCs, CD31−/CD68−/Desmin+/Vitamin A+). 3D-CHOs were formed using cholangiocytes:HSCs:LECs and kept viable for up to 1 month. Isolated primary cell lines and 3D-CHOs were further characterized by immunofluorescence (IF), qRT-PCR, and transmission electron microscopy. Gene expressions for cholangiocytes (SOX9, CFTR, EpCAM, AE, SCT, SCTR), fibrosis (ACTA2, COL1A1, DESMIN, TGFβ1), angiogenesis (PECAM, VEGF, CDH5, vWF), and inflammation (IL-6, TNF-α) confirmed PSC phenotypes of 3D-CHOs. Since cholangiocytes develop a neuroendocrine phenotype and express neuromodulators, confocal-IF demonstrated that neurokinin-1 receptor (NK-1R, expressed by cholangiocytes and upregulated in PSC), was localized within CK-19+cholangiocytes. Moreover, 3D-CHOs from PSC patients confirmed PSC phenotypes with upregulated NK-1R, tachykinin precursor 1, and downregulated membrane metalloendopeptidase. Our viable scaffold-free multiple-cell 3D-CHOs showed superiority as anin vitromodel in mimicking PSCin vivophenotypes compared to 2D cell culture, which can be used in PSC disease-related research.

Despite the rising prevalence of nonalcoholic fatty liver disease (NAFLD), the underlying disease pathophysiology remains unclear. There is a great need for an efficient and reliable “human” in vitro model to study NAFLD and the progression to nonalcoholic steatohepatitis (NASH), which will soon become the leading indication for liver transplantation. Here, we review the recent developments in the use of three-dimensional (3D) liver organoids as a model to study NAFLD and NASH pathophysiology and possible treatments. Various techniques that are currently used to make liver organoids are discussed, such as the use of induced pluripotent stem cells versus primary cell lines and human versus murine cells. Moreover, methods for inducing lipid droplet accumulation and fibrosis to model NAFLD are explored. Finally, the limitations specific to the 3D organoid model for NAFLD/NASH are reviewed, highlighting the need for further development of multilineage models to include hepatic nonparenchymal cells and immune cells. The ultimate goal is to be able to accurately recapitulate the complex liver microenvironment in which NAFLD develops and progresses to NASH.

Simple SummaryOur study used NanoString technology, a high-throughput platform measuring gene expression at the mRNA level to identify a set of genes predictive of clinical outcomes in bladder cancer patients. Twenty-seven differentially expressed genes were correlated with clinicopathological variables including molecular subtypes (luminal, basal, null/double-negative), histological subtypes (conventional urothelial carcinoma or carcinoma with variant histology), clinical subtype (NMIBC and MIBC), tumor stage category (Ta, T1 and T2-4), tumor grade, PD-L1 expression (high vs. low expression), and clinical risk categories (low, intermediate, high, and very high). Then, two risk models integrating the molecular subtypes and the level of expression of TP53, CCND1 and MKI67 were developed. These models provided a score ranging from 0 (best prognosis) to 7 (worst prognosis) that could be used to predict patient’ outcome and guide treatment decisions in bladder cancer.AbstractThis study evaluated a panel including the molecular taxonomy subtype and the expression of 27 genes as a diagnostic tool to stratify bladder cancer patients at risk of aggressive behavior, using a well-characterized series of non-muscle invasive bladder cancer (NMIBC) as well as muscle-invasive bladder cancer (MIBC). The study was conducted using the novel NanoString nCounter gene expression analysis. This technology allowed us to identify the molecular subtype and to analyze the gene expression of 27 bladder-cancer-related genes selected through a recent literature search. The differential gene expression was correlated with clinicopathological variables, such as the molecular subtypes (luminal, basal, null/double negative), histological subtype (conventional urothelial carcinoma, or carcinoma with variant histology), clinical subtype (NMIBC and MIBC), tumor stage category (Ta, T1, and T2–4), tumor grade, PD-L1 expression (high vs. low expression), and clinical risk categories (low, intermediate, high and very high). The multivariate analysis of the 19 genes significant for cancer-specific survival in our cohort study series identified TP53 (p = 0.0001), CCND1 (p = 0.0001), MKI67 (p < 0.0001), and molecular subtype (p = 0.005) as independent predictors. A scoring system based on the molecular subtype and the gene expression signature of TP53, CCND1, or MKI67 was used for risk assessment. A score ranging from 0 (best prognosis) to 7 (worst prognosis) was obtained and used to stratify our patients into two (low [score 0–2] vs. high [score 3–7], model A) or three (low [score 0–2] vs. intermediate [score 3–4] vs. high [score 5–7], model B) risk categories with different survival characteristics. Mean cancer-specific survival was longer (122 + 2.7 months) in low-risk than intermediate-risk (79.4 + 9.4 months) or high-risk (6.2 + 0.9 months) categories (p < 0.0001; model A); and was longer (122 + 2.7 months) in low-risk than high-risk (58 + 8.3 months) (p < 0.0001; model B). In conclusion, the molecular risk assessment model, as reported here, might be used better to select the appropriate management for patients with bladder cancer. This study evaluated a panel including the molecular taxonomy subtype and the expression of 27 genes as a diagnostic tool to stratify bladder cancer patients at risk of aggressive behavior, using a well-characterized series of non-muscle invasive bladder cancer (NMIBC) as well as muscle-invasive bladder cancer (MIBC). The study was conducted using the novel NanoString nCounter gene expression analysis. This technology allowed us to identify the molecular subtype and to analyze the gene expression of 27 bladder-cancer-related genes selected through a recent literature search. The differential gene expression was correlated with clinicopathological variables, such as the molecular subtypes (luminal, basal, null/double negative), histological subtype (conventional urothelial carcinoma, or carcinoma with variant histology), clinical subtype (NMIBC and MIBC), tumor stage category (Ta, T1, and T2–4), tumor grade, PD-L1 expression (high vs. low expression), and clinical risk categories (low, intermediate, high and very high). The multivariate analysis of the 19 genes significant for cancer-specific survival in our cohort study series identified TP53 (p = 0.0001), CCND1 (p = 0.0001), MKI67 (p < 0.0001), and molecular subtype (p = 0.005) as independent predictors. A scoring system based on the molecular subtype and the gene expression signature of TP53, CCND1, or MKI67 was used for risk assessment. A score ranging from 0 (best prognosis) to 7 (worst prognosis) was obtained and used to stratify our patients into two (low [score 0–2] vs. high [score 3–7], model A) or three (low [score 0–2] vs. intermediate [score 3–4] vs. high [score 5–7], model B) risk categories with different survival characteristics. Mean cancer-specific survival was longer (122 + 2.7 months) in low-risk than intermediate-risk (79.4 + 9.4 months) or high-risk (6.2 + 0.9 months) categories (p < 0.0001; model A); and was longer (122 + 2.7 months) in low-risk than high-risk (58 + 8.3 months) (p < 0.0001; model B). In conclusion, the molecular risk assessment model, as reported here, might be used better to select the appropriate management for patients with bladder cancer.

The Hippo pathway plays a central role in tissue development and homeostasis. However, the function of Hippo in pancreatic endocrine development remains obscure. Here, we examined the roles of Hippo pathway mediated YAP1/TAZ inhibition in the development stages of endocrine specification and differentiation. While YAP1 protein was localized to the nuclei in bipotent progenitor cells, Ngn3 expressing endocrine progenitors completely lost YAP1. Using genetic mouse models, we found that this inactivation of YAP1 requires both intact Hippo pathway and NGN3 protein. Deleting the Lats1 and 2 kinases (Lats1&2) in endocrine progenitor cells of developing mouse pancreas with Ngn3-Cre blocked endocrine progenitor cell differentiation and specification, resulting in reduced islets size and disorganized pancreas at birth. Loss of Lats1&2 in NGN3 expressing cells activated YAP1/TAZ transcriptional activity and recruited macrophages to the developing pancreas. These defects were rescued by deletion of YAP1/TAZ genes, suggesting that tight regulation of YAP1/TAZ by Hippo signaling is crucial for pancreatic endocrine specification. In contrast, deletion of Lats1&2 using beta-cell specific MIP1CreER resulted in a phenotypically normal pancreas, indicating that Lasts1&2 are dispensable for pancreatic beta-cell function. Our results demonstrate that YAP1/TAZ inhibition in the pancreatic endocrine compartment is not a passive consequence of endocrine specification. Rather, Hippo pathway-mediated YAP1/TAZ inhibition in endocrine progenitors is a prerequisite for endocrine specification and differentiation.

Cholangiocarcinoma (CCA) is the second most common primary liver tumor and is associated with late diagnosis, limited treatment options, and a 5-year survival rate of around 30%. CCA cell lines were first established in 1971, and since then, only 70 to 80 CCA cell lines have been established. These cell lines have been essential in basic and translational research to understand and identify novel mechanistic pathways, biomarkers, and disease-specific genes. Each CCA cell line has unique characteristics, reflecting a specific genotype, sex-related properties, and patient-related signatures, making them scientifically and commercially valuable. CCA cell lines are crucial in the use of novel technologies, such as three-dimensional organoid models, which help to model the tumor microenvironment and cell-to-cell crosstalk between tumor-neighboring cells. This review highlights crucial information on CCA cell lines, including: i) type of CCA (eg, intra- or extrahepatic), ii) isolation source (eg, primary tumor or xenograft), iii) chemical digestion method (eg, trypsin or collagenase), iv) cell-sorting method (colony isolation or removal of fibroblasts), v) maintenance-medium choice (eg, RPMI or Dulbecco's modified Eagle's medium), vi) cell morphology (eg, spindle or polygonal shape), and vii) doubling time of cells.

This forum features a discussion of the What America Ate online archive, an interactive website and database of primary sources related to U.S. foodways during the interwar period, and five short e...

Background: Pig-to-human xenotransplantation (XTx) is a promising solution to the organ shortage. Genetically engineered pigs lacking major xenoantigens have reduced hyperacute rejection and prolonged xenograft survival. Despite these advancements, acute xenograft rejection (AXR) remains a major barrier to clinical XTx. AXR is mediated by multiple immune cells, of which natural killer (NK) cells play a crucial role. Previous studies have shown that human HLA-E suppresses NK cell activation through the inhibitory receptor NKG2A. We seek to improve pig-to-human compatibility by expressing HLA-E in a genetically modified pig endothelial cell (pEC) line. This cell line 5GKO/ HLA-G+ has mutations in five genes encoding for xenoantigens and expresses HLA-G, an inhibitory ligand of the NK cell receptor KIR2DL4. In this study, the 5GKO/HLA-G+/HLA-E+ pEC line was established to examine whether co-expression of inhibitory ligands promotes NK cell tolerance. Methods: The HLA-Eα/pCDNA3.1 plasmid containing the HLA-E α-chain (HLA-Eα) cDNA driven by a CMV promoter was linearized and introduced into 106 cells of the 5GKO/HLA-G+ pEC line by electroporation. After 48 hours, HLA-E expression was analyzed by flow cytometry. HLA-E+ pECs were isolated by flow cytometry sort and co-cultured with human peripheral blood mononuclear cells (PBMCs) stimulated by IL-2. NK cell degranulation was compared between the 5GKO/HLA-G+ and 5GKO/HLA-G+/HLA-E+ pEC lines by measuring CD107a expression in the CD3- CD56+ cell population. Results: HLA-E molecules were successfully expressed on the pECs surface, indicating the HLA-E a chain can pair with the existing b2-microglobulin (B2M). The transfection efficiency was 38.2%. Three weeks later, the 5GKO/HLA-G+/HLA-E+ pEC was successfully established, confirming via flow cytometric analysis. The analysis of NK cell degranulation (CD107a) is underway. Conclusion: We established a 5GKO/HLA-G+/HLA-E+ pEC line, which is a valuable tool to study human-to-pig xenoreactive immune response in vitro, with the goal of improving pig-to-human xenograft immunotolerance.

Background and Objective: The trauma bay is a fast-paced environment where comprehension of medical jargon is difficult even for native English-speaking patients. For Spanish-speaking patients, the presence, and use of the translating tools in hospitals may change the course and/or quality of their care, especially in a trauma setting. Our objective was to gather information and perspectives of Spanish-speaking patients in the trauma bay and subsequent hospitalization. This pilot study determined if there were constant themes. Methods: In this pilot qualitative study, we successfully recruited three adult primary Spanish-speaking patients admitted to the trauma service for at least twenty-four hours in July 2021 at an urban academic level I trauma center. Spanish only in-person semi-structured interviews were used to gather patient’s perspectives, with data supplemented from electronic health records and trauma registries. The interview was transcribed in Spanish, translated to English, coded, and analyzed using thematic analysis. Results: Although recruitment occurred at both hospitals, this study includes only three patients admitted at IU Health Methodist. All three were males aged 22-37 years from Latin America. Blunt injuries occurred in two with injury severity scores (ISS) ranging from 5-11 while the third had penetrating injuries with an ISS of 10. Several themes have emerged. All patients felt they did not have autonomy or empowerment in their care. It was found that the healthcare team decided who received a translator. Two of the patients had a lack of understanding in their traumatic injuries. One patient relied on his partner for translating, even though a translator was provided. Conclusions: These results suggest that Spanish-speaking trauma patients lack autonomy, empowerment, and understanding their medical conditions. Further interviews need to be conducted in order to strengthen the perspective of a Spanish-speaking trauma patient’s care.

Objective Clinical guidelines recommend annual eye examinations to detect diabetic retinopathy (DR) in patients with diabetes. However, timely DR detection remains a problem in medically underserved and under-resourced settings in the United States. Machine learning that identifies patients with latent/undiagnosed DR could help to address this problem. Materials and Methods Using electronic health record data from 40 631 unique diabetic patients seen at Los Angeles County Department of Health Services healthcare facilities between January 1, 2015 and December 31, 2017, we compared ten machine learning environments, including five classifier models, for assessing the presence or absence of DR. We also used data from a distinct set of 9300 diabetic patients seen between January 1, 2018 and December 31, 2018 as an external validation set. Results Following feature subset selection, the classifier with the best AUC on the external validation set was a deep neural network using majority class undersampling, with an AUC of 0.8, the sensitivity of 72.17%, and specificity of 74.2%. Discussion A deep neural network produced the best AUCs and sensitivity results on the test set and external validation set. Models are intended to be used to screen guideline noncompliant diabetic patients in an urban safety-net setting. Conclusion Machine learning on diabetic patients’ routinely collected clinical data could help clinicians in safety-net settings to identify and target unscreened diabetic patients who potentially have undiagnosed DR.

Xenotransplantation (cross-species transplantation) using genetically-engineered pig organs offers a potential solution to address persistent organ shortage. Current evaluation of porcine genetic modifications is to monitor the nonhuman primate immune response and survival after pig organ xenotransplantation. This measure is an essential step before clinical xenotransplantation trials, but it is time-consuming, costly, and inefficient with many variables. We developed an efficient approach to quickly examine human-to-pig xeno-immune responses in vitro. A porcine endothelial cell was characterized and immortalized for genetic modification. Five genes includingGGTA1,CMAH,β4galNT2,SLA-I α chain,andβ2-microglobulinthat are responsible for the production of major xenoantigens (αGal, Neu5Gc, Sda, and SLA-I) were sequentially disrupted in immortalized porcine endothelial cells using CRISPR/Cas9 technology. The elimination of αGal, Neu5Gc, Sda, and SLA-I dramatically reduced the antigenicity of the porcine cells, though the cells still retained their ability to provoke human natural killer cell activation. In summary, evaluation of human immune responses to genetically modified porcine cells in vitro provides an efficient method to identify ideal combinations of genetic modifications for improving pig-to-human compatibility, which should accelerate the application of xenotransplantation to humans.

This article explores a heuristic based optimization methodology for power loss reduction and the voltage profile improvement in a medium voltage distribution network. The objective function provides minimum values for the power losses using three-phase capacitor banks located and dimensioned throughout the distribution network. This location and dimensioning were carried out using two heuristic methods: ant colony and genetic optimization algorithms. These algorithms involve determining which capacitor bank might be installed in a specific bus; under these conditions, the losses are optimized. Such heuristic optimization methods were tested in three distribution networks with radial topology to show feasibility of the methodology: the IEEE 33-bus and the IEEE 69-bus, and the long unbalanced rural Medium Voltage feeder Pinal of CNEL Guayas-Rios (Ecuador). The results show significant power losses reductions, especially in the IEEE model networks and moderate power losses reductions in Pinal. The proposed approach permits the flexible optimization variables that are represented in their natural form.

A cascade of NO in Alzheimer's disease One of the ill effects of the amyloid-β peptide that accumulates in Alzheimer's disease (AD) is the promotion of the production of nitric oxide (NO) and consequent nitrosylation of thiols in proteins such as dynamin-related protein 1 (Drp1), which can lead to loss of neuronal synapses. Nakamura et al. found that this S-nitrosylation occurs in an unusual way. They detected a series of transnitrosylation events in which an NO group is passed between at least three proteins. The deubiquinating enzyme Uch-L1 was S-nitrosylated in brains from human AD patients or in mouse models of AD. Uch-L1 could lead to S-nitrosylation of Drp1 after transferring the NO group to another enzyme, Cdk5 (cyclin-dependent kinase 5). The results implicate a mechanism in which unrelated enzymes might aberrantly function together to disrupt brain function. Science , this issue p. eaaw0843

Biomineralization is a highly regulated process where proteins/peptides-crystal interactions contribute to the shaping, phasing and aggregation of minerals. We have identified and synthesized a cementum attachment protein-derived peptide (CAP-pi), which corresponds to amino acids 40-53 of the N-terminal CAP domain (MASSDEDGTNGGAS) and its phosphorylated variant (MASpSpDEDGTNGGASp) (CAP-pip). The peptide is composed of polar and negatively charged amino acids, which are disordered, according to in silico analysis. Our results show that CAP-pi inhibits hydroxyapatite (HA) formation and growth. However, it possesses low capacity to inhibit calcium oxalate crystal growth. CAP-pip showed a stronger inhibitory effect on the formation and growth of HA. As well as a high capacity to inhibit calcium oxalate monohydrate growth, mainly due to adsorption on specific growth faces. Small peptides have many advantages over the full-size protein, including low-cost production and modulation characteristics that allow for structural changes. Our findings suggest that CAP-pip-derived peptide could possess therapeutic potential to prevent or treat pathological calcifications such as renal stones and vascular calcification.

Refactoring is the de-facto practice to optimize software health. While there has been several studies proposing refactoring strategies to optimize software design through applying design patterns and removing design defects, little is known about how developers actually refactor their code to improve its reuse. Therefore, we extract, from 1,828 open source projects, a set of refactorings which were intended to improve the software reusability. We analyze the impact of reusability refactorings on state-of-the-art reusability metrics, and we compare the distribution of reusability refactoring types, with the distribution of the remaining mainstream refactorings. Overall, we found that the distribution of refactoring types, applied in the context of reusability, is different from the distribution of refactoring types in mainstream development. In the refactorings performed to improve reusability, source files are subject to more design level types of refactorings. Reusability refactorings significantly impact, high-level code elements, such as packages, classes, and methods, while typical refactorings, impact all code elements, including identifiers, and parameters.

The goal of this work is to propose a new time-delay control law called the cascade proportional integral retarded controller, which is aimed at position control of DC servodrives. The proposed controller has a cascade inner loop-outer loop structure. The inner loop is endowed with an integral retarded algorithm, and regulates the servodrive angular velocity. A proportional controller closes the outer loop whose goal is to regulate the servodrive angular position. The tuning of the cascade proportional integral retarded controller is accomplished into two steps. In the first step, the velocity of the inner loop is tuned by assigning a triple dominant root. The second step tunes the outer position loop. It is also possible to modify the cascade proportional integral retarded controller to avoid velocity measurements without adding extra filters. Moreover, the cascade topology of the cascade proportional integral retarded controller makes it easy to introduce a nonlinear saturated gain in the outer loop. This controller termed as the cascade nonlinear proportional integral retarded controller prevents overshoots for large values of the set point, avoids excessive control effort, and maintains a prescribed value of the angular velocity. Experiments in real-time using a laboratory prototype allow assessing the performance of the proposed controllers.

This work proposes a tuning methodology for the Cascade Proportional Integral Retarded (CPIR) controller applied to a class of second order systems. Unlike the Proportional Integral Retarded (PIR) control law, the CPIR is composed of two nested loops, each of them having its own controller. The inner loop is regulated through an Integral Retarded (IR) Controller and the outer loop uses a proportional (P) controller. It is worth remarking that the stability of both loops must be simultaneously guaranteed, a problem not appearing in the PIR controller. The proposed tuning methodology is based on the spectral abscissa analysis of the Outer loop. The IR controller tuning rules and a double root placement analysis in the CPIR quasy-polynomial allows writing an analytical form of the P proportional gain. Subsequently, this gain is computed by solving a transcendental nonlinear equation. The proposed tuning method is assessed by means of experiments in a laboratory prototype.

This work presents the implementation of advanced time-delay controllers in a low-cost educational motion control platform based on a radio control (RC) servo. The highlights of the platform are presented as well as real-time experiments using the Proportional Integrated Retarded (PIR) and the Cascade Proportional Integrated Retarded (CPIR) algorithms. The experiments allow assessing the capabilities of the platform for implementing advanced controllers, and highlights the inherent filtering capabilities of time-delay controllers when they are fed by noisy measurements.