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Abstract Background Nanomedicine has evolved as precision medicine in novel therapeutic approach of cancer management. The present study investigated the efficacy of biogenic gold nanoparticles synthesized using Argemone mexicana L. aqueous extract (AM-AuNPs) against the human colon cancer cell line, HCT-15. Results Biosynthesis of AM-AuNPs was determined by ultraviolet-visible spectroscopy and further characterized by transmission electron microscopy, X-ray diffraction, and Fourier transition infrared spectroscopy analysis. The cytotoxic activity of AM-AuNPs was assessed by the 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide assay, whereas genotoxicity was evaluated by the DNA fragmentation assay. The expression of apoptosis regulatory genes such as p53 and caspase-3 was explored through semi-quantitative reverse transcriptase polymerase chain reaction (RT-PCR) and western blotting to evidence apoptotic cell death in HCT-15 cells. Biogenic AM-AuNPs inhibited cell proliferation in HCT-15 cell line with a half maximal inhibitory concentration (IC50) of 20.53 μg/mL at 24 h and 12.03 μg/mL at 48 h of exposure. The altered cell morphology and increased apoptosis due to AM-AuNPs were also evidenced through nuclear DNA fragmentation and upregulated expression of p53 and caspase-3 in HCT-15 cells. Conclusion The AM-AuNPs may exert antiproliferative and genotoxic effects on HCT-15 cells by cell growth suppression and induction of apoptosis mediated by activation of p53 and caspase-3 genes.

Objective: To identify prenatal predictors of poor perinatal outcome in fetuses with isolated sacrococcygeal teratoma (SCT). Methods: This was a retrospective study of fetuses with isolated (non‐syndromic) SCT managed at one of five pediatric surgery and/or fetal medicine centers between January 2007 and December 2017. The primary outcome was the occurrence of poor perinatal outcome, defined as prenatal death (including termination), or neonatal death or severe compromise (hemorrhagic shock). Data regarding prenatal diagnosis (sonographic features both at referral and at the last ultrasound examination before pregnancy outcome, assessment of SCT growth velocity), perinatal complications and outcome, and neonatal course were analyzed to determine prenatal SCT characteristics associated with adverse perinatal outcome. Results: Fifty‐five fetuses were included, diagnosed with isolated SCT at a median gestational age of 22 (interquartile range, 18–23) weeks. There was a poor perinatal outcome in 31% (n = 17) of these cases, including intrauterine fetal demise (4%, n = 2), pregnancy termination (13%, n = 7) and neonatal severe compromise (15%, n = 8), leading to neonatal death in five cases. The overall survival rate after prenatal diagnosis of isolated SCT was 75% (n = 41 of 55). Earlier gestational age at diagnosis (P = 0.02), large tumor volume at referral (P < 0.001), presence of one or more hemodynamic complications (P = 0.02), fast tumor growth velocity (P < 0.001) and high tumor grade (highest tumor grade ≥ 3) (P = 0.049) were associated with poor perinatal outcome on univariate analysis. On stepwise logistic regression analysis, tumor growth velocity was the only remaining independent factor associated with poor perinatal outcome (odds ratio (OR) (per 1‐mm/week increase), 1.48 (95% CI, 1.22–1.97), P = 0.001). The best predictive cut‐off of tumor growth velocity for poor perinatal outcome was 7 mm/week (OR, 25.7 (95% CI, 5.6–191.3), P < 0.001), yielding a sensitivity of 88% and a specificity of 77%. Conclusions: Approximately 30% of fetuses with a diagnosis of isolated SCT have poor perinatal outcome. Tumor growth velocity ≥ 7 mm/week appears to be an appropriate discriminative cut‐off for poor perinatal outcome. These results could help to inform prenatal management and counseling of parents with an affected pregnancy. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Abstract Background Missing data in confounding variables present a frequent challenge in generating evidence using real-world data, including electronic health records (EHR). Our objective was to apply a recently published toolkit for characterizing missing data patterns and based on the toolkit results about likely missingness mechanisms, illustrate the decision-making process for analyses in an empirical case example. Methods We utilized the Structural Missing Data Investigations (SMDI) toolkit to characterize missing data patterns in the context of a pharmacoepidemiology study comparing cardiovascular outcomes of initiating sodium-glucose-cotransporter-2 inhibitors (SGLT2i) and dipeptidyl peptidase‐4 inhibitors (DPP‐4i) among older adults. The study used a linked EHR-Medicare claims dataset from Duke Health patients (2015–2017), focusing on partially observed confounders from EHR data (HbA1c lab and body mass index [BMI] values). Our analysis incorporated SMDI's descriptive functions and diagnostic tests to explore missingness patterns and determine missingness mitigation approaches. We used findings from these investigations to inform estimation of adjusted hazard ratios comparing the two classes of medications. Results High levels of missingness were noted for important confounding variables including HbA1c (63.6%) and BMI (16.5%). Diagnostic tests resulted in output that described: 1) the distributions of patient characteristics, exposure, and outcome between patients with or without an observed value of the partially observed covariate, 2) the ability to predict missingness based on observed covariates, and 3) estimate if the missingness of a partially observed covariate is differential with respect to the outcome. There was evidence that missingness could be sufficiently described using observed data, which allowed multiple imputation by chained equations using random forests to address missing confounder data in estimating treatment effects. Multiple imputation resulted in improved alignment of effect estimates with previous studies. Conclusions We were able to demonstrate the practical application of the SMDI toolkit in a real-world setting. Application of the SMDI toolkit and the resulting insights of potential missingness patterns can inform the choice of appropriate analytic methods and increase transparency of research methods in handling missing data. This type of approach can inform analytic decision making and may increase our ability to generate evidence from real-world data.

Summary: Background: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. Methods: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). Findings: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. Interpretation: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. Funding: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.

Diabetes confers greater restenosis from neointimal hyperplasia following vascular interventions. While localized administration of nitric oxide (NO) is known to inhibit neointimal hyperplasia, the effect of NO in type 1 diabetes is unknown. Thus the aim of this study was to determine the efficacy of NO following arterial injury, with and without exogenous insulin administration. Vascular smooth muscle cells (VSMC) from lean Zucker (LZ) rats were exposed to the NO donor, DETA/NO, following treatment with different glucose and/or insulin concentrations. DETA/NO inhibited VSMC proliferation in a concentration-dependent manner to a greater extent in VSMC exposed to normal-glucose vs. high-glucose environments, and even more effectively in normal-glucose/high-insulin and high-glucose/high-insulin environments. Go/G1 cell cycle arrest and cell death were not responsible for the enhanced efficacy of NO in these environments. Next, type 1 diabetes was induced in LZ rats with streptozotocin. The rat carotid artery injury model was performed. Type 1 diabetic rats experienced no significant reduction in neointimal hyperplasia following arterial injury and treatment with the NO donor PROLI/NO. However, daily administration of insulin to type 1 diabetic rats restored the efficacy of NO at inhibiting neointimal hyperplasia (60% reduction, P < 0.05). In conclusion, these data demonstrate that NO is ineffective at inhibiting neointimal hyperplasia in an uncontrolled rat model of type 1 diabetes; however, insulin administration restores the efficacy of NO at inhibiting neointimal hyperplasia. Thus insulin may play a role in regulating the downstream beneficial effects of NO in the vasculature. proliferation; arterial injury; vascular smooth muscle cells doi: 10.1152/ajpheart.01234.2009.

Type II diabetes mellitus (DM) and metabolic syndrome are associated with accelerated restenosis following vascular interventions due to neointimal hyperplasia. The efficacy of nitric oxide (NO)-based therapies is unknown in these environments. Therefore, the aim of this study is to examine the efficacy of NO in preventing neointimal hyperplasia in animal models of type II DM and metabolic syndrome and examine possible mechanisms for differences in outcomes. Aortic vascular smooth muscle cells (VSMC) were harvested from rodent models of type II DM (Zucker diabetic fatty), metabolic syndrome (obese Zucker), and their genetic control (lean Zucker). Interestingly, NO inhibited proliferation and induced [G.sub.0]/[G.sub.1] cell cycle arrest to the greatest extent in VSMC from rodent models of metabolic syndrome and type II DM compared with controls. This heightened efficacy was associated with increased expression of cyclin-dependent kinase inhibitor p21, but not p27. Using the rat carotid artery injury model to assess the efficacy of NO in vivo, we found that the NO donor PROLI/NO inhibited neointimal hyperplasia to the greatest extent in type II DM rodents, followed by metabolic syndrome, then controls. Increased neointimal hyperplasia correlated with increased reactive oxygen species (ROS) production, as demonstrated by dihydroethidium staining, and NO inhibited this increase most in metabolic syndrome and DM. In conclusion, NO was surprisingly a more effective inhibitor of neointimal hyperplasia following arterial injury in type II DM and metabolic syndrome vs. control. This heightened efficacy may be secondary to greater inhibition of VSMC proliferation through cell cycle arrest and regulation of ROS expression, in addition to other possible unidentified mechanisms that deserve further exploration. proliferation; neointimal hyperplasia; cell cycle; reactive oxygen species; vascular smooth muscle cells

Objective: To identify favorable renal histology in fetuses with early severe lower urinary tract obstruction (LUTO) and determine the best timing and selection criteria for prenatal surgery.Methods: This multicenter, retrospective study included male fetuses with severe LUTO which died before 24 weeks of gestation during the period January 2000 to December 2018. Age-matched controls were used as reference standard for renal histology. Prenatal ultrasound features and fetal serum and/or urine β2microglobulin level were retrieved and kidney histology slides (hematein-eosin-safran and α-smooth-muscle-actin (αSMA) immunostaining) were prepared and reviewed. αSMA-positive staining of the blastema is due to its aberrant differentiation into myofibroblastic cells. Cases were sorted into histopathologic groups (favorable or unfavorable) according to the blastema's morphology and αSMA labeling and the data of these groups were compared.Results: Included in the study were 74 fetuses with a median gestational age at outcome of 17 + 6 (range, 13 + 0 to 23 + 5) weeks. Parenchymal organization was preserved in 48% of the kidneys. A blastema was present in 90% of the kidneys, but it was morphologically normal in only 9% and αSMA-negative in only 1% of them. Most (82%) fetuses had an unfavorable prognosis, and 36% of fetuses died ≤ 18 weeks and had severe renal lesions detected on histology (early unfavorable prognosis). A favorable renal prognosis was associated with an earlier gestational age (P = 0.001). Fetuses with LUTO had a significantly lower number of mature glomeruli (P < 0.001) compared with controls. However, there was no significant difference in the number of glomeruli generations between the early-unfavorable-prognosis group (≤ 18 weeks) and the group with a favorable prognosis (P = 0.19). A comparison of prenatal ultrasound features and biochemical markers between groups could not identify any prenatal selection criteria.Conclusions: Before 18 weeks, around 30% of fetuses with severe LUTO still have potential for kidney development. Identification of these cases would enable them to be targeted for prenatal therapy. © 2021 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Background: The present study was planned to investigate the possible association between polymorphisms of superoxide dismutase, SOD1 (Cu,Zn-SOD), SOD2(Mn-SOD), SOD3(EC-SOD) and catalase genes and the risk of cervical cancer in rural population of Maharashtra. Methods: A case control study included 350 proven cervical cancer cases and 400 healthy age matched control women. Genotyping of isoforms of SOD and CAT were done by polymerase chain reactionrestriction fragment length polymorphism (PCR-RFLP) method. Results: When we studied genotype frequencies of codon 326 and 262 region of promoter of CAT gene, there was no significant association between A to T transition at codon 326 (p=0.45) and CAT C262T polymorphism (p=0.30) with susceptibility to cervical cancer. The variant G allele of SOD1 at codon 251 significantly increased in cervical cancer patients as compared with the control women (OR=3.02, 95% CI: 1.72-5.31; p<0.0001). Conclusion: Findings from this investigation confirms conceivable association of A251G of SOD1 and G172A of SOD3 genes with risk of cervical cancer in women of Maharashtra. [ABSTRACT FROM AUTHOR]

Abstract Objective The aim of this study was to determine whether a secure, privacy-preserving record linkage (PPRL) methodology can be implemented in a scalable manner for use in a large national clinical research network. Results We established the governance and technical capacity to support the use of PPRL across the National Patient-Centered Clinical Research Network (PCORnet®). As a pilot, four sites used the Datavant software to transform patient personally identifiable information (PII) into de-identified tokens. We queried the sites for patients with a clinical encounter in 2018 or 2019 and matched their tokens to determine whether overlap existed. We described patient overlap among the sites and generated a “deduplicated” table of patient demographic characteristics. Overlapping patients were found in 3 of the 6 site-pairs. Following deduplication, the total patient count was 3,108,515 (0.11% reduction), with the largest reduction in count for patients with an “Other/Missing” value for Sex; from 198 to 163 (17.6% reduction). The PPRL solution successfully links patients across data sources using distributed queries without directly accessing patient PII. The overlap queries and analysis performed in this pilot is being replicated across the full network to provide additional insight into patient linkages among a distributed research network.

Abstract Background It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. There has been limited systematic evaluation of variation in U.S. local COVID-19-related policies. This study introduces the U.S. COVID-19 County Policy (UCCP) Database, whose objective is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. Methods In January-March 2021, we collected an initial wave of cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health. We characterized the presence and comprehensiveness of policies using univariate analyses. We also examined the correlation of policies with one another using bivariate Spearman’s correlations. Finally, we examined geographical variation in policies across and within states. Results There was substantial variation in the presence and comprehensiveness of county policies during January-March 2021. For containment and closure policies, the percent of counties with no restrictions ranged from 0% (for public events) to more than half for public transportation (67.8%), hair salons (52.6%), and religious gatherings (52.0%). For economic policies, 76.6% of counties had housing support, while 64.9% had utility relief. For public health policies, most were comprehensive, with 70.8% of counties having coordinated public information campaigns, and 66.7% requiring masks outside the home at all times. Correlations between containment and closure policies tended to be positive and moderate (i.e., coefficients 0.4–0.59). There was variation within and across states in the number and comprehensiveness of policies. Conclusions This study introduces the UCCP Database, presenting granular data on local governments’ responses to the COVID-19 pandemic. We documented substantial variation within and across states on a wide range of policies at a single point in time. By making these data publicly available, this study supports future research that can leverage this database to examine how policies contributed to and continue to influence pandemic-related health and socioeconomic outcomes and disparities. The UCCP database is available online and will include additional time points for 2020–2021 and additional counties nationwide.

Abstract Background Currently available medications for chronic osteoarthritis pain are only moderately effective, and their use is limited in many patients because of serious adverse effects and contraindications. The primary surgical option for osteoarthritis is total joint replacement (TJR). The objectives of this study were to describe the treatment history of patients with osteoarthritis receiving prescription pain medications and/or intra-articular corticosteroid injections, and to estimate the incidence of TJR in these patients. Methods This retrospective, multicenter, cohort study utilized health plan administrative claims data (January 1, 2013, through December 31, 2019) of adult patients with osteoarthritis in the Innovation in Medical Evidence Development and Surveillance Distributed Database, a subset of the US FDA Sentinel Distributed Database. Patients were analyzed in two cohorts: those with prevalent use of “any pain medication” (prescription non-steroidal anti-inflammatory drugs [NSAIDs], opioids, and/or intra-articular corticosteroid injections) using only the first qualifying dispensing (index date); and those with prevalent use of “each specific pain medication class” with all qualifying treatment episodes identified. Results Among 1 992 670 prevalent users of “any pain medication”, pain medications prescribed on the index date were NSAIDs (596 624 [29.9%] patients), opioids (1 161 806 [58.3%]), and intra-articular corticosteroids (323 459 [16.2%]). Further, 92 026 patients received multiple pain medications on the index date, including 71 632 (3.6%) receiving both NSAIDs and opioids. Altogether, 20.6% of patients used an NSAID at any time following an opioid index dispensing and 17.2% used an opioid following an NSAID index dispensing. The TJR incidence rates per 100 person-years (95% confidence interval [CI]) were 3.21 (95% CI: 3.20–3.23) in the “any pain medication” user cohort, and among those receiving “each specific pain medication class” were NSAIDs, 4.63 (95% CI: 4.58–4.67); opioids, 7.45 (95% CI: 7.40–7.49); and intra-articular corticosteroids, 8.05 (95% CI: 7.97–8.13). Conclusions In patients treated with prescription medications for osteoarthritis pain, opioids were more commonly prescribed at index than NSAIDs and intra-articular corticosteroid injections. Of the pain medication classes examined, the incidence of TJR was highest in patients receiving intra-articular corticosteroids and lowest in patients receiving NSAIDs.

(a) T2-weighted sequence in sagittal plane showing micropenis () and two bladders, one lower () and one protruding (#) at base of umbilical cord (UC). Unlike cloacal membrane involvement, an anomaly during secondary gastrulation could explain the continuum between epispadias and bladder/cloacal exstrophies, the associated symphysis pubis diastasis and its correlation with malformation severity[2]. Variants of bladder exstrophy (BE) represent 10% of the exstrophy-epispadias complex (EEC)[1]. [Extracted from the article]

Abstract Background Oncology rapidly shifted to telemedicine in response to the COVID‐19 pandemic. Telemedicine can increase access to healthcare, but recent research has shown disparities exist with telemedicine use during the pandemic. This study evaluated health disparities associated with telemedicine uptake during the COVID‐19 pandemic among cancer patients in a tertiary care academic medical center. Methods This retrospective cohort study evaluated telemedicine use among adult cancer patients who received outpatient medical oncology care within a tertiary care academic healthcare system between January and September 2020. We used multivariable mixed‐effects logistic regression models to determine how telemedicine use varied by patient race/ethnicity, primary language, insurance status, and income level. We assessed geospatial links between zip‐code level COVID‐19 infection rates and telemedicine use. Results Among 29,421 patient encounters over the study period, 8,541 (29%) were delivered via telemedicine. Several groups of patients were less likely to use telemedicine, including Hispanic (adjusted odds ratio [aOR] 0.86, p = 0.03), Asian (aOR 0.79, p = 0.002), Spanish‐speaking (aOR 0.71, p = 0.0006), low‐income (aOR 0.67, p

Central retinal artery occlusion (CRAO; retinal stroke or eye stroke) is an under-recognized, disabling form of acute ischemic stroke which causes severe visual loss in one eye. The classical risk factor for CRAO is ipsilateral carotid stenosis; however, nearly half of patients with CRAO do not have high-grade carotid stenosis, suggesting that other cardiovascular risk factors may exist for CRAO. Specifically, prior studies have suggested that cardioembolism, driven by underlying atrial fibrillation, may predispose patients to CRAO. We describe the design of an observational, population-based study in this protocol. We evaluate two specific objectives: 1) To determine if atrial fibrillation is an independent risk factor for CRAO after adjusting for medical and cardiovascular risk; 2) To determine if use of oral anticoagulation can modify the risk of CRAO for patients with atrial fibrillation. This protocol lays out our strategy for cohort definition, case and control definition, comorbidity ascertainment, and statistical methods.

Abstract Purpose Cancer patients frequently utilize the emergency department (ED) for a variety of diagnoses both related to and unrelated to their cancer, yet ED outcomes for cancer patients are not well documented. This study sought to define risks and identify predictors for inpatient admission and hospital mortality among cancer patients presenting to the ED. Patients and Methods We utilized the National Emergency Department Sample to identify patients with and without a diagnosis of cancer presenting to the ED between January 2016 and December 2018. We used multivariable mixed‐effects logistic regression models to assess the influence of cancer on outcomes of hospital admission after the ED visit and hospital mortality for the whole patient cohort and individual presenting diagnoses. Results There were 340 million weighted ED visits, of which 8.3 million (2.3%) were associated with a cancer diagnosis. Compared to non‐cancer patients, patients with cancer had an increased risk of inpatient admission (64.7% vs. 14.8%; p