Goblet cells populate wet-surfaced mucosa including the conjunctiva of the eye, intestine, and nose, among others. These cells function as part of the innate immune system by secreting high molecular weight mucins that interact with environmental constituents including pathogens, allergens, and particulate pollutants. Herein we determined whether IFN-γ, a Th1 cytokine increased in dry eye, alters goblet cell function. Goblet cells from rat and human conjunctiva were cultured. Changes in intracellular [Ca2+] ([Ca2+]i), high molecular weight glycoconjugate secretion, and proliferation were measured after stimulation with IFN-γ with or without the cholinergic agonist carbachol. IFN-γ itself increased [Ca2+]i in rat and human goblet cells and prevented the increase in [Ca2+]i caused by carbachol. Carbachol prevented IFN-γ-mediated increase in [Ca2+]i. This cross-talk between IFN-γ and muscarinic receptors may be partially due to use of the same Ca2+i reservoirs, but also from interaction of signaling pathways proximal to the increase in [Ca2+]i. IFN-γ blocked carbachol-induced high molecular weight glycoconjugate secretion and reduced goblet cell proliferation. We conclude that increased levels of IFN-γ in dry eye disease could explain the lack of goblet cells and mucin deficiency typically found in this pathology. IFN-γ could also function similarly in respiratory and gastrointestinal tracts.
Despite the pivotal role of MYC in the pathogenesis of T-cell acute lymphoblastic leukemia (T-ALL) and many other cancers, the mechanisms underlying MYC-mediated tumorigenesis remain inadequately understood. Here we utilized a well-characterized zebrafish model of Myc-induced T-ALL for genetic studies to identify novel genes contributing to disease onset. We found that heterozygous inactivation of a tricarboxylic acid (TCA) cycle enzyme, dihydrolipoamide S-succinyltransferase (Dlst), significantly delayed tumor onset in zebrafish without detectable effects on fish development. DLST is the E2 transferase of the α-ketoglutarate (α-KG) dehydrogenase complex (KGDHC), which converts α-KG to succinyl-CoA in the TCA cycle. RNAi knockdown of DLST led to decreased cell viability and induction of apoptosis in human T-ALL cell lines. Polar metabolomics profiling revealed that the TCA cycle was disrupted by DLST knockdown in human T-ALL cells, as demonstrated by an accumulation of α-KG and a decrease of succinyl-CoA. Addition of succinate, the downstream TCA cycle intermediate, to human T-ALL cells was sufficient to rescue defects in cell viability caused by DLST inactivation. Together, our studies uncovered an important role for DLST in MYC-mediated leukemogenesis and demonstrated the metabolic dependence of T-lymphoblasts on the TCA cycle, thus providing implications for targeted therapy.
Objective In 2001, we provided benchmark estimates of probability of pregnancy given a single act of intercourse. Those calculations assumed that intercourse and ovulation are independent. Subsequent research has shown that this assumption is not valid. We provide here an update of previous benchmark estimates. Study Design We reanalyze earlier data from two North Carolina studies that collected daily urine samples and recorded daily intercourse for multiple menstrual cycles. One study comprised 68 sexually active women with either an intrauterine device or tubal ligation. The second was of 221 women who planned to become pregnant and had discontinued use of any birth control at enrollment. Participants had no known fertility problems. New statistical analyses were based on Monte Carlo simulations and Bayesian methods. Results The probability that a single act of intercourse occurs within a woman’s fertile window is 25%, compared with 20% in previous calculations. The probability of pregnancy with intercourse on a given menstrual cycle day is correspondingly higher than previously estimated, with the largest increases occurring on menstrual days 12–22. These increases are, however, fairly small (for example, the peak chance of conception on menstrual-day 13 increased from 8.6% to 9.7%). Conclusions Previous benchmark rates of pregnancy with one act of intercourse were moderately underestimated due to a mistaken assumption about the independence of intercourse and ovulation. Implications Statement The chance of pregnancy with a single act of unprotected intercourse is greater than previously estimated. Previous benchmarks may underestimate the efficacy of post-coital contraception.
Introduction Systemic lupus erythematosus (SLE) is a complex disease that is associated with significant mortality and an increased risk of hospitalization. Several validated instruments are available to measure disease activity in SLE patients. However, these instruments were not designed to screen for SLE patients at an increased risk of hospitalization. These instruments also fail to incorporate some data that are easily obtainable from electronic health records, such as the frequency of missed outpatient appointments. Methods All patients at a single academic medical center with an International Classification of Disease (ICD-10) code for SLE (M32) that were seen at least once between 2010 and 2017 were identified. Of these 3552 patients, 813 were randomly selected for chart review using a random number generator, and 226 were verified to have seen an outpatient rheumatologist and met the American College of Rheumatology Classification Criteria for SLE. Physician notes, laboratory values, and appointment information were reviewed, and relevant data were extracted. Weighted Cox regression models were used to estimate the risk of hospitalization and develop a screening algorithm, and receiver operating characteristic (ROC) curve analysis was performed to evaluate the algorithm. Results There were 160 patients with no lupus-related hospitalizations and 66 patients with such a hospitalization. In a multivariate analysis accounting for age, gender, and race, serum creatinine >1.20 mg/dL, white blood cell count > 10 (thousand)/µL, hemoglobin <11 g/dL, platelets < 180 (thousand)/µL, high risk immunosuppression use, missing between 0 and 20% of appointments, and missing ≥ 20% of appointments were associated with an increased risk of hospitalizations. Our proposed screening algorithm does well identifying SLE patients at risk of hospitalization (area under the curve (AUC): 0.90, 95% CI: 0.86-0.94). We recommend flagging patients with a score of ≥ 3 (sensitivity: 0.95; specificity: 0.54). Conclusions A new screening algorithm accounting for serum creatinine, white blood cell count, hemoglobin, platelets, high-risk immunosuppression, and the proportion of missed appointments may be useful in identifying SLE patients at an increased risk of hospitalization. Missing appointments may be a proxy for an underlying variable (such as access to health care) that is directly related to an increased risk of hospitalization.
Background Some environmental chemical exposures are lipophilic and need to be adjusted by serum lipid levels before data analyses. There are currently various strategies that attempt to account for this problem, but all have their drawbacks. To address such concerns, we propose a new method that uses Box-Cox transformations and a simple Bayesian hierarchical model to adjust for lipophilic chemical exposures. Methods We compared our Box-Cox method to existing methods. We ran simulation studies in which increasing levels of lipid-adjusted chemical exposure did and did not increase the odds of having a disease, and we looked at both single-exposure and multiple-exposures cases. We also analyzed an epidemiology dataset that examined the effects of various chemical exposures on the risk of birth defects. Results Compared with existing methods, our Box-Cox method produced unbiased estimates, good coverage, similar power, and lower type-I error rates. This was the case in both single- and multiple-exposure simulation studies. Results from analysis of the birth-defect data differed from results using existing methods. Conclusion Our Box-Cox method is a novel and intuitive way to account for the lipophilic nature of certain chemical exposures. It addresses some of the problems with existing methods, is easily extendable to multiple exposures, and can be used in any analyses that involve concomitant variables.
Objective SLE is associated with high risks of cardiovascular disease (CVD) and mortality, and has a wide spectrum of presentations. We investigated whether SLE severity at diagnosis was associated with CVD or mortality risk. Methods Within Medicaid (2000–10), we identified patients 18–65 years of age with incident SLE. Initial SLE severity was classified—mild, moderate, or severe—during the baseline year prior to the start of follow-up (incident index date) using a published algorithm based on SLE-related medications and diagnoses. Patients were followed from the index date to the first CVD event or death, disenrollment, loss to follow-up or end of follow-up period. Cox and Fine–Gray regression models, adjusted for demographics and comorbidities accounting for the competing risk of death (for CVD), estimated CVD and mortality risks by baseline SLE severity. Results Of 15 120 incident SLE patients, 48.7% had mild initial SLE severity, 33.9% moderate and 17.4% severe. Mean (s.d.) follow-up was 3.3 (2.4) years. After multivariable adjustment, CVD subdistribution hazard ratios (HRSD) were higher for initially severe [HRSD 1.64 (95% CI 1.32, 2.04)] and moderate [HRSD 1.19 (95% CI 1.00, 1.41)] SLE vs mild SLE. Mortality HRs were also higher for initially severe [HR 3.11 (95% CI 2.49, 3.89)] and moderate [HR 1.61 (95% CI 1.29, 2.01)] SLE vs mild SLE. Conclusion SLE patients with high initial severity had elevated mortality and CVD events risks compared with those who presented with milder disease. This has implications for clinical care and risk stratification of newly diagnosed SLE patients.
ObjectiveTo develop simple but clinically informative risk stratification tools using a few top demographic factors and biomarkers at COVID-19 diagnosis to predict acute kidney injury (AKI) and death.DesignRetrospective cohort analysis, follow-up from 1 February through 28 May 2020.Setting3 teaching hospitals, 2 urban and 1 community-based in the Boston area.ParticipantsEligible patients were at least 18 years old, tested COVID-19 positive from 1 February through 28 May 2020, and had at least two serum creatinine measurements within 30 days of a new COVID-19 diagnosis. Exclusion criteria were having chronic kidney disease or having a previous AKI within 3 months of a new COVID-19 diagnosis.Main outcomes and measuresTime from new COVID-19 diagnosis until AKI event, time until death event.ResultsAmong 3716 patients, there were 1855 (49.9%) males and the average age was 58.6 years (SD 19.2 years). Age, sex, white blood cell, haemoglobin, platelet, C reactive protein (CRP) and D-dimer levels were most strongly associated with AKI and/or death. We created risk scores using these variables predicting AKI within 3 days and death within 30 days of a new COVID-19 diagnosis. Area under the curve (AUC) for predicting AKI within 3 days was 0.785 (95% CI 0.758 to 0.813) and AUC for death within 30 days was 0.861 (95% CI 0.843 to 0.878). Haemoglobin was the most predictive component for AKI, and age the most predictive for death. Predictive accuracies using all study variables were similar to using the simplified scores.ConclusionSimple risk scores using age, sex, a complete blood cell count, CRP and D-dimer were highly predictive of AKI and death and can help simplify and better inform clinical decision making.
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