Triple challenges - Small sample size in both exposure and control groups to scan rare maternal outcomes in a signal identification approach: A simulation study.

There is a dearth of safety data on maternal outcomes after perinatal medication exposure. Data-mining for unexpected adverse event occurrence in existing datasets is a potentially useful approach. One method, the Poisson tree-based scan statistic (TBSS), assumes that the expected outcome counts, based on incidence of outcomes in the control group, are estimated without error. This assumption may be difficult to satisfy with a small control group. Our simulation study evaluated the effect of imprecise incidence proportions from the control group on TBSS' ability to identify maternal outcomes in pregnancy research. We simulated base case analyses with "true" expected incidence proportions and compared these to imprecise incidence proportions derived from sparse control samples. We varied parameters impacting Type I error and statistical power (exposure group size, outcome's incidence proportion, and effect size). We found that imprecise incidence proportions generated by a small control group resulted in inaccurate alerting, inflation of Type I error, and removal of very rare outcomes for TBSS analysis due to "zero" background counts. Ideally, the control size should be at least several times larger than the exposure size to limit the number of false positive alerts and retain statistical power for true alerts.

The impact of more restrictive hydrocodone rescheduling on unintentional pediatric opioid exposures.

PURPOSE: To evaluate the impact of rescheduling hydrocodone combination products (HCPs) from schedule III of the Controlled Substances Act to the more restrictive schedule II on unintentional pediatric exposures (≤5 years old). METHODS: Using U.S. data on outpatient retail pharmacy dispensing, emergency department (ED) visits, and poison center (PC) exposure cases, we assessed trends in prescriptions dispensed and unintentional pediatric exposure cases involving hydrocodone (rescheduled from III to II) compared to oxycodone (schedule II) and codeine (schedule III for combination products) using descriptive and interrupted time-series (ITS) analyses during the 16 quarters before and after the October 2014 rescheduling of HCPs. RESULTS: Dispensing of hydrocodone products was declining before rescheduling but declined more steeply post-rescheduling. In ITS analyses, both hydrocodone and oxycodone had significant slope decreases in PC case rates in the post versus pre-period that was larger for hydrocodone, while codeine had a small but significant slope increase in PC case rates. An estimated 4202 ED visits for pediatric hydrocodone exposures occurred in the pre-period and 2090 visits occurred in the post-period, a significant decrease of 50.3%. Oxycodone exposures showed no significant decrease. CONCLUSIONS: Pediatric hydrocodone unintentional exposure ED visits and PC cases decreased after HCP rescheduling more than would be expected had the pre-rescheduling trend continued; the acceleration in the decrease in hydrocodone PC cases was partially offset by a slowing in the decrease in codeine-involved cases. The trend changes were likely due to multiple factors, including changes in dispensing that followed the rescheduling. Unintentional pediatric medication exposures and poisonings remain a public health concern requiring ongoing, multifaceted mitigation efforts.

Severe Hypocalcemia With Denosumab Among Older Female Dialysis-Dependent Patients.

Importance: Dialysis-dependent patients experience high rates of morbidity from fractures, yet little evidence is available on optimal treatment strategies. Chronic kidney disease-mineral and bone disorder is nearly universal in dialysis-dependent patients, complicating diagnosis and treatment of skeletal fragility. Objective: To examine the incidence and comparative risk of severe hypocalcemia with denosumab compared with oral bisphosphonates among dialysis-dependent patients treated for osteoporosis. Design, Setting, and Participants: Retrospective cohort study of female dialysis-dependent Medicare patients aged 65 years or older who initiated treatment with denosumab or oral bisphosphonates from 2013 to 2020. Clinical performance measures including monthly serum calcium were obtained through linkage to the Consolidated Renal Operations in a Web-Enabled Network database. Exposures: Denosumab, 60 mg, or oral bisphosphonates. Main Outcomes and Measures: Severe hypocalcemia was defined as total albumin-corrected serum calcium below 7.5 mg/dL (1.88 mmol/L) or a primary hospital or emergency department hypocalcemia diagnosis (emergent care). Very severe hypocalcemia (serum calcium below 6.5 mg/dL [1.63 mmol/L] or emergent care) was also assessed. Inverse probability of treatment-weighted cumulative incidence, weighted risk differences, and weighted risk ratios were calculated during the first 12 treatment weeks. Results: In the unweighted cohorts, 607 of 1523 denosumab-treated patients and 23 of 1281 oral bisphosphonate-treated patients developed severe hypocalcemia. The 12-week weighted cumulative incidence of severe hypocalcemia was 41.1% with denosumab vs 2.0% with oral bisphosphonates (weighted risk difference, 39.1% [95% CI, 36.3%-41.9%]; weighted risk ratio, 20.7 [95% CI, 13.2-41.2]). The 12-week weighted cumulative incidence of very severe hypocalcemia was also increased with denosumab (10.9%) vs oral bisphosphonates (0.4%) (weighted risk difference, 10.5% [95% CI, 8.8%-12.0%]; weighted risk ratio, 26.4 [95% CI, 9.7-449.5]). Conclusions and Relevance: Denosumab was associated with a markedly higher incidence of severe and very severe hypocalcemia in female dialysis-dependent patients aged 65 years or older compared with oral bisphosphonates. Given the complexity of diagnosing the underlying bone pathophysiology in dialysis-dependent patients, the high risk posed by denosumab in this population, and the complex strategies required to monitor and treat severe hypocalcemia, denosumab should be administered after careful patient selection and with plans for frequent monitoring.

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning.

We sought to determine whether machine learning and natural language processing (NLP) applied to electronic medical records could improve performance of automated health-care claims-based algorithms to identify anaphylaxis events using data on 516 patients with outpatient, emergency department, or inpatient anaphylaxis diagnosis codes during 2015-2019 in 2 integrated health-care institutions in the Northwest United States. We used one site's manually reviewed gold-standard outcomes data for model development and the other's for external validation based on cross-validated area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and sensitivity. In the development site 154 (64%) of 239 potential events met adjudication criteria for anaphylaxis compared with 180 (65%) of 277 in the validation site. Logistic regression models using only structured claims data achieved a cross-validated AUC of 0.58 (95% CI: 0.54, 0.63). Machine learning improved cross-validated AUC to 0.62 (0.58, 0.66); incorporating NLP-derived covariates further increased cross-validated AUCs to 0.70 (0.66, 0.75) in development and 0.67 (0.63, 0.71) in external validation data. A classification threshold with cross-validated PPV of 79% and cross-validated sensitivity of 66% in development data had cross-validated PPV of 78% and cross-validated sensitivity of 56% in external data. Machine learning and NLP-derived data improved identification of validated anaphylaxis events.

Monitoring Drug Safety in Pregnancy with Scan Statistics: A Comparison of Two Study Designs.

BACKGROUND: Traditional surveillance of adverse infant outcomes following maternal medication exposures relies on pregnancy exposure registries, which are often underpowered. We characterize the statistical power of TreeScan, a data mining tool, to identify potential signals in the setting of perinatal medication exposures and infant outcomes. METHODS: We used empirical data to inform background incidence of major congenital malformations and other birth conditions. Statistical power was calculated using two probability models compatible with TreeScan, Bernoulli and Poisson, while varying the sample size, magnitude of the risk increase, and incidence of a specified outcome. We also simulated larger referent to exposure matching ratios when using the Bernoulli model in the setting of fixed N:1 propensity score matching. Finally, we assessed the impact of outcome misclassification on power. RESULTS: The Poisson model demonstrated greater power to detect signals than the Bernoulli model across all scenarios and suggested a sample size of 4,000 exposed pregnancies is needed to detect a twofold increase in risk of a common outcome (approximately 8 per 1,000) with 85% power. Increasing the fixed matching ratio with the Bernoulli model did not reliably increase power. An outcome definition with high sensitivity is expected to have somewhat greater power to detect signals than an outcome definition with high positive predictive value. CONCLUSIONS: Use of the Poisson model with an outcome definition that prioritizes sensitivity may be optimal for signal detection. TreeScan is a viable method for surveillance of adverse infant outcomes following maternal medication use.

The impact of hydrocodone rescheduling on utilization, abuse, misuse, and overdose deaths.

PURPOSE: To evaluate the impact of increased federal restrictions on hydrocodone combination product (HCP) utilization, misuse, abuse, and overdose death. METHODS: We assessed utilization, misuse, abuse, and overdose death trends involving hydrocodone versus select opioid analgesics (OAs) and heroin using descriptive and interrupted time-series (ITS) analyses during the nine quarters before and after the October 2014 rescheduling of HCPs from a less restrictive (CIII) to more restrictive (CII) category. RESULTS: Hydrocodone dispensing declined >30% over the study period, and declines accelerated after rescheduling. ITS analyses showed that immediately postrescheduling, quarterly hydrocodone dispensing decreased by 177M dosage units while codeine, oxycodone, and morphine dispensing increased by 49M, 62M, and 4M dosage units, respectively. Postrescheduling, hydrocodone-involved misuse/abuse poison center (PC) case rates had a statistically significant immediate drop but a deceleration of preperiod declines. There were small level increases in codeine-involved PC misuse/abuse and overdose death rates immediately after HCP's rescheduling, but these were smaller than level decreases in rates for hydrocodone. Heroin-involved PC case rates and overdose death rates increased across the study period, with exponential increases in PC case rates beginning 2015. CONCLUSIONS: HCP rescheduling was associated with accelerated declines in hydrocodone dispensing, only partially offset by smaller increases in codeine, oxycodone, and morphine dispensing. The net impact on hydrocodone and other OA-involved misuse/abuse and fatal overdose was unclear. We did not detect an immediate impact on heroin abuse or overdose death rates; however, the dynamic nature of the crisis and data limitations present challenges to causal inference.

Novel methods for pregnancy drug safety surveillance in the FDA Sentinel System.

PURPOSE: It is a priority of the US Food and Drug Administration (FDA) to monitor the safety of medications used during pregnancy. Pregnancy exposure registries and cohort studies utilizing electronic health record data are primary sources of information but are limited by small sample sizes and limited outcome assessment. TreeScan™, a statistical data mining tool, can be applied within the FDA Sentinel System to simultaneously identify multiple potential adverse neonatal and infant outcomes after maternal medication exposure. METHODS: We implemented TreeScan using the Sentinel analytic tools in a cohort of linked live birth deliveries and infants nested in the IBM MarketScan® Research Database. As a case study, we compared first trimester fluoroquinolone use and cephalosporin use. We used the Bernoulli and Poisson TreeScan statistics with compatible propensity score-based study designs for confounding control (matching and stratification) and used multiple propensity score models with various strategies for confounding control to inform best practices. We developed a hierarchical outcome tree including major congenital malformations and outcomes of gestational length and birth weight. RESULTS: A total of 1791 fluoroquinolone-exposed and 8739 cephalosporin-exposed mother-infant pairs were eligible for analysis. Both TreeScan analysis methods resulted in single alerts that were deemed to be due to uncontrolled confounding or otherwise not warranting follow-up. CONCLUSIONS: In this implementation of TreeScan using Sentinel analytic tools, we did not observe any new safety signals for fluoroquinolone use in the first trimester. TreeScan, with tailored or high-dimensional propensity scores for confounding control, is a valuable tool in addition to current safety surveillance methods for medications used during pregnancy.

Iridoid glycosides from Morinda officinalis induce lysosomal biogenesis and promote autophagic flux to attenuate oxidative stress.

Morinda officinalis is a traditional Chinese tonic herb, and have been used in the treatment of multiple diseases. Here, three iridoid glycosides isolated from M. officinalis were evaluated for their roles in the autophagy-lysosomal pathway. All three iridoid glycosides could induce TFEB/TFE3-mediated lysosomal biogenesis and trigger autophagy. Interestingly, they promoted the nuclear import of TFEB/TFE3 without affecting their nuclear export, suggesting their role in the maintenance of lysosomal homeostasis. The results from this study shed light on the identification of autophagy activators from M. officinalis and provide a basis for developing them in the treatment of oxidative stress-involved diseases.

Nematicidal activity of tirotundin and parthenolide isolated from Tithonia diversifolia and Chrysanthemum parthenium.

Acetylcholinesterase (AChE) is an enzyme that catalyzes acetylcholine into choline and acetic acid. Conventional pesticides, including organophosphates and carbamates target and inhibit the activity of AChE. To obtain more pesticide precursors that meet the safety requirements, more than 200 compounds were screened. Tirotundin and parthenolide identified as potential neurotoxins to nematodes were isolated from Tithonia diversifolia and Chrysanthemum parthenium, respectively. Their IC50 values were 6.89 ± 0.30 and 5.51 ± 0.23 µg/mL, respectively against the AChE isolated from Caenorhabditis elegans. AChE was inhibited in a dose-dependent manner using the two compounds. And the Lineweaver-Burk and Dixon plots indicated that tirotundin and parthenolide were reversible inhibitors against AChE, both inhibiting AChE in a mixed-type competitive manner and demonstrating these compounds may possess dual binding site AChE inhibitors. LC50 values of tirotundin and parthenolide against C. elegans were 9.16 ± 0.21 and 7.23 ± 0.48 µg/mL, respectively. These results provide a certain theoretical basis for the development and utilization of novel pesticides.

Risk of Covid-19-Related Hospitalization and More Severe Outcomes in Medicare Beneficiaries Treated with Renin-Angiotensin-Aldosterone System Inhibitors for Hypertension.

BACKGROUND: There are theoretical concerns that angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) could increase the risk of severe Covid-19. OBJECTIVE: To determine if ACEIs and ARBs are associated with an increased risk of Covid-19 hospitalization overall, or hospitalization involving intensive care unit (ICU) admission, invasive mechanical ventilation, or death. DESIGN: Observational case-control study. PARTICIPANTS: Medicare beneficiaries aged ≥ 66 years with hypertension, treated with ACEIs, ARBs, calcium channel blockers (CCBs), or thiazide diuretics. MAIN MEASURES: Adjusted odds ratios (OR) and 95% confidence intervals (CI) for the outcomes of Covid-19 hospitalization, or hospitalization involving ICU admission, invasive mechanical ventilation, or death. RESULTS: A total of 35,300 cases of hospitalized Covid-19 were matched to 228,228 controls on calendar date and neighborhood of residence. The median age of cases was 79 years, 57.4% were female, and the median duration of hospitalization was 8 days (interquartile range 5-12). ACEIs and ARBs were associated with a slight reduction in Covid-19 hospitalization risk compared with treatment with other first-line antihypertensives (OR for ACEIs 0.95, 95% CI 0.92-0.98; OR for ARBs 0.94, 95% CI 0.90-0.97). Similar results were obtained for hospitalizations involving ICU admission, invasive mechanical ventilation, or death. There were no meaningful differences in risk for ACEIs compared with ARBs. In an analysis restricted to monotherapy with a first-line agent, CCBs were associated with a small increased risk of Covid-19 hospitalization compared with ACEIs (OR 1.09, 95% CI 1.04-1.14), ARBs (OR 1.10, 95% CI 1.05-1.15), or thiazide diuretics (OR 1.11, 95% CI 1.03-1.19). CONCLUSIONS: ACEIs and ARBs were not associated with an increased risk of Covid-19 hospitalization or with hospitalization involving ICU admission, invasive mechanical ventilation, or death. The finding of a small increased risk of Covid-19 hospitalization with CCBs was unexpected and could be due to residual confounding.

Use of Time-Dependent Propensity Scores to Adjust Hazard Ratio Estimates in Cohort Studies with Differential Depletion of Susceptibles.

Estimating hazard ratios (HR) presents challenges for propensity score (PS)-based analyses of cohorts with differential depletion of susceptibles. When the treatment effect is not null, cohorts that were balanced at baseline tend to become unbalanced on baseline characteristics over time as "susceptible" individuals drop out of the population at risk differentially across treatment groups due to having outcome events. This imbalance in baseline covariates causes marginal (population-averaged) HRs to diverge from conditional (covariate-adjusted) HRs over time and systematically move toward the null. Methods that condition on a baseline PS yield HR estimates that fall between the marginal and conditional HRs when these diverge. Unconditional methods that match on the PS or weight by a function of the PS can estimate the marginal HR consistently but are prone to misinterpretation when the marginal HR diverges toward the null. Here, we present results from a series of simulations to help analysts gain insight on these issues. We propose a novel approach that uses time-dependent PSs to consistently estimate conditional HRs, regardless of whether susceptibles have been depleted differentially. Simulations show that adjustment for time-dependent PSs can adjust for covariate imbalances over time that are caused by depletion of susceptibles. Updating the PS is unnecessary when outcome incidence is so low that depletion of susceptibles is negligible. But if incidence is high, and covariates and treatment affect risk, then covariate imbalances arise as susceptibles are depleted, and PS-based methods can consistently estimate the conditional HR only if the PS is periodically updated.

A comparison of opioid-involved fatalities captured in the National Poison Data System to data derived from US death certificate literal text.

PURPOSE: The purpose of the study is to describe and compare the number and characteristics of opioid-involved fatal cases captured in the National Poison Data System (NPDS) and in US death certificates. METHODS: NPDS, which collects data on all calls to US poison control centers, and Drug-Involved Mortality (DIM), which combines information from literal text of US death certificates and National Vital Statistics Systems, were queried for opioid-involved fatal cases from 2010 to 2015. Characteristics of the two case series were compared. RESULTS: DIM contained 154 016 opioid-involved overdose deaths, and NPDS contained 2524 fatal opioid exposures, a ratio of 61:1. The number of opioid deaths remained stable in NPDS but increased in DIM over the 6-year period. On average, deaths involving opioids with higher mean dosage strength (in morphine milligram equivalents) per unit among dispensed prescriptions were more likely to be captured in DIM relative to NPDS, as compared with those with a lower mean dosage strength per unit. The increase in fentanyl-related deaths seen in DIM since 2013 was not observed in NPDS. CONCLUSIONS: NPDS is a valuable drug safety surveillance resource due to its timeliness and drug specificity. However, it captures only a small fraction of opioid-involved fatal poisonings, and comparisons with data derived from death certificate literal text indicate that caution is warranted in making inferences about opioid-involved fatality trends over time or comparisons across opioids.

Pacidusin B isolated from Phyllanthus acidus triggers ferroptotic cell death in HT1080 cells.

Cancer cells generally exhibit 'iron addiction' phenotypes, which contribute to their vulnerability to ferroptosis inducers. Ferroptosis is a newly discovered form of programmed cell death caused by iron-dependent lipid peroxidation. In the present study, pacidusin B, a dichapetalin-type triterpenoid from Phyllanthus acidus (L.) Skeels (Euphorbiaceae), induces ferroptosis in the HT1080 human fibrosarcoma cell line. Cells treated with pacidusin B exhibited the morphological characteristic 'ballooning' phenotype of ferroptosis. The biochemical hallmarks of ferroptosis were also observed in pacidusin B-treated cells. Both oxidative stress and ER stress play significant roles in pacidusin B-induced ferroptosis. The activation of the PERK-Nrf2-HO-1 signaling pathway led to iron overload, while inhibition of GPX4 further sensitized cancer cells to ferroptosis. Furthermore, the molecular docking study showed that pacidusin B docked in the same pocket in xCT as the ferroptosis inducer erastin. These results revealed that pacidusin B exerts anticancer effects via inducing ER-mediated ferroptotic cell death.

Data-driven automated classification algorithms for acute health conditions: applying PheNorm to COVID-19 disease.

OBJECTIVES: Automated phenotyping algorithms can reduce development time and operator dependence compared to manually developed algorithms. One such approach, PheNorm, has performed well for identifying chronic health conditions, but its performance for acute conditions is largely unknown. Herein, we implement and evaluate PheNorm applied to symptomatic COVID-19 disease to investigate its potential feasibility for rapid phenotyping of acute health conditions. MATERIALS AND METHODS: PheNorm is a general-purpose automated approach to creating computable phenotype algorithms based on natural language processing, machine learning, and (low cost) silver-standard training labels. We applied PheNorm to cohorts of potential COVID-19 patients from 2 institutions and used gold-standard manual chart review data to investigate the impact on performance of alternative feature engineering options and implementing externally trained models without local retraining. RESULTS: Models at each institution achieved AUC, sensitivity, and positive predictive value of 0.853, 0.879, 0.851 and 0.804, 0.976, and 0.885, respectively, at quantiles of model-predicted risk that maximize F1. We report performance metrics for all combinations of silver labels, feature engineering options, and models trained internally versus externally. DISCUSSION: Phenotyping algorithms developed using PheNorm performed well at both institutions. Performance varied with different silver-standard labels and feature engineering options. Models developed locally at one site also worked well when implemented externally at the other site. CONCLUSION: PheNorm models successfully identified an acute health condition, symptomatic COVID-19. The simplicity of the PheNorm approach allows it to be applied at multiple study sites with substantially reduced overhead compared to traditional approaches.

Impacts of reclamation marsh restoration on greenhouse gas emission in the Sanjiang Plain, China.

To understand the variations in greenhouse gas fluxes during the process of returning cropland to wetland in the Sanjiang Plain, we selected naturally restored wetlands of 4, 7, 11, 16 and 20 years as research objects to compare with a cultivated site (soybean plantation for 13 years) and an uncultivated marsh dominated by Deyeuxia purpurea and Carex schmidtii. We measured carbon dioxide (CO2) and methane (CH4) fluxes using a static chamber-gas chromatography and explored the main influencing factors. The results showed that there were seasonal variations in growing-season CO2 and CH4 fluxes of the restored wetlands, with the seasonal trends in greenhouse gases becoming gradually similar to that of natural marsh with increasing restoration time. The mean growing-season CO2 fluxes increased during the early stage of restoration, but then decreased during the late stage, which decreased from 893.4 mg·m-2·h-1 to 494.0 mg·m-2·h-1 in the 4-year and 20-year sites, respectively. Mean CH4 fluxes increased with restoration time, ranging from a weak CH4 sink (soybean fields, -0.6 mg·m-2·h-1) to a CH4 source of 87.8 mg·m-2·h-1(20-year restored site). The CH4 fluxes of experimental plots were consistently lower than that of natural marsh (96.4 mg·m-2·h-1). Increases in water level and soil conductivity resulting from restoration were the main driving factors for the decrease in CO2 fluxes. The increases in water level and soil dissolved organic carbon resulting from restoration were the primary drivers for the increase of CH4 fluxes in the restored wetlands. The global warming potentials increased with restoration time, ranging from 27.8 t·CO2-eq·hm-2(soybean fields) to 130.8 t·CO2-eq·hm-2(plot of 20-year restoration), which gradually approached that of natural marsh (156.3 t·CO2-eq·hm-2). The emission of GHGs from restored wetlands in the Sanjiang Plain gradually approached those of natural marsh. Further monitoring is required to identify the maturity of restored wetlands for achieving greenhouse gas emissions equivalent to that of natural marshland.

Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing.

We used social media data from "covid19positive" subreddit, from 03/2020 to 03/2022 to identify COVID-19 cases and extract their reported symptoms automatically using natural language processing (NLP). We trained a Bidirectional Encoder Representations from Transformers classification model with chunking to identify COVID-19 cases; also, we developed a novel QuadArm model, which incorporates Question-answering, dual-corpus expansion, Adaptive rotation clustering, and mapping, to extract symptoms. Our classification model achieved a 91.2% accuracy for the early period (03/2020-05/2020) and was applied to the Delta (07/2021-09/2021) and Omicron (12/2021-03/2022) periods for case identification. We identified 310, 8794, and 12,094 COVID-positive authors in the three periods, respectively. The top five common symptoms extracted in the early period were coughing (57%), fever (55%), loss of sense of smell (41%), headache (40%), and sore throat (40%). During the Delta period, these symptoms remained as the top five symptoms with percent authors reporting symptoms reduced to half or fewer than the early period. During the Omicron period, loss of sense of smell was reported less while sore throat was reported more. Our study demonstrated that NLP can be used to identify COVID-19 cases accurately and extracted symptoms efficiently.

Trigonochinene E promotes lysosomal biogenesis and enhances autophagy via TFEB/TFE3 in human degenerative NP cells against oxidative stress.

BACKGROUND: Macroautophagy (henceforth autophagy) is the major form of autophagy, which delivers intracellular cargo to lysosomes for degradation. Considerable research has revealed that the impairment of lysosomal biogenesis and autophagic flux exacerbates the development of autophagy-related diseases. Therefore, reparative medicines restoring lysosomal biogenesis and autophagic flux in cells may have therapeutic potential against the increasing prevalence of these diseases. PURPOSE: The aim of the present study was thus to explore the effect of trigonochinene E (TE), an aromatic tetranorditerpene isolated from Trigonostemon flavidus, on lysosomal biogenesis and autophagy and to elucidate the potential underlying mechanism. METHODS: Four human cell lines, HepG2, nucleus pulposus (NP), HeLa and HEK293 cells were applied in this study. The cytotoxicity of TE was evaluated by MTT assay. Lysosomal biogenesis and autophagic flux induced by 40 µM TE were analyzed using gene transfer techniques, western blotting, real-time PCR and confocal microscopy. Immunofluorescence, immunoblotting and pharmacological inhibitors/activators were applied to determine the changes in the protein expression levels in mTOR, PKC, PERK, and IRE1α signaling pathways. RESULTS: Our results showed that TE promotes lysosomal biogenesis and autophagic flux by activating the transcription factors of lysosomes, transcription factor EB (TFEB) and transcription factor E3 (TFE3). Mechanistically, TE induces TFEB and TFE3 nuclear translocation through an mTOR/PKC/ROS-independent and endoplasmic reticulum (ER) stress-mediated pathway. The PERK and IRE1α branches of ER stress are crucial for TE-induced autophagy and lysosomal biogenesis. Whereas TE activated PERK, which mediated calcineurin dephosphorylation of TFEB/TFE3, IRE1α was activated and led to inactivation of STAT3, which further enhanced autophagy and lysosomal biogenesis. Functionally, knockdown of TFEB or TFE3 impairs TE-induced lysosomal biogenesis and autophagic flux. Furthermore, TE-induced autophagy protects NP cells from oxidative stress to ameliorate intervertebral disc degeneration (IVDD). CONCLUSIONS: Here, our study showed that TE can induce TFEB/TFE3-dependent lysosomal biogenesis and autophagy via the PERK-calcineurin axis and IRE1α-STAT3 axis. Unlike other agents regulating lysosomal biogenesis and autophagy, TE showed limited cytotoxicity, thereby providing a new direction for therapeutic opportunities to use TE to treat diseases with impaired autophagy-lysosomal pathways, including IVDD.

Comparative Risk of Angioedema With Sacubitril-Valsartan vs Renin-Angiotensin-Aldosterone Inhibitors.

BACKGROUND: Data on angioedema risk among sacubitril-valsartan (SV) users in real-world settings are limited. OBJECTIVES: We sought to evaluate the risk of angioedema among SV new users compared with angiotensin-converting enzyme (ACE) inhibitor and angiotensin-receptor-blocker (ARB) new users separately. METHODS: We conducted a propensity score-matched cohort study, comparing SV new users (no use of SV, ACE inhibitor, ARB 6 months before) and SV new users with prior use (within 183 or 14 days) of ACE inhibitor or ARB (ACE inhibitor-SV and ARB-SV users; recent ACE inhibitor-SV and recent ARB-SV users, respectively) vs ACE inhibitor and ARB new users separately. RESULTS: Compared with ACE inhibitor, SV new (HR: 0.18; 95% CI: 0.11-0.29) and ACE inhibitor-SV users (HR: 0.31; 95% CI: 0.23-0.43) showed lower risk of angioedema. On the other hand, there was no difference in angioedema risk when SV new users (HR: 0.59; 95% CI: 0.35-1.01) or ARB-SV users (HR: 0.85; 95% CI: 0.58-1.26) were compared with ARB new users. Compared with SV new users, ACE inhibitor-SV users (HR: 1.62; 95% CI: 0.91-2.89) trended toward higher angioedema risk, which intensified when the ACE inhibitor to SV switch occurred within 14 days (recent ACE inhibitor-SV) (HR: 1.98; 95% CI: 1.11-3.53). Similarly, ARB-SV users (HR: 2.03; 95% CI: 1.16-3.54) experienced an increased risk compared with SV new users, which intensified for the more recent switchers (recent ARB-SV) (HR: 2.45; 95% CI: 1.36-4.43). CONCLUSIONS: We did not observe an increased risk of angioedema among SV new users compared with ACE inhibitor or ARB users. However, there was an increased risk of angioedema among SV users who recently switched from ACE inhibitor or ARB compared with SV new users.

Risk of Severe COVID-19 in Prevalent Users of Alpha-1 Adrenergic Receptor Antagonists: A National Case-Control Study of Medicare Beneficiaries.

BACKGROUND: Alpha-1 adrenergic receptor antagonists prevent cytokine storm in mouse sepsis models. This led to the hypothesis that alpha-1 blockers may prevent severe coronavirus disease 2019 (COVID-19), which is characterized by hypercytokinemia and progressive respiratory failure. METHODS: We performed an observational case-control study in male Medicare beneficiaries aged 65 years or older, with or without benign prostatic hyperplasia (BPH), and treated with alpha-1 receptor blockers or 5-alpha reductase inhibitors. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were estimated for outcomes of uncomplicated and severe COVID-19 hospitalization (intensive care unit admission, invasive mechanical ventilation, or death). RESULTS: There were 20,963 cases of hospitalized COVID-19 matched to 101,161 controls on calendar date and neighborhood of residence. In the primary analysis (males with BPH), there was no difference in risk of uncomplicated COVID-19 hospitalization (aOR 1.08, 95% CI 0.996-1.17) or hospitalization with severe complications (aOR 0.97, 95% CI 0.88-1.08). In the secondary analysis (males with or without BPH), the corresponding aORs were 1.02 (95% CI, 0.96-1.09) (uncomplicated) and 0.99 (95% CI, 0.91-1.07) (complicated), respectively. Subgroup and sensitivity analyses yielded similar results. Of note, there was no difference in risk of severe COVID-19 hospitalization when comparing non-selective vs selective alpha-1 blocker use (aOR 0.98, 95% CI 0.86-1.10), higher- vs lower-dose alpha-1 blocker use (aOR 0.96, 95% CI 0.86-1.08), or current vs remote alpha-1 blocker use (aOR 1.04, 95% CI 0.91-1.18). CONCLUSIONS: Prevalent use of alpha-1 receptor blockers was not associated with a protective or harmful effect on risk of uncomplicated or severe hospitalized COVID-19.

Orodental manifestations of facial port-wine stains.

BACKGROUND: Patients with facial port-wine stains (PWS) often demonstrate oral manifestations of their disorder; however, the spectrum and prevalence of such findings among a cohort of patients with PWS has not been established. As a result, dermatologists and oral health specialists may be uncertain how to counsel their patients with PWS regarding oral hypervascularity, bony oral changes, and oral hygiene. OBJECTIVES: We sought to identify physical findings and complications involving the teeth, oral cavity, and perioral structures in individuals with facial PWS. METHODS: This was a cross-sectional study of 30 patients with facial PWS. Descriptive data were collected through anonymous paired surveys completed by patients and their dentists, and analyzed (Fisher exact test) for trends based on physical findings and stage of the PWS. RESULTS: The most common orodental manifestations according to patients were enlargement of the lip (53.3%), stained gums (46.7%), abnormal bite (30%), and spontaneous bleeding of the gums (26.7%). Staining of the gingiva correlated significantly with gingival hyperplasia (P = .006), maxillary hyperplasia (P = .014), and widened interdental spaces (P = .002), and in all cases gingival staining predated these findings. Lip hyperplasia was reported more frequently by patients than by their dentists (50% vs 18.2%, P = .008). Orodental manifestations were more common among patients with darker and thicker PWS. Hemorrhage after dental procedures was rare (4.5%). LIMITATIONS: Modest sample size and difficulty recruiting control subjects are limitations. CONCLUSIONS: Facial PWS commonly affect the orodental structures, and intraoral staining may predict future complications.