Enhancing glycolysis attenuates Parkinson's disease progression in models and clinical databases

Parkinson's disease (PD) is a common neurodegenerative disease that lacks therapies to prevent progressive neurodegeneration. Impaired energy metabolism and reduced ATP levels are common features of PD. Previous studies revealed that terazosin (TZ) enhances the activity of phosphoglycerate kinase 1 (PGK1), thereby stimulating glycolysis and increasing cellular ATP levels. Therefore, we asked whether enhancement of PGK1 activity would change the course of PD. In toxin-induced and genetic PD models in mice, rats, flies, and induced pluripotent stem cells, TZ increased brain ATP levels and slowed or prevented neuron loss. The drug increased dopamine levels and partially restored motor function. Because TZ is prescribed clinically, we also interrogated 2 distinct human databases. We found slower disease progression, decreased PD-related complications, and a reduced frequency of PD diagnoses in individuals taking TZ and related drugs. These findings suggest that enhancing PGK1 activity and increasing glycolysis may slow neurodegeneration in PD

MRSA in Conventional and Alternative Retail Pork Products

In order to examine the prevalence of Staphylococcus aureus on retail pork, three hundred ninety-five pork samples were collected from a total of 36 stores in Iowa, Minnesota, and New Jersey. S. aureus was isolated from 256 samples (64.8%, 95% confidence interval [CI] 59.9%–69.5%). S. aureus was isolated from 67.3% (202/300) of conventional pork samples and from 56.8% (54/95) of alternative pork samples (labeled “raised without antibiotics” or “raised without antibiotic growth promotants”). Two hundred and thirty samples (58.2%, 95% CI 53.2%–63.1%) were found to carry methicillin-sensitive S. aureus (MSSA). MSSA was isolated from 61.0% (183/300) of conventional samples and from 49.5% (47/95) of alternative samples. Twenty-six pork samples (6.6%, 95% CI 4.3%–9.5%) carried methicillin-resistant S. aureus (MRSA). No statistically significant differences were observed for the prevalence of S. aureus in general, or MSSA or MRSA specifically, when comparing pork products from conventionally raised swine and swine raised without antibiotics, a finding that contrasts with a prior study from the Netherlands examining both conventional and “biologic” meat products. In our study spa types associated with “livestock-associated” ST398 (t034, t011) were found in 26.9% of the MRSA isolates, while 46.2% were spa types t002 and t008—common human types of MRSA that also have been found in live swine. The study represents the largest sampling of raw meat products for MRSA contamination to date in the U.S. MRSA prevalence on pork products was higher than in previous U.S.-conducted studies, although similar to that in Canadian studies

Using Search Volume for Surveillance of Medication Prescribing

Over the past five years, the potential for web search volume to provide insight into the present has become increasingly apparently. To date, much of these methods have focused on syndromic keywords and are not directly suitable for surveillance of less common or highly variable diseases. The more unique mapping between drug therapy had disease provides a potential workout this problem. We demonstrate the high degree of correlation between search volume and drug utilization and apply this method of keyword generation to modeling drug utilization, patent expirations and TB incidence in the US

Using Search Volume for Surveillance of Medication Prescribing

OBJECTIVE: To validate search volume estimation for outpatient medication prescribing. INTRODUCTION: Investigators have used the volume of internet search queries to model disease incidence, especially influenza and general consumer behavior [1]. Our group has used search volume to model interest in FDA safety alerts and adverse drug event incidence. We found evidence of changes in search behavior following warnings and the expected relationship between search volume and adverse drug event incidence. Thus, search volume may help provide near real time surveillance of drug use patterns to help monitor and mitigate risk to the population from adverse drug events. However, the use of search query volume as a proxy for drug use has yet to be validated. We attempt to validate search volume estimation of drug utilization in three ways: 1) explore seasonal variations in search volume and outpatient utilization, 2) monitor change between substitute drugs following patent expirations and 3) use search volume estimation methods to estimate TB incidence. METHODS: Google Insights normalized search share was used to characterize interest in a drug. The estimates of drug utilization were derived from the Medical Expenditure Panel Survey (MEPS), a nationally representative sample of the US population. Substitute drugs and notable patent expirations between 2004 and 2011 were obtained via pharmacist review. TB incidence was derived from the MMWR yearly Summary of Notifiable Diseases. To validate the assumption that search volume relates to drug utilization, we estimated weekly utilization for 9 drugs (amoxicillin, azelastine, azithromycin, benzomatate, cefdinir, ciprofloxacin, levofloxacin, moxifloxacin and olopatadine) using MEPS for 2004–2009. The weekly utilization volume was cross-correlated with the Google Insights series with lags ranging from −6 to +6 months. To compare the rate of substitution between name brand and generic drugs following the expiration of a patent, we treated the generic drug search volume as the independent variable and the name brand as the dependent variable. Using OLS, we calculated the marginal rate of substitution between the name brand and generic search queries. Preliminary work has focused on substitution of generic simvastatin for branded Zocor. As TB treatment regimens usually include a fixed set of medications (isoniazid, rifampin, pyrazinamide, ethambutol), the utilization of these drugs should correspond with TB incidence. We modeled national TB incidence using OLS with search volume and an indicator for the month of December. The number of reported cases in December is inconsistent with the seasonality of TB in the US and is a significant departure from the expected value given the rest of the series. We suspect this is due to a reporting artifact and include the indicator variable in our model to mitigate the effects of this inconsistency. RESULTS: The seasonality of drug use is reflected in search volume. Only 3 of the 9 drugs (33%, amoxicillin, azithromycin and cefdinir) had enough volume in the MEPS to create a reasonable time series. All 3 drugs had statistically significant positive correlations at lags near 0 and significant negative correlations at lags of +/− 6 months. Amoxicillin, for example, had a significant correlation at lags around 0 of 0.55–0.60 and correlations at a lag of −5 or +5 months of −0.4. The magnitude of this correlation coefficient would suggest that the two series track closely. Patent expirations (and the resulting emergence of generic medications with new names) are apparent in search volume as well. We find a strong negative relationship between search volume for simvastatin and Zocor. Specifically, a one unit increase in search volume for ‘simvastatin’ is associated with a 0.96 (p < 0.0001) unit decrease in the search volume for ‘Zocor.’ The simple model for TB incidence demonstrates the utility of using drugs as queries for disease. Search volume was a significant (p = 0.006) and positive predictor of TB incidence controlling for the December aberrations. CONCLUSIONS: The Google Insights search volume for a set of highly seasonal drugs is highly correlated with community utilization as measured by seasonal variance in utilization, change in search and prescribing patterns and expected prescribing following TB. The ability to estimate use of drugs from search volume presents a new method for keyword selection in search based incidence models and a method to monitor changes in the pharmaceutical market

Uninterrupted Classroom Sitting is Associated with Increased Discomfort and Sleepiness Among College Students

Acute bouts of uninterrupted sitting has been associated with discomfort and fatigue in adult populations. However, little is known regarding the impact of uninterrupted sitting on such outcomes among college students. Understanding these relations would be useful for informing best practice and future interventions. The present study explored the relation between uninterrupted sitting and perceived levels of physical discomfort and sleepiness among college students in a real classroom setting. We recruited 54 undergraduate students enrolled in a single class at a Midwestern university. Participants remained seated throughout a 2.5 h lecture while completing the Stanford Sleepiness Scale (SSS) and General Comfort Scale (GCS) every 15 min. Linear mixed effect model analyses were used to determine the relations between the independent and dependent variables and the duration at which students reported significant impairments in discomfort and/or sleepiness. Classroom sitting time was associated with increases in discomfort (r = 0.28, p &lt; 0.01) and sleepiness (r = 0.30, p &lt; 0.01). Students reported significant impairments in discomfort and sleepiness after 75 and 15 min, respectively. These findings support further research into the acceptability, feasibility and efficacy of interventions designed to interrupt classroom sitting on discomfort, sleepiness and measures of academic performance

Weather-Dependent Risk for Legionnaires’ Disease, United States

Using the Nationwide Inpatient Sample and US weather data, we estimated the probability of community-acquired pneumonia (CAP) being diagnosed as Legionnaires’ disease (LD). LD risk increases when weather is warm and humid. With warm weather, we found a dose-response relationship between relative humidity and the odds for LD. When the mean temperature was 60°–80°F with high humidity (>80.0%), the odds for CAP being diagnosed with LD were 3.1 times higher than with lower levels of humidity (<50.0%). Thus, in some regions (e.g., the Southwest), LD is rarely the cause of hospitalizations. In other regions and seasons (e.g., the mid-Atlantic in summer), LD is much more common. Thus, suspicion for LD should increase when weather is warm and humid. However, when weather is cold, dry, or extremely hot, empirically treating all CAP patients for LD might contribute to excessive antimicrobial drug use at a population level

Rurality modifies the association between symptoms and the diagnosis of amyotrophic lateral sclerosis

We utilized national claims-based data to identify the change in odds of diagnosis of ALS following possible-ALS-symptoms-and whether the change varies in urban/rural areas. Insurance claims were obtained from the Merative MarketScan databases, 2001–2021 in the United States. Individuals with incident ALS were identified and matched on age, sex, and enrollment period to individuals without ALS. For all individuals, claims for 8 possible-ALS-symptoms in the time before any ALS diagnosis were identified. We then used conditional logistic regression to estimate the odds of being diagnosed with ALS following these symptoms and whether the association varied by urban/rural location. 19,226 individuals with ALS were matched to 96,126 controls. Patients with ALS were more likely to live in an urban area (87.0% vs 84.5%). Of those with ALS 84% had 1+ of our 8 possible-ALS-symptom compared to 51% of controls. After adjustment for confounders, having possible-ALS-symptoms increased the odds of a future ALS diagnosis by nearly 5-fold. A dose-response pattern was present with increasing odds as the number of symptoms increased. In all models, urban areas were associated with increased odds of diagnosis with ALS while the effect of having a symptom was smaller in urban places. Urban cases of ALS are diagnosed at younger ages. These results suggest symptoms may appear and be noted years before the diagnosis of ALS. Additionally, rural patients are diagnosed at later ages with a greater dependence on symptoms than urban patients. These results highlight potential improvements for screening for ALS.</p