Relative Expression of Germination Genes SleB, GerAC, and gpr in Heat Treated Bacillus licheniformis and Bacillus subtilis

Endospore-forming bacteria of the genus Bacillus are of significant importance to the food industry. Species from this genus exhibit the ability to form metabolically dormant endospores characterized by resistance to heat, UV, and chemical treatment. Spores have undetectable metabolic activity and remain impervious to the harsh conditions of their environment, but they can detect environmental cues signaling favorable growth conditions and begin the process of germination. Once germination and outgrowth are complete, the fully viable cell is capable of reproducing and forming colonies. The resistance of these endospores has been a topic of decades of research, particularly because of their impact on food processing. Only a few species of Bacillus are actually pathogenic, but many others present quality defects, particularly in milk and other dairy products. This study involved the selection and use of primers specific for GerAC, gpr, and SleB genes to evaluate their relative expression and potential for indicators of lag phase in germination. Gene expression studies with qPCR were carried out during germination in Bacillus subtilis and Bacillus licheniformis spores that were given a heat shock in a tryptic soy broth at 80°C and subsequently incubated for 0, 30, 60, and 120 minutes at their optimal growth temperatures. Expression ratios calculated relative to the samples incubated for 120min (R=1) showed increased expression as germination and outgrowth progressed (GerAC gene on B. licheniformis and B. subtilis; R30min=0.14 and 0.14, R60min=0.76 and 0.51). The different expression levels measured in this preliminary study suggest that the selected genes and methodology merit further optimization to verify the accuracy and significance of the assay as well as its application it to the milk powder process

Preventing Substance Use and Related Negative Outcomes in Jackson County, OR

Goal Statement: The goal of this Social Change Portfolio is to raise awareness of the dangers of certain substances such as fentanyl, increase prevention measures, and reduce overall overdoses in Jackson County for the teen population. Significant Findings: This paper examines substance abuse in Jackson County, Oregon. The county has over 229,000 residents, with over 105 overdoses so far in 2023. Looking at various factors, we can look at what contributes to and protects people from getting involved in substance abuse. Many people need help in Jackson County, but one population in particular is the American Indians and Alaska Natives (AI/AN). Additionally, in order to prevent substance abuse, we need to focus prevention measures on those who would benefit the most, such as adolescents. Objectives/Strategies/Interventions/Next Steps: We can see what is needed to help those in Jackson County by looking at past successful prevention measures. We can also take the risk and protective factors to see where efforts are needed. If we can increase education for adolescents to prevent substance abuse while also increasing protective factors, we can help protect the vulnerable. This can be accomplished by focusing on prevention measures during school times. These would teach the children the consequences of substance abuse, teaching life skills and how to successfully navigate challenges

Prevalence And Health Burden Of Cardiovascular Disease In Older U.s. Veterans: Results From The 2019-2020 National Health And Resilience In Veterans Study

Importance. Cardiovascular disease (CVD) is one of the leading causes of death in the U.S. and is associated with a range of demographic, military, trauma, and clinical characteristics and physical and mental health conditions. Older military veterans may have an increased risk for CVD, given their advanced age and military experiences. However, the prevalence and health burden of CVD in population-based samples has not been well characterized. Objective. To characterize the current prevalence of CVD, and its association with sociodemographic, military, trauma, and clinical variables in a large, contemporary, and nationally representative sample of older U.S. veterans. Design. Cross-sectional study of 3,001 older U.S. military veterans (age 60 and older) using data from the 2019-2020 National Health and Resilience in Veterans Study (NHRVS). Main Outcomes. Veterans were classified according to lifetime CVD status (CVD or no CVD [health care professional diagnoses of heart disease, heart attack, and/or stroke]). To determine the association of CVD with health status, a comprehensive range of mental and physical health variables were assessed using validated self-report assessments. Results. 25.5% of veterans reported having been diagnosed with CVD. Greater age, cumulative trauma burden, nicotine use disorder, and diagnoses of hypertension, high cholesterol, and diabetes were associated with CVD. CVD was independently associated with a range of mental (odds ratios [ORs]= 1.53-2.27) and physical (ORs=1.53-3.43) health conditions. Conclusions and Relevance. 1 in 4 older U.S. veterans reported having been diagnosed with CVD in their lifetimes. CVD was independently associated with a broad range of demographic, clinical, physical, and mental health variables in U.S. veterans, suggesting that CVD is linked to multiple health outcomes. Results highlighted the importance of CVD for prevention and intervention efforts in the older U.S. veteran population

Nurse Practitioner Led Identification and Treatment of Knee Pain Severity Based on Evidence Classification Protocols

Title: Nurse Practitioner Led Identification and Treatment of Knee Pain Severity Based on Evidence Classification Protocols Background: Knee pain has become the 10th leading office visit in the United States. Prevalence of knee pain has increased 65% in the past 20 years accounting for approximately 4 million clinic visits every year. One out of five men and one out of four women in the United States suffers from knee pain. Treatment protocols in actuality are based on physical therapy, pharmacological treatment, or surgical management. However, research has demonstrated that knee pain and progression of knee related illnesses may be prevented by diet, weight control, knee exercises, and early treatment intervention. Purpose of Project: a) To determine the level of knee pain severity after administration of the Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire; b) To increase knee pain management knowledge by at least 50% in a 2-month period. EBP Model/ Framework: The John Hopkins Model was used to guide this project. Evidence Based Intervention(s): The WOMAC questionnaire was provided to every patient presenting to the clinic with a complaint of knee pain. Printed material on knee pain management and resources were provided based on WOMAC Scores. Evaluation/ Results: A total of eighteen patients received knee pain management educational material. Fourteen respondents expressed an increase in knowledge on how to properly manage knee pain. One respondent expressed no benefit, and three respondents were not able to be reached by phone. Implications on Practice: Early non-surgical interventions may contribute to prevention and a better management of knee pain. Early detection and management will improve quality of life, decrease progression, and decrease clinic visits. Conclusion: The WOMAC instrument is a reliable and validated tool that has been utilized in numerous research trials as an assessment tool for different knee conditions. Implementation of the WOMAC tool on a primary care facility will assist on obtaining specific information related to knee pain to ensure that patients are provided with the most up to date research information

Forward Invariant Cuts to Simplify Proofs of Safety

The use of deductive techniques, such as theorem provers, has several advantages in safety verification of hybrid sys- tems; however, state-of-the-art theorem provers require ex- tensive manual intervention. Furthermore, there is often a gap between the type of assistance that a theorem prover requires to make progress on a proof task and the assis- tance that a system designer is able to provide. This paper presents an extension to KeYmaera, a deductive verification tool for differential dynamic logic; the new technique allows local reasoning using system designer intuition about per- formance within particular modes as part of a proof task. Our approach allows the theorem prover to leverage for- ward invariants, discovered using numerical techniques, as part of a proof of safety. We introduce a new inference rule into the proof calculus of KeYmaera, the forward invariant cut rule, and we present a methodology to discover useful forward invariants, which are then used with the new cut rule to complete verification tasks. We demonstrate how our new approach can be used to complete verification tasks that lie out of the reach of existing deductive approaches us- ing several examples, including one involving an automotive powertrain control system.Comment: Extended version of EMSOFT pape

Faster Constraint Solving Using Learning Based Abstractions

This work addresses the problem of scalable constraint solving. Our technique combines traditional constraint-solving approaches with machine learning techniques to propose abstractions that simplify the problem. First, we use a collection of heuristics to learn sets of constraints that may be well abstracted as a single, simpler constraint. Next, we use an asymmetric machine learning procedure to abstract the set of clauses, using satisfying and falsifying instances as training data. Next, we solve a reduced constraint problem to check that the learned formula is indeed a consequent (or antecedent) of the formula we sought to abstract, and finally we use the learned formula to check the original property. Our experiments show that our technique allows improved handling of constraint solving instances that are slow to complete on a conventional solver. Our technique is complementary to existing constraint solving approaches, in the sense that it can be used to improve the scalability of any existing tool

Full-Scale Turbofan Engine Noise-Source Separation Using a Four-Signal Method

Contributions from the combustor to the overall propulsion noise of civilian transport aircraft are starting to become important due to turbofan design trends and expected advances in mitigation of other noise sources. During on-ground, static-engine acoustic tests, combustor noise is generally sub-dominant to other engine noise sources because of the absence of in-flight effects. Consequently, noise-source separation techniques are needed to extract combustor-noise information from the total noise signature in order to further progress. A novel four-signal source-separation method is applied to data from a static, full-scale engine test and compared to previous methods. The new method is, in a sense, a combination of two- and three-signal techniques and represents an attempt to alleviate some of the weaknesses of each of those approaches. This work is supported by the NASA Advanced Air Vehicles Program, Advanced Air Transport Technology Project, Aircraft Noise Reduction Subproject and the NASA Glenn Faculty Fellowship Program