Antibodies targeting BDNF reduced pain-like behavior in rat and mouse models of neuropathic pain . In rat models of OA, intra-articular BDNF injection exacerbated pain behavior, whereas sequestration of BDNF with TrkB-Fc antibodies reversed pain . These results further indicate the contribution of the BDNF/TrkB pathway in chronic pain and its potential as therapeutic target. Finally, the latest emerging target for pain is the gut microbiota . These microbes may modulate inflammatory response –associated pain both in the PNS and CNS and thus offer numerous therapeutic targets for chronic pain . Therefore, chronic pain management requires multiple treatment targets. Yaksh and colleagues have summarized other potential regimens . Pain management should thus involve a multidisciplinary approach and vision, combining pharmacological therapies with non pharmacological and self-management strategies. Current pharmacological management of chronic pain is mostly symptomatic, not disease-modifying, and shows only limited efficacy and many adverse effects. A common finding is the low effect sizes of all monomodal treatment strategies, irrespective of medical, psychological, or physiotherapeutic approaches. New treatment strategies are urgently needed. At the same time, risk factors for the development of chronic pain are often ignored. In this review, we focused specifically on therapeutic strategies involving neuropeptide mediators of neurogenic inflammation. Research has targeted inhibiting neuropeptides such as CGRP, SP, and NGF or their receptors,drying racks with varying degrees of success. As several molecules come into action during neurogenic inflammation and chronic pain, redundancy in these molecules can limit the action of targeted treatments.

Pharmacological regimens, strategies to modify risk factors, and in vestment in prevention are of paramount importance.In addition, identification of new biomarkers could promote the development of new analgesics . Finally, although most countries offer a limited multimodal and interdisciplinary care for chronic pain, the healthcare system should encourage a holistic and collaborative approach to providing better care to patients suffering from chronic pain. Perseverance in research, education, and advocacy are the main instruments to leverage in improving management for millions of patients with chronic pain. Prior to the start of the 2014 legislative session, there were a number of positive signs related to the health of the state’s economy. Utah typically grows more rapidly than the nation after a recession and that pattern held after the Great Recession . In 2013, U.S. employment grew at 1.6 percent compared to 3.3 percent for Utah . The state’s unemployment rate also improved to 4.8 per cent down from 5.7 percent in 2012 . Additional bright spots for the state included improvements in personal income, growth in construction, and increases in taxable sales. Total personal income in 2013 was estimated to be $105.2 billion. Utah’s estimated 2013 percapita income was $36,308, up 2.5 percent from 2012. Going into 2014, as the economy continued to recovery, personal income was expected to in crease to 5.3 percent . The construction industry also showed continued improvement since the recession. The value of permit-authorized construction was estimated at $4.7 billion in 2014 . Total taxable sales were estimated to be $49.78 billion in 2013. Taxable sales include retail trade, business investment and utilities, and taxable services . Overall, the economy in 2013 had improved and was expected to continue to improve in 2014, all of which had an impact on the revenue estimates that were used during the 2014 session. In 2014 the Utah Legislature implemented a significant process change for budgeting.

They established the first week of the session to be the “Base Budget Week,” during which only appropriation committee meetings would be held. All other committees are now delayed for seven days. During the Base Budget Week, legislators scrutinize the base budgets, while saving the al location of new revenue for later in the session. Establishing the Base Budget Week involved more work for the legislative analyst’s staff up front, but it was valuable for both legislators and the staff through more effective use of time for legislators, and with increased efficiencies for the staff. A time analysis of previous sessions determined that several legislative standing committee meetings were cancelled or the time was not well-used. This year, legislators and drafting attorneys had another week to prepare legislation resulting in more bills done by the time standing committees started meeting. The budget week change also resulted in high engagement from legislators in the budgeting processes as subcommittees led the processes, not just leadership. Another reason for front loading the budget process was to improve efficiencies for staff. The analyst’s office likes to measure outcomes. In reviewing staff time, they found that the analyst’s office gets slammed with fiscal notes around day 20, when legislators have to have bills numbered or abandon them. By moving the base-budgeting to the first week of the session, fiscal analysts weren’t staffing subcommittees when the large number of bills came all at that one time. The office had a goal of 95 percent of fiscal notes on-time and had only achieved that goal in 2013 . In 2014, with the budget schedule change and some new technology, the office was on-time 99.5 percent of the time. The result of the Base Budget week was identifying $70 million in offsets within base budgets.

A few notable adjustments in the 2014 session had an impact on the budgeting process. HB 311 requires the Legislative Fiscal Analyst and Governor’s Office of Management and Budget to produce 15-year trend analyses alongside traditional point-in-time revenue estimates. HJR 11 asks that legislators consider using above trend revenue for one-time costs like buildings and roads, debt reduction, or rainy day deposits. The legislature also recognized unfunded liabilities in two areas and addressed those with legislation. The first is post employment benefits. SB 10 funded a new 401k benefit that ends defined OPEB benefits for state employees. The second area is leave time for state employees. SB 269 requires a new Annual Leave II program for state employees—annual leave costs will be sunk at time of accrual rather than at time of use/separation from employment, addressing an $85 million unfunded liability. Just prior to the 2014 General Session, the legislature held the first of its kind long-term policy and budget planning conference. The 1st Biennial Legislative Policy Summit, hosted by the University of Utah’s David Eccles School of Business, focused on how underlying economic and demographic changes will influence Utah’s future public policy environment. Members from both the house and senate met together for a full day to look beyond the two-year election cycle and talk about infrastructure, economic, and education policy modifications necessary to meet Utah’s changing socioeconomic make-up. Future conferences were assured by the passage of House Joint Resolution 10 “Joint Rules Resolution Regarding a Long-Term Planning Conference,” during the 2014 General Session. Tobacco dependence is particularly concerning in adolescence, when the developing brain is especially vulnerable and dependence symptoms may arise after minimal exposure.Presently, electronic cigarettes , which provide pulmonary nicotine and therefore possess high dependence potential,are the most popular tobacco product among US youth.The occurrence of e-cigarette dependence symptoms and their association with nicotine exposure have been documented; however,cannabis drying foundational evidence on the symptom presentation, prevalence, and subgroups at elevated risk of e-cigarette dependence among youth is lacking, as is information on its association with future e-cigarette use, to our knowledge. The objective of this prospective cohort study was to examine the prevalence and symptom expression of e-cigarette dependence and its association with future e-cigarette use among past year e-cigarette users aged 16 to 18 years in Southern California. Specifically, we examined similarities and differences in prevalence and symptom expression between e-cigarette dependence and combustible cigarette dependence among youth, the prevalence of e-cigarette dependence symptoms stratified by subgroups presumed to be at elevated risk , and associations of baseline e-cigarette dependence with subsequent vaping continuation, frequency, and intensity patterns 6 months later. This study aims to provide foundational descriptive evidence on the expression and progression of e-cigarette dependence as a potential presentation of tobacco use disorder among youth.

Such evidence could help establish whether e-cigarette dependence is a health outcome of e-cigarette use that should be considered in federal regulatory decisions that weigh the relative harms and benefits of e-cigarettes.Data were drawn from the Happiness & Health Study,a prospective cohort study of behavioral health. All ninth-grade students in 10 participating public high schools in Los Angeles County, California, in 2013 were eligible. Semiannual in-classroom assessments were administered from 2013 to 2017. Students who were not in class on survey days completed abbreviated surveys, which excluded dependence measures. Data on e-cigarette dependence were first collected in the fall 12th grade survey in 2016, which was considered baseline; follow-up data were collected in the spring of 12th grade, approximately 6 months later, in 2017. The University of Southern California Institutional Review Board approved this study. Participants provided active assent and a parent or legal guardian provided written or verbal informed consent prior to study enrollment. This study is reported according to Strengthening the Reporting of Observational Studies in Epidemiology reporting guideline.At baseline, tobacco product dependence symptoms were measured using the Hooked on Nicotine Checklist,which was originally developed to measure combustible cigarette dependence and has demonstrated adequate psychometric properties. Students reported whether they had ever experienced each of 10 dependence symptoms for e-cigarettes and combustible cigarettes separately. Electronic cigarette and combustible cigarette dependence items were identically worded, except for substitution of e-cigarette and vaping terms for cigarette and smoking. Endorsing 1 or more symptoms indicated that the participant screened positive for dependence.Students presenting 2 or more or 3 or more total symptoms of e-cigarette or combustible cigarette dependence symptoms were also classified.At baseline, use of e-cigarettes with nicotine and e-cigarettes without nicotine or cannabis oil were measured as yes-or-no questions.Affirmative responses to either or both questions over the past year were used to classify past-year any e-cigarette use , which was necessary for sample inclusion. Past-month vaping and past-year vaping of e-cigarettes that contained nicotine were also assessed. We assessed baseline past-year combustible cigarette smoking using items from previously derived epidemiologic surveys.Vaping continuation was operationalized as any past 6-month use of e-cigarettes at follow-up. Additional survey items assessed past 30-day nicotine vaping frequency and intensity, including number of nicotine vaping sessions per vaping day and puffs per nicotine vaping session.We collected several additional measures to describe the sample and assess risk factors for e-cigarette dependence to be included in an e-cigarette propensity score covariate. These variables may have also influenced e-cigarette use progression patterns and therefore confounded associations between e-cigarette dependence and future use. Participants reported age at e-cigarette use initiation. The following tobacco product use characteristics were measured: past 30-day number of days smoked cigarettes , cigarettes smoked per day on smoking days , and ever use of cigars, hookah, or smokeless tobacco .Participants reported ever use of alcohol, combustible cannabis, vaporized cannabis, or other drugs using questions derived from previously validated items.To assess a potential association of mental health with e-cigarette dependence and future use, we measured symptoms of major depressive disorder, generalized anxiety disorder, social phobia, panic disorder, obsessive-compulsive disorder, manic symptoms, attention-deficit/hyperactivity disorder, and conduct disorder symptoms .Additionally, age, sex , self-reported race/ethnicity and highest level of parental education were surveyed, per past work.After descriptive analyses, we reported prevalence of e-cigarette dependence and prevalence of the 10 specific dependence symptoms among all past-year e-cigarette users and by combustible cigarette use status. Among past-year e-cigarette and combustible cigarette dual users, McNemar tests for within-participant comparisons were used to conduct cross– tobacco product comparisons of e-cigarette dependence, combustible cigarette dependence, and individual symptoms. Prevalence of e-cigarette dependence symptoms was compared across binary sub-classifications of past-year vaping of e-cigarettes with nicotine, past-month vaping , and past-year combustible cigarette and e-cigarette dual use using χ2 tests. For descriptive data, prevalence of meeting 2 or more or 3 or more symptom thresholds were also reported. The prospective association of baseline e-cigarette dependence symptom status with nicotine vaping status at follow-up was tested using binary logistic regression. Prospective associations of baseline e-cigarette dependence symptom status with nicotine vaping frequency and intensity at follow-up were tested using negative binomial regression models. All regressions included baseline status of each respective outcome as a covariate.