Modeling the evolution of the US opioid crisis for national policy development.

The opioid crisis is a major public health challenge in the United States, killing about 70,000 people in 2020 alone. Long delays and feedbacks between policy actions and their effects on drug-use behavior create dynamic complexity, complicating policy decision-making. In 2017, the National Academies of Sciences, Engineering, and Medicine called for a quantitative systems model to help understand and address this complexity and guide policy decisions. Here, we present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), a dynamic simulation model developed in response to that charge. SOURCE tracks the US population aged ≥12 y through the stages of prescription and illicit opioid (e.g., heroin, illicit fentanyl) misuse and use disorder, addiction treatment, remission, and overdose death. Using data spanning from 1999 to 2020, we highlight how risks of drug use initiation and overdose have evolved in response to essential endogenous feedback mechanisms, including: 1) social influence on drug use initiation and escalation among people who use opioids; 2) risk perception and response based on overdose mortality, influencing potential new initiates; and 3) capacity limits on treatment engagement; as well as other drivers, such as 4) supply-side changes in prescription opioid and heroin availability; and 5) the competing influences of illicit fentanyl and overdose death prevention efforts. Our estimates yield a more nuanced understanding of the historical trajectory of the crisis, providing a basis for projecting future scenarios and informing policy planning.

Unspoken Truths: Mental Health Among Academic Surgeons.

OBJECTIVE: To characterize the current state of mental health within the surgical workforce in the United States. BACKGROUND: Mental illness and suicide is a growing concern in the medical community; however, the current state is largely unknown. METHODS: Cross-sectional survey of the academic surgery community assessing mental health, medical error, and suicidal ideation. The odds of suicidal ideation adjusting for sex, prior mental health diagnosis, and validated scales screening for depression, anxiety, post-traumatic stress disorder (PTSD), and alcohol use disorder were assessed. RESULTS: Of 622 participating medical students, trainees, and surgeons (estimated response rate=11.4%-14.0%), 26.1% (141/539) reported a previous mental health diagnosis. In all, 15.9% (83/523) of respondents screened positive for current depression, 18.4% (98/533) for anxiety, 11.0% (56/510) for alcohol use disorder, and 17.3% (36/208) for PTSD. Medical error was associated with depression (30.7% vs. 13.3%, P <0.001), anxiety (31.6% vs. 16.2%, P =0.001), PTSD (12.8% vs. 5.6%, P =0.018), and hazardous alcohol consumption (18.7% vs. 9.7%, P =0.022). Overall, 13.2% (73/551) of respondents reported suicidal ideation in the past year and 9.6% (51/533) in the past 2 weeks. On adjusted analysis, a previous history of a mental health disorder (aOR: 1.97, 95% CI: 1.04-3.65, P =0.033) and screening positive for depression (aOR: 4.30, 95% CI: 2.21-8.29, P <0.001) or PTSD (aOR: 3.93, 95% CI: 1.61-9.44, P =0.002) were associated with increased odds of suicidal ideation over the past 12 months. CONCLUSIONS: Nearly 1 in 7 respondents reported suicidal ideation in the past year. Mental illness and suicidal ideation are significant problems among the surgical workforce in the United States.

Correlation of miR-155-5p, KRAS, and CREB Expression in Patients with Acute Myeloid Leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is a type of blood cancer involving numerous aberrant genes and microRNAs. MiRNAs are non-coding sequences that have been proven to be players in the biological processes of various cancers. The present study is designed to illustrate the relationship between miR-155, KRAS, and CREB. METHODS: This case-control study was conducted on 21 patients with AML and 9 healthy individuals. The expressions of miR-155, KRAS, and CREB were measured using RT-PCR. Demographic data were extracted from the documents of individuals. SPSS and GraphPad Prism software were used to analyze the data. RESULTS: The expression of miR-155 in patients with AML was 35 times higher than in the control group (p < 0.0001). Also, CREB fold change increased by 1.92-fold in patients compared to the controls (p = 0.034), but no difference in KRAS was observed between the control and AML groups (p > 0.05). There was no change in miR-155, CREB, and KRAS expression based on gender, age, and blast percentage (p > 0.5). Nevertheless, there was a direct correlation between CREB and KRAS expressions (p = 0.0002). Our result showed that overexpression of CREB and KRAS would cause an increase in white blood cells (WBCs) (p = 0.001, 0.045 respectively), but there was no correlation between miR-155 with WBCs (p > 0.5). CONCLUSIONS: Our study revealed that miR-155 and CREB had overexpression compared to the control group.

State-level racial and ethnic disparities in buprenorphine treatment duration in the United States.

BACKGROUND AND OBJECTIVES: National trends reveal a concerning escalation in racial and ethnic disparities in buprenorphine treatment duration for opioid use disorder. However, the extent of such disparities at the state level remains largely unexplored. This study aims to examine such disparities at the state level. METHODS: We analyzed 9,040,620 buprenorphine prescriptions dispensed between January 2011 and December 2020 from IQVIA Longitudinal Prescription data. The primary outcome was the difference in median treatment duration between White people and racial and ethnic minorities. We also included a second outcome measurement to quantify the difference in median treatment duration among episodes lasting ≥180 days. Using quantile regressions, we examined racial and ethnic disparities in treatment duration, adjusting for the patient's age, sex, payment type, and calendar year of the treatment episode. All analyses were conducted at the state level. RESULTS: Our study revealed substantial statewide variations in racial and ethnic disparities. Specifically, 21 states showed longer treatment durations for White people across all episodes, and eight states displayed similar trends among episodes lasting ≥180 days. Five states exhibited longer treatment durations for White people in both overall and long-term episodes. Fifteen states showed no racial and ethnic disparities. CONCLUSION AND SCIENTIFIC SIGNIFICANCE: These results are among the first to indicate substantial statewide variations in racial and ethnic disparities in buprenorphine treatment episode duration, providing a critical foundation for targeted interventions to enhance buprenorphine treatment, especially in states confronting such pronounced racial and ethnic disparities.

Severity of adipose tissue dysfunction is associated with progression of pre-diabetes to type 2 diabetes: the Tehran Lipid and Glucose Study.

BACKGROUND: The association of prediabetes (Pre-DM) regression and progression with visceral adiposity index (VAI) and adipose tissue dysfunction (ATD) remains to be investigated. METHODS: The present cohort study was conducted within the framework of the Tehran Lipid and Glucose Study (TLGS) on 1458 Pre-DM cases (aged ≥ 21 years) who were followed for nine years. VAI was estimated based on waist circumference, body mass index, triglycerides, and high-density lipoprotein cholesterol. ATD status (i.e., absent, mild-moderate, and severe) was defined based on the age-stratified cutoff values of VAI. Multinomial logistic regression models with adjustment of potential confounders were used to estimate the chance of Pre-DM regression to normoglycemia or progression to T2D across ATD status. RESULTS: During the study follow-up, 39.0% of the participants developed T2D, and 37.7% returned to normoglycemia. Compared to mild-moderate ATD, Pre-DM subjects with severe ATD had a higher risk of developing T2D by 45% (OR = 1.45, 95% CI = 11.08-1.93). Severe ATD was also associated with a decreased chance of returning to normoglycemia by 26% (OR = 0.74, 95% CI = 0.55-0.99). Participants with severe ATD had significantly higher fasting (overall mean = 111, 95% CI = 109-112 vs. 106, 95% CI = 105-108 mg/dL) and 2h-serum glucose (overall mean = 165, 95% CI = 161-168 vs. 153, 95% CI = 149-156 mg/dL) concentrations over time. CONCLUSION: Severe ATD was associated with an elevated risk of developing T2D and longitudinal poor-glycemic controls in Pre-DM subjects. ATD may be a simple and useful index for detecting subjects at a higher risk of Pre-DM progression to T2D, allowing for timely intervention strategies.

The association of dietary carbohydrate quality and quantity with obesity among Iranian adolescents: a case-control study.

BACKGROUND: Adolescent obesity is considered as a major health concern worldwide which is closely linked to the quality of diet. The purpose of the present study was to assess the carbohydrate quality and quantity in relation to odds of overweight and obesity in adolescents. METHODS: This case-control study with a 1:1 ratio was conducted on 406 adolescents (14 to 18 years old) matched for age and gender. Participants were selected by multistage cluster random sampling method from March to October 2019 in Shiraz, Iran. Dietary intakes of the study population were assessed by a validated semi-quantitative food frequency questionnaire. Also anthropometric indices were measured using standard methods and demographic information was recorded via face to face interview. The relation between low carbohydrate diet score (LCDS) and carbohydrate quality index (CQI), and odds of obesity was evaluated by multiple Logistic regression. RESULTS: After adjusting the role of potential confounders, the participants in the third tertiles of LCDS (OR = 0.443, 95% CI = (0.260 to 0.755)) and CQI (OR = 0.005, 95% CI = (0.001 to 0.025)) had less odds of being overweight and obese compared to the first tertile. CONCLUSION: The present study found an inverse relationship between dietary quantity and quality of carbohydrate intake and the odds of overweight and obesity in a sample of Iranian adolescents.

Planning, implementing and governing systems-based co-creation: the DISCOVER framework.

BACKGROUND: Increasingly, public health faces challenges requiring complex, multifaceted and multi-sectoral responses. This calls for systems-based approaches that facilitate the kind of collective and collaborative thinking and working required to address complexity. While the literature on systems thinking, system dynamics and the associated methodologies is extensive, there remains little clear guidance on how to plan, govern and implement participatory systems approaches within a co-creation process. METHODS: We used a three-step process to develop DISCOVER, a framework for implementing, and governing systems-based co-creation: Stage 1: We conducted a literature analysis of key texts to identify well-documented methods and phases for co-creation using a systems approach, as well as areas where gaps existed. Stage 2: We looked for the most appropriate methods and approaches to fill the gaps in the knowledge production chain. Stage 3: We developed the framework, identifying how the different tools and approaches fit together end-to-end, from sampling and recruiting participants all the way through to responding with an action plan. RESULTS: We devised DISCOVER to help guide researchers and stakeholders to collectively respond to complex social, health and wider problems. DISCOVER is a strategic research planning and governance framework that provides an actionable, systematic way to conceptualise complex problems and move from evidence to action, using systems approaches and co-creation. In this article, we introduce the eight-step framework and provide an illustrative case study showcasing its potential. The framework integrates complementary approaches and methods from social network analysis, systems thinking and co-creation literature. The eight steps are followed sequentially but can overlap. CONCLUSIONS: DISCOVER increases rigour and transparency in system approaches to tackling complex issues going from planning to action. It is being piloted in environmental health research but may be suitable to address other complex challenges and could be incorporated into research proposals and protocols for future projects.

Dynamics of colorectal cancer screening in low and middle-income countries: A modeling analysis from Thailand.

BACKGROUND: Low and middle-income countries face constraints for early colorectal cancer (CRC) detection, including restricted access to care and low colonoscopy capacity. Considering these constraints, we studied strategies for increasing access to early CRC detection and reducing CRC progression and mortality rates in Thailand. METHODS: We developed a system dynamics model to simulate CRC death and progression trends. We analyzed the impacts of increased access to screening via fecal immunochemical test and colonoscopy, improving access to CRC diagnosis among symptomatic individuals, and their combination. RESULTS: Projecting the status quo (2023-2032), deaths per 100K people increase from 87.5 to 115.4, and CRC progressions per 100K people rise from 131.8 to 159.8. In 2032, improved screening access prevents 2.5 CRC deaths and 2.5 progressions per 100K people, with cumulative prevented 7K deaths and 9K progressions, respectively. Improved symptom evaluation access prevents 7.5 CRC deaths per 100K with no effect on progression, totaling 35K saved lives. A combined approach prevents 9.3 deaths and 1.8 progressions per 100K, or 41K and 7K cumulatively. The combined strategy prevents most deaths; however, there is a tradeoff: It prevents fewer CRC progressions than screening access improvement. Increasing the current annual colonoscopy capacity (200K) to sufficient capacity (681K), the combined strategy achieves the best results, preventing 15.0 CRC deaths and 10.3 CRC progressions per 100K people, or 54K and 30K cumulatively. CONCLUSION: Until colonoscopy capacity increases, enhanced screening and symptom evaluation are needed simultaneously to curb CRC deaths, albeit not the best strategy for CRC progression prevention.

Social vulnerability predictors of drug poisoning mortality: A machine learning analysis in the United States.

BACKGROUND AND OBJECTIVES: Drug poisoning is a leading cause of unintentional deaths in the United States. Despite the growing literature, there are a few recent analyses of a wide range of community-level social vulnerability features contributing to drug poisoning mortality. Current studies on this topic face three limitations: often studying a limited subset of vulnerability features, focusing on small sample sizes, or solely including local data. To address this gap, we conducted a national-level analysis to study the impacts of several social vulnerability features in predicting drug mortality rates in the United States. METHODS: We used machine learning to investigate the role of 16 social vulnerability features in predicting drug mortality rates for US counties in 2014, 2016, and 2018-the most recent available data. We estimated each vulnerability feature's gain relative contribution in predicting drug poisoning mortality. RESULTS: Among all social vulnerability features, the percentage of noninstitutionalized persons with a disability is the most influential predictor, with a gain relative contribution of 18.6%, followed by population density and the percentage of minority residents (13.3% and 13%, respectively). Percentages of households with no available vehicles, mobile homes, and persons without a high school diploma are the following features with gain relative contributions of 6.3%, 5.8%, and 5.1%, respectively. CONCLUSION AND SCIENTIFIC SIGNIFICANCE: We identified social vulnerability features that are most predictive of drug poisoning mortality. Public health interventions and policies targeting vulnerable communities may increase the resilience of these communities and mitigate the overdose death and drug misuse crisis.

The Antibacterial Effect of Ciprofloxacin Loaded Calcium Carbonate (CaCO3) Nanoparticles Against the Common Bacterial Agents of Osteomyelitis.

The present study aimed to investigate the biocompatibility, antibacterial/anti-biofilm effects of ciprofloxacin-loaded calcium carbonate (Cip- loaded CaCO3) nanoparticles against the common organisms responsible for osteomyelitis. The antibacterial and biofilm inhibitory activities were studied by determination of minimum inhibitory concentrations (MICs) and minimum biofilm inhibitory concentrations (MBICs), respectively. Hemolytic effects were determined for studying hemocompatibility. The SDS-PAGE method was used to study the interaction of Cip- loaded CaCO3 with plasma proteins. The effects of Cip- loaded CaCO3 on the cell viability of human bone marrow mesenchymal stem cells (hBM-MSCs) was detected. The Cip- loaded CaCO3 nanoparticles were shown a significant antimicrobial effect at lower concentrations than free ciprofloxacin. No significant hemolytic effect was observed. The Cip- loaded CaCO3 nanoparticles have shown interaction with apolipoprotein A1 (28 kDa) and albumin (66.5 kDa). The viability of hBM-MSCs treated with Cip- loaded CaCO3 was more than 96%. Our results indicated that Cip-loaded CaCO3 nanoparticles had favorable in vitro compatibility with human red blood cells, antimicrobial effects, and low cytotoxicity.

Dietary sodium to potassium ratio is an independent predictor of cardiovascular events: a longitudinal follow-up study.

BACKGROUND: The current prospective cohort study aimed to explore the potential associations between dietary sodium (Na), potassium (K), and sodium-to-potassium (Na-to-K) ratio with an incidence risk of cardiovascular disease (CVD) among Iranian adults. METHODS: The participants of the Tehran Lipid and Glucose Study (men and women aged 30-84 years, n = 2050), free of CVD at baseline (2006-2008) were included. Dietary intakes were assessed using a validated food frequency questionnaire (FFQ), and incident CVD (i.e., coronary heart disease, stroke, and CVD mortality) were documented up to March 2018. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence interval (CI) regarding the association between dietary Na, K, and Na-to-K ratio with CVD events. RESULTS: During a median follow-up of 10.6 years, 10.14% of participants experienced CVD outcomes. A 41% increased risk of CVD in relation to each increase in 1000 mg/d of Na intake. In the fully-adjusted model, higher Na intake (> 4143 versus < 3049 mg/d) was significantly related to the increased risk of CVD (HR = 1.99, 95% CI = 1.06-3.74). Independent of the well-known risk factors, a 56% reduced risk of CVD was observed in the participants with a higher dietary K intake (HR = 0.44, 95% CI = 0.20-0.94). A Higher Na-to-K ratio was associated with an increased risk of CVD (HR = 1.99, 95% CI = 1.13-3.52). CONCLUSION: Our study showed that the Na-to-K ratio might independently predict future risk of CVD events in adults.

Evolution and Reproducibility of Simulation Modeling in Epidemiology and Health Policy Over Half a Century.

Simulation models are increasingly being used to inform epidemiologic studies and health policy, yet there is great variation in their transparency and reproducibility. In this review, we provide an overview of applications of simulation models in health policy and epidemiology, analyze the use of best reporting practices, and assess the reproducibility of the models using predefined, categorical criteria. We identified and analyzed 1,613 applicable articles and found exponential growth in the number of studies over the past half century, with the highest growth in dynamic modeling approaches. The largest subset of studies focused on disease policy models (70%), within which pathological conditions, viral diseases, neoplasms, and cardiovascular diseases account for one-third of the articles. Model details were not reported in almost half of the studies. We also provide in-depth analysis of modeling best practices, reporting quality and reproducibility of models for a subset of 100 articles (50 highly cited and 50 randomly selected from the remaining articles). Only 7 of 26 in-depth evaluation criteria were satisfied by more than 80% of samples. We identify areas for increased application of simulation modeling and opportunities to enhance the rigor and documentation in the conduct and reporting of simulation modeling in epidemiology and health policy.

A Systematic Review of Simulation Models to Track and Address the Opioid Crisis.

The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models are a tool to help us understand and address thiscomplex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings; created a database of model parameters used for model calibration; and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and agent-based models (16%). Intervention cost-effectiveness was evaluated in 40% of the studies, and 39% focused on services for people with opioid use disorder (OUD). In 61% of the eligible articles, authors discussed calibrating their models to empirical data, and in 31%, validation approaches used in the modeling process were discussed. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation or relapse, emergency medical services, and death parameters. From this database, potential model inputs can be identified and models can be compared with prior work. Simulation models should be used to tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.

Health-related quality of life in cancer immunotherapy: a systematic perspective, using causal loop diagrams.

PURPOSE: System science offers a unique set of tools, including causal loop diagrams (CLDs), for stakeholders to better grasp the complexity of factors surrounding quality of life. Because the health-related quality of life (HRQoL) of cancer immunotherapy patients exists within an intricate system affected by and affecting many factors across multiple dimensions, the development of a systems-level model can provide a powerful framework to aid the understanding of this complexity. We developed a CLD for HRQoL of cancer immunotherapy patients. METHODS: We first applied a literature-based approach to construct a CLD for patients following immunotherapy. We then iteratively reviewed and enhanced the CLD through interviews with subject matter experts. RESULTS: Based on the reviewed literature and subject matter expert input, we produced a CLD representing the system surrounding cancer immunotherapy patients' HRQoL. Several feedback loops are identified that span clinical experiences, oncology teams' perceptions about immunotherapy, social support structures, and further research and development in cancer immunotherapy, in addition to other components. The CLD enables visualization of thought experiments regarding how a change anywhere in the system can ultimately worsen or improve patients' HRQoL. CONCLUSION: The CLD illustrates the valuable contribution of a systems perspective to quality-of-life research. This systems-based qualitative representation gives insight on strategies to inhibit harmful effects, enhance beneficial effects, and inherent tradeoffs within the system. The CLD identifies gaps in the literature and offers a communication tool for diverse stakeholders. Our research method provides an example for studying the complexities of quality of life in other health domains.

Impact of Florida's prescription drug monitoring program on drug- related fatal vehicle crashes: a difference-in-differences approach.

BACKGROUND: Prescription drug use has soared in the USA within the last two decades. Prescription drugs can impair motor skills essential for the safe operation of a motor vehicle, and therefore can affect traffic safety. As one of the epicentres of the opioid epidemic, Florida has been struck by high opioid misuse and overdose rates, and has concurrently suffered major threats to traffic disruptions safety caused by driving under the influence of drugs. To prevent prescription opioid misuse in Florida, Prescription Drug Monitoring Programs (PDMPs) were implemented in September 2011. OBJECTIVE: To examine the impact of Florida's implementation of a mandatory PDMP on drug-related MVCs occurring on public roads. METHODS: We employed a difference-in-differences approach to estimate the difference in prescription drug-related fatal crashes in Florida associated with its 2011 PDMP implementation relative to those in Georgia, which did not use PDMPs during the same period (2009-2013). The analyses were conducted in 2020. RESULTS: In Florida, there was a significant decline in drug-related vehicle crashes during the 22 months post-PDMP. PDMP implementation was associated with approximately two (-2.21; 95% CI -4.04 to -0.37; p<0.05) fewer prescribed opioid-related fatal crashes every month, indicating 25% reduction in the number of monthly crashes. We conducted sensitivity analyses to investigate the impact of PDMP implementation on central nervous system depressants and stimulants as well as cocaine and marijuana-related fatal crashes but found no robust significant reductions. CONCLUSIONS: The implementation of PDMPs in Florida provided important benefits for traffic safety, reducing the rates of prescription opioid-related vehicle crashes.

Advances in Aptamers-Based Applications in Breast Cancer: Drug Delivery, Therapeutics, and Diagnostics.

Aptamers are synthetic single-stranded oligonucleotides (such as RNA and DNA) evolved in vitro using Systematic Evolution of Ligands through Exponential enrichment (SELEX) techniques. Aptamers are evolved to have high affinity and specificity to targets; hence, they have a great potential for use in therapeutics as delivery agents and/or in treatment strategies. Aptamers can be chemically synthesized and modified in a cost-effective manner and are easy to hybridize to a variety of nano-particles and other agents which has paved a way for targeted therapy and diagnostics applications such as in breast tumors. In this review, we systematically explain different aptamer adoption approaches to therapeutic or diagnostic uses when addressing breast tumors. We summarize the current therapeutic techniques to address breast tumors including aptamer-base approaches. We discuss the next aptamer-based therapeutic and diagnostic approaches targeting breast tumors. Finally, we provide a perspective on the future of aptamer-based sensors for breast therapeutics and diagnostics. In this section, the therapeutic applications of aptamers will be discussed for the targeting therapy of breast cancer.

Equitable Policies Need Equitable Practices: Alcohol- and Substance-Exposed Pregnancy as a Case Study.

There is clear need for more effective public health policies. Coupled with calls for more effective policies, increasing demand to address public health disparities experienced by systemically marginalized and historically oppressed groups emphasizes the long-standing need for policies that improve public health equity. Such need is highlighted when examining public health issues such as alcohol- and substance-exposed pregnancy (ASEP): Current policies are ineffective at reducing ASEP, and marginalized groups experience disproportionately lower benefits and higher negative consequences as a result of such policies. Powerful strategies to develop more effective policies that can account for the complexity of such issues, such as systems science methods (SSMs), are becoming popular. However, current best practices for such methods often do not emphasize the additional efforts that will be required to develop equitable, not just effective policies. Using ASEP as an example of a crucial complex issue requiring new policy, we suggest additional steps to include in SSM projects for developing more effective policies that will also help stakeholders determine high-equity policies to reduce health disparities. These steps include modeling structural differences experienced by marginalized groups via systemic racism and oppression, incorporating existing cultural and community sources of strength and resilience as key areas for policy development, and evaluating the sustainability of policies as a dimension of efficacy. We also discuss using community-based participatory approaches as a framework for all SSM processes to ensure that policy development itself is grounded in equitable shared decision-making for marginalized individuals.

Frequency-based decoupling and finite element model updating in vibration of cable-beam systems.

Interactions between cable and structure affect the modal properties of cabled structures such as overhead electricity transmission and distribution line systems. Modal properties of a single in-service pole are difficult to determine. A frequency response function of a pole impacted with a modal hammer will contain information about not only the pole but also the conductors and adjacent poles connected thereby. This article presents a generally applicable method to extract modal properties of a single structural element, within an interacting system of cables and structures, with particular application to electricity poles. A scalable experimental lab-scale pole-line consisting of a cantilever beam and stranded cable and a more complex system consisting of three cantilever beams and a stranded cable are used to validate the method. The frequency response function of a cantilever ("pole") is predicted by substructural decoupling of measured cable dynamics (known frequency response function matrix) from the measured response of the assembled cable-beam system (known frequency response function matrix). Various amounts of sag can be present in the cable. Comparison of the estimated and directly obtained pole frequency response functions show good agreement, demonstrating that the method can be used in cabled structures to obtain modal properties of an individual structural element with the effects of cables and adjacent structural elements filtered out. A frequency response function-based finite element model updating is then proposed to overcome the practical limitation of accessing some components of the real-world system for mounting sensors. Frequency response functions corresponding to inaccessible points are generated based on the measured frequency response functions corresponding to accessible points. The results verify that the frequency response function-based finite element model updating can be used for substructural decoupling of systems in which some essential points, such as coupling points, are inaccessible for direct frequency response function measurement.

Zinc supplementation is associated with a reduction in serum markers of inflammation and oxidative stress in adults: A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Zinc (Zn) is a trace metal that is considered to have an impact on chronic inflammation. However, findings of clinical trials have been inconsistent. The present systematic review and meta-analysis aimed to provide a more robust examination of the evidence on the effectiveness of Zn supplements on markers of inflammation and oxidative stress. METHODS: A systematic search in PubMed, Scopus, Web of Science and Cochrane Library was undertaken to identify relevant randomized controlled trials (RCTs) assessing the impact of Zn on inflammation and oxidative stress until 17 August 2020. We applied a random-effects method to obtain effect sizes (ES) and 95% confidence intervals (CIs). Meta-regression was used to detect the potential source of between-study heterogeneity. RESULTS: Twenty-one eligible RCTs comprising 1321 participants were included in the meta-analysis. In comparison with the control groups, serum C-reactive protein (CRP) (ES = -0.92 mg/L, 95% CI = [-1.36, -0.48], P < 0.001, I2 = 90.2%), tumor necrosis factor-alpha (TNF-α) (ES = -0.49 pg/mL, 95% CI = [-084, -0.14], P = 0.006, I2 = 34.6%) and malondialdehyde (MDA) (ES = -0.42, 95% CI = [-083, -0.01], P = 0.04, I2 = 76.1%) were significantly reduced in the groups receiving Zn. Serum interleukin 6 (ES = -1.02 pg/mL, 95% CI = [-2.06, 0.02], P = 0.05, I2 = 92.3%) was marginally reduced following Zn supplementation. Moreover, treatment duration was found as the source of inter-study heterogeneity. CONCLUSION: This meta-analysis suggests that Zn supplements reduce serum concentrations of markers of inflammation and oxidation: CRP, TNF-α and MDA.

Insights into vaccine hesitancy from systems thinking, Rwanda.

OBJECTIVE: To investigate vaccine hesitancy leading to underimmunization and a measles outbreak in Rwanda and to develop a conceptual, community-level model of behavioural factors. METHODS: Local immunization systems in two Rwandan communities (one recently experienced a measles outbreak) were explored using systems thinking, human-centred design and behavioural frameworks. Data were collected between 2018 and 2020 from: discussions with 11 vaccination service providers (i.e. hospital and health centre staff); interviews with 161 children's caregivers at health centres; and nine validation interviews with health centre staff. Factors influencing vaccine hesitancy were categorized using the 3Cs framework: confidence, complacency and convenience. A conceptual model of vaccine hesitancy mechanisms with feedback loops was developed. FINDINGS: A comparison of service providers' and caregivers' perspectives in both rural and peri-urban settings showed that similar factors strengthened vaccine uptake: (i) high trust in vaccines and service providers based on personal relationships with health centre staff; (ii) the connecting role of community health workers; and (iii) a strong sense of community. Factors identified as increasing vaccine hesitancy (e.g. service accessibility and inadequate follow-up) differed between service providers and caregivers and between settings. The conceptual model could be used to explain drivers of the recent measles outbreak and to guide interventions designed to increase vaccine uptake. CONCLUSION: The application of behavioural frameworks and systems thinking revealed vaccine hesitancy mechanisms in Rwandan communities that demonstrate the interrelationship between immunization services and caregivers' vaccination behaviour. Confidence-building social structures and context-dependent challenges that affect vaccine uptake were also identified.