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Background: We sought to determine the knowledge of, perception, attitudes, and behaviors toward influenza virus and immunization, and the determinants of vaccination among students, patients, and Healthcare Workers (HCWs) at the American University of Beirut and its affiliated Medical Center. Methods: We conducted a cross-sectional study between October 2016 and January 2017 utilizing a self-administered questionnaire that was provided to 247 randomly selected adult participants. Data collected included socio-demographic characteristics, prior vaccination against influenza, knowledge, perception, attitudes, and behaviors toward influenza and influenza immunization. A multivariable regression model was used to evaluate for independent associations between the different variables and regular or yearly vaccination as a primary outcome. Results: The overall survey response rate was 77%. A substantial proportion of respondents (47.4%) had never received the influenza vaccine. Only 10.2% of students, 19.1% of patients, and 35.6% of HCWs reported regular or yearly influenza vaccine uptake. HCWs had the lowest knowledge score about influenza and its vaccine despite high self-reported levels of knowledge. Barriers to vaccinations included lack of information (31%), fear of adverse effects (29%), and a perception of not being at risk (23%). Several factors were independently associated with regular or yearly vaccination uptake including having children (adjusted OR = 3.8; 95% CI 1.2–12.5), a “very good” self-reported level of knowledge (OR = 16.3; 95% CI 1.4–194.2) and being afraid of the consequences of influenza (OR = 0.2; 95% CI 0.1–0.6). Conclusion: Adherence rates with regular or yearly vaccination against influenza remain low across all study groups. We were able to identify predictors as well as barriers to vaccination. Future awareness and vaccination campaigns should specifically aim at correcting misconceptions about vaccination, particularly among HCWs, along with addressing the barriers to vaccination. Predictors of vaccination should be integrated in the design of future campaigns.

The ideal engineered vascular graft would utilize human-derived materials to minimize foreign body response and tissue rejection. Current biological engineered blood vessels (BEBVs) inherently lack the structure required for implantation. We hypothesized that an ECM material would provide the structure needed. Skin dermis ECM is commonly used in reconstructive surgeries, is commercially available and FDA-approved. We evaluated the commercially-available decellularized skin dermis ECM Alloderm for efficacy in providing structure to BEBVs. Alloderm was incorporated into our lab’s unique protocol for generating BEBVs, using fibroblasts to establish the adventitia. To assess structure, tissue mechanics were analyzed. Standard BEBVs without Alloderm exhibited a tensile strength of 67.9 ± 9.78 kPa, whereas Alloderm integrated BEBVs showed a significant increase in strength to 1500 ± 334 kPa. In comparison, native vessel strength is 1430 ± 604 kPa. Burst pressure reached 51.3 ± 2.19 mmHg. Total collagen and fiber maturity were significantly increased due to the presence of the Alloderm material. Vessels cultured for 4 weeks maintained mechanical and structural integrity. Low probability of thrombogenicity was confirmed with a negative platelet adhesion test. Vessels were able to be endothelialized. These results demonstrate the success of Alloderm to provide structure to BEBVs in an effective way.

We have previously shown that patients with abdominal aortic aneurysm (AAA) have decreased number and diminished immune suppressive function of regulatory type 1 T cells (Tr1) and increased numbers of activated effector Th17 cells. The objective of this clinical trial was to assess the efficacy of allogeneic mesenchymal stem cells (MSCs) in inducing Tr1 cells and suppressing AAA inflammation. Methods: The AneuRysm Repression with mEsenchymal STem cells (ARREST) trial is a blinded, placebo-controlled phase 1 study in which patients with small AAA (30-to 50-mm diameter) are randomized to intravenous infusion of placebo (plasmalyte A), 1 million MSCs/kg, and 3 million MSCs/kg (n ¼ 12/group). Blood samples are collected at baseline and at days 3, 7, 14, 28, and 60 and yearly. The primary end point is change in the ratio of Tr1:Th17 cells at 14 days after treatment using flow cytometry. Secondary end points are changes in FoxP3 + T-regulatory cells, myeloid-derived suppressor cells, microRNA profiles, serum cytokine levels, changes in AAA inflammation as measured by 18-fluorodeoxyglucose positron emission tomography/computed tomography, and changes in aneurysm diameter and volume at years 1 to 5. Results: Twenty-one patients have been enrolled to date. There have been no treatment-related adverse events, and one patient withdrew after discovery of an occult pulmonary malignant neoplasm on baseline positron emission tomography/computed tomography. At day 14, the ratio of Tr1:Th17 cells increased by 20.3 6 1.3-fold from baseline for the highdose MSC group (n ¼ 7) compared with 4.3 6-fold for the low-dose group (n ¼ 7; P < .01) and À10 .66 2.3-fold for the placebo group (n ¼ 7; P ¼ .001; Fig). There was a decrease in 18-fluorodeoxyglucose uptake as measured by standard uptake values by 5.6% 61.3% in the combined MSC group (n ¼ 7) compared with an increase in standard uptake values of 4.1% 6 1.0% in the placebo group (n ¼ 4; P < .05). Although the sample size was too small for statistical comparison, the average increase in maximal transverse diameter of AAA at 12 months after treatment was À1.6 6 0.6 mm in the combined MSC group (n ¼ 4) and 4.3 6 0.9 mm in the placebo group. Conclusions: The results of the ARREST trial demonstrate a significant increase in Tr1 cells concurrent with a decrease in cytotoxic effector Th17 cells in an MSC dose-dependent fashion, achieving the primary end point. Preliminary data suggest that aneurysm inflammation and expansion are decreased with MSC treatment.

IntroductionAdult spinal deformity (ASD) is classically evaluated by health-related quality of life (HRQoL) questionnaires and static radiographic spino-pelvic and global alignment parameters. Recently, 3D movement analysis (3DMA) was used for functional assessment of ASD to objectively quantify patient's independence during daily life activities. The aim of this study was to determine the role of both static and functional assessments in the prediction of HRQoL outcomes using machine learning methods.MethodsASD patients and controls underwent full-body biplanar low-dose x-rays with 3D reconstruction of skeletal segment as well as 3DMA of gait and filled HRQoL questionnaires: SF-36 physical and mental components (PCS&amp;MCS), Oswestry Disability Index (ODI), Beck's Depression Inventory (BDI), and visual analog scale (VAS) for pain. A random forest machine learning (ML) model was used to predict HRQoL outcomes based on three simulations: (1) radiographic, (2) kinematic, (3) both radiographic and kinematic parameters. Accuracy of prediction and RMSE of the model were evaluated using 10-fold cross validation in each simulation and compared between simulations. The model was also used to investigate the possibility of predicting HRQoL outcomes in ASD after treatment.ResultsIn total, 173 primary ASD and 57 controls were enrolled; 30 ASD were followed-up after surgical or medical treatment. The first ML simulation had a median accuracy of 83.4%. The second simulation had a median accuracy of 84.7%. The third simulation had a median accuracy of 87%. Simulations 2 and 3 had comparable accuracies of prediction for all HRQoL outcomes and higher predictions compared to Simulation 1 (i.e., accuracy for PCS = 85 ± 5 vs. 88.4 ± 4 and 89.7% ± 4%, for MCS = 83.7 ± 8.3 vs. 86.3 ± 5.6 and 87.7% ± 6.8% for simulations 1, 2 and 3 resp., p &lt; 0.05). Similar results were reported when the 3 simulations were tested on ASD after treatment.DiscussionThis study showed that kinematic parameters can better predict HRQoL outcomes than stand-alone classical radiographic parameters, not only for physical but also for mental scores. Moreover, 3DMA was shown to be a good predictive of HRQoL outcomes for ASD follow-up after medical or surgical treatment. Thus, the assessment of ASD patients should no longer rely on radiographs alone but on movement analysis as well.