Ameliorative effect of metformin on cyclophosphamide-induced memory impairment in mice

OBJECTIVE

Cyclophosphamide (CYP) is a chemotherapeutic agent that is widely used as an adjuvant cancer treatment. Unfortunately, this drug is associated with secondary side effects, including cognitive impairment up to 70% of cancer survivors. The mechanism of this memory impairment is unclear. Thus, to understand the cognitive impairments caused by this chemotherapeutic agent, a clinically relevant dose to cancer treatment was used in mice to establish the chemobrain models, and the spatial memory of these mice was assessed using multiple behavior tests. In addition, metformin (MET) is widely used as an anti-diabetic drug and protects against oxidative stress and hepatotoxicity. Thus, this study tested the protective effects of MET in the chemobrain models.

MATERIALS AND METHODS

Four groups of mice, which weighed about 18-30 g, were collected and divided into 4 groups: control, CYP, MET, and CYP+MET groups. A 100 mg/kg dose of CYP was administered intraperitoneal (on alternate days) for a total of 4 doses. MET was dissolved in the mice's drinking water bottles at a 5 mg/ml concentration from day zero to the end of the treatment period. The mice's memory was tested using hippocampal-dependent tests, including the Y-maze, novel object recognition, and elevated plus maze tests. These tests were performed for three consecutive days after 24 h of the last dose of CYP.

RESULTS

The mice treated with CYP exhibited a decline in memory function in all the behavioral test studies, and this decline was significant in the Y-maze test. However, this decline was rescued by MET administration.

CONCLUSIONS

The clinically relevant model suggests that CYP treatment causes a decline in mice models spatial memory that might be improved by MET administration.

Persistent arterial wall inflammation in patients with elevated lipoprotein(a) despite strong low-density lipoprotein cholesterol reduction by proprotein convertase subtilisin/kexin type 9 antibody treatment

AIMS

Subjects with lipoprotein(a) [Lp(a)] elevation have increased arterial wall inflammation and cardiovascular risk. In patients at increased cardiovascular risk, arterial wall inflammation is reduced following lipid-lowering therapy by statin treatment or lipoprotein apheresis. However, it is unknown whether lipid-lowering treatment in elevated Lp(a) subjects alters arterial wall inflammation. We evaluated whether evolocumab, which lowers both low-density lipoprotein cholesterol (LDL-C) and Lp(a), attenuates arterial wall inflammation in patients with elevated Lp(a).

METHODS AND RESULTS

In this multicentre, randomized, double-blind, placebo-controlled study, 129 patients {median [interquartile range (IQR)]: age 60.0 [54.0-67.0] years, Lp(a) 200.0 [155.5-301.5] nmol/L [80.0 (62.5-121.0) mg/dL]; mean [standard deviation (SD)] LDL-C 3.7 [1.0] mmol/L [144.0 (39.7) mg/dL]; National Cholesterol Education Program high risk, 25.6%} were randomized to monthly subcutaneous evolocumab 420 mg or placebo. Compared with placebo, evolocumab reduced LDL-C by 60.7% [95% confidence interval (CI) 65.8-55.5] and Lp(a) by 13.9% (95% CI 19.3-8.5). Among evolocumab-treated patients, the Week 16 mean (SD) LDL-C level was 1.6 (0.7) mmol/L [60.1 (28.1) mg/dL], and the median (IQR) Lp(a) level was 188.0 (140.0-268.0) nmol/L [75.2 (56.0-107.2) mg/dL]. Arterial wall inflammation [most diseased segment target-to-background ratio (MDS TBR)] in the index vessel (left carotid, right carotid, or thoracic aorta) was assessed by 18F-fluoro-deoxyglucose positron-emission tomography/computed tomography. Week 16 index vessel MDS TBR was not significantly altered with evolocumab (-8.3%) vs. placebo (-5.3%) [treatment difference -3.0% (95% CI -7.4% to 1.4%); P = 0.18].

CONCLUSION

Evolocumab treatment in patients with median baseline Lp(a) 200.0 nmol/L led to a large reduction in LDL-C and a small reduction in Lp(a), resulting in persistent elevated Lp(a) levels. The latter may have contributed to the unaltered arterial wall inflammation.

Immune Checkpoint Inhibitor Therapy Aggravates T Cell-Driven Plaque Inflammation in Atherosclerosis

BACKGROUND

Immunotherapy has revolutionized cancer treatment. However, immune checkpoint inhibitors (ICIs) that target PD-1 (programmed cell death protein-1) and/or CTLA-4 (cytotoxic T lymphocyte-associated antigen-4) are commonly associated with acute immune-related adverse events. Accumulating evidence also suggests that ICIs aggravate existing inflammatory diseases.

OBJECTIVES

As inflammation drives atherosclerotic cardiovascular disease, we studied the propensity of short-term ICI therapy to aggravate atherosclerosis.

METHODS

We used 18F-FDG (2-deoxy-2-[fluorine-18]fluoro-D-glucose) positron emission tomography-computed tomography to detect macrophage-driven vascular and systemic inflammation in pembrolizumab and nivolumab/ipilimumab-treated melanoma patients. In parallel, atherosclerotic Ldlr -/- mice were treated with CTLA-4 and PD-1 inhibition to study the proinflammatory consequences of immune checkpoint inhibition.

RESULTS

ICI treatment did not affect 18F-FDG uptake in the large arteries, spleen, and bone marrow of melanoma patients, nor myeloid cell activation in blood and lymphoid organs in hyperlipidemic mice. In contrast, we found marked changes in the adaptive immune response (i.e., increased CD4+ effector T cell and CD8+ cytotoxic T cell numbers in lymphoid organs and the arterial wall of our hyperlipidemic mice). Although plaque size was unaffected, plaques had progressed toward a lymphoid-based inflammatory phenotype, characterized by a 2.7-fold increase of CD8+ T cells and a 3.9-fold increase in necrotic core size. Increased endothelial activation was observed with a 2.2-fold and 1.6-fold increase in vascular cell adhesion molecule-1 and intercellular adhesion molecule-1, respectively.

CONCLUSIONS

This study demonstrates that combination therapy with anti-CTLA-4 and anti-PD-1 antibodies does not affect myeloid-driven vascular and systemic inflammation in melanoma patients and hyperlipidemic mice. However, short-term ICI therapy in mice induces T cell-mediated plaque inflammation and drives plaque progression.

Review of radiographic findings in COVID-19

The purpose of this study is to review the published literature for the range of radiographic findings present in patients suffering from coronavirus disease 2019 infection. This novel corona virus is currently the cause of a worldwide pandemic. Pulmonary symptoms and signs dominate the clinical picture and radiologists are called upon to evaluate chest radiographs (CXR) and computed tomography (CT) images to assess for infiltrates and to define their extent, distribution and progression. Multiple studies attempt to characterize the disease course by looking at the timing of imaging relative to the onset of symptoms. In general, plain CXR show bilateral disease with a tendency toward the lung periphery and have an appearance most consistent with viral pneumonia. Chest CT images are most notable for showing bilateral and peripheral ground glass and consolidated opacities and are marked by an absence of concomitant pulmonary nodules, cavitation, adenopathy and pleural effusions. Published literature mentioning organ systems aside from pulmonary manifestations are relatively less common, yet present and are addressed in this review. Similarly, publications focusing on imaging modalities aside from CXR and chest CT are sparse in this evolving crisis and are likewise addressed in this review. The role of imaging is examined as it is currently being debated in the medical community, which is not at all surprising considering the highly infectious nature of Severe Acute Respiratory Syndrome coronavirus 2.

Quantification of uric acid in vasculature of patients with gout using dual-energy computed tomography

BACKGROUND

Gout, caused by hyperuricemia and subsequent deposition of aggregated monosodium urate crystals (MSU) in the joints or extra-articular regions, is the most common inflammatory arthritis. There is increasing evidence that gout is an independent risk factor for hypertension, cardiovascular disease progression and mortality.

AIM

To evaluate if dual energy computed tomography (DECT) could identify MSU within vessel walls of gout patients, and if MSU deposits within the vasculature differed between patients with gout and controls. This study may help elucidate why individuals with gout have increased risk for cardiovascular disease.

METHODS

31 gout patients and 18 controls underwent DECT scans of the chest and abdomen. A material decomposition algorithm was used to distinguish regions of MSU (coded green), and calcifications (coded purple) from soft tissue (uncoded). Volume of green regions was calculated using a semi-automated volume assessment program. Between-group differences were analyzed using Mann-Whitney U exact test and nonparametric rank regression.

RESULTS

Gout patients had significantly higher volume of MSU within the aorta compared to controls [Median (Min-Max) of 43.9 (0-1113.5) vs 2.9 (0-219.4), P = 0.01]. Number of deposits was higher in gout patients compared to controls [Median (Min-Max) of 20 (0-739) vs 1.5 (0-104), P = 0.008]. However, the difference was insignificant after adjustment for age, gender, history of cardiovascular disease and diabetes. Increased age was positively associated with total urate volume (r_s = 0.64; 95% confidence interval: 0.43-0.78).

CONCLUSION

This pilot study showed that DECT can quantify vascular urate deposits with variation across groups, with gout patients possibly having higher deposition. This relationship disappeared when adjusted for age, and there was a positive relationship between age and MSU deposition. While this study does not prove that green coded regions are truly MSU deposition, it corroborates recent studies that show the presence of vascular deposition.

Enhancing business performance through green human resource management practices: an empirical evidence from Malaysian manufacturing industry

Purpose

The purpose of this study is to assess the key determinants of green human resource management (GHRM) and investigate its impact on environmental performance (EP) and business performance (BP).

Design/methodology/approach

The research employed SmartPLS 3 and follows a cross-sectional research design. Data from 179 employees were collected using a convenience sampling technique from the firms that adopted GHRM practices.

Findings

The research found a significant relationship of GHRM with EP and also reported the significant relationship between EP and BP. Moreover, EP significantly mediates the relationship of GHRM with BP.

Research limitations/implications

A relatively small sample size of employees was used that may suggest the need for a diverse and more representative sample. The paper is based on data collected from the Malaysian manufacturing industry – other economic sectors and Asian countries may offer different results.

Practical implications

The paper identifies the need for incorporating GHRM practices and culture at the workplace to encourage positive green behavior in employees which will increase the EP and BP of the firm.

Originality/value

This paper reported the initial empirical findings after the March 7th incident on EP of businesses in Malaysia, where businesses have initiated the adoption of GHRM practices.

Artificial intelligence-enabled rapid diagnosis of patients with COVID-19

For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of patients with COVID-19. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiological findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history and laboratory testing to rapidly diagnose patients who are positive for COVID-19. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of patients who were positive for COVID-19 via RT-PCR who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

A Preliminary 18F-FDG-PET/MRI Study Shows Increased Vascular Inflammation in Moderate-to-Severe Atopic Dermatitis

BACKGROUND

Recent data suggest that patients with atopic dermatitis (AD) have increased systemic immune activation and cardiovascular risk. However, unlike psoriasis, evaluation of active vascular inflammation using state-of-the-art imaging is lacking in AD.

OBJECTIVE

To assess aortic and carotid vascular inflammation using ¹⁸F-fluorodeoxyglucose-positron emission tomography/magnetic resonance imaging (¹⁸F-FDG-PET/MRI) imaging in moderate-to-severe AD versus healthy individuals.

METHODS

A total of 27 patients with moderate-to-severe AD and 12 healthy controls were imaged using ¹⁸F-FDG-PET/MRI. Target-to-background ratio (TBR) values were calculated in multiple segments of the aorta and carotid vessels.

RESULTS

Patients with AD had elevated aortic max TBR (fold change [FCH] = 1.45, P = .057) versus healthy controls and significantly elevated mean TBR (FCH = 1.20; P < .05) in the right carotid (RC) arteries versus controls. When examining greatest focal inflammation (most diseased segment [MDS] TBR), patients with AD had higher aortic inflammation (FCH = 1.28; P = .052). AD clinical severity significantly correlated with C-reactive protein (ρ = 0.60, P < .01) and with RC mean TBR levels (ρ = 0.60, P = .04). Stratifying patients into moderate-to-severe and very severe AD showed greater RC mean TBR in patients with very severe AD versus controls (FCH = 1.31; P = .02) and versus patients with moderate/severe AD (FCH = 1.23, P = .05). Aortic inflammation was also significantly greater in patients with very severe AD versus controls (max TBR: FCH = 1.6, P = .04; MDS TBR: FCH = 1.73, P = .03).

CONCLUSIONS

This preliminary study is the first that establishes greater vascular (aorta and carotid) inflammation in moderate-to-severe AD versus healthy controls. Furthermore, very severe AD showed higher inflammation than both moderate/severe patients and healthy controls. Future studies with larger patient cohorts and evaluation before and after treatment are needed to determine the extent to which vascular inflammation in AD is modifiable.

Artificial intelligence-enabled rapid diagnosis of COVID-19 patients

For diagnosis of COVID-19, a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to two days to complete, serial testing may be required to rule out the possibility of false negative results, and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of COVID-19 patients. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiologic findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history, and laboratory testing to rapidly diagnose COVID-19 positive patients. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an AUC of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of RT-PCR positive COVID-19 patients who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

Respirator usage protects brain white matter from welding fume exposure: A pilot magnetic resonance imaging study of welders

Welding fume exposure has been associated with structural brain changes and a wide variety of clinical and sub-clinical outcomes including cognitive, behavioral and motor abnormalities. Respirator use has been shown to decrease exposure to welding fumes; however, the associations between respirator use and health outcomes, particularly neurologic health, have been understudied. In this preliminary study, we used diffusion tensor imaging (DTI) to investigate the effectiveness of respirator use in protecting workers' white matter (WM) from the harmful effects related to welding fume exposure. Fractional anisotropy (FA), a common DTI measurement of water diffusion properties, was used as a marker of WM microstructure integrity. We hypothesized that FA in brain regions involved in motor and neurocognitive functions would differ between welders reporting respirator use compared to those not using a respirator. We enrolled a pilot cohort of 19 welders from labor unions in the New York City area. All welders completed questionnaires to assess welding history and occupational health. All completed a DTI acquisition on a 3 T Siemens scanner. Partial least squares discriminant analysis (PLS-DA), a bioinformatic analytical strategy, was used to model the divergence of WM microstructures in 48 regions defined by the ICBM-DTI-81 atlas between respirator users compared to non-users. This yielded an effective discrimination of respirator users from non-users, with the uncinate fasciculus, the cerebellar peduncle and the superior longitudinal fasciculus contributing most to the discrimination of these groups. These white matter tracts are involved in widespread motor and cognitive functions. To our knowledge, this study is the first to suggest a protective effect of respirator on WM microstructure, indicating that the lack of respirator may present unsafe working conditions for welders. These preliminary findings may inform a larger, longitudinal intervention study that would be more appropriate to investigate the potential protective effect of respirator usage on brain white matter in welders.

Segmentation of carotid arterial walls using neural networks

BACKGROUND

Automated, accurate, objective, and quantitative medical image segmentation has remained a challenging goal in computer science since its inception. This study applies the technique of convolutional neural networks (CNNs) to the task of segmenting carotid arteries to aid in the assessment of pathology.

AIM

To investigate CNN’s utility as an ancillary tool for researchers who require accurate segmentation of carotid vessels.

METHODS

An expert reader delineated vessel wall boundaries on 4422 axial T2-weighted magnetic resonance images of bilateral carotid arteries from 189 subjects with clinically evident atherosclerotic disease. A portion of this dataset was used to train two CNNs (one to segment the vessel lumen and the other to segment the vessel wall) with the remaining portion used to test the algorithm’s efficacy by comparing CNN segmented images with those of an expert reader.

RESULTS

Overall quantitative assessment between automated and manual segmentations was determined by computing the DICE coefficient for each pair of segmented images in the test dataset for each CNN applied. The average DICE coefficient for the test dataset (CNN segmentations compared to expert’s segmentations) was 0.96 for the lumen and 0.87 for the vessel wall. Pearson correlation values and the intra-class correlation coefficient (ICC) were computed for the lumen (Pearson = 0.98, ICC = 0.98) and vessel wall (Pearson = 0.88, ICC = 0.86) segmentations. Bland-Altman plots of area measurements for the CNN and expert readers indicate good agreement with a mean bias of 1%-8%.

CONCLUSION

Although the technique produces reasonable results that are on par with expert human assessments, our application requires human supervision and monitoring to ensure consistent results. We intend to deploy this algorithm as part of a software platform to lessen researchers’ workload to more quickly obtain reliable results.

Combined PET/DCE-MRI in a Rabbit Model of Atherosclerosis: Integrated Quantification of Plaque Inflammation, Permeability, and Burden During Treatment With a Leukotriene A4 Hydrolase Inhibitor

OBJECTIVES

The authors sought to develop combined positron emission tomography (PET) dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) to quantify plaque inflammation, permeability, and burden to evaluate the efficacy of a leukotriene A4 hydrolase (LTA4H) inhibitor in a rabbit model of atherosclerosis.

BACKGROUND

Multimodality PET/MRI allows combining the quantification of atherosclerotic plaque inflammation, neovascularization, permeability, and burden by combined ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET, DCE-MRI, and morphological MRI. The authors describe a novel, integrated PET-DCE/MRI protocol to noninvasively quantify these parameters in aortic plaques of a rabbit model of atherosclerosis. As proof-of-concept, the authors apply this protocol to assess the efficacy of the novel LTA4H inhibitor BI691751.

METHODS

New Zealand White male rabbits (N = 49) were imaged with integrated PET-DCE/MRI after atherosclerosis induction and 1 and 3 months after randomization into 3 groups: 1) placebo; 2) high-dose BI691751; and 3) low-dose BI691751. All animals were euthanized at the end of the study.

RESULTS

Among the several metrics that were quantified, only maximum standardized uptake value and target-to-background ratio by ¹⁸F-FDG PET showed a modest, but significant, reduction in plaque inflammation in rabbits treated with low-dose BI691751 (p = 0.03), whereas no difference was detected in the high-fat diet and in the high-dose BI691751 groups. No differences in vessel wall area by MRI and area under the curve by DCE-MRI were detected in any of the groups. No differences in neovessel and macrophage density were found at the end of study among groups.

CONCLUSIONS

The authors present a comprehensive, integrated ¹⁸F-FDG PET and DCE-MRI imaging protocol to noninvasively quantify plaque inflammation, neovasculature, permeability, and burden in a rabbit model of atherosclerosis on a simultaneous PET/MRI scanner. A modest reduction was found in plaque inflammation by ¹⁸F-FDG PET in the group treated with a low dose of the LTA4H inhibitor BI691751.

Imaging-assisted nanoimmunotherapy for atherosclerosis in multiple species

Nanomedicine research produces hundreds of studies every year, yet very few formulations have been approved for clinical use. This is due in part to a reliance on murine studies, which have limited value in accurately predicting translational efficacy in larger animal models and humans. Here, we report the scale-up of a nanoimmunotherapy from mouse to large rabbit and porcine atherosclerosis models, with an emphasis on the solutions we implemented to overcome production and evaluation challenges. Specifically, we integrated translational imaging readouts within our workflow to both analyze the nanoimmunotherapeutic's in vivo behavior and assess treatment response in larger animals. We observed our nanoimmunotherapeutic's anti-inflammatory efficacy in mice, as well as rabbits and pigs. Nanoimmunotherapy-mediated reduction of inflammation in the large animal models halted plaque progression, supporting the approach's translatability and potential to acutely treat atherosclerosis.

133 Effect of a proprietary medium chain fatty acid blend on nursery pig performance

Previous studies have shown that the inclusion of medium chain fatty acids (MCFA) results in an improvement in nursery pig performance. Therefore, the objective of this study was to evaluate a proprietary C8:C10 MCFA blend (CaptiSURE, Kemin Industries, Inc., Des Moines, IA) on nursery pig performance. A total of 360 weaned piglets (initial BW = 6.1 kg) were randomly assigned to a control (no MCFA blend) or 10 kg/t MCFA blend (10 pigs/pen, 18 replicate pens/treatment), in which MCFA blend was substituted at the expense of tallow at a 1:1 rate. Diets were manufactured in 3 dietary phases (d 0–7, 7–21, and 21–42) in pelleted form. Due to an unintended bacterial challenge at the sow farm, pigs were treated with amoxicillin using a pulse protocol (48 hrs on / 48 hrs off) from placement to d 21. Data were analyzed using the students T-test procedure, and pen served as the experimental unit. Within dietary phase 2 (d 7–21), the inclusion of MCFA blend improved ADG (264g vs 326g, P = 0.017) and G:F (0.79 vs 0.89, P = 0.005), while exhibiting a trend to improve ADFI (330g vs 364g, P = 0.080). Within dietary phase 3 (d 21–42), the inclusion of MCFA blend improved ADG (518g vs 581g, P = 0.024) and ADFI (719g vs 799g, P = 0.006). Overall (d 0–42), the inclusion of MCFA blend improved ADG (379g vs 438g, P = 0.007), ADFI (503g vs 0.562g, P = 0.009), and G:F (0.75 vs 0.78, P = 0.042), resulting in a 2 kg heavier pig (P = 0.043). In summary, the inclusion of a proprietary C8:C10 MCFA blend at 1.0% in nursery pig diets improved growth performance.

Imaging plaque inflammation in asymptomatic cocaine addicted individuals with simultaneous positron emission tomography/magnetic resonance imaging

BACKGROUND

Chronic cocaine use is associated with stroke, coronary artery disease and myocardial infarction, resulting in severe impairments or sudden mortality. In the absence of clear cardiovascular symptoms, individuals with cocaine use disorder (iCUD) seeking addiction treatment receive mostly psychotherapy and psychiatric pharmacotherapy, with no attention to vascular disease (i.e., atherosclerosis). Little is known about the pre-clinical signs of cardiovascular risk in iCUD and early signs of vascular disease are undetected in this underserved population.

AIM

To assess inflammation, plaque burden and plaque composition in iCUD aiming to detect markers of atherosclerosis and vascular disease.

METHODS

The bilateral carotid arteries were imaged with positron emission tomography/magnetic resonance imaging (PET/MRI) in iCUD asymptomatic for cardiovascular disease, healthy controls, and individuals with cardiovascular risk. PET with 18F-fluorodeoxyglucose (¹⁸F-FDG) evaluated vascular inflammation and 3-D dark-blood MRI assessed plaque burden including wall area and thickness. Drug use and severity of addiction were assessed with standardized instruments.

RESULTS

The majority of iCUD and controls had carotid FDG-PET signal greater than 1.6 but lower than 3, indicating the presence of mild to moderate inflammation. However, the MRI measure of wall structure was thicker in iCUD as compared to the controls and cardiovascular risk group, indicating greater carotid plaque burden. iCUD had larger wall area as compared to the healthy controls but not as compared to the cardiovascular risk group, indicating structural wall similarities between the non-control study groups. In iCUD, wall area correlated with greater cocaine withdrawal and craving.

CONCLUSION

These preliminary results show markers of carotid artery disease burden in cardiovascular disease-asymptomatic iCUD. Broader trials are warranted to develop protocols for early detection of cardiovascular risk and preventive intervention in iCUD.

Sex Differences in the Association Between Smoking and Sleep-Disordered Breathing in the Hispanic Community Health Study/Study of Latinos

BACKGROUND

Results of previous studies examining associations between cigarette smoking and sleep-disordered breathing (SDB) are inconsistent. We therefore investigated this association in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

METHODS

A total of 13,863 US Hispanic/Latino subjects, 18 to 76 years old, provided smoking histories and underwent home SDB testing. Logistic regression analyses were conducted to assess the independent association of smoking and SDB with covariate adjustment. Sex- and age-stratified analyses were performed.

RESULTS

The weighted prevalence of moderate to severe SDB was 9.7% (95% CI, 9.0-10.5). No independent and statistically significant association was observed between ever smoking (defined as minimum lifetime cigarette use of 100) and moderate to severe SDB (defined as an apnea-hypopnea index ≥ 15 events per hour) (OR, 1.02; 95% CI, 0.85-1.22; P = .85). Sex and age were effect modifiers of the aforementioned association. Stratification according to age and sex revealed that younger (aged 35-54 years) female smokers had 83% higher odds of SDB compared with younger female never smokers (OR, 1.83; 95% CI, 1.19-2.81; P = .01). A significant dose-response relation was noted between smoking intensity and SDB in younger female smokers (P < .01). Lastly, use of ≥ 10 cigarettes per day was associated with a nearly threefold increase in SDB odds in younger female ever smokers. These associations were not observed in younger male subjects.

CONCLUSIONS

In the HCHS/SOL, no independent and statistically significant association was found between smoking and SDB. Sex and age stratification revealed a novel statistically significant association between smoking and SDB in younger (35-54 years old) female smokers. Our findings highlight the importance of investigating sex- and age-specific associations of SDB risk factors.

Evaluation of the protective effects of zinc butyrate in IPEC-J2 cells and grower pigs under heat stress

Heat stress (HS) is a major environmental stressor primarily affecting swine performance through negative effects on intestinal health. Zinc and butyric acid supplementation help maintain intestinal integrity and barrier function, and has been shown to be beneficial to swine during stress conditions. We tested a novel formulation of zinc butyrate (ZnB) to study whether it has protective effects toward swine using pig intestinal epithelial cells (IPEC-J2) and in a grower swine HS trial. IPEC-J2 cells were grown either under an inflammatory challenge (Escherichia coli lipopolysaccharide) or HS (41.5 °C for 48 h) using Transwell plates. The tight junction integrity of the cells under various treatments, including ZnB, zinc sulfate, and calcium butyrate, was followed over a period of 36 to 48 h by measuring transepithelial electrical resistance (TER). During inflammatory challenge, ZnB-treated cells had the greatest TER (P < 0.05) at 36 h. When the cells were exposed to HS at 41.5 °C, ZnB-treated cells had similar TER to the cells incubated at 37.0 °C, indicating significant protection against HS. In the swine trial (two dietary treatments, control and an encapsulated form of 40% zinc butyrate [E-ZnB] in hydrogenated palm oil pearls, 12 pigs per treatment), grower gilts (35 ± 1 kg) were supplemented with E-ZnB for 24 d before being subjected to biphasic HS for 7 d, 30 to 32 °C for 8 h and 28 °C for 16 h, for a total duration of 56 h of HS. At the end of the HS phase, half the pigs were euthanized from each treatment (n = 6 per treatment), and growth performance was calculated. During the HS phase, average daily gain (ADG; 0.53 vs. 0.79 kg) and gain-to-feed ratio (G:F; 0.33 vs. 0.43) were greater in the E-ZnB group (P < 0.05). Although in vivo intestinal permeability increased during the HS phase (P < 0.05), no differences were observed in the present study for the intestinal health parameters measured including TER, villus height:crypt depth ratio, and in vivo and ex vivo intestinal permeability between the two treatment groups. In conclusion, results presented here demonstrate that E-ZnB supplementation during HS improves ADG and G:F in grower pigs. Although we could not measure any differences, the mode of action of butyric acid and zinc suggests that the performance improvements are related to improved intestinal health.

Benchmarking of factors influencing adoption of innovation in software product SMEs

Purpose

The purpose of this paper is to investigate the factors influencing small and medium enterprises’ (SMEs) adoption of innovation approaches.

Design/methodology/approach

The methodology involves two steps. First, all the variables relevant to the adoption of innovation in SMEs are identified. Subsequently, primary data are gathered from decision makers of 213 SMEs, and a multinomial logistic regression analysis is performed.

Findings

The results indicate that SMEs adopt both open innovation and closed innovation approaches. The firm-level factors such as firm age, firm size, education qualification, work experience and culture, and external factors such as customers, competition, technological advances and ecosystem influence adoption of open innovation approach compared to closed innovation approach. Factors such as culture among firm-level factors and competition among external factors influence the adoption of closed innovation approach.

Practical implications

The study helps the managers or the decision makers of the SMEs to know the suitable factors influencing the firm to adopt innovation which could potentially help the firms in their business strategy.

Originality/value

The study explores the adoption of innovation approaches of SMEs in emerging economies. The outcomes of this research have far-reaching implications for theory and practitioners in emerging economies.

Reproducibility of thrombus volume quantification in multicenter computed tomography pulmonary angiography studies

AIM

To evaluate reproducibility of pulmonary embolism (PE) clot volume quantification using computed tomography pulmonary angiogram (CTPA) in a multicenter setting.

METHODS

This study was performed using anonymized data in conformance with HIPAA and IRB Regulations (March 2015-November 2016). Anonymized CTPA data was acquired from 23 scanners from 18 imaging centers using each site’s standard PE protocol. Two independent analysts measured PE volumes using a semi-automated region-growing algorithm on an FDA-approved image analysis platform. Total thrombus volume (TTV) was calculated per patient as the primary endpoint. Secondary endpoints were individual thrombus volume (ITV), Qanadli score and modified Qanadli score per patient. Inter- and intra-observer reproducibility were assessed using intra-class correlation coefficient (ICC) and Bland-Altman analysis.

RESULTS

Analyst 1 found 72 emboli in the 23 patients with a mean number of emboli of 3.13 per patient with a range of 0-11 emboli per patient. The clot volumes ranged from 0.0041 - 47.34 cm³ (mean +/- SD, 5.93 +/- 10.15cm³). On the second read, analyst 1 found the same number and distribution of emboli with a range of volumes for read 2 from 0.0041 – 45.52 cm³ (mean +/- SD, 5.42 +/- 9.53cm³). Analyst 2 found 73 emboli in the 23 patients with a mean number of emboli of 3.17 per patient with a range of 0-11 emboli per patient. The clot volumes ranged from 0.00459-46.29 cm³ (mean +/- SD, 5.91 +/- 10.06 cm³). Inter- and intra-observer variability measurements indicated excellent reproducibility of the semi-automated method for quantifying PE volume burden. ICC for all endpoints was greater than 0.95 for inter- and intra-observer analysis. Bland-Altman analysis indicated no significant biases.

CONCLUSION

Semi-automated region growing algorithm for quantifying PE is reproducible using data from multiple scanners and is a suitable method for image analysis in multicenter clinical trials.

Effect of varying computed tomography acquisition and reconstruction parameters on semi-automated clot volume quantification

AIM

To examine effects of computed tomography (CT) image acquisition/reconstruction parameters on clot volume quantification in vitro for research method validation purposes.

METHODS

This study was performed in conformance with HIPAA and IRB Regulations (March 2015-November 2016). A ten blood clot phantom was designed and scanned on a dual-energy CT scanner (SOMATOM Force, Siemens Healthcare GmBH, Erlangen, Germany) with varying pitch, iterative reconstruction, energy level and slice thickness. A range of clot and tube sizes were used in an attempt to replicate in vivo emboli found within central and segmental branches of the pulmonary arteries in patients with pulmonary emboli. Clot volume was the measured parameter and was analyzed by a single image analyst using a semi-automated region growing algorithm implemented in the FDA-approved Siemens syngo.via image analysis platform. Mixed model analysis was performed on the data.

RESULTS

On the acquisition side, the continuous factor of energy showed no statistically significant effect on absolute clot volume quantification (P = 0.9898). On the other hand, when considering the fixed factor of pitch, there were statistically significant differences in clot volume quantification (P < 0.0001). On the reconstruction side, with the continuous factor of reconstruction slice thickness no statistically significant effect on absolute clot volume quantification was demonstrated (P = 0.4500). Also on the reconstruction side, with the fixed factor of using iterative reconstructions there was also no statistically significant effect on absolute clot volume quantification (P = 0.3011). In addition, there was excellent R² correlation between the scale-measured mass of the clots both with respect to the CT measured volumes and with respect to volumes measure by the water displacement method.

CONCLUSION

Aside from varying pitch, changing CT acquisition parameters and using iterative reconstructions had no significant impact on clot volume quantification with a semi-automated region growing algorithm.