Late Blood Levels of Neurofilament Light Correlate With Outcome in Patients With Traumatic Brain Injury

Neurofilament light (NF-L) is an axonal protein that has shown promise as a traumatic brain injury (TBI) biomarker. Serum NF-L shows a rather slow rise after injury, peaking after 1-2 weeks, although some studies suggest that it may remain elevated for months after TBI. The aim of this study was to examine if plasma NF-L levels several months after the injury correlate with functional outcome in patients who have sustained TBIs of variable initial severity. In this prospective study of 178 patients with TBI and 40 orthopedic injury controls, we measured plasma NF-L levels in blood samples taken at the follow-up appointment on average 9 months after injury. Patients with TBI were divided into two groups (mild [mTBI] vs. moderate-to-severe [mo/sTBI]) according to the severity of injury assessed with the Glasgow Coma Scale upon admission. Recovery and functional outcome were assessed using the Extended Glasgow Outcome Scale (GOSE). Higher levels of NF-L at the follow-up correlated with worse outcome in patients with moderate-to-severe TBI (Spearman's rho = -0.18; p < 0.001). In addition, in computed tomography-positive mTBI group, the levels of NF-L were significantly lower in patients with GOSE 7-8 (median 18.14; interquartile range [IQR] 9.82, 32.15) when compared with patients with GOSE <7 (median 73.87; IQR 32.17, 110.54; p = 0.002). In patients with mTBI, late NF-L levels do not seem to provide clinical benefit for late-stage assessment, but in patients with initially mo/sTBI, persistently elevated NF-L levels are associated with worse outcome after TBI and may reflect ongoing brain injury.

Neuroimmune activation and increased brain aging in chronic pain patients after the COVID-19 pandemic onset

The COVID-19 pandemic has exerted a global impact on both physical and mental health, and clinical populations have been disproportionally affected. To date, however, the mechanisms underlying the deleterious effects of the pandemic on pre-existing clinical conditions remain unclear. Here we investigated whether the onset of the pandemic was associated with an increase in brain/blood levels of inflammatory markers and MRI-estimated brain age in patients with chronic low back pain (cLBP), irrespective of their infection history. A retrospective cohort study was conducted on 56 adult participants with cLBP (28 'Pre-Pandemic', 28 'Pandemic') using integrated Positron Emission Tomography/ Magnetic Resonance Imaging (PET/MRI) and the radioligand [11C]PBR28, which binds to the neuroinflammatory marker 18 kDa Translocator Protein (TSPO). Image data were collected between November 2017 and January 2020 ('Pre-Pandemic' cLBP) or between August 2020 and May 2022 ('Pandemic' cLBP). Compared to the Pre-Pandemic group, the Pandemic patients demonstrated widespread and statistically significant elevations in brain TSPO levels (P =.05, cluster corrected). PET signal elevations in the Pandemic group were also observed when 1) excluding 3 Pandemic subjects with a known history of COVID infection, or 2) using secondary outcome measures (volume of distribution -VT- and VT ratio - DVR) in a smaller subset of participants. Pandemic subjects also exhibited elevated serum levels of inflammatory markers (IL-16; P <.05) and estimated BA (P <.0001), which were positively correlated with [11C]PBR28 SUVR (r's ≥ 0.35; P's < 0.05). The pain interference scores, which were elevated in the Pandemic group (P <.05), were negatively correlated with [11C]PBR28 SUVR in the amygdala (r = -0.46; P<.05). This work suggests that the pandemic outbreak may have been accompanied by neuroinflammation and increased brain age in cLBP patients, as measured by multimodal imaging and serum testing. This study underscores the broad impact of the pandemic on human health, which extends beyond the morbidity solely mediated by the virus itself.

Outlier Analysis for Acute Blood Biomarkers of Moderate and Severe Traumatic Brain Injury

Blood biomarkers have been studied to improve the clinical assessment and prognostication of patients with moderate-severe traumatic brain injury (mo/sTBI). To assess their clinical usability, one needs to know of potential factors that might cause outlier values and affect clinical decision making. In a prospective study, we recruited patients with mo/sTBI (n = 85) and measured the blood levels of eight protein brain pathophysiology biomarkers, including glial fibrillary acidic protein (GFAP), S100 calcium-binding protein B (S100B), neurofilament light (Nf-L), heart-type fatty acid-binding protein (H-FABP), interleukin-10 (IL-10), total tau (T-tau), amyloid β40 (Aβ40) and amyloid β42 (Aβ42), within 24 h of admission. Similar analyses were conducted for controls (n = 40) with an acute orthopedic injury without any head trauma. The patients with TBI were divided into subgroups of normal versus abnormal (n = 9/76) head computed tomography (CT) and favorable (Glasgow Outcome Scale Extended [GOSE] 5-8) versus unfavorable (GOSE <5) (n = 38/42, 5 missing) outcome. Outliers were sought individually from all subgroups from and the whole TBI patient population. Biomarker levels outside Q1 - 1.5 interquartile range (IQR) or Q3 + 1.5 IQR were considered as outliers. The medical records of each outlier patient were reviewed in a team meeting to determine possible reasons for outlier values. A total of 29 patients (34%) combined from all subgroups and 12 patients (30%) among the controls showed outlier values for one or more of the eight biomarkers. Nine patients with TBI and five control patients had outlier values in more than one biomarker (up to 4). All outlier values were > Q3 + 1.5 IQR. A logical explanation was found for almost all cases, except the amyloid proteins. Explanations for outlier values included extremely severe injury, especially for GFAP and S100B. In the case of H-FABP and IL-10, the explanation was extracranial injuries (thoracic injuries for H-FABP and multi-trauma for IL-10), in some cases these also were associated with abnormally high S100B. Timing of sampling and demographic factors such as age and pre-existing neurological conditions (especially for T-tau), explained some of the abnormally high values especially for Nf-L. Similar explanations also emerged in controls, where the outlier values were caused especially by pre-existing neurological diseases. To utilize blood-based biomarkers in clinical assessment of mo/sTBI, very severe or fatal TBIs, various extracranial injuries, timing of sampling, and demographic factors such as age and pre-existing systemic or neurological conditions must be taken into consideration. Very high levels seem to be often associated with poor prognosis and mortality (GFAP and S100B).

Plasma neurofilament light admission levels and development of axonal pathology in mild traumatic brain injury

BACKGROUND

It is known that blood levels of neurofilament light (NF-L) and diffusion-weighted magnetic resonance imaging (DW-MRI) are both associated with outcome of patients with mild traumatic brain injury (mTBI). Here, we sought to examine the association between admission levels of plasma NF-L and white matter (WM) integrity in post-acute stage DW-MRI in patients with mTBI.

METHODS

Ninety-three patients with mTBI (GCS ≥ 13), blood sample for NF-L within 24 h of admission, and DW-MRI ≥ 90 days post-injury (median = 229) were included. Mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated from the skeletonized WM tracts of the whole brain. Outcome was assessed using the Extended Glasgow Outcome Scale (GOSE) at the time of imaging. Patients were divided into CT-positive and -negative, and complete (GOSE = 8) and incomplete recovery (GOSE < 8) groups.

RESULTS

The levels of NF-L and FA correlated negatively in the whole cohort (p = 0.002), in CT-positive patients (p = 0.016), and in those with incomplete recovery (p = 0.005). The same groups showed a positive correlation with mean MD, AD, and RD (p < 0.001-p = 0.011). In CT-negative patients or in patients with full recovery, significant correlations were not found.

CONCLUSION

In patients with mTBI, the significant correlation between NF-L levels at admission and diffusion tensor imaging (DTI) measurements of diffuse axonal injury (DAI) over more than 3 months suggests that the early levels of plasma NF-L may associate with the presence of DAI at a later phase of TBI.

Trajectories of interleukin 10 and heart fatty acid-binding protein levels in traumatic brain injury patients with or without extracranial injuries

Background

Interleukin 10 (IL-10) and heart fatty acid-binding protein (H-FABP) have gained interest as diagnostic biomarkers of traumatic brain injury (TBI), but factors affecting their blood levels in patients with moderate-to-severe TBI are largely unknown.

Objective

To investigate the trajectories of IL-10 and H-FABP between TBI patients with and without extracranial injuries (ECI); to investigate if there is a correlation between the levels of IL-10 and H-FABP with the levels of inflammation/infection markers C-reactive protein (CRP) and leukocytes; and to investigate if there is a correlation between the admission level of H-FABP with admission levels of cardiac injury markers, troponin (TnT), creatine kinase (CK), and creatine kinase MB isoenzyme mass (CK-MBm).

Materials and methods

The admission levels of IL-10, H-FABP, CRP, and leukocytes were measured within 24 h post-TBI and on days 1, 2, 3, and 7 after TBI. The admission levels of TnT, CK, and CK-MBm were measured within 24 h post-TBI.

Results

There was a significant difference in the concentration of H-FABP between TBI patients with and without ECI on day 0 (48.2 ± 20.5 and 12.4 ± 14.7 ng/ml, p = 0.02, respectively). There was no significant difference in the levels of IL-10 between these groups at any timepoints. There was a statistically significant positive correlation between IL-10 and CRP on days 2 (R = 0.43, p &lt; 0.01) and 7 (R = 0.46, p = 0.03) after injury, and a negative correlation between H-FABP and CRP on day 0 (R = -0.45, p = 0.01). The levels of IL-10 or H-FABP did not correlate with leukocyte counts at any timepoint. The admission levels of H-FABP correlated with CK (R = 0.70, p &lt; 0.001) and CK-MBm (R = 0.61, p &lt; 0.001), but not with TnT.

Conclusion

Inflammatory reactions during the early days after a TBI do not significantly confound the use of IL-10 and H-FABP as TBI biomarkers. Extracranial injuries and cardiac sources may influence the levels of H-FABP in patients with moderate-to-severe TBI.

A comparison of diffusion tensor imaging tractography and constrained spherical deconvolution with automatic segmentation in traumatic brain injury

Detection of microstructural white matter injury in traumatic brain injury (TBI) requires specialised imaging methods, of which diffusion tensor imaging (DTI) has been extensively studied. Newer fibre alignment estimation methods, such as constrained spherical deconvolution (CSD), are better than DTI in resolving crossing fibres that are ubiquitous in the brain and may improve the ability to detect microstructural injuries. Furthermore, automatic tract segmentation has the potential to improve tractography reliability and accelerate workflow compared to the manual segmentation commonly used. In this study, we compared the results of deterministic DTI based tractography and manual tract segmentation with CSD based probabilistic tractography and automatic tract segmentation using TractSeg. 37 participants with a history of TBI (with Glasgow Coma Scale 13-15) and persistent symptoms, and 41 healthy controls underwent deterministic DTI-based tractography with manual tract segmentation and probabilistic CSD-based tractography with TractSeg automatic segmentation.Fractional anisotropy (FA) and mean diffusivity of corpus callosum and three bilateral association tracts were measured. FA and MD values derived from both tractography methods were generally moderately to strongly correlated. CSD with TractSeg differentiated the groups based on FA, while DTI did not. CSD and TractSeg-based tractography may be more sensitive in detecting microstructural changes associated with TBI than deterministic DTI tractography. Additionally, CSD with TractSeg was found to be applicable at lower b-value and number of diffusion-encoding gradients data than previously reported.

Differentially Expressed Genes Enrichment Analysis of Pancreatic Ductal Adenocarcinoma and Pancreatic Intraepithelial Neoplasia; an In Silico Study

Introduction/Objective

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related death in the United States. Determining the genetic alterations involved in the formation of PDAC and its precursor, pancreatic intraepithelial neoplasia (PanIN), may lead to earlier detection and new therapeutic options. We performed an analysis of the genetic alterations responsible for the progression of the normal pancreatic tissue to PanIN and ultimately from PanIN to PDAC.

Methods/Case Report

Initially, we used the continuous bioinformatic analysis in such a way that the RNA-seq datasets were extracted from the Biojupies database. We separately analyzed two datasets that included PDAC and PanIN, where their differentially expressed genes (DEGs) were obtained by comparison with controls. A Venn diagram was drawn to visualize the overlapping and non-overlapping DEGs in both groups. Using the Enrichr and ShinyGO databases, we examined the cell signaling pathways and ontologies of up/down-regulated genes. We mapped the protein network of important genes involved in cancer pathways by the STRING database. Finally, the shared and non-shared candidate proteins in the PDAC and PanIN pathways with the GEPIA database were confirmed in human samples.

Results (if a Case Study enter NA)

We found six shared genes in PDAC and PanIN including RAC1, RAP1A, ITGA5, RHOA, FZD2, and FN1, which appear to take part in the transition of PanIN to PDAC. Our result showed that the aforementioned genes are critical in the cell cycle, angiogenesis, and cell death processes. In the next step, the DEGs analysis in both PDAC and PanIN revealed the role of candidate genes (COX5B, NME2, MGLL, and PAICS for PanIN and PRKCA, PLCG2, NOS3, and PTK2 for PDAC) in cellular aging, MAPK, and PI3K/Akt signaling pathways.

Conclusion

Our findings showed that the overexpression of RAC1, RAP1A, ITGA5, RHOA, FZD2, and FN1 may have an important role in PanIN shifting to PDAC.

Cerebral Microbleeds and Structural White Matter Integrity in Patients With Traumatic Brain Injury-A Diffusion Tensor Imaging Study

Diffuse axonal injury (DAI) is a common neuropathological manifestation of traumatic brain injury (TBI), presenting as traumatic alterations in the cerebral white matter (WM) microstructure and often leading to long-term neurocognitive impairment. These WM alterations can be assessed using diffusion tensor imaging (DTI). Cerebral microbleeds (CMBs) are a common finding on head imaging in TBI and are often considered a visible sign of DAI, although they represent diffuse vascular injury. It is poorly known how they associate with long-term white matter integrity. This study included 20 patients with TBI and CMBs, 34 patients with TBI without CMBs, and 11 controls with orthopedic injuries. DTI was used to assess microstructural WM alterations. CMBs were detected using susceptibility-weighted imaging (SWI) and graded according to their location in the WM and total lesion load was counted. Patients underwent SWI within 2 months after injury. DTI and clinical outcome assessment were performed at an average of eight months after injury. Outcome was assessed using the extended Glasgow Outcome Scale (GOSe). The Glasgow Coma Scale (GCS) and length of post-traumatic amnesia (PTA) were used to assess clinical severity of the injury. We found that CMB grading and total lesion load were negatively associated with fractional anisotropy (FA) and positively associated with mean diffusivity (MD). Patients with TBI and CMBs had decreased FA and increased MD compared with patients with TBI without CMBs. CMBs were also associated with worse clinical outcome. When adjusting for the clinical severity of the injury, none of the mentioned associations were found. Thus, the difference in FA and MD is explained by patients with TBI and CMBs having more severe injuries. Our results suggest that CMBs are not associated with greater WM alterations when adjusting for the clinical severity of TBI. Thus, CMBs and WM alterations may not be strongly associated pathologies in TBI.

Structural brain connectivity correlates with outcome in mild traumatic brain injury

We investigated the topology of structural brain connectivity networks and its association to outcome following mild traumatic brain injury, a major cause of permanent disability. Eighty-five patients with mild traumatic brain injury underwent MRI twice, about three weeks and eight months after injury, and 30 age-matched orthopedic trauma control subjects were scanned. Outcome was assessed with Extended Glasgow Outcome Scale on average eight months after injury. We performed constrained spherical deconvolution based probabilistic streamlines tractography on diffusion MRI data and parcellated cortical and subcortical gray matter into 84 regions based on T1-weighted data to reconstruct structural brain connectivity networks weighted by the number of streamlines. Graph theoretical methods were employed to measure network properties in both patients and controls, and correlations between these properties and outcome were calculated. We found no global differences in the network properties between patients with mild traumatic brain injury and orthopedic control subjects at either stage. However, we found significantly increased betweenness centrality of the right pars opercularis in the chronic stage compared to control subjects. Furthermore, both global and local network properties correlated significantly with outcome. Higher normalized global efficiency, degree, and strength as well as lower small-worldness were associated with better outcome. Correlations between the outcome and the local network properties were the most prominent in the left putamen and the left postcentral gyrus. Our results indicate that both global and local network properties provide valuable information about the outcome already in the acute/subacute stage, and therefore, are promising biomarkers for prognostic purposes in mild traumatic brain injury.

Potential of heart fatty-acid binding protein, neurofilament light, interleukin-10 and S100 calcium-binding protein B in the acute diagnostics and severity assessment of traumatic brain injury

BACKGROUND

There is substantial interest in blood biomarkers as fast and objective diagnostic tools for traumatic brain injury (TBI) in the acute setting.

METHODS

Adult patients (≥18) with TBI of any severity and indications for CT scanning and orthopaedic injury controls were prospectively recruited during 2011-2013 at Turku University Hospital, Finland. The severity of TBI was classified with GCS: GCS 13-15 was classified as mild (mTBI); GCS 9-12 as moderate (moTBI) and GCS 3-8 as severe (sTBI). Serum samples were collected within 24 hours of admission and biomarker levels analysed with high-performance kits. The ability of biomarkers to distinguish between severity of TBI and CT-positive and CT-negative patients was assessed.

RESULTS

Among 189 patients recruited, neurofilament light (NF-L) was obtained from 175 patients with TBI and 40 controls. S100 calcium-binding protein B (S100B), heart fatty-acid binding protein (H-FABP) and interleukin-10 (IL-10) were analysed for 184 patients with TBI and 39 controls. There were statistically significant differences between levels of all biomarkers between the severity classes, but none of the biomarkers distinguished patients with moTBI from patients with sTBI. Patients with mTBI discharged from the ED had lower levels of IL-10 (0.26, IQR=0.21, 0.39 pg/mL), H-FABP (4.15, IQR=2.72, 5.83 ng/mL) and NF-L (8.6, IQR=6.35, 15.98 pg/mL) compared with those admitted to the neurosurgical ward, IL-10 (0.55, IQR=0.31, 1.42 pg/mL), H-FABP (6.022, IQR=4.19, 20.72 ng/mL) and NF-L (13.95, IQR=8.33, 19.93 pg/mL). We observed higher levels of H-FABP and NF-L in older patients with mTBI. None of the biomarkers or their combinations was able to distinguish CT-positive (n=36) or CT-negative (n=58) patients with mTBI from controls.

CONCLUSIONS

S100B, H-FABP, NF-L and IL-10 levels in patients with mTBI were significantly lower than in patients with moTBI and sTBI but alone or in combination, were unable to distinguish patients with mTBI from orthopaedic controls. This suggests these biomarkers cannot be used alone to diagnose mTBI in trauma patients in the acute setting.

Alterations in Microstructure and Local Fiber Orientation of White Matter Are Associated with Outcome after Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) can have long-lasting consequences. We investigated white matter (WM) alterations at 6-12 months following mTBI using diffusion tensor imaging (DTI) and assessed if the alterations associate with outcome. Eighty-five patients with mTBI underwent diffusion-weighted magnetic resonance imaging (MRI) on average 8 months post-injury and patients' outcome was assessed at the time of imaging using the Glasgow Outcome Scale-Extended (GOS-E). Additionally, 30 age-matched patients with extracranial orthopedic injuries were used as control subjects. Voxel-wise analysis of the data was performed using a tract-based spatial statistics (TBSS) approach and differences in microstructural metrics between groups were investigated. Further, the susceptibility of the abnormalities to specific fiber orientations was investigated by analyzing the first eigenvector of the diffusion tensor in the voxels with significant differences. We found significantly lower fractional anisotropy (FA) and higher mean diffusivity (MD) and radial diffusivity (RD) in patients with mTBI compared with control subjects, whereas no significant differences were observed in axial diffusivity (AD) between the groups. The differences were present bilaterally in several WM regions and correlated with outcome. Moreover, multiple clusters were found in the principal fiber orientations of the significant voxels in anisotropy, and similar orientation patterns were found for the diffusivity metrics. These directional clusters correlated with patients' functional outcome. Our study showed that mTBI is associated with WM changes at the chronic stage and these alterations occur in several WM regions. In addition, several significant clusters of WM alterations in specific fiber orientations were found and these clusters were associated with outcome.

Admission Levels of Interleukin 10 and Amyloid β 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI).

Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI.

Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%.

Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4).

Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI.

Admission Levels of Total Tau and β-Amyloid Isoforms 1-40 and 1-42 in Predicting the Outcome of Mild Traumatic Brain Injury

Background: The purpose of this study was to investigate if admission levels of total tau (T-tau) and β-amyloid isoforms 1-40 (Aβ40) and 1-42 (Aβ42) could predict clinical outcome in patients with mild traumatic brain injury (mTBI).

Methods: A total of 105 patients with mTBI [Glasgow Coma Scale (GCS) ≥ 13] recruited in Turku University Hospital, Turku, Finland were included in this study. Blood samples were drawn within 24 h of admission for analysis of plasma T-tau, Aβ40, and Aβ42. Patients were divided into computed tomography (CT)-positive and CT-negative groups. The outcome was assessed 6–12 months after the injury using the Extended Glasgow Outcome Scale (GOSE). Outcomes were defined as complete (GOSE 8) or incomplete (GOSE < 8) recovery. The Rivermead Post Concussion Symptoms Questionnaire (RPCSQ) was also used to assess mTBI-related symptoms. Predictive values of the biomarkers were analyzed independently, in panels and together with clinical parameters.

Results: The admission levels of plasma T-tau, Aβ40, and Aβ42 were not significantly different between patients with complete and incomplete recovery. The levels of T-tau, Aβ40, and Aβ42 could poorly predict complete recovery, with areas under the receiver operating characteristic curve 0.56, 0.52, and 0.54, respectively. For the whole cohort, there was a significant negative correlation between the levels of T-tau and ordinal GOSE score (Spearman ρ = −0.231, p = 0.018). In a multivariate logistic regression model including age, GCS, duration of posttraumatic amnesia, Injury Severity Score (ISS), time from injury to sampling, and CT findings, none of the biomarkers could predict complete recovery independently or together with the other two biomarkers. Plasma levels of T-tau, Aβ40, and Aβ42 did not significantly differ between the outcome groups either within the CT-positive or CT-negative subgroups. Levels of Aβ40 and Aβ42 did not significantly correlate with outcome, but in the CT-positive subgroup, the levels of T-tau significantly correlated with ordinal GOSE score (Spearman ρ = −0.288, p = 0.035). The levels of T-tau, Aβ40, and Aβ42 were not correlated with the RPCSQ scores.

Conclusions: The early levels of T-tau are correlated with the outcome in patients with mTBI, but none of the biomarkers either alone or in any combinations could predict complete recovery in patients with mTBI.

Insights into disseminated MS brain pathology with multimodal diffusion tensor and PET imaging

OBJECTIVE

To evaluate in vivo the co-occurrence of microglial activation and microstructural white matter (WM) damage in the MS brain and to examine their association with clinical disability.

METHODS

18-kDa translocator protein (TSPO) brain PET imaging was performed for evaluation of microglial activation by using the radioligand [11C](R)-PK11195. TSPO binding was evaluated as the distribution volume ratio (DVR) from dynamic PET images. Diffusion tensor imaging (DTI) and conventional MRI (cMRI) were performed at the same time. Mean fractional anisotropy (FA) and mean (MD), axial, and radial (RD) diffusivities were calculated within the whole normal-appearing WM (NAWM) and segmented NAWM regions appearing normal in cMRI. Fifty-five patients with MS and 15 healthy controls (HCs) were examined.

RESULTS

Microstructural damage was observed in the NAWM of the MS brain. DTI parameters of patients with MS were significantly altered in the NAWM compared with an age- and sex-matched HC group: mean FA was decreased, and MD and RD were increased. These structural abnormalities correlated with increased TSPO binding in the whole NAWM and in the temporal NAWM (p < 0.05 for all correlations; p < 0.01 for RD in the temporal NAWM). Both compromised WM integrity and increased microglial activation in the NAWM correlated significantly with higher clinical disability measured with the Expanded Disability Status Scale score.

CONCLUSIONS

Widespread structural disruption in the NAWM is linked to neuroinflammation, and both phenomena associate with clinical disability. Multimodal PET and DTI allow in vivo evaluation of widespread MS pathology not visible using cMRI.

Correlation of Blood Biomarkers and Biomarker Panels with Traumatic Findings on Computed Tomography after Traumatic Brain Injury

The aim of the study was to examine the ability of eight protein biomarkers and their combinations in discriminating computed tomography (CT)-negative and CT-positive patients with traumatic brain injury (TBI), utilizing highly sensitive immunoassays in a well-characterized cohort. Blood samples were obtained from 160 patients with acute TBI within 24 h of admission. Levels of β-amyloid isoforms 1-40 (Aβ40) and 1-42 (Aβ42), glial fibrillary acidic protein (GFAP), heart fatty-acid binding protein (H-FABP), interleukin 10 (IL-10), neurofilament light (NF-L), S100 calcium-binding protein B (S100B), and tau were measured. Patients were divided into CT-negative (n = 65) and CT-positive (n = 95), and analyses were conducted separately for TBIs of all severities (Glasgow Coma Scale [GCS] score 3-15) and mild TBIs (mTBIs; GCS 13-15). NF-L, GFAP, and tau were the best in discriminating CT-negative and CT-positive patients, both in patients with mTBI and with all severities. In patients with all severities, area under the curve of the receiver operating characteristic (AUC) was 0.822, 0.817, and 0.781 for GFAP, NF-L, and tau, respectively. In patients with mTBI, AUC was 0.720, 0.689, and 0.676, for GFAP, tau, and NF-L, respectively. The best panel of three biomarkers for discriminating CT-negative and CT-positive patients in the group of all severities was a combination of GFAP+H-FABP+IL-10, with a sensitivity of 100% and specificity of 38.5%. In patients with mTBI, the best panel of three biomarkers was H-FABP+S100B+tau, with a sensitivity of 100% and specificity of 46.4%. Panels of biomarkers outperform individual biomarkers in separating CT-negative and CT-positive patients. Panels consisted mainly of different biomarkers than those that performed best as an individual biomarker.

Early Levels of Glial Fibrillary Acidic Protein and Neurofilament Light Protein in Predicting the Outcome of Mild Traumatic Brain Injury

The purpose of this study was to correlate the early levels of glial fibrillary acidic protein (GFAP) and neurofilament light protein (NF-L) with outcome in patients with mild traumatic brain injury (mTBI). A total of 107 patients with mTBI (Glasgow Coma Scale ≥13) who had blood samples for GFAP and NF-L available within 24 h of arrival were included. Patients with mTBI were divided into computed tomography (CT)-positive and CT-negative groups. Glasgow Outcome Scale-Extended (GOSE) was used to assess the outcome. Outcomes were defined as complete (GOSE 8) versus incomplete (GOSE <8), and favorable (GOSE 5-8) versus unfavorable (GOSE 1-4). GFAP and NF-L concentrations in blood were measured using ultrasensitive single molecule array technology. Patients with incomplete recovery had significantly higher levels of NF-L compared with those with complete recovery (p = 0.005). The levels of GFAP and NF-L were significantly higher in patients with unfavorable outcome than in patients with favorable outcome (p = 0.002 for GFAP and p < 0.001 for NF-L). For predicting favorable outcome, the area under the receiver operating characteristic curve for GFAP and NF-L was 0.755 and 0.826, respectively. In a multi-variate logistic regression model, the level of NF-L was still a significant predictor for complete recovery (odds ratio [OR] = 1.008; 95% confidence interval [CI], 1.000-1.016). Moreover, the level of NF-L was a significant predictor for complete recovery in CT-positive patients (OR = 1.009; 95% CI, 1.001-1.016). The early levels of GFAP and NF-L are significantly correlated with the outcome in patients with mTBI. The level of NF-L within 24 h from arrival has a significant predictive value in mTBI also in a multi-variate model.

CFPD simulation of magnetic drug delivery to a human lung using an SAW nebulizer

Targeted drug delivery is an impressive topic that attracted the attention of many scientists in various scientific communities. Magnetic drug targeting is one of the targeted drug delivery techniques, which uses the magnetic field to externally control the magnetic drug particles. In this study, we aim to assess the magnetic drug delivery to the human respiratory system using a new aerosolization technique driven by surface acoustic waves (SAWs) into a realistic lung model geometrically reconstructed using computed tomography scan images. To achieve this aim, a simulation study using computational fluid-particle dynamics considering the Lagrangian approach for particle tracking is carried out. An external magnetic field was applied to govern the Magnetit (Fe₃O₄) particles as the magnetic drug career. The drug particles were assumed to be spherical and inert. The effects of magnetic field intensity, magnetic source position, and SAW injection position were examined for a light breathing condition (Q = 15 L/min). Given the realistic geometry of the respiratory system and its complexity, the airflow patterns vary as it penetrates deeper into the lung and experiences many irregularities, and bending deflections exist in the airways model. High-inertia particles tend to deposit at locations where the geometry experiences a significant reduction in cross section. Our results show that the magnetic field highly affects the particle deposition efficiency for fourfold. However, the magnet and SAW injection positions have a low impact on the deposition efficiency of drug particles.

High angular resolution diffusion-weighted imaging in mild traumatic brain injury

We sought to investigate white matter abnormalities in mild traumatic brain injury (mTBI) using diffusion-weighted magnetic resonance imaging (DW-MRI). We applied a global approach based on tract-based spatial statistics skeleton as well as constrained spherical deconvolution tractography. DW-MRI was performed on 102 patients with mTBI within two months post-injury and 30 control subjects. A robust global approach considering only the voxels with a single-fiber configuration was used in addition to global analysis of the tract skeleton and probabilistic whole-brain tractography. In addition, we assessed whether the microstructural parameters correlated with age, time from injury, patient's outcome and white matter MRI hyperintensities. We found that whole-brain global approach restricted to single-fiber voxels showed significantly decreased fractional anisotropy (FA) (p = 0.002) and increased radial diffusivity (p = 0.011) in patients with mTBI compared with controls. The results restricted to single-fiber voxels were more significant and reproducible than those with the complete tract skeleton or the whole-brain tractography. FA correlated with patient outcomes, white matter hyperintensities and age. No correlation was observed between FA and time of scan post-injury. In conclusion, the global approach could be a promising imaging biomarker to detect white matter abnormalities following traumatic brain injury.

Molecular detection of Crimean-Congo haemorrhagic fever virus in ticks collected from infested livestock populations in a New Endemic Area, South of Iran

OBJECTIVE

Crimean-Congo haemorrhagic fever (CCHF) is a viral zoonotic disease with potentially fatal systemic effects on man. We aimed to determine the presence of CCHF virus among collected ticks from domestic livestock from October 2012 to September 2013.

METHODS

A total of 1245 hard and soft ticks were collected from naturally infested ruminants in Marvdasht County, Fars Province, south of Iran. Nine tick species and one unidentified species in four disparate genera were detected. A total of 200 ticks were randomly selected and analysed by reverse transcription-polymerase chain reaction (RT-PCR) for the presence of CCHF virus genome.

RESULTS

The viral genome was detected in 4.5% (9 samples) of the studied tick population. The infected ticks belonged to the species of Hyalomma marginatum' Hyalomma anatolicum and Rhipicephalus sanguineus. The viruses detected in these three tick species were clustered in the same lineage as Matin and SR3 strains in Pakistan and some other Iranian strains. These results indicate that the ticks were wildly infected with a genetically closely related CCHF virus in the region.

CONCLUSION

Regular controls and monitoring of livestock to reduce the dispersion of ticks and providing information to those involved in high-risk occupations are urgently required.

Combined impacts of future climate and land use changes on discharge, nitrogen and phosphorus loads for a Canadian river basin

Both climate and land use changes can influence water quality and quantity in different ways. Thus, for predicting future water quality and quantity trends, simulations should ideally account for both projected climate and land use changes. In this paper, land use projections and climate change scenarios were integrated with a hydrological model to estimate the relative impact of climate and land use projections on a suite of water quality and quantity endpoints for a Canadian watershed. Climatic time series representing SRES change scenario A2 were generated by downscaling the outputs of the Canadian Regional Climate Model (version 4.1.1) using a combination of quantile-quantile transformation and nearest neighbor search. The SWAT (Soil and Water Assessment Tool) model was used to simulate streamflow, nitrogen and phosphorus loading under different climate and land use scenarios. Results showed that a) climate change will drive up maximum monthly streamflow, nitrate loads, and organic phosphorus loads, while decreasing organic nitrogen and nitrite loads; and b) land use changes were found to drive the same water quality/quantity variables in the same direction as climate change, except for organic nitrogen loads, for which the effects of the two stressors had a reverse impact on loading.

Red/blue spectral shifts of laser-induced fluorescence emission due to different nanoparticle suspensions in various dye solutions

Red/blue shifts of laser-induced fluorescence (LIF) are investigated using several guest dielectric nanoscatterers, such as TiO2, ZnO, Al2O3, and SiO2, in the host Rd6G, RdB, Coumarin 4, and Coumarin 7 ethanolic solutions. A couple of inflection points are identified varying nanoparticle (NP) density into dye solutions based on LIF spectroscopy. The inflection of the spectral shift exhibits that the suspension of NPs in dye solutions significantly involves a couple of competitive chemical and optical mechanisms during photon traveling in scattering media regarding ballistic and diffusive transport. It is shown that the low, medium, and high NP additives in fluorescent suspension induce blue, red, and blue spectral shifts, respectively.

Designing Unsupervised Hierarchical Fuzzy Logic Systems

Systems such as robotic systems and systems with large input-output data tend to be difficult to model using mathematical techniques. These systems have typically high dimensionality and have degrees of uncertainty in many parameters. Artificial intelligence techniques such as neural networks, fuzzy logic, genetic algorithms and evolutionary algorithms have created new opportunities to solve complex systems. Application of fuzzy logic [Bai, Y., Zhuang H. and Wang, D. (2006)] in particular, to model and solve industrial problems is now wide spread and has universal acceptance. Fuzzy modelling or fuzzy identification has numerous practical applications in control, prediction and inference. It has been found useful when the system is either difficult to predict and or difficult to model by conventional methods. Fuzzy set theory provides a means for representing uncertainties. The underlying power of fuzzy logic is its ability to represent imprecise values in an understandable form. The majority of fuzzy logic systems to date have been static and based upon knowledge derived from imprecise heuristic knowledge of experienced operators, and where applicable also upon physical laws that governs the dynamics of the process. Although its application to industrial problems has often produced results superior to classical control, the design procedures are limited by the heuristic rules of the system. It is simply assumed that the rules for the system are readily available or can be obtained. This implicit assumption limits the application of fuzzy logic to the cases of the system with a few parameters. The number of parameters of a system could be large. The number of fuzzy rules of a system is directly dependent on these parameters. As the number of parameters increase, the number of fuzzy rules of the system grows exponentially. Genetic Algorithms can be used as a tool for the generation of fuzzy rules for a fuzzy logic system. This automatic generation of fuzzy rules, via genetic algorithms, can be categorised into two learning techniques, supervised and unsupervised. In this paper unsupervised learning of fuzzy rules of hierarchical and multi-layer fuzzy logic control systems are considered. In unsupervised learning there is no external teacher or critic to oversee the learning process. In other words, there are no specific examples of the function to be learned by the system. Rather, provision is made for a task-independent measure of the quality or representation that the system is required to learn. That is the system learns statistical regularities of the input data and it develops the ability to learn the feature of the input data and thereby create new classes automatically [Mohammadian, M., Nainar, I. and Kingham, M. (1997)]. To perform unsupervised learning, a competitive learning strategy may be used. The individual strings of genetic algorithms compete with each other for the “opportunity” to respond to features contained in the input data. In its simplest form, the system operates in accordance with the strategy that ‘the fittest wins and survives’. That is the individual chromosome in a population with greatest fitness ‘wins’ the competition and gets selected for the genetic algorithms operations (cross-over and mutation). The other individuals in the population then have to compete with fit individual to survive. The diversity of the learning tasks shown in this paper indicates genetic algorithm’s universality for concept learning in unsupervised manner. A hybrid integrated architecture incorporating fuzzy logic and genetic algorithm can generate fuzzy rules for problems requiring supervised or unsupervised learning. In this paper only unsupervised learning of fuzzy logic systems is considered. The learning of fuzzy rules and internal parameters in an unsupervised manner is performed using genetic algorithms. Simulations results have shown that the proposed system is capable of learning the control rules for hierarchical and multi-layer fuzzy logic systems. Application areas considered are, hierarchical control of a network of traffic light control and robotic systems. A first step in the construction of a fuzzy logic system is to determine which variables are fundamentally important. Any number of these decision variables may appear, but the more that are used, the larger the rule set that must be found. It is known [Raju, S., Zhou J. and Kisner, R. A. (1990), Raju G. V. S. and Zhou, J. (1993), Kingham, M., Mohammadian, M, and Stonier, R. J. (1998)], that the total number of rules in a system is an exponential function of the number of system variables. In order to design a fuzzy system with the required accuracy, the number of rules increases exponentially with the number of input variables and its associated fuzzy sets for the fuzzy logic system. A way to avoid the explosion of fuzzy rule bases in fuzzy logic systems is to consider Hierarchical Fuzzy Logic Control (HFLC) [Raju G. V. S. and Zhou, J. (1993)]. A learning approach based on genetic algorithms [Goldberg, D. (1989)] is discussed in this paper for the determination of the rule bases of hierarchical fuzzy logic systems.