We examined the interplay between cytokines and adjuvants to optimize the induction of CTL by a mucosal HIV peptide vaccine. We show synergy between IL-12 and GM-CSF when administered together with ...the HIV peptide PCLUS3-18IIIB and cholera toxin (CT) in the induction of CTL activity and protection against mucosal viral transmission. Further, we examine the efficacy of mutant Escherichia coli labile toxin, LT(R192G), as a less toxic adjuvant than CT. LT(R192G) was as effective as or more effective than CT at inducing a mucosal CTL response. Moreover, LT(R192G) was as effective without IL-12 as CT was when combined with IL-12, and the response elicited by LT(R192G) with the vaccine was not further enhanced by the addition of IL-12. GM-CSF synergized with LT(R192G) without exogenous IL-12. Therefore, LT(R192G) may induce a more favorable cytokine response by not inhibiting IL-12 production. In particular, less IL-4 is made after LT(R192G) than CT immunization, and the response is less susceptible to anti-IL-12 inhibition. Thus, the choice of mucosal adjuvant affects the cytokine environment, and the mucosal response and protection can be enhanced by manipulating the cytokine environment with synergistic cytokine combinations incorporated in the vaccine.
Precise determination of transgene zygosity is essential for use of transgenic mice in research. Because integration loci of transgenes are usually unknown due to their random insertion, assessment ...of transgene zygosity remains a challenge. Current zygosity genotyping methods (progeny testing, qPCR, and NGS-computational biology analysis) are time consuming, prone to error or technically challenging. Here, we developed a novel method to determine transgene zygosity requiring no knowledge of transgene insertion loci. This method applies allele-specific restriction enzyme digestion of PCR products (RE/PCR) to rapidly and reliably quantify transgene zygosity. We demonstrate the applicability of this method to three transgenic strains of mice (
Tg
,
, and
) harboring a unique restriction enzyme site on either the transgene or its homologous sequence in the mouse genome. This method is as accurate as the gold standard of progeny testing but requires 2 d instead of a month or more. It is also exceedingly more accurate than the most commonly used approach of qPCR quantification. Our novel method represents a significant technical advance in determining transgene zygosities in mice.
Background: White matter hyperintensities (WMHs) are foci of abnormal signal intensity in white matter regions seen with magnetic resonance imaging (MRI). WMHs are associated with normal ageing and ...have shown prognostic value in neurological conditions such as traumatic brain injury (TBI). The impracticality of manually quantifying these lesions limits their clinical utility and motivates the utilization of machine learning techniques for automated segmentation workflows.
Methods: This study develops a concatenated random forest framework with image features for segmenting WMHs in a TBI cohort. The framework is built upon the Advanced Normalization Tools (ANTs) and ANTsR toolkits. MR (3D FLAIR, T2- and T1-weighted) images from 24 service members and veterans scanned in the Chronic Effects of Neurotrauma Consortium's (CENC) observational study were acquired. Manual annotations were employed for both training and evaluation using a leave-one-out strategy. Performance measures include sensitivity, positive predictive value,
score and relative volume difference.
Results: Final average results were: sensitivity = 0.68 ± 0.38, positive predictive value = 0.51 ± 0.40,
= 0.52 ± 0.36, relative volume difference = 43 ± 26%. In addition, three lesion size ranges are selected to illustrate the variation in performance with lesion size.
Conclusion: Paired with correlative outcome data, supervised learning methods may allow for identification of imaging features predictive of diagnosis and prognosis in individual TBI patients.
Blast-induced traumatic brain injury (TBI) has been a major cause of morbidity and mortality in the conflicts in Iraq and Afghanistan. How the primary blast wave affects the brain is not well ...understood. In particular, it is unclear whether blast injures the brain through mechanisms similar to those found in non-blast closed impact injuries (nbTBI). The β-amyloid (Aβ) peptide associated with the development of Alzheimer's disease is elevated acutely following TBI in humans as well as in experimental animal models of nbTBI. We examined levels of brain Aβ following experimental blast injury using enzyme-linked immunosorbent assays for Aβ 40 and 42. In both rat and mouse models of blast injury, rather than being increased, endogenous rodent brain Aβ levels were decreased acutely following injury. Levels of the amyloid precursor protein (APP) were increased following blast exposure although there was no evidence of axonal pathology based on APP immunohistochemical staining. Unlike the findings in nbTBI animal models, levels of the β-secretase, β-site APP cleaving enzyme 1, and the γ-secretase component presenilin-1 were unchanged following blast exposure. These studies have implications for understanding the nature of blast injury to the brain. They also suggest that strategies aimed at lowering Aβ production may not be effective for treating acute blast injury to the brain.
Two studies were conducted that examined the preference of a student diagnosed with a brain injury. In Study 1, a preference assessment was followed by a three‐choice concurrent‐operants reinforcer ...assessment. Two choices resulted in access to preferred activities for completing work, and a third choice resulted in access to nothing (i.e., no activity). Unpredictably, the participant consistently chose the no‐activity option. Study 2 examined why this student preferred work associated with no activity over preferred activities. Through a variety of concurrent‐operants procedures, it was determined that she preferred fluent work followed by reinforcers rather than work that was broken up by access to preferred activities. Implications for research on preference are discussed.
To quantify and correlate the morphological and functional effects of the recommended loading regimen with intravitreal ranibizumab in neovascular age-related macular degeneration (AMD).
In a ...prospective, interventional clinical trial, 29 consecutive patients (29 eyes) with choroidal neovascularisation secondary to AMD received three initial monthly intravitreal injections of ranibizumab. During this loading regimen, best corrected visual acuity (BCVA) and microperimetry (MP) testing, as well as optical coherence tomography and fluorescein angiography (FA), were performed using a standardised protocol and the results correlated.
Significant morphological and functional therapeutic effects were observed as early as 1 week following the first treatment. Throughout the loading-dose period, central retinal thickness, including intraretinal cysts and subretinal fluid, decreased fast and significantly (p<0.01); pigment epithelial detachment resolved less rapidly. The mean leakage area by FA decreased (p<0.01) and retinal function (BCVA and MP) increased significantly (both p<0.01). However, the change in morphology and function was only significant between baseline and week 1. There was no significant additional morphological or functional benefit following the second and third injection.
The initial administration of intravitreal ranibizumab in neovascular AMD induced a significant effect on intra- and subretinal fluid and visual function; subsequent injections had a less pronounced effect. It remains to be determined whether this loading regimen should be mandatory in all patients or if a single dose regimen would lead to a comparable functional and morphological retinal improvement.
Introduction:
Primary CNS lymphomas (PCNSL) are heterogeneous, aggressive, extra-nodal non-Hodgkin lymphomas limited to the neuraxis. Published response rates to high-dose methotrexate (MTX) based ...induction regimens for PCNSL range from 35-78%. However, >50% of patients relapse and have a median survival of 2 months without additional treatment. Our ability to prognosticate outcomes is limited to clinical models like the International Extranodal Lymphoma Study Group (IELSG) score and Memorial Sloan-Kettering Cancer Center (MSKCC) classifier. There is an urgent need to develop improved biologic and radiologic predictive models for PCNSL to facilitate therapeutic advances. We hypothesize that a machine learning model using advanced magnetic resonance imaging (MRI) tumor characteristics will improve the accuracy of clinical models to predict response to MTX and survival outcomes.
Methods:
Data from patients with PCNSL treated at UT Southwestern and Parkland Health and Hospital System hospitals from 2008-2020 (n=95) were collected. An analytical dataset of 61 patients was selected based on the availability of T1 postcontrast (T1c) and T2w FLAIR MR images. A subset of 47 patients was used to evaluate MTX treatment response. Expert neuroradiologists drew regions of interest (ROIs) on the multiparametric MR images including whole tumor (consisting of edema + enhancing tumor + necrosis), enhancing tumor and necrosis (Figure 1). Response to methotrexate-based induction was defined per the International Primary CNS Lymphoma Collaborative Group (IPCG) criteria. For overall- and progression-free survival (OS and PFS) analysis, short (≤1 year) and long-term (>1 year) survivor groups were defined. A support vector machine (SVM) network was used for predicting treatment response to MTX and for predicting the OS groups. A Multinomial Naive Bayes (MNB) network was used for predicting the PFS groups. PyRadiomics package was used to extract 106 texture-based features from the combination of each MR image and tumor ROI. A total of 642 features were extracted from the imaging parameters. Clinical features including age, race, performance status, MSKCC class, IELSG score, histology, delay from 1st MRI to start of treatment, induction and consolidation treatments used were included in the analysis. Feature reduction methodology based on the feature importance derived from the gradient boost model was applied to reduce the number of features. 17 features (imaging = 14, clinical = 3) were used for predicting OS/PFS and 7 features (imaging = 5, clinical = 2) were used for predicting treatment response to MTX. Networks utilizing only clinical features were analyzed for comparison. The sklearn package in python was used for the machine learning analysis. 5-Fold cross validation was performed to generalize the network performance.
Results:
Baseline wclinical characteristics of the study population is shown in Table 1. Table 2 lists the accuracy, F1 score, sensitivity, specificity, positive predictive value, negative predictive value and area under the curve (AUC) values averaged for the 5-fold cross validation. The SVM network achieved a mean testing accuracy of 81.1 ± 12.3% for predicting the treatment response to MTX-based induction. Sensitivity, specificity and AUC values were 90.5 ± 13.1%, 63.3 ± 22.1% and 0.81 ± 0.14 respectively. The SVM and the MNB network achieved mean testing accuracies of 80.3 ± 11.4% and 83.3 ± 11.8% for predicting the long and short survival groups in OS and PFS respectively. Sensitivity, specificity and AUC values for the SVM and MNB networks were 79.3 ± 6.5%, 80.5 ± 16.5% and 0.86 ± 0.12 and 85.3 ± 12.9%, 81.9 ± 11.8% and 0.86 ± 0.13 respectively. The accuracy values for predicting treatment response to MTX, OS and PFS using only the clinical features were 61.6 ± 9.2%, 59.1 ± 16.4% and 62.1 ± 17.5% respectively.
Conclusion:
This machine learning model boosted the accuracy (≥20%) over currently validated clinical models alone in predicting response to methotrexate-based therapies and survival outcomes in PCNSL. The current analysis is limited by the small sample size, and we plan to statistically test this model across a larger dataset and report results at the meeting. Our preliminary results suggest that machine learning based radiomic analysis may predict biologic aggressiveness in PCNSL and has the potential to be integrated in clinical predictive tools and design of clinical trials.
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Awan:Blueprint medicines: Consultancy; Celgene: Consultancy; Sunesis: Consultancy; Karyopharm: Consultancy; MEI Pharma: Consultancy; Astrazeneca: Consultancy; Genentech: Consultancy; Dava Oncology: Consultancy; Kite Pharma: Consultancy; Gilead Sciences: Consultancy; Pharmacyclics: Consultancy; Janssen: Consultancy; Abbvie: Consultancy. Desai:Boston Scientific: Consultancy, Other: Trial Finding.
Blast-related traumatic brain injury (TBI) has been a significant cause of injury in the military operations of Iraq and Afghanistan, affecting as many as 10-20% of returning veterans. However, how ...blast waves affect the brain is poorly understood. To understand their effects, we analyzed the brains of rats exposed to single or multiple (three) 74.5 kPa blast exposures, conditions that mimic a mild TBI.
Rats were sacrificed 24 hours or between 4 and 10 months after exposure. Intraventricular hemorrhages were commonly observed after 24 hrs. A screen for neuropathology did not reveal any generalized histopathology. However, focal lesions resembling rips or tears in the tissue were found in many brains. These lesions disrupted cortical organization resulting in some cases in unusual tissue realignments. The lesions frequently appeared to follow the lines of penetrating cortical vessels and microhemorrhages were found within some but not most acute lesions.
These lesions likely represent a type of shear injury that is unique to blast trauma. The observation that lesions often appeared to follow penetrating cortical vessels suggests a vascular mechanism of injury and that blood vessels may represent the fault lines along which the most damaging effect of the blast pressure is transmitted.
Background
We examined the effects of moderate prenatal alcohol exposure and/or prenatal stress exposure on (D1R) binding in a non human primate model. The dopamine D1R is involved in executive ...function, and it may play a role in cognitive behavioral deficits associated with prenatal alcohol and/or stress exposure. Little is known, however, about the effects of prenatal alcohol and/or stress exposure on the D1R. We expected that prenatal insults would lead to alterations in D1R binding in prefrontal cortex (PFC) and striatum in adulthood.
Methods
Rhesus macaque females were randomly assigned to moderate alcohol exposure and/or mild prenatal stress as well as a control condition during pregnancy. Thirty‐eight offspring were raised identically and studied as adults by noninvasive in vivo neuroimaging using positron emission tomography with the D1 antagonist radiotracer 11CSCH 23390. Radiotracer binding in PFC and striatum was evaluated by 2 (alcohol) × 2 (stress) × 2 (sex) analysis of variance.
Results
In PFC, a significant alcohol × sex interaction was observed with prenatal alcohol exposure leading to increased 11CSCH 23390 binding in male monkeys. No main effect of prenatal alcohol or prenatal stress exposure was observed.
Conclusions
These results suggest that prenatal alcohol exposure results in long‐term increases in prefrontal dopamine D1R binding in males. This may help explain gender differences in the prevalence of neurodevelopmental disorders consequent to prenatal alcohol exposure.
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