Replication Data for: PLoS One article entitled "Indocyanine green fluorescence in second near-infrared (NIR-II) window"

This is the complete data set. It consist with the raw data : stacks of TIFF files and AVI files which is described in main manuscript

A natural language processing and deep learning approach to identify child abuse from pediatric electronic medical records.

Child physical abuse is a leading cause of traumatic injury and death in children. In 2017, child abuse was responsible for 1688 fatalities in the United States, of 3.5 million children referred to Child Protection Services and 674,000 substantiated victims. While large referral hospitals maintain teams trained in Child Abuse Pediatrics, smaller community hospitals often do not have such dedicated resources to evaluate patients for potential abuse. Moreover, identification of abuse has a low margin of error, as false positive identifications lead to unwarranted separations, while false negatives allow dangerous situations to continue. This context makes the consistent detection of and response to abuse difficult, particularly given subtle signs in young, non-verbal patients. Here, we describe the development of artificial intelligence algorithms that use unstructured free-text in the electronic medical record-including notes from physicians, nurses, and social workers-to identify children who are suspected victims of physical abuse. Importantly, only the notes from time of first encounter (e.g.: birth, routine visit, sickness) to the last record before child protection team involvement were used. This allowed us to develop an algorithm using only information available prior to referral to the specialized child protection team. The study was performed in a multi-center referral pediatric hospital on patients screened for abuse within five different locations between 2015 and 2019. Of 1123 patients, 867 records were available after data cleaning and processing, and 55% were abuse-positive as determined by a multi-disciplinary team of clinical professionals. These electronic medical records were encoded with three natural language processing (NLP) algorithms-Bag of Words (BOW), Word Embeddings (WE), and Rules-Based (RB)-and used to train multiple neural network architectures. The BOW and WE encodings utilize the full free-text, while RB selects crucial phrases as identified by physicians. The best architecture was selected by average classification accuracy for the best performing model from each train-test split of a cross-validation experiment. Natural language processing coupled with neural networks detected cases of likely child abuse using only information available to clinicians prior to child protection team referral with average accuracy of 0.90±0.02 and average area under the receiver operator characteristic curve (ROC-AUC) 0.93±0.02 for the best performing Bag of Words models. The best performing rules-based models achieved average accuracy of 0.77±0.04 and average ROC-AUC 0.81±0.05, while a Word Embeddings strategy was severely limited by lack of representative embeddings. Importantly, the best performing model had a false positive rate of 8%, as compared to rates of 20% or higher in previously reported studies. This artificial intelligence approach can help screen patients for whom an abuse concern exists and streamline the identification of patients who may benefit from referral to a child protection team. Furthermore, this approach could be applied to develop computer-aided-diagnosis platforms for the challenging and often intractable problem of reliably identifying pediatric patients suffering from physical abuse

Structure-Guided Design, Synthesis, and Evaluation of 1-Indanone and 1,3-Indandione Derivatives as Ligands for Misfolded α-Synuclein Aggregates

The development of imaging agents for in vivo detection of alpha-synuclein (α-syn) pathologies faces several challenges. A major gap in the field is the lack of diverse molecular scaffolds with high affinity and selectivity to α-syn fibrils for in vitro screening assays. Better in vitro scaffolds can instruct the discovery of better in vivo agents. We report the rational design, synthesis, and in vitro evaluation of a series of novel 1-indanone and 1,3-indandione derivatives from a Structure-Activity Relationship (SAR) study centered on some existing α-syn fibril binding ligands. Our results from fibril saturation binding experiments show that two of the lead candidates bind α-syn fibrils with binding constants (Kd) of 9.0 and 18.8 nM, respectively, and selectivity of greater than 10x for α-syn fibrils compared with amyloid-β (Aβ) fibrils. Our results demonstrate that the lead ligands avidly label all forms of α-syn on PD brain tissue sections, but only the dense core of senile plaques in AD brain tissue, respectively. These results are corroborated by ligand-antibody colocalization data from Syn211, which shows immunoreactivity towards all forms of α-syn aggregates, and Syn303, which displays preferential reactivity towards mature Lewy pathology. Our results reveal that 1-indanone derivatives have desirable properties for the biological evaluation of α-synucleinopathies.</p

Computed Tomography Imaging of Solid Tumors Using a Liposomal-Iodine Contrast Agent in Companion Dogs with Naturally Occurring Cancer.

OBJECTIVES:Companion dogs with naturally occurring cancer serve as an important large animal model in translational research because they share strong similarities with human cancers. In this study, we investigated a long circulating liposomal-iodine contrast agent (Liposomal-I) for computed tomography (CT) imaging of solid tumors in companion dogs with naturally occurring cancer. MATERIALS AND METHODS:The institutional animal ethics committees approved the study and written informed consent was obtained from all owners. Thirteen dogs (mean age 10.1 years) with a variety of masses including primary and metastatic liver tumors, sarcomas, mammary carcinoma and lung tumors, were enrolled in the study. CT imaging was performed pre-contrast and at 15 minutes and 24 hours after intravenous administration of Liposomal-I (275 mg/kg iodine dose). Conventional contrast-enhanced CT imaging was performed in a subset of dogs, 90 minutes prior to administration of Liposomal-I. Histologic or cytologic diagnosis was obtained for each dog prior to admission into the study. RESULTS:Liposomal-I resulted in significant (p < 0.05) enhancement and uniform opacification of the vascular compartment. Non-renal, reticulo-endothelial systemic clearance of the contrast agent was demonstrated. Liposomal-I enabled visualization of primary and metastatic liver tumors. Sub-cm sized liver lesions grossly appeared as hypo-enhanced compared to the surrounding normal parenchyma with improved lesion conspicuity in the post-24 hour scan. Large liver tumors (> 1 cm) demonstrated a heterogeneous pattern of intra-tumoral signal with visibly higher signal enhancement at the post-24 hour time point. Extra-hepatic, extra-splenic tumors, including histiocytic sarcoma, anaplastic sarcoma, mammary carcinoma and lung tumors, were visualized with a heterogeneous enhancement pattern in the post-24 hour scan. CONCLUSIONS:The long circulating liposomal-iodine contrast agent enabled prolonged visualization of small and large tumors in companion dogs with naturally occurring cancer. The study warrants future work to assess the sensitivity and specificity of the Liposomal-I agent in various types of naturally occurring canine tumors

Indocyanine green fluorescence in second near-infrared (NIR-II) window

<div><p>Indocyanine green (ICG), a FDA approved near infrared (NIR) fluorescent agent, is used in the clinic for a variety of applications including lymphangiography, intra-operative lymph node identification, tumor imaging, superficial vascular imaging, and marking ischemic tissues. These applications operate in the so-called “NIR-I” window (700–900 nm). Recently, imaging in the “NIR-II” window (1000–1700 nm) has attracted attention since, at longer wavelengths, photon absorption, and scattering effects by tissue components are reduced, making it possible to image deeper into the underlying tissue. Agents for NIR-II imaging are, however, still in pre-clinical development. In this study, we investigated ICG as a NIR-II dye. The absorbance and NIR-II fluorescence emission of ICG were measured in different media (PBS, plasma and ethanol) for a range of ICG concentrations. In vitro and in vivo testing were performed using a custom-built spectral NIR assembly to facilitate simultaneous imaging in NIR-I and NIR-II window. In vitro studies using ICG were performed using capillary tubes (as a simulation of blood vessels) embedded in Intralipid solution and tissue phantoms to evaluate depth of tissue penetration in NIR-I and NIR-II window. In vivo imaging using ICG was performed in nude mice to evaluate vascular visualization in the hind limb in the NIR-I and II windows. Contrast-to-noise ratios (CNR) were calculated for comparison of image quality in NIR-I and NIR-II window. ICG exhibited significant fluorescence emission in the NIR-II window and this emission (similar to the absorption profile) is substantially affected by the environment of the ICG molecules. In vivo imaging further confirmed the utility of ICG as a fluorescent dye in the NIR-II domain, with the CNR values being ~2 times those in the NIR-I window. The availability of an FDA approved imaging agent could accelerate the clinical translation of NIR-II imaging technology.</p></div

Replication Data for: PLoS One article entitled "Heterogeneous uptake of nanoparticles in mouse models of pediatric high-risk neuroblastoma"

This dataset contains computed tomography images (DICOM file format) related to the article published in PLoS One (2016), entitled "Heterogeneous uptake of nanoparticles in mouse models of pediatric high-risk neuroblastoma"

Signal attenuation properties of Liposomal-I.

<p>(A) Vascular CT signal was determined in descending aorta (Desc Ao), inferior vena cava (IVC) and portal vein (PV). (B) CT signal was determined in the liver and spleen, primary organs for systemic clearance of Liposomal-I, (C) CT signal was also measured in the kidney (cortex), bladder and muscle (erector spinae). CT signal measurements were determined in images acquired at 120 kVp. Measurements were performed pre-contrast and then at 15 min and 24 h after administration of Liposomal-I. The dose of Liposomal-I administered was 275 mg I/kg. Significant differences were observed in CT signal measured at each time point for all the ROIs in Fig 1A and Fig 1B (p < 0.05). In Fig 1A, CT signal measured for different vascular structures at each time were not significantly different. In Fig 1C, the CT signal in kidney, bladder and muscle measured at each time point were not significantly different (p > 0.05).</p