Determining topical product bioequivalence with stimulated Raman scattering microscopy

Generic drugs are essential for affordable medicine and improving accessibility to treatments. Bioequivalence (BE) is typically demonstrated by assessing a generic product's pharmacokinetics (PK) relative to a reference-listed drug (RLD). Accurately estimating cutaneous PK (cPK) at or near the site of action can be challenging for locally acting topical products. Certain cPK approaches are available for assessing local bioavailability (BA) in the skin. Stimulated Raman scattering (SRS) microscopy has unique capabilities enabling continuous, high spatial and temporal resolution and quantitative imaging of drugs within the skin. In this paper, we developed an approach based on SRS and a polymer-based standard reference for the evaluation of topical product BA and BE in human skin ex vivo. BE assessment of tazarotene-containing formulations was achieved using cPK parameters obtained within different skin microstructures. The establishment of BE between the RLD and an approved generic product was successfully demonstrated. Interestingly, within the constraints of the current study design the results suggest similar BA between the tested gel formulation and the reference cream formulation, despite the differences in the formulation/dosage form. Another formulation containing polyethylene glycol as the vehicle was demonstrated to be not bioequivalent to the RLD. Compared to using the SRS approach without a standard reference, the developed approach enabled more consistent and reproducible results, which is crucial in BE assessment. The abundant information from the developed approach can help to systematically identify key areas of study design that will enable a better comparison of topical products and support an assessment of BE.

Exploring the Clinical Utility of Raman Spectroscopy for Point-of-Care Cardiovascular Disease Biomarker Detection

A variety of innovative point-of-care (POC) solutions using Raman systems have been explored. However, the vast effort is in assay development, while studies of the characteristics required for Raman spectrometers to function in POC applications are lacking. In this study, we tested and compared the performance of eight commercial Raman spectrometers ranging in size from benchtop Raman microscopes to portable and handheld Raman spectrometers using paper fluidic cartridges, including their ability to detect cardiac troponin I and heart fatty acid binding protein, both of which are well-established biomarkers for evaluating cardiovascular health. Each spectrometer was evaluated in terms of excitation wavelength, laser characteristics, and ease of use to investigate POC utility. We found that the Raman spectrometers equipped with 780 and 785 nm laser sources exhibited a reduced background signal and provided higher sensitivity compared to those with 633 and 638 nm laser sources. Furthermore, the spectrometer equipped with the single acquisition line readout functionality showed improved performance when compared to the point scan spectrometers and allowed measurements to be made faster and easier. The portable and handheld spectrometers also showed similar detection sensitivity to the gold standard instrument. Lastly, we reduced the laser power for the spectrometer with single acquisition line readout capability to explore the system performance at a laser power that change the classification from a Class 3B laser device to a Class 3R device and found that it showed comparable performance. Overall, these findings show that portable Raman spectrometers have the potential to be used in POC settings with accuracy comparable to laboratory-grade instruments, are relatively low-cost, provide fast signal readout, are easy to use, and can facilitate access for underserved communities.

A Polarity-Sensitive Far-Red Fluorescent Probe for Glucose Sensing through Skin

The field of glucose biosensors for diabetes management has been of great interest over the past 60 years. Continuous glucose monitoring (CGM) is important to continuously track the glucose level to provide better management of the disease. Concanavalin A (ConA) can reversibly bind to glucose and mannose molecules and form a glucose biosensor via competitive binding. Here, we developed a glucose biosensor using ConA and a fluorescent probe, which generated a fluorescent intensity change based on solvatochromism, the reversible change in the emission spectrum dependent on the polarity of the solvent. The direction in which the wavelength shifts as the solvent polarity increases can be defined as positive (red-shift), negative (blue-shift), or a combination of the two, referred to as reverse. To translate this biosensor to a subcutaneously implanted format, Cyanine 5.5 (Cy5.5)-labeled small mannose molecules were used, which allows for the far-red excitation wavelength range to increase the skin penetration depth of the light source and returned emission. Three Cy5.5-labeled small mannose molecules were synthesized and compared when used as the competing ligand in the competitive binding biosensor. We explored the polarity-sensitive nature of the competing ligands and examined the biosensor's glucose response. Cy5.5-mannotetraose performed best as a biosensor, allowing for the detection of glucose from 25 to 400 mg/dL. Thus, this assay is responsive to glucose within the physiologic range when its concentration is increased to levels needed for an implantable design. The biosensor response is not statistically different when placed under different skin pigmentations when comparing the percent increase in fluorescence intensity. This shows the ability of the biosensor to produce a repeatable signal across the physiologic range for subcutaneous glucose monitoring under various skin tones.

Unsupervised Cross-Modality Adaptation via Dual Structural-Oriented Guidance for 3D Medical Image Segmentation

Deep convolutional neural networks (CNNs) have achieved impressive performance in medical image segmentation; however, their performance could degrade significantly when being deployed to unseen data with heterogeneous characteristics. Unsupervised domain adaptation (UDA) is a promising solution to tackle this problem. In this work, we present a novel UDA method, named dual adaptation-guiding network (DAG-Net), which incorporates two highly effective and complementary structural-oriented guidance in training to collaboratively adapt a segmentation model from a labelled source domain to an unlabeled target domain. Specifically, our DAG-Net consists of two core modules: 1) Fourier-based contrastive style augmentation (FCSA) which implicitly guides the segmentation network to focus on learning modality-insensitive and structural-relevant features, and 2) residual space alignment (RSA) which provides explicit guidance to enhance the geometric continuity of the prediction in the target modality based on a 3D prior of inter-slice correlation. We have extensively evaluated our method with cardiac substructure and abdominal multi-organ segmentation for bidirectional cross-modality adaptation between MRI and CT images. Experimental results on two different tasks demonstrate that our DAG-Net greatly outperforms the state-of-the-art UDA approaches for 3D medical image segmentation on unlabeled target images.

Electrocatalytic NAD+ reduction via hydrogen atom-coupled electron transfer

Nicotinamide adenine dinucleotide cofactor (NAD(P)H) is regarded as an important energy carrier and charge transfer mediator. Enzyme-catalyzed NADPH production in natural photosynthesis proceeds via a hydride transfer mechanism. Selective and effective regeneration of NAD(P)H from its oxidized form by artificial catalysts remains challenging due to the formation of byproducts. Herein, electrocatalytic NADH regeneration and the reaction mechanism on metal and carbon electrodes are studied. We find that the selectivity of bioactive 1,4-NADH is relatively high on Cu, Fe, and Co electrodes without forming commonly reported NAD2 byproducts. In contrast, more NAD2 side product is formed with the carbon electrode. ADP-ribose is confirmed to be a side product caused by the fragmentation reaction of NAD+. Based on H/D isotope effects and electron paramagnetic resonance analysis, it is proposed that the formation of NADH on these metal electrodes proceeds via a hydrogen atom-coupled electron transfer (HadCET) mechanism, in contrast to the direct electron-transfer and NAD˙ radical pathway on carbon electrodes, which leads to more by-product, NAD2. This work sheds light on the mechanism of electrocatalytic NADH regeneration, which is different from biocatalysis.

Portable, multi-modal Raman and fluorescence spectroscopic platform for point-of-care applications

SIGNIFICANCE

Point-of-care (POC) platforms utilizing optical biosensing strategies can achieve on-site detection of biomarkers to improve the quality of care for patients in low-resource settings.

AIM

We aimed to develop a portable, multi-modal spectroscopic platform capable of performing Raman and fluorescence measurements from a single sample site.

APPROACH

We designed the spectroscopic platform in OpticStudio using commercial optical components and built the system on a portable optical breadboard. Two excitation and collection arms were utilized to detect the two optical signals. The multi-modal functionality was validated using ratiometric Raman/fluorescence samples, and the potential utility was demonstrated using a model bioassay for cardiac troponin I.

RESULTS

The designed spectroscopic platform achieved a spectral resolution of 0.67 ± 0.2 nm across the Raman detection range (660 to 770 nm). The ratiometric Raman/fluorescence samples demonstrated no crosstalk between the two detector arms across a gradient of high molar concentrations. Testing of the model bioassay response showed that the integrated approach improved the linearity of the calibration curve from (R² = 0.977) for the Raman only and (R² = 0.972) for the fluorescence only to (R2 = 0.988) for the multi-modal approach.

CONCLUSION

These findings demonstrate the potential impact of a multi-modal POC spectroscopic platform to improve the sensitivity and robustness necessary for biomarker detection.

Deep Learning for Automatic Upper Airway Obstruction Detection by Analysis of Flow-Volume Curve

BACKGROUND

Due to the similar symptoms of upper airway obstruction to asthma, misdiagnosis is common. Spirometry is a cost-effective screening test for upper airway obstruction and its characteristic patterns involving fixed, variable intrathoracic and extrathoracic lesions. We aimed to develop a deep learning model to detect upper airway obstruction patterns and compared its performance with that of lung function clinicians.

METHODS

Spirometry records were reviewed to detect the possible condition of airway stenosis. Then they were confirmed by the gold standard (e.g., computed tomography, endoscopy, or clinic diagnosis of upper airway obstruction). Images and indices derived from flow-volume curves were used for training and testing the model. Clinicians determined cases using spirometry records from the test set. The deep learning model evaluated the same data.

RESULTS

Of 45,831 patients' spirometry records, 564 subjects with curves suggesting upper airway obstruction, after verified by the gold standard, 351 patients were confirmed. These cases and another 200 cases without airway stenosis were used as the training and testing sets. 432 clinicians evaluated 20 cases of each of the three patterns and 20 no airway stenosis cases (n = 80). They assigned an accuracy of 41.2% (±15.4) (interquartile range: 27.5-52.5%), with poor agreements (κ = 0.12). For the same cases, the model generated a correct detection of 81.3% (p < 0.0001).

CONCLUSIONS

Deep learning could detect upper airway obstruction patterns from other classic patterns of ventilatory defects with high accuracy, whereas clinicians presented marked errors and variabilities. The model may serve as a support tool to enhance clinicians' correct diagnosis of upper airway obstruction using spirometry.

Deep learning for spirometry quality assurance with spirometric indices and curves

Background

Spirometry quality assurance is a challenging task across levels of healthcare tiers, especially in primary care. Deep learning may serve as a support tool for enhancing spirometry quality. We aimed to develop a high accuracy and sensitive deep learning-based model aiming at assisting high-quality spirometry assurance.

Methods

Spirometry PDF files retrieved from one hospital between October 2017 and October 2020 were labeled according to ATS/ERS 2019 criteria and divided into training and internal test sets. Additional files from three hospitals were used for external testing. A deep learning-based model was constructed and assessed to determine acceptability, usability, and quality rating for FEV₁ and FVC. System warning messages and patient instructions were also generated for general practitioners (GPs).

Results

A total of 16,502 files were labeled. Of these, 4592 curves were assigned to the internal test set, the remaining constituted the training set. In the internal test set, the model generated 95.1%, 92.4%, and 94.3% accuracy for FEV₁ acceptability, usability, and rating. The accuracy for FVC acceptability, usability, and rating were 93.6%, 94.3%, and 92.2%. With the assistance of the model, the performance of GPs in terms of monthly percentages of good quality (A, B, or C grades) tests for FEV₁ and FVC was higher by ~ 21% and ~ 36%, respectively.

Conclusion

The proposed model assisted GPs in spirometry quality assurance, resulting in enhancing the performance of GPs in quality control of spirometry.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02014-9.

Erratum: Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence

[This corrects the article DOI: 10.1038/s42256-021-00421-z.].

The complete chloroplast genome of Indosasa hispida ‘Rainbow’ (Poaceae, Bambuseae): an ornamental bamboo species in horticulture

Indosasa hispida ‘Rainbow’ is a new horticultural plant variety for anthocyanin production, which has great ornamental value and huge market potential. The chloroplast genome is 139,690 bp in length, containing a large single-copy region (LSC) of 83,268 bp, a small single-copy region (SSC) of 12,830 bp, and a pair of 21,796 bp inverted repeats region (IR). The GC content of chloroplast genome is 38.9%. There are 130 genes in the cp genome, including 83 protein-coding genes, 8 ribosomal RNA genes, and 39 transfer RNA genes. In addition, phylogenetic analysis firmly supported that I. hispida 'Rainbow' constituted that a sister species with Pleioblastus maculatus.

Nonalloy Model-Based Ternary Organic Solar Cells

Ternary blending based on an alloy-like model has been proved as an efficient strategy for high-efficiency organic solar cells (OSCs). However, the third component that possesses excellent miscibility with host materials in the alloy-like model may trigger adverse effects for the active layer, especially at a high doping ratio. In this work, we propose a new concept of nonalloy model for the ternary OSCs in which the third component presents moderate miscibility with the acceptor and distributes at the interspace between donor and acceptor domains. The nonalloy model is constructed based on the PM6:Y6 system, and a Y6 analogue (BTP-MCA) is synthesized as the third component. The BTP-MCA can maintain initial excellent morphology of the active layer and enhance the morphological stability by acting as a frame around the host materials. As a result, ternary OSCs based on the PM6:Y6:BTP-MCA blend exhibit an impressive efficiency of 17.0% with a high open-circuit voltage of 0.87 V. Moreover, the devices present a high doping tolerance (keeping high efficiency with a doping ratio of 50%) and improved stability. This work indicates that the nonalloy model can be a promising method to fabricate efficient and stable ternary OSCs apart from the conventional alloy-like model.

Synthesis of SERS-active core-satellite nanoparticles using heterobifunctional PEG linkers

Surface-enhanced Raman scattering (SERS) is a sensitive analytical technique capable of magnifying the vibrational intensity of molecules adsorbed onto the surface of metallic nanostructures. Various solution-based SERS-active metallic nanostructures have been designed to generate substantial SERS signal enhancements. However, most of these SERS substrates rely on the chemical aggregation of metallic nanostructures to create strong signals. While this can induce high SERS intensities through plasmonic coupling, most chemically aggregated assemblies suffer from poor signal reproducibility and reduced long-term stability. To overcome these issues, here we report for the first time the synthesis of gold core-satellite nanoparticles (CSNPs) for robust SERS signal generation. The novel CSNP assemblies consist of a 30 nm spherical gold core linked to 18 nm satellite particles via linear heterobifunctional thiol-amine terminated PEG chains. We explore the effects that the varying chain lengths have on SERS hot-spot generation, signal reproducibility and long-term activity. The chain length was varied by using PEGs with different molecular weights (1000 Da, 2000 Da, and 3500 Da). The CSNPs were characterized via UV-Vis spectrophotometry, transmission electron microscopy (TEM), ζ-potential measurements, and lastly SERS measurements. The versatility of the synthesized SERS-active CSNPs was revealed through characterization of optical stability and SERS enhancement at 0, 1, 3, 5, 7 and 14 days.

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence

Artificial intelligence provides a promising solution for streamlining COVID-19 diagnoses; however, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalized model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the artificial intelligence (AI) model can be distributedly trained and independently executed at each host institution under a federated learning framework without data sharing. Here we show that our federated learning framework model considerably outperformed all of the local models (with a test sensitivity/specificity of 0.973/0.951 in China and 0.730/0.942 in the United Kingdom), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals without the federated learning framework) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans from 3,336 patients collected from 23 hospitals located in China and the United Kingdom. Collectively, our work advanced the prospects of utilizing federated learning for privacy-preserving AI in digital health.

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence

Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses. However, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalised model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the AI model can be distributedly trained and independently executed at each host institution under a federated learning framework (FL) without data sharing. Here we show that our FL model outperformed all the local models by a large yield (test sensitivity /specificity in China: 0.973/0.951, in the UK: 0.730/0.942), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals leaving out the FL) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans (CTs) from 3,336 patients collected from 23 hospitals located in China and the UK. Collectively, our work advanced the prospects of utilising federated learning for privacy-preserving AI in digital health.

Deep learning for predicting COVID-19 malignant progression

As COVID-19 is highly infectious, many patients can simultaneously flood into hospitals for diagnosis and treatment, which has greatly challenged public medical systems. Treatment priority is often determined by the symptom severity based on first assessment. However, clinical observation suggests that some patients with mild symptoms may quickly deteriorate. Hence, it is crucial to identify patient early deterioration to optimize treatment strategy. To this end, we develop an early-warning system with deep learning techniques to predict COVID-19 malignant progression. Our method leverages CT scans and the clinical data of outpatients and achieves an AUC of 0.920 in the single-center study. We also propose a domain adaptation approach to improve the generalization of our model and achieve an average AUC of 0.874 in the multicenter study. Moreover, our model automatically identifies crucial indicators that contribute to the malignant progression, including Troponin, Brain natriuretic peptide, White cell count, Aspartate aminotransferase, Creatinine, and Hypersensitive C-reactive protein.

Paper Microfluidic Device with a Horizontal Motion Valve and a Localized Delay for Automatic Control of a Multistep Assay

A microfluidic paper-based analytical device (μPAD) is a cost-effective platform to implement assays, especially for point-of-care testing. Developing μPADs with fluidic control is important to implement multistep assays and provide high sensitivities. However, current localized delays in μPADs made of sucrose have a limited ability to decrease the flow rate. In addition, existing μPADs for automatic multistep assays are limited by their need for auxiliary instruments, their false activation, or their unavoidable tradeoff between available fluid volumes and temporal differences between steps. Here, a novel μPAD composed of a localized dissolvable delay and a horizontal motion mechanical valve for use as an automatic multistep assay is reported. A mixture of fructose and sucrose was used in the localized dissolvable delay and it provided an effective decrease in the flow rate to ensure adequate sensitivity in an assay. The dissolvable delay effectively doubled the flow time. A mechanical valve using a horizontal movement was developed to automatically implement a multistep process. Two-step and four-step processes were enabled with the μPAD. Cardiac troponin I (cTnI), a gold-standard biomarker for myocardial infarction, was used as a model analyte to show the performance of the developed μPAD in an assay. The designed μPAD, with the simple-to-make localized dissolvable delay and the robust mechanical valve, provides the potential to automatically implement high-performance multistep assays toward a versatile platform for point-of-care diagnostics.

Isomeric anthracene diimide polymers

N-type semiconducting polymers are attractive for organic electronics, but desirable electron-deficient units for synthesizing such polymers are still lacking. As a cousin of rylene diimides such as naphthalene diimide (NDI) and perylene diimide (PDI), anthracene diimide (ADI) is a promising candidate; its polymers, however, have not been achieved yet because of synthetic challenges for its polymerizable monomers. Herein, we present ingenious synthesis of two dibromide ADI monomers with dibromination at differently symmetrical positions of the ADI core, which are further employed to construct ADI polymers. More interestingly, the two obtained ADI polymers possess the same main-chain and alkyl-chain structures but different backbone conformations owing to varied linking positions between repeating units. This feature enables their different optoelectronic properties and film-state packing behavior. The ADI polymers offer first examples of conjugated polymer conformational isomers and are highly promising as a new class of n-type semiconductors for various organic electronics applications.

A review of biosensor technologies for blood biomarkers toward monitoring cardiovascular diseases at the point-of-care

Cardiovascular diseases (CVDs) cause significant mortality globally. Notably, CVDs disproportionately negatively impact underserved populations, such as those that are economically disadvantaged and often located in remote regions. Devices to measure cardiac biomarkers have traditionally been focused on large instruments in a central laboratory but the development of affordable, portable devices that measure multiple cardiac biomarkers at the point-of-care (POC) are needed to improve clinical outcomes for patients, especially in underserved populations. Considering the enormity of the global CVD problem, complexity of CVDs, and the large candidate pool of biomarkers, it is of great interest to evaluate and compare biomarker performance and identify potential multiplexed panels that can be used in combination with affordable and robust biosensors at the POC toward improved patient care. This review focuses on describing the known and emerging CVD biosensing technologies for analysis of cardiac biomarkers from blood. Initially, the global burden of CVDs and the standard of care for the primary CVD categories, namely heart failure (HF) and acute coronary syndrome (ACS) including myocardial infarction (MI) are discussed. The latest United States, Canadian and European society guidelines recommended standalone, emerging, and add-on cardiac biomarkers, as well as their combinations are then described for the prognosis, diagnosis, and risk stratification of CVDs. Finally, both commercial in vitro biosensing devices and recent state-of-art techniques for detection of cardiac biomarkers are reviewed that leverage single and multiplexed panels of cardiac biomarkers with a view toward affordable, compact devices with excellent performance for POC diagnosis and monitoring.

Deep Learning for Detecting Cerebral Aneurysms with CT Angiography

Background Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive tool for more accurate interpretation. Purpose To develop a highly sensitive deep learning-based algorithm that assists in the detection of cerebral aneurysms on CT angiography images. Materials and Methods Head CT angiography images were retrospectively retrieved from two hospital databases acquired across four different scanners between January 2015 and June 2019. The data were divided into training and validation sets; 400 additional independent CT angiograms acquired between July and December 2019 were used for external validation. A deep learning-based algorithm was constructed and assessed. Both internal and external validation were performed. Jackknife alternative free-response receiver operating characteristic analysis was performed. Results A total of 1068 patients (mean age, 57 years ± 11 [standard deviation]; 660 women) were evaluated for a total of 1068 CT angiograms encompassing 1337 cerebral aneurysms. Of these, 534 CT angiograms (688 aneurysms) were assigned to the training set, and the remaining 534 CT angiograms (649 aneurysms) constituted the validation set. The sensitivity of the proposed algorithm for detecting cerebral aneurysms was 97.5% (633 of 649; 95% CI: 96.0, 98.6). Moreover, eight new aneurysms that had been overlooked in the initial reports were detected (1.2%, eight of 649). With the aid of the algorithm, the overall performance of radiologists in terms of area under the weighted alternative free-response receiver operating characteristic curve was higher by 0.01 (95% CI: 0.00, 0.03). Conclusion The proposed deep learning algorithm assisted radiologists in detecting cerebral aneurysms on CT angiography images, resulting in a higher detection rate. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kallmes and Erickson in this issue.

Aptamer-based surface-enhanced resonance Raman scattering assay on a paper fluidic platform for detection of cardiac troponin I

SIGNIFICANCE

Cardiac troponin I (cTnI) is a primary biomarker for diagnosis of myocardial infarction (MI). In contrast to central laboratory tests for cTnI, point-of-care (POC) testing has the advantage of providing results when the patient is first encountered, which helps high-risk patients to be treated more rapidly and low-risk patients to be released in a timely fashion. A paper fluidic platform is good for POC testing because the paper is abundant, low cost, and disposable. However, current cTnI assays on paper platforms use antibodies as the recognition element, which has limitations due to the high cost of production and antibody stability issues at the POC.

AIM

To develop an aptamer-based assay on a paper strip using surface-enhanced resonance Raman spectroscopy (SERRS) for detection of cTnI in the clinically relevant range at the POC.

APPROACH

Gold nanoparticles (AuNPs) were functionalized with a Raman reporter molecule, malachite green isothiocyanate. The functionalized AuNPs were encapsulated in a silica shell and provided a SERRS signal using a handheld Raman system with a 638-nm excitation wavelength. A primary aptamer and a secondary aptamer of cTnI were used in a sandwich assay format to bind the cTnI on a test line of a paper fluidic platform. By measuring the SERRS signal from the test line, the concentration of cTnI was quantitatively determined.

RESULTS

The aptamer-based SERRS assay on a paper strip had a detection range of 0.016 to 0.1  ng  /  ml for cTnI, had good selectivity for cTnI compared to three other markers, had good stability over 10 days, and had good performance in the more complex serum sample matrix.

CONCLUSIONS

The aptamer-based SERRS assay on a paper strip has the potential to provide a sensitive, selective, stable, repeatable, and cost-effective platform for the detection of cTnI toward eventual use in diagnosis of MI at the POC.

Benzene Derivatives Analysis Using Aluminum Nitride Waveguide Raman Sensors

Raman spectroscopy using aluminum nitride (AlN) optical waveguides was demonstrated for organic compound analysis. The AlN waveguide device was prepared by reactive sputtering deposition and complementary-metal-oxide semiconductor (CMOS) processes. A fundamental waveguide mode was observed over a broad visible spectrum and the waveguide evanescent wave was used to excite the Raman signals of the test analytes. The performance of the waveguide sensor was characterized by measuring the Raman spectra of the benzene derivative mixtures consisting of benzene, anisole, and toluene. The compositions and concentrations were resolved by correlating the obtained Raman spectrum with the characteristic Raman peaks associated with C-C, C-H, and C-O functional groups. With the advantages of real-time detection and enhanced Raman signal intensity, the AlN waveguides provided a sensor platform for nondestructive and online chemical compound monitoring.

A collaborative online AI engine for CT-based COVID-19 diagnosis

Artificial intelligence can potentially provide a substantial role in streamlining chest computed tomography (CT) diagnosis of COVID-19 patients. However, several critical hurdles have impeded the development of robust AI model, which include deficiency, isolation, and heterogeneity of CT data generated from diverse institutions. These bring about lack of generalization of AI model and therefore prevent it from applications in clinical practices. To overcome this, we proposed a federated learning-based Unified CT-COVID AI Diagnostic Initiative (UCADI, http://www.ai-ct-covid.team/), a decentralized architecture where the AI model is distributed to and executed at each host institution with the data sources or client ends for training and inferencing without sharing individual patient data. Specifically, we firstly developed an initial AI CT model based on data collected from three Tongji hospitals in Wuhan. After model evaluation, we found that the initial model can identify COVID from Tongji CT test data at near radiologist-level (97.5% sensitivity) but performed worse when it was tested on COVID cases from Wuhan Union Hospital (72% sensitivity), indicating a lack of model generalization. Next, we used the publicly available UCADI framework to build a federated model which integrated COVID CT cases from the Tongji hospitals and Wuhan Union hospital (WU) without transferring the WU data. The federated model not only performed similarly on Tongji test data but improved the detection sensitivity (98%) on WU test cases. The UCADI framework will allow participants worldwide to use and contribute to the model, to deliver a real-world, globally built and validated clinic CT-COVID AI tool. This effort directly supports the United Nations Sustainable Development Goals' number 3, Good Health and Well-Being, and allows sharing and transferring of knowledge to fight this devastating disease around the world.

A Canadian cancer trials group phase IB study of durvalumab (anti-PD-L1) plus tremelimumab (anti-CTLA-4) given concurrently or sequentially in patients with advanced, incurable solid malignancies

Background The IND.226 study was a phase Ib study to determine the recommended phase II dose of durvalumab + tremelimumab in combination with standard platinum-doublet chemotherapy. Sequential administration of multiple agents increases total chair time adding costs overall and inconvenience for patients. This cohort of the IND.226 study evaluated the safety and tolerability of durvalumab + tremelimumab given either sequentially (SEQ) or concurrently (CON). Methods Patients with advanced solid tumours were enrolled and randomised to either SEQ tremelimumab 75 mg IV over 1 h followed by durvalumab 1500 mg IV over 1 h q4wks on the same day, or CON administration over 1 h. The serum pharmacokinetic profile of SEQ versus CON of durvalumab and tremelimumab administration was also evaluated. Results 14 patients either received SEQ (n = 7pts) or CON (n = 7 pts). There were no infusion related reactions. Drug related adverse events (AEs) were mainly low grade and manageable, and comparable in frequency between SEQ/CON- fatigue (43%/57%), rash (43%/43%), pruritus (43%/29%) and nausea (14%/29%). One patient in each cohort discontinued treatment due to toxicity. The PK profiles of durvalumab and tremelimumab were similar between CON and SEQ, and to historical reference data. Conclusions Concurrent administration of durvalumab and tremelimumab over 1 h is safe with a comparable PK profile to sequential administration.

2D Conjugated Polyelectrolytes Possessing Identical Backbone with Active-Layer Polymer as Cathode Interlayer for Organic Solar Cells

A 2D conjugated polyelectrolyte (CPE), PBDTTh-TT-NBr, having the same backbone as the highly efficient donor polymer PTB7-Th and the quaternary ammonium pendant, is synthesized as a cathode interlayer (CIL) material for PTB7-Th-based fullerene and non-fullerene solar cells. The quaternary ammonium group is connected to the 2D conjugated backbone by a long, flexible alkyl chain, facilitating the modification of cathode via forming interface dipoles. Moreover, compared with another CPE analogue to PTB7, PBDT-TT-NBr, without the 2D conjugated backbone, the PBDTTh-TT-NBr presents a higher similarity in polymer structure to the donor polymer PTB7-Th. This feature makes it more compatible with the PTB7-Th-based active-layer film, improving the electron transport. With the PBDTTh-TT-NBr as the CIL, devices afford higher performances than those using the PBDT-TT-NBr in both fullerene and non-fullerene systems. This work offers guidance on choosing the CIL material that ought to possess a highly similar structure to the active-layer component.

Simple Is Best: A p-Phenylene Bridging Methoxydiphenylamine-Substituted Carbazole Hole Transporter for High-Performance Perovskite Solar Cells

Methoxydiphenylamine-substituted carbazole (MODPACz) is widely used to construct hole-transporting materials (HTMs) for perovskite solar cells (PSCs), whose performances rely highly on the linking way of the MODPACz units and the simplicity of the π-bridge. In this paper, we report a new HTM, pPh-2MODPACz, using one of the simplest π-bridges p-phenylene to link the MODPACz units. The structural feature endows pPh-2MODPACz with high hole mobility and conductivity, efficient hole extraction ability, and good film-forming property. MAPbI₃-based PSCs using doped and undoped pPh-2MODPACz as the HTM offer efficiencies of ∼20% and 16.07%, respectively; both are better than those of the devices with spiro-OMeTAD as the HTM. The device stability of pPh-2MODPACz-based PSCs is also greatly enhanced. This work demonstrates that the simplest p-phenylene bridge for linking MODPACz can derive a promising HTM with a high device performance, providing a distinctive pathway to develop new HTMs.

The economic impact of the transition from branded to generic oncology drugs

Background

Economic evaluations are an integral component of many clinical trials. Costs used in those analyses are based on the prices of branded drugs when they first enter the market. The effect of genericization on the cost-effectiveness (ce) or cost-utility (cu) of an intervention is unknown because economic analyses are rarely updated using the costs of generic drugs.

Methods

We re-examined the ce or cu of regimens previously evaluated in Canadian Cancer Trials Group (cctg) studies that included prospective economic evaluations and where genericization has occurred or is anticipated in Canada. We incorporated the new costs of generic drugs to characterize changes in ce or cu. We also determined acceptable cost levels of generic drugs that would make regimens reimbursable in a publicly funded health care system.

Results

The four randomized controlled trials included (representing 1979 patients) were cctg br.10 (early lung cancer, adjuvant vinorelbine-cisplatin vs. observation, n = 172), cctg br.21 (metastatic lung cancer, erlotinib vs. placebo, n = 731), cctg co.17 (metastatic colon cancer, cetuximab vs. best supportive care, n = 557), and cctg ly.12 (relapsed or refractory lymphoma, gemcitabine-dexamethasone-cisplatin vs. cytarabine-dexamethasone-cisplatin, n = 619). Since the initial publication of those trials, the genericization of vinorelbine, erlotinib, cetuximab, and cisplatin has taken place or is expected in Canada. Costs of generics improved the ces and cus of treatment significantly. For example, genericization of erlotinib ($1460.25 per 30 days) resulted in an incremental cost-effectiveness ratio (icer) of $45,746 per life-year gained compared with $94,638 for branded erlotinib. Likewise, genericization of cetuximab ($275.80 per 100 mg) produced an icer of $261,126 per quality-adjusted life-year (qaly) gained compared with $299,613 for branded cetuximab. Decreases in the cost of generic cetuximab to $129.39 and $63.51 would further improve the icer to $150,000 and $100,000 per QALY respectively.

Conclusions

Genericization of a costly oncology drug can modify the ce and cu of a regimen significantly. Failure to revisit economic analyses with the costs of generics could be a missed opportunity for funding bodies to optimize value-based allocation of health care resources. At current levels, the costs of generics might not be sufficiently low to sustain publicly funded health care systems.

A polymeric ionic liquid as a cathode interlayer of organic photovoltaics with improved reproducibility

A polymeric ionic liquid (PIL) was synthesized from a small-molecule one (MIL, the monomer), and they were used as cathode interlayers in organic solar cells. Compared with the MIL, the PIL can form a more uniform film for full coverage of an active layer and efficient cathode modification, resulting in higher device efficiency and reproducibility.

Abstract P4-14-03: Influence of competing risks of death on the interpretation of adjuvant endocrine therapy trials for breast cancer

Background: Early stage, hormone sensitive breast cancer is associated generally with a good prognosis, with only a minority of patients expected to die of breast cancer. Death from causes other than breast cancer can dilute the patients at risk of breast cancer events and result in over-estimation of risk of recurrence and consequently the benefit from breast cancer therapy, a so-called immortal time bias. The MA.17R trial (Goss et al 2016) evaluated the role of extending adjuvant treatment with letrozole from 5 to 10 years. Here we determine the effect of analyzing the MA.17R trial using methods accounting for competing risks.

Methods: We compared conventional and competing risk methods for disease-free survival (DFS) and for distant recurrence-free survival (DRFS). In Kaplan-Meier analyses death from any cause was considered an event while cumulative incidence functions (CIFs) assumed death without recurrence to be a competing risk. The complement of the survival function (one minus the survival function) was used to estimate incidence of the primary event of interest. This was compared to estimates obtained using CIFs accounting for the occurrence of competing events.

Results: Non-breast cancer death was the most common event defining DFS and DRFS. Over the course of follow-up, there was increasing discrepancy between the risk of disease recurrence measured using Kaplan-Meier and CIF. Among letrozole treated patients the estimated distant recurrence at 5 years of follow-up was 5.4% using CIF and 9.6% using Kaplan-Meier. At 10 years of follow-up, the estimated distant recurrence was 8.4% using CIF and 20.0% using Kaplan-Meier. Similar results were observed for the placebo group (8.5% vs 12.1% at 5 years and 14.8% vs 27.3% at 10 years), and in patients with baseline cardiovascular disease (see Table). Benefit from letrozole on DFS and DRFS was greater when accounting for competing risk (hazard ratio [HR] for DFS 0.66, 95%CI 0.48-0.90; DFRS HR 0.75, 0.50-1.14) compared to the conventional method (DFS HR 0.79, 0.62-0.99; DRFS HR 0.91, 0.70-1.18). In women with baseline cardiovascular risk, the benefits of extended adjuvant letrozole when considering competing risk (DFS HR 0.38, 0.16-0.89; DRFS HR 0.46, 0.16-1.35) were also greater than those observed in the conventional analysis (DFS HR 0.55, 0.32-0.93; DRFS HR 0.59, 0.33-1.04). Treatment with extended letrozole did not influence non-breast cancer death in women who died with disease recurrence (HR 1.06, 0.74 -1.50) or in those with competing risk or censored from the analysis (HR 1.05, 0.73 -1.49).

Conclusion: Over the course of follow-up, estimates of DFS and DRFS differ increasingly if measured using Kaplan-Meier or CIF, with CIF estimates of risk being substantially lower. Using a competing risk model, the reduction in distant recurrence at 8 years with extended letrozole is less than 1%. Additional competing risk analyses of the MA.17 (Goss 2006) and MA.27 (Goss 2013) trials are ongoing.

Cumulative incidence of disease recurrence in patients with baseline cardiovascular riskTime (years)CIF (%)1-KM (%)Letrozole11.51.534.46.555.813.8Placebo13.53.538.311.8512.520.3

Citation Format: Ethier J-L, Parulekar W, Shepherd L, Summers L, Strasser-Weippl K, Tu D, Amir E. Influence of competing risks of death on the interpretation of adjuvant endocrine therapy trials for breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-14-03.

A SERS aptasensor for sensitive and selective detection of bis(2-ethylhexyl) phthalate

Bis(2-ethylhexyl)phthalate (DEHP) is an endocrine disruptor commonly present in plastic products, such as PVC tubes and water bottles. In this work, a surface enhanced Raman spectroscopy (SERS) based aptasensor was developed and utilized for rapid, easy, sensitive, and specific detection of trace DEHP. A DEHP aptamer was immobilized on magnetic particles. Raman reporter molecule conjugated silver nanoparticles were clustered and coated with silica to provide a stable SERS signal. The SERS silica particle was then functionalized with 1,2,4-benzenetricarboxylic acid 1,2-bis(2-ethylhexyl) ester to increase its affinity to the DEHP aptamer. In the presence of a sample with DEHP, the high-affinity SERS silica particle competes with the DEHP molecule to bind with the aptamer on the magnetic particle. By measuring the signal of free SERS silica particles in the supernatant after magnetic separation, the concentration of DEHP in the sample was quantitatively determined. The developed DEHP aptasensor had a detection range from 0.008 to 182 nM and a limit of detection (LOD) of 8 pM. The aptasensor also showed high selectivity when exposed to interferents with analogous structures. The aptasensor was successfully tested for the detection of DEHP spiked in tap water, bottled water, and a carbonate beverage. The developed SERS-based aptasensor provides a rapid, sensitive, and easy-to-use method for the quantitative detection of DEHP in environmental and food analysis.

This paper reports a SERS aptasensor developed to detect DEHP at relevant ranges with ultrasensitive performance and good selectivity.

Mobilization of iron from ferritin: new steps and details

Much evidence indicates that iron stored in ferritin is mobilized through protein degradation in lysosomes, but concerns about this process have lingered, and the mechanistic details of its aspects are lacking. In the studies presented here, ⁵⁹Fe-labeled ferritin was induced by preloading hepatic (HepG2) cells with radiolabeled Fe. Placing these cells in a medium containing desferrioxamine resulted in the loss of ferritin-⁵⁹Fe, but adding high concentrations of reducing agents or modulating the internal GSH concentration failed to alter the rates of ferritin-⁵⁹Fe release. Confocal microscopy showed that Fe deprivation increased the movement of ferritin into lysosomes and hyperaccumulation was observed when lysosomal proteolysis was inhibited. It also resulted in the rapid movement of DMT1 to lysosomes, which was inhibited by bafilomycin. Ferrihydrite crystals isolated from purified rat liver/spleen ferritin were solubilized at pH 5 and 7 by GSH, ascorbate, citrate and lysosomal fluids obtained from livers and J774a.1 macrophages. The inhibition of DMT1/Nramp2 and siRNA knockdown of Nramp1 each reduced the transfer of ⁵⁹Fe from lysosomes to the cytosol; and hepatocyte-specific knockout of DMT1 in mice prevented the release of Fe from the liver responding to EPO treatment, but did not inhibit lysosomal ferritin degradation. We conclude that ferritin-Fe mobilization does not occur through changes in cellular concentrations of reducing/chelating agents but by the coordinated movement of ferritin and DMT1 to lysosomes, where the ferrihydrite crystals exposed by ferritin degradation dissolve in the lysosomal fluid, and the reduced iron is transported back to the cytosol via DMT1 in hepatocytes, and by both DMT1 and Nramp1 in macrophages, prior to release into the blood or storage in ferritin.

Hypertension as a predictor of advanced colorectal cancer outcome and cetuximab treatment response

Background

Adrenergic receptor stimulation is involved in the development of hypertension (htn) and has been implicated in cancer progression and dissemination of metastases in various tumours, including colon cancer. Adrenergic antagonists such as beta-blockers (bbs) demonstrate inhibition of invasion and migration in colon cancer cell lines and have been associated with decreased mortality in colorectal cancer (crc). We examined the association of baseline htn and bb use with overall (os) and progression-free survival (pfs) in patients with pretreated, chemotherapy refractory, metastatic crc (mcrc). We also examined baseline htn as a predictor of cetuximab efficacy.

Methods

Using data from the Canadian Cancer Trials Group co.17 study [cetuximab vs. best supportive care (bsc)], we coded baseline htn and use of anti-htn medications, including bbs, for 572 patients. The chi-square test was used to assess the associations between those variables and baseline characteristics. Cox regression models were used for univariate and multivariate analyses of os and pfs by htn diagnosis and bb use.

Results

Baseline htn, bb use, and anti-htn medication use were not found to be prognostic for improved os. Baseline htn and bb use were not significant predictors of cetuximab benefit.

Conclusions

In chemorefractory mcrc, neither baseline htn nor bb use is a significant prognostic factor. Baseline htn and bb use are not predictive of cetuximab benefit. Further investigation to determine whether baseline htn or bb use have a similarly insignificant impact on prognosis in patients receiving earlier lines of treatment remains warranted.

Lowering Molecular Symmetry To Improve the Morphological Properties of the Hole-Transport Layer for Stable Perovskite Solar Cells

Inspired by the structural feature of the classical hole-transport material (HTM), Spiro-OMeTAD, many analogues based on a highly symmetrical spiro-core were reported for perovskite solar cells (PSCs). However, these HTMs were prone to crystallize because of the high molecular symmetry, forming non-uniform films, unfavorable for the device stability and large-area processing. By lowering the symmetry of spiro-core, we report herein a novel spirobisindane-based HTM, Spiro-I, which could form amorphous films with high uniformity and morphological stability. Compared to the Spiro-OMeTAD-based PSCs, those containing Spiro-I exhibit similar efficiencies for small area but higher ones for large area (1 cm² ), and especially much higher air stability (retaining 80 % of initial PCE after 2400 h storage without encapsulation). Moreover, the Spiro-I can be synthesized from a cheap starting material bisphenol A and used with a small amount for the device fabrication.

OV21/PETROC: a randomized Gynecologic Cancer Intergroup phase II study of intraperitoneal versus intravenous chemotherapy following neoadjuvant chemotherapy and optimal debulking surgery in epithelial ovarian cancer

Background

The purpose of this multistage, adaptively, designed randomized phase II study was to evaluate the role of intraperitoneal (i.p.) chemotherapy following neoadjuvant chemotherapy (NACT) and optimal debulking surgery in women with epithelial ovarian cancer (EOC).

Patients and methods

We carried out a multicenter, two-stage, phase II trial. Eligible patients with stage IIB-IVA EOC treated with platinum-based intravenous (i.v.) NACT followed by optimal (<1 cm) debulking surgery were randomized to one of the three treatment arms: (i) i.v. carboplatin/paclitaxel, (ii) i.p. cisplatin plus i.v./i.p. paclitaxel, or (iii) i.p. carboplatin plus i.v./i.p. paclitaxel. The primary end point was 9-month progressive disease rate (PD9). Secondary end points included progression-free survival (PFS), overall survival (OS), toxicity, and quality of life (QOL).

Results

Between 2009 and 2015, 275 patients were randomized; i.p. cisplatin containing arm did not progress beyond the first stage of the study after failing to meet the pre-set superiority rule. The final analysis compared i.v. carboplatin/paclitaxel (n = 101) with i.p. carboplatin, i.v./i.p. paclitaxel (n = 102). The intention to treat PD9 was lower in the i.p. carboplatin arm compared with the i.v. carboplatin arm: 24.5% (95% CI 16.2% to 32.9%) versus 38.6% (95% CI 29.1% to 48.1%) P = 0.065. The study was underpowered to detect differences in PFS: HR PFS 0.82 (95% CI 0.57-1.17); P = 0.27 and OS HR 0.80 (95% CI 0.47-1.35) P = 0.40. The i.p. carboplatin-based regimen was well tolerated with no reduction in QOL or increase in toxicity compared with i.v. administration alone.

Conclusion

In women with stage IIIC or IVA EOC treated with NACT and optimal debulking surgery, i.p. carboplatin-based chemotherapy is well tolerated and associated with an improved PD9 compared with i.v. carboplatin-based chemotherapy.

Clinical trial number

clinicaltrials.gov, NCT01622543.

OV21/PETROC: a randomized Gynecologic Cancer Intergroup phase II study of intraperitoneal versus intravenous chemotherapy following neoadjuvant chemotherapy and optimal debulking surgery in epithelial ovarian cancer

Background

The purpose of this multistage, adaptively, designed randomized phase II study was to evaluate the role of intraperitoneal (i.p.) chemotherapy following neoadjuvant chemotherapy (NACT) and optimal debulking surgery in women with epithelial ovarian cancer (EOC).

Patients and methods

We carried out a multicenter, two-stage, phase II trial. Eligible patients with stage IIB-IVA EOC treated with platinum-based intravenous (i.v.) NACT followed by optimal (<1 cm) debulking surgery were randomized to one of the three treatment arms: (i) i.v. carboplatin/paclitaxel, (ii) i.p. cisplatin plus i.v./i.p. paclitaxel, or (iii) i.p. carboplatin plus i.v./i.p. paclitaxel. The primary end point was 9-month progressive disease rate (PD9). Secondary end points included progression-free survival (PFS), overall survival (OS), toxicity, and quality of life (QOL).

Results

Between 2009 and 2015, 275 patients were randomized; i.p. cisplatin containing arm did not progress beyond the first stage of the study after failing to meet the pre-set superiority rule. The final analysis compared i.v. carboplatin/paclitaxel (n = 101) with i.p. carboplatin, i.v./i.p. paclitaxel (n = 102). The intention to treat PD9 was lower in the i.p. carboplatin arm compared with the i.v. carboplatin arm: 24.5% (95% CI 16.2% to 32.9%) versus 38.6% (95% CI 29.1% to 48.1%) P = 0.065. The study was underpowered to detect differences in PFS: HR PFS 0.82 (95% CI 0.57-1.17); P = 0.27 and OS HR 0.80 (95% CI 0.47-1.35) P = 0.40. The i.p. carboplatin-based regimen was well tolerated with no reduction in QOL or increase in toxicity compared with i.v. administration alone.

Conclusion

In women with stage IIIC or IVA EOC treated with NACT and optimal debulking surgery, i.p. carboplatin-based chemotherapy is well tolerated and associated with an improved PD9 compared with i.v. carboplatin-based chemotherapy.

Clinical trial number

clinicaltrials.gov, NCT01622543.

A randomized phase II study of weekly paclitaxel with or without pelareorep in patients with metastatic breast cancer: final analysis of Canadian Cancer Trials Group IND.213

BACKGROUND

Pelareorep, a serotype 3 reovirus, has demonstrated preclinical and early clinical activity in breast cancer and synergistic cytotoxic activity with microtubule targeting agents. This multicentre, randomized, phase II trial was undertaken to evaluate the efficacy and safety of adding pelareorep to paclitaxel for patients with metastatic breast cancer (mBC).

METHODS

Following a safety run-in of 7 patients, 74 women with previously treated mBC were randomized either to paclitaxel 80 mg/m² intravenously on days 1, 8, and 15 every 4 weeks plus pelareorep 3 × 10¹⁰ TCID₅₀ intravenously on days 1, 2, 8, 9, 15, and 16 every 4 weeks (Arm A) or to paclitaxel alone (Arm B). Primary endpoint was progression-free survival (PFS). Secondary endpoints were objective response rate, overall survival (OS), circulating tumour cell counts, safety, and exploratory correlative analyses. All comparisons used a two-sided test at an alpha level of 20%. Survival analyses were adjusted for prior paclitaxel.

RESULTS

Final analysis was performed after a median follow-up of 29.5 months. Pelareorep was well tolerated. Patients in Arm A had more favourable baseline prognostic variables. Median adjusted PFS (Arm A vs B) was 3.78 mo vs 3.38 mo (HR 1.04, 80% CI 0.76-1.43, P = 0.87). There was no difference in response rate between arms (P = 0.87). Median OS (Arm A vs B) was 17.4 mo vs 10.4 mo (HR 0.65, 80% CI 0.46-0.91, P = 0.1).

CONCLUSIONS

This first, phase II, randomized study of pelareorep and paclitaxel in previously treated mBC did not show a difference in PFS (the primary endpoint) or RR. However, there was a significantly longer OS for the combination. Further exploration of this regimen in mBC may be of interest.

Reappearance of buffalo-origin-like porcine circovirus type 2 strains in swine herds in southern China

Previously, we identified three porcine circovirus type 2 (PCV2) strains in buffalo meat samples from southern China. In this study, we confirmed the reappearance of those buffalo-origin-like PCV2 strains in swine herds in this region, which supported the possible cross-species infection of PCV2 between buffalos and pigs under field conditions.

Germline polymorphisms as biomarkers of tumor response in colorectal cancer patients treated with anti-EGFR monoclonal antibodies: a systematic review and meta-analysis

Studies of germline polymorphisms as predictors of tumor response to anti-epidermal growth factor receptor (EGFR) monoclonal antibody agents in metastatic colorectal cancer have reported inconsistent results. We performed a systematic review of studies from 1990 to September 2015, followed by random-effects meta-analyses for polymorphisms examined in at least three studies. Of 87 studies, 40 passed the criteria for systematic review and 23 for meta-analysis. The polymorphisms suitable for meta-analysis were CCND1 (rs17852153), COX2 (rs20417), EGF (rs4444903), EGFR (rs712829, rs11543848, 3'UTR CA repeat), FCGR2A (rs1801274), FCGR3A (rs396991), IL8 (rs4073), KRAS (rs61764370) and VEGFA (rs3025039). Meta-analysis yielded nominal significance (at α=0.05) for rs4444903 and rs11543848, but showed no significant results after multiple testing correction; this was unchanged by sensitivity analyses to address subgroups, funnel-plot asymmetries, and study quality. This highlights a tendency for lack of replication in the face of initial positive results, and possibly the unsuitability of relying on tumor response as a surrogate marker in this setting.

Imaging characteristics associated with failure of nonoperative management in high-grade pediatric blunt renal trauma

INTRODUCTION

Some children who sustain high-grade blunt renal injury may require operative intervention. In the present study, it was hypothesized that there are computed tomography (CT) characteristics that can identify which of these children are most likely to need operative intervention.

MATERIALS AND METHODS

A retrospective review was performed of all pediatric blunt renal trauma patients at a single level-I trauma center from 1990 to 2015. Inclusion criteria were: children with American Association for the Surgery of Trauma (AAST) Grade-IV or V renal injuries, aged ≤18 years, and having available CT images with delayed cuts. The CTs were regraded according to the revised AAST grading system proposed by Buckley and McAninch in 2011. Radiographic characteristics of renal injury were correlated with the primary outcome of any operative intervention: ureteral stent, angiography, nephrectomy/renorrhaphy, and percutaneous nephrostomy/drain.

RESULTS

One patient had a Grade-V injury and 26 patients had Grade-IV injuries. Nine patients (33.3%) underwent operative interventions. Patients in the operative intervention cohort were more likely to manifest a collecting system filling defect (P = 0.040) (Fig. A) and lacked ureteral opacification (P = 0.010). The CT characteristics, including percentage of devascularized parenchyma, medial contrast extravasation, intravascular contrast extravasation, perirenal hematoma distance and laceration location, were not statistically significant. Of the 21 patients who had a collecting system injury, eight (38.1%) needed ureteral stents. Renorrhaphy was necessary for one patient. Although the first operative intervention occurred at a median of hospital day 1 (range 0.5-2.5), additional operative interventions occurred from day 4-16. Thus, it is prudent to closely follow-up these patients for the first month after injury. Two patients with complex renal injuries had an accessory renal artery resulting in well-perfused upper and lower pole fragments, and were managed nonoperatively without readmission (Fig. B).

CONCLUSIONS

Collecting system defects and lack of ureteral opacification were significantly associated with failure of nonoperative management. A multicenter trial is needed to confirm these findings and whether nonsignificant CT findings are associated with operative intervention. In the month after renal injury, these patients should be mindful of any changes in symptoms, and maintain a low index of suspicion for an emergency room visit. For the physician, close follow-up and appropriate counseling of these high-risk patients is advised.