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SignificanceOral cancer is among the most common cancers globally, especially in low- and middle-income countries. Early detection is the most effective way to reduce the mortality rate. Deep learning-based cancer image classification models usually need to be hosted on a computing server. However, internet connection is unreliable for screening in low-resource settings.AimTo develop a mobile-based dual-mode image classification method and customized Android application for point-of-care oral cancer detection.ApproachThe dataset used in our study was captured among 5025 patients with our customized dual-modality mobile oral screening devices. We trained an efficient network MobileNet with focal loss and converted the model into TensorFlow Lite format. The finalized lite format model is ∼16.3 MB and ideal for smartphone platform operation. We have developed an Android smartphone application in an easy-to-use format that implements the mobile-based dual-modality image classification approach to distinguish oral potentially malignant and malignant images from normal/benign images.ResultsWe investigated the accuracy and running speed on a cost-effective smartphone computing platform. It takes ∼300 ms to process one image pair with the Moto G5 Android smartphone. We tested the proposed method on a standalone dataset and achieved 81% accuracy for distinguishing normal/benign lesions from clinically suspicious lesions, using a gold standard of clinical impression based on the review of images by oral specialists.ConclusionsOur study demonstrates the effectiveness of a mobile-based approach for oral cancer screening in low-resource settings.

Quality of language comprehension determines performance in all kinds of activities including academics. Processing of words initially develops as auditory, and gradually extends to visual as children learn to read. School failure is highly related to listening and reading comprehension problems. In this study we analyzed sex-differences in comprehension of texts in Spanish (standardized reading test PROLEC-R) in three modalities (visual, auditory, and both simultaneously: dual-modality) presented to 12–14-years old students, native in Spanish. We controlled relevant cognitive variables such as attention (d2), phonological and semantic fluency (FAS) and speed of processing (WISC subtest Coding). Girls’ comprehension was similar in the three modalities of presentation, however boys were importantly benefited by dual-modality as compared to boys exposed only to visual or auditory text presentation. With respect to the relation of text comprehension and school performance, students with low grades in Spanish showed low auditory comprehension. Interestingly, visual and dual modalities preserved comprehension levels in these low skilled students. Our results suggest that the use of visual-text support during auditory language presentation could be beneficial for low school performance students, especially boys, and encourage future research to evaluate the implementation in classes of the rapidly developing technology of simultaneous speech transcription, that could be, in addition, beneficial to non-native students, especially those recently incorporated into school or newly arrived in a country from abroad.

SignificanceOral cancer is among the most common cancers globally, especially in low- and middle-income countries. Early detection is the most effective way to reduce the mortality rate. Deep learning-based cancer image classification models usually need to be hosted on a computing server. However, internet connection is unreliable for screening in low-resource settings.AimTo develop a mobile-based dual-mode image classification method and customized Android application for point-of-care oral cancer detection.ApproachThe dataset used in our study was captured among 5025 patients with our customized dual-modality mobile oral screening devices. We trained an efficient network MobileNet with focal loss and converted the model into TensorFlow Lite format. The finalized lite format model is ∼16.3 MB and ideal for smartphone platform operation. We have developed an Android smartphone application in an easy-to-use format that implements the mobile-based dual-modality image classification approach to distinguish oral potentially malignant and malignant images from normal/benign images.ResultsWe investigated the accuracy and running speed on a cost-effective smartphone computing platform. It takes ∼300 ms to process one image pair with the Moto G5 Android smartphone. We tested the proposed method on a standalone dataset and achieved 81% accuracy for distinguishing normal/benign lesions from clinically suspicious lesions, using a gold standard of clinical impression based on the review of images by oral specialists.ConclusionsOur study demonstrates the effectiveness of a mobile-based approach for oral cancer screening in low-resource settings.

Quality of language comprehension determines performance in all kinds of activities including academics. Processing of words initially develops as auditory, and gradually extends to visual as children learn to read. School failure is highly related to listening and reading comprehension problems. In this study we analyzed sex-differences in comprehension of texts in Spanish (standardized reading test PROLEC-R) in three modalities (visual, auditory, and both simultaneously: dual-modality) presented to 12–14-years old students, native in Spanish. We controlled relevant cognitive variables such as attention (d2), phonological and semantic fluency (FAS) and speed of processing (WISC subtest Coding). Girls’ comprehension was similar in the three modalities of presentation, however boys were importantly benefited by dual-modality as compared to boys exposed only to visual or auditory text presentation. With respect to the relation of text comprehension and school performance, students with low grades in Spanish showed low auditory comprehension. Interestingly, visual and dual modalities preserved comprehension levels in these low skilled students. Our results suggest that the use of visual-text support during auditory language presentation could be beneficial for low school performance students, especially boys, and encourage future research to evaluate the implementation in classes of the rapidly developing technology of simultaneous speech transcription, that could be, in addition, beneficial to non-native students, especially those recently incorporated into school or newly arrived in a country from abroad.

Fluorescence techniques have been extensively employed to develop non-invasive methodologies for tracking and understanding complex biological processes both in vitro and in vivo, which is of high importance in modern life science research. Among a variety of fluorescent probes, inorganic semiconductor quantum dots (QDs) have shown advantages in terms of better photostability, larger Stokes shift and more feasible surface functionalization. However, their intrinsic toxic heavy metal components and unstable fluorescence at low pH greatly impede the applications of QDs in in vivo studies. In this work, we developed novel fluorescent probes that can outperform currently available QD based probes in practice. Using conjugated oligomer with aggregation-induced emission characteristics as the fluorescent domain and biocompatible lipid-PEG derivatives as the encapsulation matrix, the obtained organic dots have shown higher brightness, better stability in biological medium and comparable size and photostability as compared to their counterparts of inorganic QDs. More importantly, unlike QD-based probes, the organic fluorescent dots do not blink, and also do not contain heavy metal ions that could be potentially toxic when applied for living biosubstrates. Upon surface functionalization with a cell-penetrating peptide, the organic dots greatly outperform inorganic quantum dots in both in vitro and in vivo long-term cell tracing studies, which will be beneficial to answer crucial questions in stem cell/immune cell therapies. Considering the customized fluorescent properties and surface functionalities of the organic dots, a series of biocompatible organic dots will be developed to serve as a promising platform for multifarious bioimaging tasks in future. © 2014 SPIE.

Fluorescence techniques have been extensively employed to develop non-invasive methodologies for tracking and understanding complex biological processes both in vitro and in vivo, which is of high importance in modern life science research. Among a variety of fluorescent probes, inorganic semiconductor quantum dots (QDs) have shown advantages in terms of better photostability, larger Stokes shift and more feasible surface functionalization. However, their intrinsic toxic heavy metal components and unstable fluorescence at low pH greatly impede the applications of QDs in in vivo studies. In this work, we developed novel fluorescent probes that can outperform currently available QD based probes in practice. Using conjugated oligomer with aggregation-induced emission characteristics as the fluorescent domain and biocompatible lipid-PEG derivatives as the encapsulation matrix, the obtained organic dots have shown higher brightness, better stability in biological medium and comparable size and photostability as compared to their counterparts of inorganic QDs. More importantly, unlike QD-based probes, the organic fluorescent dots do not blink, and also do not contain heavy metal ions that could be potentially toxic when applied for living biosubstrates. Upon surface functionalization with a cell-penetrating peptide, the organic dots greatly outperform inorganic quantum dots in both in vitro and in vivo long-term cell tracing studies, which will be beneficial to answer crucial questions in stem cell/immune cell therapies. Considering the customized fluorescent properties and surface functionalities of the organic dots, a series of biocompatible organic dots will be developed to serve as a promising platform for multifarious bioimaging tasks in future. © 2014 SPIE.

Understanding the localization and engraftment of tumor cells at postintravasation stage of metastasis is of high importance in cancer diagnosis and treatment. Advanced fluorescent probes and facile methodologies for cell tracing play a key role in metastasis studies. In this work, we design and synthesize a dual-modality imaging dots with both optical and magnetic contrast through integration of a magnetic resonance imaging reagent, gadolinium(III), into a novel long-term cell tracing probe with aggregation-induced emission (AIE) in far-red/near-infrared region. The obtained fluorescent-magnetic AIE dots have both high fluorescence quantum yield (25%) and T-1 relaxivity (7.91 mM(-1) s(-1)) in aqueous suspension. After further conjugation with a cell membrane penetrating peptide, the dual-modality dots can be efficiently internalized into living cells. The gadolinium(III) allows accurate quantification of biodistribution of cancer cells via intraveneous injection, while the high fluorescence provides engraftment information of cells at single cellular level. The dual-modality AIE dots show obvious synergistic advantages over either single imaging modality and hold great promises in advanced biomedical studies.

Understanding the localization and engraftment of tumor cells at postintravasation stage of metastasis is of high importance in cancer diagnosis and treatment. Advanced fluorescent probes and facile methodologies for cell tracing play a key role in metastasis studies. In this work, we design and synthesize a dual-modality imaging dots with both optical and magnetic contrast through integration of a magnetic resonance imaging reagent, gadolinium(III), into a novel long-term cell tracing probe with aggregation-induced emission (AIE) in far-red/near-infrared region. The obtained fluorescent-magnetic AIE dots have both high fluorescence quantum yield (25%) and T-1 relaxivity (7.91 mM(-1) s(-1)) in aqueous suspension. After further conjugation with a cell membrane penetrating peptide, the dual-modality dots can be efficiently internalized into living cells. The gadolinium(III) allows accurate quantification of biodistribution of cancer cells via intraveneous injection, while the high fluorescence provides engraftment information of cells at single cellular level. The dual-modality AIE dots show obvious synergistic advantages over either single imaging modality and hold great promises in advanced biomedical studies.

Understanding the localization and engraftment of tumor cells at postintravasation stage of metastasis is of high importance in cancer diagnosis and treatment. Advanced fluorescent probes and facile methodologies for cell tracing play a key role in metastasis studies. In this work, we design and synthesize a dual-modality imaging dots with both optical and magnetic contrast through integration of a magnetic resonance imaging reagent, gadolinium(III), into a novel long-term cell tracing probe with aggregation-induced emission (AIE) in far-red/near-infrared region. The obtained fluorescent-magnetic AIE dots have both high fluorescence quantum yield (25%) and T-1 relaxivity (7.91 mM(-1) s(-1)) in aqueous suspension. After further conjugation with a cell membrane penetrating peptide, the dual-modality dots can be efficiently internalized into living cells. The gadolinium(III) allows accurate quantification of biodistribution of cancer cells via intraveneous injection, while the high fluorescence provides engraftment information of cells at single cellular level. The dual-modality AIE dots show obvious synergistic advantages over either single imaging modality and hold great promises in advanced biomedical studies.

The current clinical standard for breast cancer screening is mammography. However, this technique has a low sensitivity which results in missed cancers. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has recently emerged as a promising technique for breast cancer diagnosis and has been reported as being superior to mammography for screening of high-risk women and evaluation of extent of disease. At the same time, low and variable specificity has been documented in the literature as well as a rising number of mastectomies possibly due to the increasing use of DCE-MRI. In this study, we developed and characterized a dual-modality, x-ray and DCE-MRI, anthropomorphic breast phantom for the quantitative assessment of breast imaging protocols. X-ray properties of the phantom were quantitatively compared with patient data, including attenuation coefficients, which matched human values to within the measurement error, and tissue structure using spatial covariance matrices of image data, which were found to be similar in size to patient data. Simulations of the phantom scatter-to-primary ratio (SPR) were produced and experimentally validated then compared with published SPR predictions for homogeneous phantoms. SPR values were as high as 85% in some areas and were heavily influenced by the heterogeneous tissue structure. MRI properties of the phantom, T1 and T2 relaxation values and tissue structure, were also quantitatively compared with patient data and found to match within two error bars. Finally, a dynamic lesion that mimics lesion border shape and washout curve shape was included in the phantom. High spatial and temporal resolution x-ray measurements of the washout curve shape were performed to determine the true contrast agent concentration as a function of time. DCE-MRI phantom measurements using a clinical imaging protocol were compared against the x-ray truth measurements. MRI signal intensity curves were shown to be less specific to lesion type tha