A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.

Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneumonia caused by coronavirus disease 2019 (COVID-19) and assess its severity, and can also discriminate between viral pneumonia caused by COVID-19 and other types of pneumonia. The deep-learning system was developed using a heterogeneous multicentre dataset of 145,202 images, and tested retrospectively and prospectively with thousands of additional images across four patient cohorts and multiple countries. The system generalized across settings, discriminating between viral pneumonia, other types of pneumonia and the absence of disease with areas under the receiver operating characteristic curve (AUCs) of 0.94-0.98; between severe and non-severe COVID-19 with an AUC of 0.87; and between COVID-19 pneumonia and other viral or non-viral pneumonia with AUCs of 0.87-0.97. In an independent set of 440 chest X-rays, the system performed comparably to senior radiologists and improved the performance of junior radiologists. Automated deep-learning systems for the assessment of pneumonia could facilitate early intervention and provide support for clinical decision-making.

Circulating tumour DNA methylation in hepatocellular carcinoma diagnosis using digital droplet PCR.

OBJECTIVE: To evaluate the performance of a DNA methylation-based digital droplet polymerase chain reaction (ddPCR) assay to detect aberrant DNA methylation in cell-free DNA (cfDNA) and to determine its application in the detection of hepatocellular carcinoma (HCC). METHODS: The present study recruited patients with liver-related diseases and healthy control subjects. Blood samples were used for the extraction of cfDNA, which was then bisulfite converted and the extent of DNA methylation quantified using a ddPCR platform. RESULTS: A total of 97 patients with HCC, 80 healthy control subjects and 46 patients with chronic hepatitis B/C virus infection were enrolled in the study. The level of cfDNA in the HCC group was significantly higher than that in the healthy control group. For the detection of HCC, based on a cut-off value of 15.7% for the cfDNA methylation ratio, the sensitivity and specificity were 78.57% and 89.38%, respectively. The diagnostic accuracy was 85.27%, the positive predictive value was 81.91% and the negative predictive value was 87.20%. The positive likelihood ratio of 15.7% in HCC diagnosis was 7.40, while the negative likelihood ratio was 0.24. CONCLUSIONS: A sensitive methylation-based assay might serve as a liquid biopsy test for diagnosing HCC.

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

DNA methylation markers in the diagnosis and prognosis of common leukemias.

The ability to identify a specific type of leukemia using minimally invasive biopsies holds great promise to improve the diagnosis, treatment selection, and prognosis prediction of patients. Using genome-wide methylation profiling and machine learning methods, we investigated the utility of CpG methylation status to differentiate blood from patients with acute lymphocytic leukemia (ALL) or acute myelogenous leukemia (AML) from normal blood. We established a CpG methylation panel that can distinguish ALL and AML blood from normal blood as well as ALL blood from AML blood with high sensitivity and specificity. We then developed a methylation-based survival classifier with 23 CpGs for ALL and 20 CpGs for AML that could successfully divide patients into high-risk and low-risk groups, with significant differences in clinical outcome in each leukemia type. Together, these findings demonstrate that methylation profiles can be highly sensitive and specific in the accurate diagnosis of ALL and AML, with implications for the prediction of prognosis and treatment selection.

Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancer.

Circulating tumor DNA (ctDNA) has emerged as a useful diagnostic and prognostic biomarker in many cancers. Here, we conducted a study to investigate the potential use of ctDNA methylation markers for the diagnosis and prognostication of colorectal cancer (CRC) and used a prospective cohort to validate their effectiveness in screening patients at high risk of CRC. We first identified CRC-specific methylation signatures by comparing CRC tissues to normal blood leukocytes. Then, we applied a machine learning algorithm to develop a predictive diagnostic and a prognostic model using cell-free DNA (cfDNA) samples from a cohort of 801 patients with CRC and 1021 normal controls. The obtained diagnostic prediction model discriminated patients with CRC from normal controls with high accuracy (area under curve = 0.96). The prognostic prediction model also effectively predicted the prognosis and survival of patients with CRC (P < 0.001). In addition, we generated a ctDNA-based molecular classification of CRC using an unsupervised clustering method and obtained two subgroups of patients with CRC with significantly different overall survival (P = 0.011 in validation cohort). Last, we found that a single ctDNA methylation marker, cg10673833, could yield high sensitivity (89.7%) and specificity (86.8%) for detection of CRC and precancerous lesions in a high-risk population of 1493 participants in a prospective cohort study. Together, our findings showed the value of ctDNA methylation markers in the diagnosis, surveillance, and prognosis of CRC.

Impaired D2 receptor-dependent dopaminergic transmission in prefrontal cortex of awake mouse model of Parkinson's disease.

The loss-of-function mutation in PARK7/DJ-1 is one of the most common causes of autosomal recessive Parkinson's disease, and patients carrying PARK7 mutations often exhibit both a progressive movement disorder and emotional impairment, such as anxiety. However, the causes of the emotional symptom accompanying PARK7-associated and other forms of Parkinson's disease remain largely unexplored. Using two-photon microscopic Ca2+ imaging in awake PARK7-/- and PARK7+/+ mice, we found that (i) PARK7-/- neurons in the frontal association cortex showed substantially higher circuit activity recorded as spontaneous somatic Ca2+ signals; (ii) both basal and evoked dopamine release remained intact, as determined by both electrochemical dopamine recordings and high performance liquid chromatography in vivo; (iii) D2 receptor expression was significantly decreased in postsynaptic frontal association cortical neurons, and the hyper-neuronal activity were rescued by D2 receptor intervention using either local pharmacology or viral D2 receptor over-expression; and (iv) PARK7-/- mice showed anxiety-like behaviours that were rescued by either local D2 receptor pharmacology or overexpression. Thus, for first time, we demonstrated a robust D2 receptor-dependent phenotype of individual neurons within the prefrontal cortex circuit in awake parkinsonian mice that linked with anxiety. Our work sheds light on early-onset phenotypes and the mechanisms underlying Parkinson's disease by imaging brain circuits in an awake mouse model.

Differential Co-release of Two Neurotransmitters from a Vesicle Fusion Pore in Mammalian Adrenal Chromaffin Cells.

Co-release of multiple neurotransmitters from secretory vesicles is common in neurons and neuroendocrine cells. However, whether and how the transmitters co-released from a single vesicle are differentially regulated remains unknown. In matrix-containing dense-core vesicles (DCVs) in chromaffin cells, there are two modes of catecholamine (CA) release from a single DCV: quantal and sub-quantal. By combining two microelectrodes to simultaneously record co-release of the native CA and ATP from a DCV, we report that (1) CA and ATP were co-released during a DCV fusion; (2) during kiss-and-run (KAR) fusion, the co-released CA was sub-quantal, whereas the co-released ATP was quantal; and (3) knockdown and knockout of the DCV matrix led to quantal co-release of both CA and ATP even in KAR mode. These findings strongly imply that, in contrast to sub-quantal CA release in chromaffin cells, fast synaptic transmission without transmitter-matrix binding is mediated exclusively via quantal release in neurons.

Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence.

Artificial intelligence (AI)-based methods have emerged as powerful tools to transform medical care. Although machine learning classifiers (MLCs) have already demonstrated strong performance in image-based diagnoses, analysis of diverse and massive electronic health record (EHR) data remains challenging. Here, we show that MLCs can query EHRs in a manner similar to the hypothetico-deductive reasoning used by physicians and unearth associations that previous statistical methods have not found. Our model applies an automated natural language processing system using deep learning techniques to extract clinically relevant information from EHRs. In total, 101.6 million data points from 1,362,559 pediatric patient visits presenting to a major referral center were analyzed to train and validate the framework. Our model demonstrates high diagnostic accuracy across multiple organ systems and is comparable to experienced pediatricians in diagnosing common childhood diseases. Our study provides a proof of concept for implementing an AI-based system as a means to aid physicians in tackling large amounts of data, augmenting diagnostic evaluations, and to provide clinical decision support in cases of diagnostic uncertainty or complexity. Although this impact may be most evident in areas where healthcare providers are in relative shortage, the benefits of such an AI system are likely to be universal.

Dynamin 1 Restrains Vesicular Release to a Subquantal Mode In Mammalian Adrenal Chromaffin Cells.

Dynamin 1 (dyn1) is required for clathrin-mediated endocytosis in most secretory (neuronal and neuroendocrine) cells. There are two modes of Ca2+-dependent catecholamine release from single dense-core vesicles: full-quantal (quantal) and subquantal in adrenal chromaffin cells, but their relative occurrences and impacts on total secretion remain unclear. To address this fundamental question in neurotransmission area using both sexes of animals, here we report the following: (1) dyn1-KO increased quantal size (QS, but not vesicle size/content) by ≥250% in dyn1-KO mice; (2) the KO-increased QS was rescued by dyn1 (but not its deficient mutant or dyn2); (3) the ratio of quantal versus subquantal events was increased by KO; (4) following a release event, more protein contents were retained in WT versus KO vesicles; and (5) the fusion pore size (dp) was increased from ≤9 to ≥9 nm by KO. Therefore, Ca2+-induced exocytosis is generally a subquantal release in sympathetic adrenal chromaffin cells, implying that neurotransmitter release is generally regulated by dynamin in neuronal cells.SIGNIFICANCE STATEMENT Ca2+-dependent neurotransmitter release from a single vesicle is the primary event in all neurotransmission, including synaptic/neuroendocrine forms. To determine whether Ca2+-dependent vesicular neurotransmitter release is "all-or-none" (quantal), we provide compelling evidence that most Ca2+-induced secretory events occur via the subquantal mode in native adrenal chromaffin cells. This subquantal release mode is promoted by dynamin 1, which is universally required for most secretory cells, including neurons and neuroendocrine cells. The present work with dyn1-KO mice further confirms that Ca2+-dependent transmitter release is mainly via subquantal mode, suggesting that subquantal release could be also important in other types of cells.

Stretch-induced Ca2+ independent ATP release in hippocampal astrocytes.

KEY POINTS: Similar to neurons, astrocytes actively participate in synaptic transmission via releasing gliotransmitters. The Ca2+ -dependent release of gliotransmitters includes glutamate and ATP. Following an 'on-cell-like' mechanical stimulus to a single astrocyte, Ca2+ independent single, large, non-quantal, ATP release occurs. Astrocytic ATP release is inhibited by either selective antagonist treatment or genetic knockdown of P2X7 receptor channels. Our work suggests that ATP can be released from astrocytes via two independent pathways in hippocampal astrocytes; in addition to the known Ca2+ -dependent vesicular release, larger non-quantal ATP release depends on P2X7 channels following mechanical stretch. ABSTRACT: Astrocytic ATP release is essential for brain functions such as synaptic long-term potentiation for learning and memory. However, whether and how ATP is released via exocytosis remains hotly debated. All previous studies of non-vesicular ATP release have used indirect assays. By contrast, two recent studies report vesicular ATP release using more direct assays. In the present study, using patch clamped 'ATP-sniffer cells', we re-investigated astrocytic ATP release at single-vesicle resolution in hippocampal astrocytes. Following an 'on-cell-like' mechanical stimulus of a single astrocyte, a Ca2+ independent single large non-quantal ATP release occurred, in contrast to the Ca2+ -dependent multiple small quantal ATP release in a chromaffin cell. The mechanical stimulation-induced ATP release from an astrocyte was inhibited by either exposure to a selective antagonist or genetic knockdown of P2X7 receptor channels. Functional P2X7 channels were expressed in astrocytes in hippocampal brain slices. Thus, in addition to small quantal ATP release, larger non-quantal ATP release depends on P2X7 channels in astrocytes.

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning.

The implementation of clinical-decision support algorithms for medical imaging faces challenges with reliability and interpretability. Here, we establish a diagnostic tool based on a deep-learning framework for the screening of patients with common treatable blinding retinal diseases. Our framework utilizes transfer learning, which trains a neural network with a fraction of the data of conventional approaches. Applying this approach to a dataset of optical coherence tomography images, we demonstrate performance comparable to that of human experts in classifying age-related macular degeneration and diabetic macular edema. We also provide a more transparent and interpretable diagnosis by highlighting the regions recognized by the neural network. We further demonstrate the general applicability of our AI system for diagnosis of pediatric pneumonia using chest X-ray images. This tool may ultimately aid in expediting the diagnosis and referral of these treatable conditions, thereby facilitating earlier treatment, resulting in improved clinical outcomes. VIDEO ABSTRACT.

Synaptotagmin-11 is a critical mediator of parkin-linked neurotoxicity and Parkinson's disease-like pathology.

Loss-of-function mutations in Parkin are the most common causes of autosomal recessive Parkinson's disease (PD). Many putative substrates of parkin have been reported; their pathogenic roles, however, remain obscure due to poor characterization, particularly in vivo. Here, we show that synaptotagmin-11, encoded by a PD-risk gene SYT11, is a physiological substrate of parkin and plays critical roles in mediating parkin-linked neurotoxicity. Unilateral overexpression of full-length, but not C2B-truncated, synaptotagmin-11 in the substantia nigra pars compacta (SNpc) impairs ipsilateral striatal dopamine release, causes late-onset degeneration of dopaminergic neurons, and induces progressive contralateral motor abnormalities. Mechanistically, synaptotagmin-11 impairs vesicle pool replenishment and thus dopamine release by inhibiting endocytosis. Furthermore, parkin deficiency induces synaptotagmin-11 accumulation and PD-like neurotoxicity in mouse models, which is reversed by SYT11 knockdown in the SNpc or knockout of SYT11 restricted to dopaminergic neurons. Thus, PD-like neurotoxicity induced by parkin dysfunction requires synaptotagmin-11 accumulation in SNpc dopaminergic neurons.

CaV2.2 Gates Calcium-Independent but Voltage-Dependent Secretion in Mammalian Sensory Neurons.

Action potential induces membrane depolarization and triggers intracellular free Ca2+ concentration (Ca2+)-dependent secretion (CDS) via Ca2+ influx through voltage-gated Ca2+ channels. We report a new type of somatic exocytosis triggered by the action potential per se-Ca2+-independent but voltage-dependent secretion (CiVDS)-in dorsal root ganglion neurons. Here we uncovered the molecular mechanism of CiVDS, comprising a voltage sensor, fusion machinery, and their linker. Specifically, the voltage-gated N-type Ca2+ channel (CaV2.2) is the voltage sensor triggering CiVDS, the SNARE complex functions as the vesicle fusion machinery, the "synprint" of CaV2.2 serves as a linker between the voltage sensor and the fusion machinery, and ATP is a cargo of CiVDS vesicles. Thus, CiVDS releases ATP from the soma while CDS releases glutamate from presynaptic terminals, establishing the CaV2.2-SNARE "voltage-gating fusion pore" as a novel pathway co-existing with the canonical "Ca2+-gating fusion pore" pathway for neurotransmitter release following action potentials in primary sensory neurons.

Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma.

An effective blood-based method for the diagnosis and prognosis of hepatocellular carcinoma (HCC) has not yet been developed. Circulating tumour DNA (ctDNA) carrying cancer-specific genetic and epigenetic aberrations may enable a noninvasive 'liquid biopsy' for diagnosis and monitoring of cancer. Here, we identified an HCC-specific methylation marker panel by comparing HCC tissue and normal blood leukocytes and showed that methylation profiles of HCC tumour DNA and matched plasma ctDNA are highly correlated. Using cfDNA samples from a large cohort of 1,098 HCC patients and 835 normal controls, we constructed a diagnostic prediction model that showed high diagnostic specificity and sensitivity (P < 0.001) and was highly correlated with tumour burden, treatment response, and stage. Additionally, we constructed a prognostic prediction model that effectively predicted prognosis and survival (P < 0.001). Together, these findings demonstrate in a large clinical cohort the utility of ctDNA methylation markers in the diagnosis, surveillance, and prognosis of HCC.

Ligand- and voltage-gated Ca2+ channels differentially regulate the mode of vesicular neuropeptide release in mammalian sensory neurons.

Neuropeptides released from dorsal root ganglion (DRG) neurons play essential roles in the neurotransmission of sensory inputs, including those underlying nociception and pathological pain. Neuropeptides are released from intracellular vesicles through two modes: a partial release mode called "kiss-and-run" (KAR) and a full release mode called "full fusion-like" (FFL). Using total internal reflection fluorescence (TIRF) microscopy, we traced the release of pH-sensitive green fluorescent protein-tagged neuropeptide Y (pHluorin-NPY) from individual dense-core vesicles in the soma and axon of single DRG neurons after Ca2+ influx through either voltage-gated Ca2+ channels (VGCCs) or ligand-gated transient receptor potential vanilloid 1 (TRPV1) channels. We found that Ca2+ influx through VGCCs stimulated FFL and a greater single release of neuropeptides. In contrast, Ca2+ influx through TRPV1 channels stimulated KAR and a pulsed but prolonged release of neuropeptides that was partially mediated by Dynamin 1, which limits fusion pore expansion. Suppressing the Ca2+ gradient to an extent similar to that seen after TRPV1 activation abolished the VGCC preference for FFL. The findings suggest that by generating a steeper Ca2+ gradient, VGCCs promote a more robust fusion pore opening that facilitates FFL. Thus, KAR and FFL release modes are differentially regulated by the two principal types of Ca2+-permeable channels in DRG neurons.

DNA methylation markers for diagnosis and prognosis of common cancers.

The ability to identify a specific cancer using minimally invasive biopsy holds great promise for improving the diagnosis, treatment selection, and prediction of prognosis in cancer. Using whole-genome methylation data from The Cancer Genome Atlas (TCGA) and machine learning methods, we evaluated the utility of DNA methylation for differentiating tumor tissue and normal tissue for four common cancers (breast, colon, liver, and lung). We identified cancer markers in a training cohort of 1,619 tumor samples and 173 matched adjacent normal tissue samples. We replicated our findings in a separate TCGA cohort of 791 tumor samples and 93 matched adjacent normal tissue samples, as well as an independent Chinese cohort of 394 tumor samples and 324 matched adjacent normal tissue samples. The DNA methylation analysis could predict cancer versus normal tissue with more than 95% accuracy in these three cohorts, demonstrating accuracy comparable to typical diagnostic methods. This analysis also correctly identified 29 of 30 colorectal cancer metastases to the liver and 32 of 34 colorectal cancer metastases to the lung. We also found that methylation patterns can predict prognosis and survival. We correlated differential methylation of CpG sites predictive of cancer with expression of associated genes known to be important in cancer biology, showing decreased expression with increased methylation, as expected. We verified gene expression profiles in a mouse model of hepatocellular carcinoma. Taken together, these findings demonstrate the utility of methylation biomarkers for the molecular characterization of cancer, with implications for diagnosis and prognosis.

Intracellular TRPA1 mediates Ca2+ release from lysosomes in dorsal root ganglion neurons.

Transient receptor potential A1 (TRPA1) is a nonselective cation channel implicated in thermosensation and inflammatory pain. In this study, we show that TRPA1 (activated by allyl isothiocyanate, acrolein, and 4-hydroxynonenal) elevates the intracellular Ca2+ concentration ([Ca2+]i) in dorsal root ganglion (DRG) neurons in the presence and absence of extracellular Ca2+ Pharmacological and immunocytochemical analyses revealed the presence of TRPA1 channels both on the plasma membrane and in endolysosomes. Confocal line-scan imaging demonstrated Ca2+ signals elicited from individual endolysosomes ("lysosome Ca2+ sparks") by TRPA1 activation. In physiological solutions, the TRPA1-mediated endolysosomal Ca2+ release contributed to ∼40% of the overall [Ca2+]i rise and directly triggered vesicle exocytosis and calcitonin gene-related peptide release, which greatly enhanced the excitability of DRG neurons. Thus, in addition to working via Ca2+ influx, TRPA1 channels trigger vesicle release in sensory neurons by releasing Ca2+ from lysosome-like organelles.

Sensory Response of Transplanted Astrocytes in Adult Mammalian Cortex In Vivo.

Glial precursor transplantation provides a potential therapy for brain disorders. Before its clinical application, experimental evidence needs to indicate that engrafted glial cells are functionally incorporated into the existing circuits and become essential partners of neurons for executing fundamental brain functions. While previous experiments supporting for their functional integration have been obtained under in vitro conditions using slice preparations, in vivo evidence for such integration is still lacking. Here, we utilized in vivo two-photon Ca(2+) imaging along with immunohistochemistry, fluorescent indicator labeling-based axon tracing and correlated light/electron microscopy to analyze the profiles and the functional status of glial precursor cell-derived astrocytes in adult mouse neocortex. We show that after being transplanted into somatosensory cortex, precursor-derived astrocytes are able to survive for more than a year and respond with Ca(2+) signals to sensory stimulation. These sensory-evoked responses are mediated by functionally-expressed nicotinic receptors and newly-established synaptic contacts with the host cholinergic afferents. Our results provide in vivo evidence for a functional integration of transplanted astrocytes into adult mammalian neocortex, representing a proof-of-principle for sensory cortex remodeling through addition of essential neural elements. Moreover, we provide strong support for the use of glial precursor transplantation to understand glia-related neural development in vivo.