Large-Scale and Pan-Cancer Multi-omic Analyses with Machine Learning

Multi-omic data analysis has been foundational in many fields of molecular biology, including cancer research. Investigation of the relationship between different omic data types reveals patterns that cannot otherwise be found in a single data type alone. With recent technological advancements in mass spectrometry (MS), MS-based proteomics has enabled the quantification of thousands of proteins in hundreds of cell lines and human tissue samples. This thesis presents several machine learning-based methods that facilitate the integrative analysis of multi-omic data. First, we reviewed five existing multi-omic data integration methods and performed a benchmarking analysis, using a large-scale multi-omic cancer cell line dataset. We evaluated the performance of these machine learning methods for drug response prediction and cancer type classification. Our result provides recommendations to researchers regarding optimal machine learning method selection for their applications. Second, we generated a pan-cancer proteomic map of 949 cancer cell lines across 40 cancer types and developed a machine learning method DeeProM to analyse the multi-omic information of these lines. This pan-cancer proteomic map (ProCan-DepMapSanger) is now publicly available and represents a major resource for the scientific community, for biomarker discovery and for the study of fundamental aspects of protein regulation. Third, we focused on publicly available multi-omic datasets of both cancer cell lines and human tissue samples and developed a Transformer-based deep learning method, DeePathNet, which integrates human knowledge with machine intelligence. We applied DeePathNet on three evaluation tasks, namely drug response prediction, cancer type classification and breast cancer subtype classification. Taken together, our analyses and methods allowed more accurate cancer diagnosis and prognosis

Real-time moving object classification with automatic scene division

ABSTRACT We address the problem of moving object classification. Our aim is to classify moving objects of traffic scene videos into pedestrians, bicycles and vehicles. Instead of supervised learning and manual labeling of large training samples, our classifiers are initialized and refined online automatically. With efficient features extracted and organized, the approach can be real-time and achieve high classification accuracy. Once the view or scene changes detected, the algorithm can automatically refine the classifiers and adapt them to new environments. Experimental results demonstrate the effectiveness and robustness of the proposed approach

Computed Tomography Screening for Early Lung Cancer, COPD and Cardiovascular Disease in Shanghai:Rationale and Design of a Population-based Comparative Study

Rationale and Objectives: To describe the rational and design of a population-based comparative study. The objective of the study is to assess the screening performance of volume-based management of CT-detected lung nodule in comparison to diameter-based management, and to improve the effectiveness of CT screening for chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD), in addition to lung cancer, based on quantitative measurement of CT imaging biomarkers in a Chinese screening setting. Materials and Methods: A population-based comparative study is being performed, including 10,000 asymptomatic participants between 40 and 74 years old from Shanghai urban population. Participants in the intervention group undergo a low-dose chest and cardiac CT scan at baseline and 1 year later, and are managed according to NELCIN-B3 protocol. Participants in the control group undergo a low-dose chest CT scan according to the routine CT protocol and are managed according to the clinical practice. Epidemiological data are collected through questionnaires. In the fourth year from baseline, the diagnosis of the three diseases will be collected. Results: The unnecessary referral rate will be compared between NELCIN-B3 and standard protocol for managing early-detected lung nodules. The effectiveness of quantitative measurement of CT imaging biomarkers for early detection of lung cancer, COPD and CVD will be evaluated. Conclusion: We expect that the quantitative assessment of the CT imaging biomarkers will reduce the number of unnecessary referrals for early detected lung nodules, and will improve the early detection of COPD and CVD in a Chinese urban population

<i>Corynebacterium</i> sp. 2-TD Mediated Toxicity of 2-Tridecanone to <i>Helicoverpa armigera</i>

Cotton bollworm (Helicoverpa armigera) is a Lepidopteran noctuid pest with a global distribution. It has a wide range of host plants and can harm cotton, tomato, tobacco, and corn, as well as other crops. H. armigera larvae damage the flower buds, flowers, and fruits of tomato and cause serious losses to tomato production. Tomato uses the allelochemical 2-tridecanone to defend against this damage. So far, there have been no reports on whether the adaptation of H. armigera to 2-tridecanone is related to its symbiotic microorganisms. Our study found that Corynebacterium sp. 2-TD, symbiotic bacteria in H. armigera, mediates the toxicity of the 2-tridecanone to H. armigera. Corynebacterium sp. 2-TD, which was identified by 16S rDNA gene sequence analysis, was screened out using a basal salt medium containing a unique carbon source of 2-tridecanone. Then, Corynebacterium sp. 2-TD was confirmed to be distributed in the gut of H. armigera by quantitative PCR (qPCR) and fluorescence in situ hybridization (FISH). The survival rate of H. armigera increased by 38.3% under 2-tridecanone stress after inoculation with Corynebacterium sp. 2-TD. The degradation effect of Corynebacterium sp. 2-TD on 2-tridecanone was verified by ultra-high-performance liquid chromatography (UPLC). Our study is the first to report the isolation of gut bacteria that degrade 2-tridecanone from the important agricultural pest H. armigera and to confirm bacterial involvement in host adaptation to 2-tridecanone, which provides new insights into the adaptive mechanism of agricultural pests to host plants

Novel Stimulation Paradigms with Temporally-Varying Parameters to Reduce Synchronous Activity at the Onset of High Frequency Stimulation in Rat Hippocampus

Deep brain stimulation (DBS) has shown wide applications for treating various disorders in the central nervous system by using high frequency stimulation (HFS) sequences of electrical pulses. However, upon the onset of HFS sequences, the narrow pulses could induce synchronous firing of action potentials among large populations of neurons and cause a transient phase of “onset response” that is different from the subsequent steady state. To investigate the transient onset phase, the antidromically-evoked population spikes (APS) were used as an electrophysiological marker to evaluate the synchronous neuronal reactions to axonal HFS in the hippocampal CA1 region of anesthetized rats. New stimulation paradigms with time-varying intensity and frequency were developed to suppress the “onset responses”. Results show that HFS paradigms with ramp-up intensity at the onset phase could suppress large APS potentials. In addition, an intensity ramp with a slower ramp-up rate or with a higher pulse frequency had greater suppression on APS amplitudes. Therefore, to reach a desired pulse intensity rapidly, a stimulation paradigm combining elevated frequency and ramp-up intensity was used to shorten the transition phase of initial HFS without evoking large APS potentials. The results of the study provide important clues for certain transient side effects of DBS and for development of new adaptive stimulation paradigms

Experimental Study on Compression and Torsion Fracture within 3D Printed Cementation-Weak and Porosity-High Sandstones

Cretaceous sandstones have weak cementation and high porosity while exhibit a high apparent brittleness. Compression and torsion (C-T) fractures are widely distributed in Cretaceous sandstones due to asymmetric tectonic convergence action. However, studies on C-T fracture formation and the mechanisms causing variability in Cretaceous sandstones containing no oil or gas are rare due to the challenges in sampling intact sandstone cores, despite their significance to mine shaft sinking. Therefore, this study used binder jetting-based 3D printing to prepare artificial Cretaceous sandstone and developed a real-time X-ray computed tomography- (CT-) aided torsion shear apparatus to test them. The test results showed that the 3D printed (3DP) sandstone had characteristic indexes that approached and even exceeded the lower limits of Cretaceous sandstone cores, thereby accurately representing the unavailable cores. Furthermore, the 3DP sandstones had anisotropic properties comparable to the sandstone cores. Under C-T action, the 3DP sandstone exhibited a pronounced strain gradient of 2.0 %/mm perpendicular to fracture inclination. The inclination angles of fractures formed under C-T action tended to increase as the cell pressure increased, and that approached the orientation angles of maximal principal stress. The maximal and minimal principal stresses exerted inclination-slip and width-stretching effects, respectively, on C-T fractures. But the effect of inclination-slip on the C-T fractures was stronger than that of width-stretching. This insight into C-T fracture formation will guide future studies on the fracture evolution and its disaster-dominating mechanisms arisen from disturbances by shaft sinking

Barcode-Like Paper Sensor for Smartphone Diagnostics: An Application of Blood Typing

This study introduced a barcode-like design into a paper-based blood typing device by integrating with smartphone-based technology. The concept of presenting a paper-based blood typing assay in a barcode-like pattern significantly enhanced the adaptability of the assay to the smartphone technology. The fabrication of this device involved the use of a printing technique to define hydrophilic bar channels which were, respectively, treated with Anti-A, -B, and -D antibodies. These channels were then used to perform blood typing assays by introducing a blood sample. Blood type can be visually identified from eluting lengths in bar channels. A smartphone-based analytical application was designed to read the bar channels, analogous to scanning a barcode, interpret this information, and then report results to users. The proposed paper-based blood typing device is rapidly read by smartphones and easy for the user to operate. We envisage that the adaptation of paper-based devices to the widely accepted smartphone technology will increase the capability of paper-based diagnostics with rapid assay result interpretation, data storage, and transmission

Astrometric Support for the Lunar-based Ultraviolet Telescope

The Lunar-based Ultraviolet Telescope (LUT) is an astronomical instrument aboard Chang&#39;e 3, the lunar probe of China&#39;s Lunar Exploration Program that successfully landed on the northern part of the Moon&#39;s Mare Imbrium (340.4884E, 44.1214N) in late 2013. LUT is charting an ultraviolet map of the plane of the Milky Way and is also providing long-term light variability monitoring for a sample of RR Lyrae stars. However, the principal goal of the computer-controlled landing of the probe was a safe descent to a stable resting-place, and therefore, the precise orientation of LUT was never a priority. For this reason, at least theoretically, touch-down could have occurred anywhere and, for LUT, at any attitude, which would make the pointing and tracking of the wanted celestial objects practically impossible. Moreover, to reduce the data transmission load, the whole frame of every exposure could not be downloaded: only the image data containing the objects can make it to the ground; also, in order to save on electricity, the telescope does not usually track objects, which means that targets&#39; accurate positions and velocities (within the focal plane CCD) are both needed. This paper presents the astrometric solution devised to solve these problems: feasibility is first shown with experiments done from Earth, and then confirmed with actual LUT observations from the Moon&#39;s surface