Highly accurate model for prediction of lung nodule malignancy with CT scans

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://bioinformatics.astate.edu/NoduleX

Online auction-based relay selection for cooperative communication in CR networks

Cognitive radio and cooperative communication are two new network technologies. So, the combination of these two new technologies is a novel solution to solve the problem of spectrum scarcity. Two main challenges exist in the integration of cognitive radio and cooperative communication. First, there is a lack of incentives for the participating wireless devices to serve as relay nodes. Second, there is not an effective relay selection policy. In this paper, we propose an online auction-based relay selection scheme for cooperative communication in cognitive radio (CR) networks. Specifically, we design an auction scheme through adopting stopping theory. The proposed scheme ensures that the primary user (PU) can effectively select a CR relay to transmit its packets in a given time bound. In addition, we have analytically proven the truthfulness and the individual rationality of our online auction scheme. Extensive simulations demonstrate that the proposed relay selection scheme can always successfully and efficiently select a proper relay for a PU and can achieve a higher cooperative communication throughput compared with the conventional schemes

Meta-Information as a Service: A Big Social Data Analysis Framework

Social information services generate a large amount of data. Traditional social information service analysis techniques first require the large data to be stored, and afterwards processed and analyzed. However, as the size of the data grows the storing and processing cost increases. In this paper, we propose a ‘Meta-Information as a Service’ (MIaaS) framework that extracts the data from various social information services and transforms into useful information. The framework provides a new formal model to present the services required for social information service data analysis. An efficient data model to store and access the information. We also propose a new Quality of Service (QoS) model to capture the dynamic features of social information services. We use social information service based sentiment analysis as a motivating scenario. Experiments are conducted on real dataset. The preliminary results prove the feasibility of the proposed approach

Doxorubicin@Bcl-2 siRNA core@shell nanoparticles for synergistic anticancer chemotherapy

Acquired drug resistance in malignant tumors seriously hinders effective chemotherapy against cancer. The main mechanisms of drug resistance include decreased drug influx, increased drug efflux, as well as antiapoptotic defense behavior in cancerous cells. To overcome these issues, we have designed a nanomedicine composed of pure doxorubicin (DOX) as the core and B-cell lymphoma-2 (Bcl-2) siRNA as the shell for synergistic cancer treatment. Between the core and shell, polyethylene glycol (PEG) and polyethylenimine (PEI) are employed to increase the stability of the core DOX NPs and facilitate siRNA coating, respectively. In this design, the siRNA is able to inhibit the expression of Bcl-2 protein which has a role of protecting cancer cells from apoptosis. DOX not only is for anticancer therapy but also acts as a nanocarrier for Bcl-2 siRNA delivery. Our studies show that Bcl-2 siRNA and DOX are efficiently delivered into tumor cells and tumor tissues, and such a codelivery nanosystem possesses synergistic effects on tumor inhibition, enabling significantly enhanced antitumor outcome. This work demonstrates that the codelivery of tumor-suppressive Bcl-2 siRNA and chemotherapeutic agents without using an excipient material as a drug carrier represents a promising therapy for enhanced cancer therapy

Social Big Data: Mining, Applications, and Beyond

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Therapeutic effect of a combination of montelukast and vitamins A and D drops in children with bronchial asthma, and its influence on quality of life

Purpose: To investigate the efficacy of a combination of montelukast and vitamins A and D drops in bronchial asthma children, and its effect on quality of life.Methods: Sixty bronchial asthma children from June 2018 to June 2020 were collected and randomized into study group and control group (30 cases in each group). Control group received montelukast sodium (chewable tablets), while the study group received vitamins A and D drops (capsules) plus. Clinical efficacy, lung function, serum inflammatory factors, and quality of life were evaluated and compared.Results: Compared with control group, total treatment effectiveness was higher and the symptom remission period was shorter in the study group (p < 0.05). Post-treatment, the parameters of FEV1 and FVC increased in both groups, but higher in the study group (p < 0.05). Serum levels of CRP and IL-4 in both groups decreased after treatment, while serum IL-10 levels were significantly up-regulated. Compared with control group, the levels of these indicators were improved in the study group (p < 0.05). Post-treatment Chinese Version of Pediatric Quality of Life Asthma Specific Scale (PedSQL) score was higher than before treatment, with higher values (for all indicators) in the study group (p < 0.05).Conclusion: The combination therapy of montelukast and vitamins A and D drops produces good clinical efficacy in children with bronchial asthma. It significantly shortens the time taken for relief of clinical symptoms, improves lung function, reduces inflammatory response, controls asthma, and improves the quality of life of the patients

IgnitionInnovators at "Discharge Me!": Chain-of-Thought Instruction Finetuning Large Language Models for Discharge Summaries

This paper presents our proposed approach to the Discharge Me! shared task, collocated with the 23th Workshop on Biomedical Natural Language Processing (BioNLP). In this work, we develop an LLM-based framework for solving the Discharge Summary Documentation (DSD) task, i.e., generating the two critical target sections `Brief Hospital Course' and `Discharge Instructions' in the discharge summary. By streamlining the recent instruction-finetuning process on LLMs, we explore several prompting strategies for optimally adapting LLMs to specific generation task of DSD. Experimental results show that providing a clear output structure, complimented by a set of comprehensive Chain-of-Thoughts (CoT) questions, effectively improves the model's reasoning capability, and thereby, enhancing the structural correctness and faithfulness of clinical information in the generated text. Source code is available at: https://github.com/antangrocket1312/Discharge_LLMComment: Accepted by BioNLP2024 Worksho