Improved Fruit Fly Optimization Algorithm-based density peak clustering and its applications

Kao algoritam temeljen na gustoći, algoritam grupiranja na osnovu najviše gustoće (Density Peak Clustering - DPC) superioran je u grupiranju pronalaženjem vršne gustoće. No, smanjena udaljenost i središta grupiranja trebaju se postaviti slučajno, što bi utjecalo na rezultate grupiranja. Voćne mušice pronalaze najbolju hranu lokalnim pretraživanjem i globalnim pretraživanjem. Pronađena hrana je ekstremna vrijednost parametra izračunata algoritmom optimizacije voćne mušice (Fruit Fly Optimization Algorithm - FOA). Na osnovu brze pretrage i superiornosti brze konvergencije FOA-e, moguće je nadoknaditi slučajnost DPC-a. Poboljšana vršna gustoća grupiranja voćnih mušica, temeljena na algoritmu optimizacije, predložena je kao FOA-DPC. Taj bi algoritam trebao biti efikasniji i učinkovitiji od DPC algoritma. Rezultati sedam simulacijskih eksperimenata na UCI nizovima podataka potvrdili su da predloženi algoritam nije imao samo bolju performansu grupiranja već je bio bliži pravim brojevima grupiranja. Nadalje, FOA-DPC primijenjen je i u analizi financijskih podataka i pokazao se vrlo učinkovitim.As density-based algorithm, Density Peak Clustering (DPC) algorithm has superiority of clustering by finding the density peaks. But the cut-off distance and clustering centres had to be set at random, which would influence clustering outcomes. Fruit flies find the best food by local searching and global searching. The food found was the parameter extreme value calculated by Fruit Fly Optimization Algorithm (FOA). Based on the rapid search and fast convergence superiorities of FOA, it is possible to make up the casualness of DPC. An improved fruit fly optimization-based density peak clustering algorithm was proposed as FOA-DPC. The FOA-DPC algorithm would be more efficient and effective than DPC algorithm. The results of seven simulation experiments in UCI data sets validated that the proposed algorithm did not only have better clustering performance, but also were closer to the true clustering numbers. Furthermore, FOA-DPC was applied to practical financial data analysis and the conclusion was also effective

An Experimental Study on the Establishment of Pulmonary Hypertension Model in Rats induced by Monocrotaline

Pulmonary hypertension is called PH for short. It is caused by the pulmonary artery vascular disease leading to pulmonary vascular resistance, and the increase right lung compartment load, which resulting in weakening or even collapse of the right ventricular function. The establishment of rat PH model under the action of monocrotaline is a repeatable, simple and accessible operation technique, which has been widely used in the treatment of pulmonary hypertension. This paper discusses the principle and properties of the PH model on rats under the monocrotaline action

Homozygous p.Ser267Phe in SLC10A1 is associated with a new type of hypercholanemia and implications for personalized medicine.

SLC10A1 codes for the sodium-taurocholate cotransporting polypeptide (NTCP), which is a hepatocellular transporter for bile acids (BAs) and the receptor for hepatitis B and D viruses. NTCP is also a target of multiple drugs. We aimed to evaluate the medical consequences of the loss of function mutation p.Ser267Phe in SLC10A1. We identified eight individuals with homozygous p.Ser267Phe mutation in SLC10A1 and followed up for 8-90 months. We compared their total serum BAs and 6 species of BAs with 170 wild-type and 107 heterozygous healthy individuals. We performed in-depth medical examinations and exome sequencing in the homozygous individuals. All homozygous individuals had persistent hypercholanemia (P = 5.8 × 10-29). Exome sequencing excluded the involvement of other BA metabolism-associated genes in the hypercholanemia. Although asymptomatic, all individuals had low vitamin D levels. Of six adults that were subjected to bone mineral density analysis, three presented with osteoporosis/osteopenia. Sex hormones and blood lipids were deviated in all subjects. Homozygosity of p.Ser267Phe in SLC10A1 is associated with asymptomatic hypercholanemia. Individuals with homozygous p.Ser267Phe in SLC10A1 are prone to vitamin D deficiency, deviated sex hormones and blood lipids. Surveillance of these parameters may also be needed in patients treated with drugs targeting NTCP.This project is supported by the National Natural Science Foundation of China (31471193, 81570539, 81370535, 91331204 and 31525014). S.X. acknowledges financial support from the Strategic Priority Research Program (XDB13040100) and Key Research Program of Frontier Sciences (QYZDJ-SSW-SYS009) of the Chinese Academy of Sciences (CAS)

Qishen Yiqi dripping pills for chronic ischaemic heart failure:results of the CACT-IHF randomized clinical trial

10.1002/ehf2.12980ESC Heart Failure763881-389

The Study on Newly Developed McAb NJ001 Specific to Non-Small Cell Lung Cancer and Its Biological Characteristics

Monoclonal antibody (McAb) is the key tool for cancer immunodiagnosis and immunotherapy. McAb-based immunotherapy that targets tumor antigens has had great achivement. In this study, a cell clone which kept secreting high-titer IgG1-type McAb named NJ001 against human non-small cell lung cancer (NSCLC) cells was obtained. The titer of purified NJ001 was 2×106. The antigen named SP70 of NSCLC specifically identified by NJ001 was proved to be a protein with the relative molecular mass (Mr) of 70 kDa. The results of immunohistochemical staining indicated that NJ001 could positively react to NSCLC, but weak positively or negatively react to human small-cell lung cancer (SCLC), pulmonary pseudotumor and other epithelial tumors. In soft agar assay, the colony formation efficiency in NJ001 groups decreased in a dose-dependent manner. For the concentration of 100 µg/ml, 200 µg/ml and 400 µg/ml, the inhibition ratio of colony formation was 23.4%, 62.5% and 100% respectively. Meanwhile, NJ001 caused significant reduction in tumor volume and tumor weight compared to control mice in lung cancer xenograft model. The tumor growth inhibition ratio in 200 µg, 400 µg and 800 µg NJ001 groups was 10.44%, 37.29% and 44.04%, respectively. NJ001 also led to cytomorphological changes and induced the apoptosis of human lung adenocarcinoma cell line SPC-A1 significantly. The newly developed NJ001 selectively reacted to NSCLC and exhibited anti-tumor activity both in vitro and in vivo. NJ001 is of great value concerning immunodiagnostics and immunotherapy for NSCLC and holds promise for further research regarding the mechanism underlying tumor progression of NSCLC

Development and validation of a three-dimensional deep learning-based system for assessing bowel preparation on colonoscopy video

BackgroundThe performance of existing image-based training models in evaluating bowel preparation on colonoscopy videos was relatively low, and only a few models used external data to prove their generalization. Therefore, this study attempted to develop a more precise and stable AI system for assessing bowel preparation of colonoscopy video.MethodsWe proposed a system named ViENDO to assess the bowel preparation quality, including two CNNs. First, Information-Net was used to identify and filter out colonoscopy video frames unsuitable for Boston bowel preparation scale (BBPS) scoring. Second, BBPS-Net was trained and tested with 5,566 suitable short video clips through three-dimensional (3D) convolutional neural network (CNN) technology to detect BBPS-based insufficient bowel preparation. Then, ViENDO was applied to complete withdrawal colonoscopy videos from multiple centers to predict BBPS segment scores in clinical settings. We also conducted a human-machine contest to compare its performance with endoscopists.ResultsIn video clips, BBPS-Net for determining inadequate bowel preparation generated an area under the curve of up to 0.98 and accuracy of 95.2%. When applied to full-length withdrawal colonoscopy videos, ViENDO assessed bowel cleanliness with an accuracy of 93.8% in the internal test set and 91.7% in the external dataset. The human-machine contest demonstrated that the accuracy of ViENDO was slightly superior compared to most endoscopists, though no statistical significance was found.ConclusionThe 3D-CNN-based AI model showed good performance in evaluating full-length bowel preparation on colonoscopy video. It has the potential as a substitute for endoscopists to provide BBPS-based assessments during daily clinical practice