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DeepSecE:A Deep-Learning-Based Framework for Multiclass Prediction of Secreted Proteins in Gram-Negative Bacteria

Research 2024年第3期2023卷 243-257页

作者： Yumeng Zhang Jiahao Guan Chen Li Zhikang Wang Zixin Deng Robin BGasser Jiangning Song Hong-Yu Ou state Key Laboratory of Microbial Metabolism Joint International Laboratory on Metabolic&Developmental SciencesSchool of Life Sciences and BiotechnologyShanghai Jiao Tong UniversityShanghai 200240China Shanghai Key Laboratory of Veterinary Biotechnology Shanghai Jiao Tong UniversityShanghai 200240China Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology Monash UniversityMelbourneViC 3800Australia Monash Data Futures Institute Monash UniversityMelbourneViC 3800Australia Melbourne Veterinary School Faculty of ScienceThe University of MelbourneParkvilleVIC 3010Australia.

Proteins secreted by Gram-negative bacteria are tightly linked to the virulence and adaptability of these microbes to environmental *** identification of such secreted proteins can facilitate the investigations of infections and diseases caused by these bacterial ***,current bioinformatic methods for predicting bacterial secreted substrate proteins have limited computational efficiency and application scope on a genome-wide ***,we propose a novel deep-learning-based framework—DeepSecE—for the simultaneous inference of multiple distinct groups of secreted proteins produced by Gram-negative *** remarkably improves their classification from nonsecreted proteins using a pretrained protein language model and transformer,achieving a macro-average accuracy of 0.883 on 5-fold *** benchmarking suggests that DeepSecE achieves competitive performance with the state-of-the-art binary predictors specialized for individual types of secreted *** attention mechanism corroborates salient patterns and motifs at the N or C termini of the protein *** this pipeline,we further investigate the genome-wide prediction of novel secreted proteins and their taxonomic distribution across~1,000 Gram-negative bacterial *** present analysis demonstrates that DeepSecE has major potential for the discovery of disease-associated secreted proteins in a diverse range of Gram-negative *** online web server of DeepSecE is also publicly available to predict and explore various secreted substrate proteins via the input of bacterial genome sequences.

关键词： Deep server competitive

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Efficacy of a 0.1% pterostilbene containing skincare emulsion on anti-ageing: A 28-day clinical trial

Journal of Dermatologic Science and Cosmetic Technology

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Journal of Dermatologic science and Cosmetic Technology 2025年

作者： Zongxiao Cen Zhiyuan Chen Ding Wang Yuqin Zuo Xueping Chen Junyuan Chen Guangzhou Luanying Cosmetics Co. LTD 2210 22nd Floor No. 180 Jiangnan Road Haizhu District Guangzhou 510000 China Centre for Biotech Big Data Research & Development Research Institute of Tsinghua Pearl River Delta 510300 China Vitargent (International) Biotechnology Limited Unit 203 No.15 Science Park West Avenue Hong Kong Science Park Shatin Hong Kong SAR 999077 China

Pterostilbene is emerging as a promising ingredient in skincare for its anti-aging properties. This study evaluated the clinical efficacy of a 0.1% pterostilbene-containing skincare emulsion compared to a control base emulsion in a 28-day trial involving 31 subjects. A double-blind, split-face design was employed, comparing the left and right sides of the face and pre- and post-treatment conditions. Efficacy was assessed using advanced tools, including the Skin Elasticity Tester Cutometer® dual MPA580, the facial imaging and analysis system VISIA®-CR, the skin microstructure 3D imaging system PRIMOS CR , and the in vivo two-photon microscopy imaging system SUPERVISION-780, along with subjects’ self-assessment after 14 and 28 days of continual use. Results demonstrated that the 0.1% pterostilbene emulsion significantly improved skin elasticity R2 and firmness F4, reduced the area and volume of forehead and undern-eye wrinkles, decreased the percentage of Crow’s feet wrinkles area, improved the aging index ELCOR, and increased the thickness of the epidermis layer, collagen intensity, elastic fiber fluorescence, and the standardized area of the epidermal-dermal junction (DEJ). Compared to the control base emulsion, the pterostilbene emulsion showed statistically significant ( p < 0.05) improvements across these metrics, as well as aging index SAIID, and skin pore size. All subjects expressed higher satisfaction with the pterostilbene emulsion than with the control, highlighting its superior skincare benefits. The findings underscore the potent anti-aging efficacy of pterostilbene, reinforcing its value as an active ingredient in cosmetics formulations.

关键词： Pterostilbene clinical study wrinkles, antiaging

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“Find Me”and“Eat Me”signals:tools to drive phagocytic processes for modulating antitumor immunity

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Cancer Communications 2024年第7期44卷 791-832页

作者： Lingjun Xiao Louqian Zhang Ciliang Guo Qilei Xin Xiaosong Gu Chunping Jiang Junhua Wu State Key Laboratory of Pharmaceutical Biotechnology National Institute of Healthcare Data Science at Nanjing UniversityJiangsu Key Laboratory of Molecular MedicineMedical SchoolNanjing UniversityNanjingJiangsuP.R.China Jinan Microecological Biomedicine Shandong Laboratory JinanShandongP.R.China

Phagocytosis,a vital defense mechanism,involves the recognition and elimination of foreign substances by ***,such as neutrophils and macrophages,rapidly respond to invaders;macrophages are especially important in later stages of the immune *** detect“find me”signals to locate apoptotic cells and migrate toward *** cells then send“eat me”signals that are recognized by phagocytes via specific receptors.“Find me”and“eat me”signals can be strategically harnessed to modulate antitumor immunity in support of cancer *** signals,such as calreticulin and phosphatidylserine,mediate potent pro-phagocytic effects,thereby promoting the engulfment of dying cells or their remnants by macrophages,neutrophils,and dendritic cells and inducing tumor cell *** review summarizes the phagocytic“find me”and“eat me”signals,including their concepts,signaling mechanisms,involved ligands,and ***,we delineate the relationships between“find me”and“eat me”signaling molecules and tumors,especially the roles of these molecules in tumor initiation,progression,diagnosis,and patient *** interplay of these signals with tumor biology is elucidated,and specific approaches to modulate“find me”and“eat me”signals and enhance antitumor immunity are ***,novel therapeutic strategies that combine“find me”and“eat me”signals to better bridge innate and adaptive immunity in the treatment of cancer patients are discussed.

关键词： cancer immunotherapy CARL CX3CL1 “Eat me”signal “Find me”signal Fc LPC Phagocytosis PtSer SLAMF7

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Decoding the Molecular Mechanisms of BRAFV600E-Induced Nevi Formation

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Biomedical and Environmental sciences 2024年第7期37卷 774-784页

作者： Weizheng Liang Yuxuan Liu Dandan Xu Wenjie Jiang Rensen Ran Central Laboratory The First Affiliated Hospital of Hebei North UniversityZhangjiakou 075000HebeiChina Institute of Molecular Immunology School of Laboratory Medicine and BiotechnologySouthern Medical UniversityGuangzhou 510515GuangdongChina Department of Artificial Intelligence and Data Science Hebei University of TechnologyTianjin 300401China Department of Chemical Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055GuangdongChina

Melanocytes derived from neural crest cells harbor the BRAFV600E mutation,which is the predominant driver of nevus formation in *** mutation leads to malignant cell proliferation and subsequent cell cycle arrest,culminating in oncogene-induced senescence and nevus ***,emerging evidence has highlighted the heterogeneity of cellular senescence markers in BRAFV600E-induced senescent ***,the capacity of melanocytes within nevi to regain their proliferative ability raises questions about the molecular mechanisms by which BRAFV600E,via the mitogen-activated protein kinase signaling pathway,triggers nevus *** study provides an overview and discussion of the molecular mechanisms underpinning BRAFV600E-induced melanocyte nevus formation and the relevant animal models employed for their *** also highlights the significance of elucidating dynamic changes in cytoplasmic and nuclear substrates that interact with phosphorylated extracellular signal-regulated protein kinases 1 and 2 and underscores the value of using targeted BRAFV600E animal models created through gene editing technologies.

关键词： BRAFV600E Melanocytes Nevi Oncogene-induced senescence Animal models

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Implementing Solar Panel Surface Dust Cleaning Innovation Using a Solar Innovation Framework Model

Implementing Solar Panel Surface Dust Cleaning Innovation Us...

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International Conference on Business Intelligence and Information Technology, BIIT 2022

作者： Dutta, P.K. Dey, Sujatra Majumder, Sayani Sen, Pritha Roy, Sudipta Amity School of Engineering and Technology Amity University Kolkata West Bengal Kolkata India Amity Institute of Biotechnology Amity University Kolkata West Bengal Kolkata India Artificial Intelligence and Data Science Jio Institute Navi Mumbai410206 India

ISBN: (纸本)9789819934157

The accumulation of dust on the surface of the solar modules decreases the amount of sunlight that hits the solar cells beneath, lowering the solar panel’s efficiency. They must always be scrubbed on a regular basis, usually with water, to function properly. Because of the abundance of sunlight, the Middle East region is ideal for harvesting solar energy, but there is also a lot of sand and dust. Cleaning becomes difficult and expensive in this area due to water scarcity. The cleaning procedure is performed by using a compressed air spray and is hereafter rubbed with a foam surface rolling material with a poly wool synthetic surface remover. An electronically controlled mechanical assembly is used to fix the rollers and make them move along the surface of the solar panels. In this study, we suggest a nanoparticle-based technology that does not allow dust to make the surface opaque, thus enabling it to be easily removed with microfiber without affecting effectiveness of the panel power efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Dust

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Nanotechnology and the Application of Information Technology for Sustainable Innovation in Agriculture

Nanotechnology and the Application of Information Technology...

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International Conference on Business Intelligence and Information Technology, BIIT 2022

作者： Dutta, Pushan Kumar Banerjee, Ujan Manna, Banani Hazarika, Kabyashree Das, Bimalangshu Roy, Sudipta Amity School of Engineering and Technology Amity University Kolkata West Bengal Kolkata India Amity Institute of Biotechnology Amity University Kolkata West Bengal Kolkata India Artificial Intelligence and Data Science Jio Institute Navi Mumbai410206 India

ISBN: (纸本)9789819934157

The field of nanomaterials has been constantly explored finding solutions to enhance the overall crop quality and production scale. Those nanoparticles with tiny size to broad surface area (1–100 nm) have plenty potential functions specifically in the field of agriculture. These days, sustainable agriculture is required. The evolution of nanomaterials has appeared as promising agents for the plant growth, fertilizers, and pesticides. This review provides basic data regarding CNTs, as well as their various properties, with a focus on their applications in the agriculture domain. Furthermore, the mechanisms of the uptake and translocation of CNTs in plants and their defense mechanisms against environmental stresses, and uses in pesticide, antimicrobial activity, development of robust nanosensors and targeted drug delivery systems are mentioned. Mainstream farming methods are now becoming progressively inadequate as the requirements on the key ecological increase. New technology adoption is essential if output is to be enlarged to encounter demand for food, fodder, and fiber. Nanotechnology guarantees an advancement in improving nutrient use efficiency through nano-formulation of fertilizers, having broken yield and nutritional quality barriers through bio-nanotechnology, pest and disease monitoring and control, and understanding the molecular pathways of host-parasite interactions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Nanoparticles

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Artificial intelligence for a bio-sensored detection of tuberculosis

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Network Modeling Analysis in Health Informatics and Bioinformatics 2021年第1期10卷 1-11页

作者： Tamilselvi, S. Saravana Kumar, N.M. Lavanya, S. Bindhu, J. Kaviyavarshini, N. Department of Biotechnology Bannari Amman Institute of Technology Erode India Department of Artificial Intelligence and Data Science M. Kumarasamy College of Engineering Karur India Department of Information Technology Sri Krishna College of Engineering and Technology Coimbatore India Department of Information Technology Vivekanandha College of Engineering for Women Namakkal India

The advancement and well-evolved technology in international clinical discipline, tuberculosis remains a major health hazard. To resolve the hassle of tuberculosis, synthetic artificial intelligence (AI) affords the manner for solving trouble in actual global and enlightens the sector in bringing a human’s mind to a gadget. This paper targets to discover the presence of Mycobacterium tuberculosis infection within a brief span of time as compared to historical technique. it is designed in this type of way that the breath of the inflamed man or woman may be used to diagnose the sickness at premiere stage. The main goal is to design and implement a portable diagnostic package for Tuberculosis the use of Neural Networks and synthetic Intelligence. The device package known as digital nose that is enormous synthetic sensible element built through neural network consists of a biosensor having an electrode lined with the galectin. The indicators of hybridization on binding can be captured and processed with the aid of system gaining knowledge of sensor and the output is displayed the use of artificial intelligence. Feed-ahead back propagation neural community is used as a classifier to distinguish between inflamed or non-infected man and woman. In advance case of analysis approached on the basis of grouping microorganism’s days together. However this observe quicker to find the document in an hour. Therefore, the time taken for diagnosing the presence of the bacterium may be decreased and this additionally paves the manner for starting the remedy right now with ease. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, AT part of Springer Nature.

关键词： Health hazards

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In-silico Prediction of Synergistic Anti-Cancer Drug Combinations Using Multi-omics data

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Scientific Reports 2019年第1期9卷 1-10页

作者： Celebi, Remzi Bear Don’t Walk, Oliver Movva, Rajiv Alpsoy, Semih Dumontier, Michel Maastricht University Institute of Data Science Maastricht Netherlands Columbia University Department of Biomedical Informatics New York City United States Stanford University Department of Genetics Palo Alto United States Turkish-German University Department of Molecular Biotechnology Istanbul Turkey

Chemotherapy is a routine treatment approach for early-stage cancers, but the effectiveness of such treatments is often limited by drug resistance, toxicity, and tumor heterogeneity. Combination chemotherapy, in which two or more drugs are applied simultaneously, offers one promising approach to address these concerns, since two single-target drugs may synergize with one another through interconnected biological processes. However, the identification of effective dual therapies has been particularly challenging;because the search space is large, combination success rates are low. Here, we present our method for DREAM AstraZeneca-Sanger Drug Combination Prediction Challenge to predict synergistic drug combinations. Our approach involves using biologically relevant drug and cell line features with machine learning. Our machine learning model obtained the primary metric = 0.36 and the tie-breaker metric = 0.37 in the extension round of the challenge which was ranked in top 15 out of 76 submissions. Our approach also achieves a mean primary metric of 0.39 with ten repetitions of 10-fold cross-validation. Further, we analyzed our model’s predictions to better understand the molecular processes underlying synergy and discovered that key regulators of tumorigenesis such as TNFA and BRAF are often targets in synergistic interactions, while MYC is often duplicated. Through further analysis of our predictions, we were also ble to gain insight into mechanisms and potential biomarkers of synergistic drug pairs. © 2019, The Author(s).

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High biomass yields of Chlorella protinosa with efficient nitrogen removal from secondary effluent in a membrane photobioreactor

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Journal of Environmental sciences 2024年第12期146卷 272-282页

作者： Min Yang Zhen Liu Aijie Wang Ingmar Nopens Hairong Hu Hong Chen School of Civil and Environmental Engineering Harbin Institute of Technology(Shenzhen)Shenzhen 518055China Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province Changsha 410114China BIOMATH Department of Data Analysis and Mathematical ModellingGhent UniversityGent B 9000Belgium Key Laboratory of Environmental Biotechnology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China School of Materials Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Further treatment of secondary effluents before their discharge into the receiving water bodies could alleviate water *** this study,the Chlorella proteinosa was cultured in a membrane photobioreactor to further remove nitrogen from the secondary *** effect of hydraulic retention time(HRT)on microalgae biomass yields and nutrient removal was *** results showed that soluble algal products concentration reduced in the suspension at low HRT,thereby alleviating microalgal growth *** addition,the lower HRT reduced the nitrogen limitation for Chlorella proteinosa’s growth through the phase-out of nitrogen-related functional *** a result,the productivity for Chlorella proteinosa increased from 6.12 mg/L/day at an HRT of 24 hr to 20.18 mg/L/day at an HRT of 8 *** highest removal rates of 19.7 mg/L/day,23.8 mg/L/day,and 105.4 mg/L/day were achieved at an HRT of 8 hr for total nitrogen(TN),ammonia,and chemical oxygen demand(COD),***,in terms of removal rate,TN and COD were the largest when HRT is 24 hr,which were 74.5%and 82.6%*** maximum removal rate of ammonia nitrogen was 99.2%when HRT was 8 hr.

关键词： Chlorella MPBR Fouling HRT SAP Nutrient

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Thorny but rosy: prosperities and difficulties in 'AI plus medicine' concerning data collection, model construction and clinical deployment

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General Psychiatry 2024年第6期37卷 618-623页

作者： Yujia Xia Zhangsheng Yu Departmentof Bioinformatics and Biostatistics School of Life Sciences and BiotechnologyShanghai Jiao Tong UniversityShanghaiChina SJTU-Yale Joint Center for Biostatistics and Data Science School of Life Sciences and BiotechnologyShanghai Jiao Tong UniversityShanghaiChina Clinical Research Institute Shanghai Jiao Tong University School of MedicineShanghaiChina

INTRODUCTION Artificial intelligence(AI)has brought about revolutionary changes in the medical field,including clinical practice,basic research and health *** powerful computing capabilities and intelligent algorithms... 详细信息

关键词： computing concerning enable

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