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3. Towards development of functional climate-driven early warning systems for climate-sensitive infectious diseases: Statistical models and recommendations.

Author

Haque, S, Mengersen, K, Barr, I, Wang, L, Yang, W, Vardoulakis, S, Bambrick, H, Hu, W, Haque, S, Mengersen, K, Barr, I, Wang, L, Yang, W, Vardoulakis, S, Bambrick, H, and Hu, W

Abstract

Climate, weather and environmental change have significantly influenced patterns of infectious disease transmission, necessitating the development of early warning systems to anticipate potential impacts and respond in a timely and effective way. Statistical modelling plays a pivotal role in understanding the intricate relationships between climatic factors and infectious disease transmission. For example, time series regression modelling and spatial cluster analysis have been employed to identify risk factors and predict spatial and temporal patterns of infectious diseases. Recently advanced spatio-temporal models and machine learning offer an increasingly robust framework for modelling uncertainty, which is essential in climate-driven disease surveillance due to the dynamic and multifaceted nature of the data. Moreover, Artificial Intelligence (AI) techniques, including deep learning and neural networks, excel in capturing intricate patterns and hidden relationships within climate and environmental data sets. Web-based data has emerged as a powerful complement to other datasets encompassing climate variables and disease occurrences. However, given the complexity and non-linearity of climate-disease interactions, advanced techniques are required to integrate and analyse these diverse data to obtain more accurate predictions of impending outbreaks, epidemics or pandemics. This article presents an overview of an approach to creating climate-driven early warning systems with a focus on statistical model suitability and selection, along with recommendations for utilizing spatio-temporal and machine learning techniques. By addressing the limitations and embracing the recommendations for future research, we could enhance preparedness and response strategies, ultimately contributing to the safeguarding of public health in the face of evolving climate challenges.

Published
2024

4. Catalytic pyrolysis of duckweed with phosphoric acid : Pyrolysis behavior and kinetics analysis

Author

Zhu, Y., Huo, G., Yang, W., Liu, H., Zhang, Wennan, Cheng, W., Yang, H., Wang, Z., Jin, Y., Zhao, H., Zhu, Y., Huo, G., Yang, W., Liu, H., Zhang, Wennan, Cheng, W., Yang, H., Wang, Z., Jin, Y., and Zhao, H.

Abstract

Duckweed (DW) has a promising potential for wastewater treatment due to its outstanding performance in the fixation of nutrient elements and heavy metals. The conversion of harvested duckweed into value-added products through pyrolysis is an attractive method for duckweed utilization as fuels or chemicals. In this work, the duckweed was prepared by deashing treatment and subsequent impregnation with different phosphoric acid concentrations (ADW-P). The pyrolysis behavior and kinetics of raw and impregnated duckweeds were studied with respect to the ash contained in the duckweed and the phosphoric acid catalytic effect by thermogravimetric analysis-fourier transform infrared spectrometer (TG-FTIR) and pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). The results show that the pyrolysis reaction zone is extended for the impregnated duckweed by reducing the initial pyrolysis temperature and increasing the final temperature. Specifically, a shoulder peak situated at the right side of the main peak is present in the DTG curves of ADW-P, suggesting the formation of relatively stable substance after phosphoric acid impregnation. Phosphoric acid promotes the release of H2O, CH4, CO2 and NH3 as well as light volatiles with C[dbnd]C and C[dbnd]O groups during pyrolysis. Meanwhile, decarboxylation and aromatization as well as deamination of organic compounds are strengthened, resulting in an increase of aromatic hydrocarbons and furans and a decrease of N-heterocyclic compounds. The activation energy of ADW-P is lower than that of DW and ADW at conversion rate less than 75% but increases remarkably at high conversion rate. This implies that phosphoric acid facilitates the thermal decomposition of DW at low temperatures but hinders its decomposition at high temperatures probably due to the formation of stable cross-linked structures such as phosphate and polyphosphate esters.

Published
2024
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12. Ammonia combustion in furnaces: A review

Author

Valera-Medina, A., primary, Vigueras-Zuniga, M.O., additional, Shi, H., additional, Mashruk, S., additional, Alnajideen, M., additional, Alnasif, A., additional, Davies, J., additional, Wang, Y., additional, Zhu, X., additional, Yang, W., additional, and Cheng, Y.B., additional

Published
2023
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23. A phase Ib/II dose expansion study of subcutaneous sasanlimab in patients with locally advanced or metastatic non-small-cell lung cancer and urothelial carcinoma

Author

Cho, B.C., primary, Penkov, K., additional, Bondarenko, I., additional, Kurochkin, A., additional, Pikiel, J., additional, Ahn, H.K., additional, Korożan, M.E., additional, Osipov, M., additional, Odintsova, S., additional, Braiteh, F., additional, Ribas, A., additional, Grilley-Olson, J.E., additional, Lugowska, I., additional, Bonato, V., additional, Damore, M.A., additional, Yang, W., additional, Jacobs, I.A., additional, Bowers, M., additional, Li, M., additional, and Johnson, M.L., additional

Published
2023
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26. iCGPN: Interaction-centric graph parsing network for human-object interaction detection

Author

Yang, W, Chen, G, Zhao, Z, Su, F, and Meng, H

Subjects
Artificial Intelligence, Cognitive Neuroscience, Attention mechanism, Multi-relation graph convolutional network, Human-object interaction detection, Multi-IOU random shift, Computer Science Applications
Abstract

Human-Object Interaction (HOI) detection aims to infer different interactions, which occur between humans and related objects of images. HOI is usually represented by a triplet and can be modeled as a graph. Thus, with global structural information of images, graph-based methods can detect interactions. However, in existing graph networks, although different fully-connected graphs are built, all detected bounding boxes are regarded as graph nodes equally or different types of nodes according to the category, thereby the dominant role of humans in HOI is ignored. In addition, object node representations mainly focus on appearance features, contributing little to HOI inference. To address these issues, a novel graph-based HOI detection model, named interaction-centric graph parsing network (iCGPN), models one human node as a central node, and other nodes as semantic nodes. Firstly, for each detected human instance, a human-centric fully-connected graph is constructed to learn related HOIs. Secondly, in order to reflect the difference between central nodes and semantic nodes, we design different feature representations and model different edge relationships. Through introducing the attention mechanism, global information related to human-object interaction is explored to enrich the semantic node representation, in which spatial layout, relative locations and object categories information are also combined. Finally, a multi-relation graph convolutional network is applied to update the node feature and infer the HOI. Furthermore, a multi-IOU random shift scheme is proposed to augment the data of the training set to fit the object detection deviation and enhance the generalization ability of our network. Extensive experimental results show that iCGPN achieves very competitive results in comparison with state-of-the-arraph-based methods on the V-COCO and HICO-DET datasets, which demonstrate the effectiveness of the proposed method.

Published
2022
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28. Effect of the COVID-19 pandemic on surgery for indeterminate thyroid nodules (THYCOVID): a retrospective, international, multicentre, cross-sectional study

Author

Medas, Fabio, primary, Dobrinja, Chiara, additional, Al-Suhaimi, Ebtesam Abdullah, additional, Altmeier, Julia, additional, Anajar, Said, additional, Arikan, Akif Enes, additional, Azaryan, Irina, additional, Bains, Lovenish, additional, Basili, Giancarlo, additional, Bolukbasi, Hakan, additional, Bononi, Marco, additional, Borumandi, Farzad, additional, Bozan, Mehmet Buğra, additional, Brenta, Gabriela, additional, Brunaud, Laurent, additional, Brunner, Maximilian, additional, Buemi, Antoine, additional, Canu, Gian Luigi, additional, Cappellacci, Federico, additional, Cartwright, Sara Burchfield, additional, Castells Fusté, Ignasi, additional, Cavalheiro, Beatriz, additional, Cavallaro, Giuseppe, additional, Chala, Andres, additional, Chan, Shun Yan Bryant, additional, Chaplin, John, additional, Cheema, Mustafa Sajjad, additional, Chiapponi, Costanza, additional, Chiofalo, Maria Grazia, additional, Chrysos, Emmanuel, additional, D'Amore, Annamaria, additional, de Cillia, Michael, additional, De Crea, Carmela, additional, de Manzini, Nicolò, additional, de Matos, Leandro Luongo, additional, De Pasquale, Loredana, additional, Del Rio, Paolo, additional, Demarchi, Marco Stefano, additional, Dhiwakar, Muthuswamy, additional, Donatini, Gianluca, additional, Dora, Jose Miguel, additional, D'Orazi, Valerio, additional, Doulatram Gamgaram, Viyey Kishore, additional, Eismontas, Vitalijus, additional, Kabiri, El Hassane, additional, El Malki, Hadj Omar, additional, Elzahaby, Islam, additional, Enciu, Octavian, additional, Eskander, Antoine, additional, Feroci, Francesco, additional, Figueroa-Bohorquez, David, additional, Filis, Dimitrios, additional, Gorostidi, François, additional, Frías-Fernández, Pedro, additional, Gamboa-Dominguez, Armando, additional, Genc, Volkan, additional, Giordano, Davide, additional, Gómez-Pedraza, Antonio, additional, Graceffa, Giuseppa, additional, Griffin, James, additional, Guerreiro, Sofia Cuco, additional, Gupta, Karan, additional, Gupta, Keshav Kumar, additional, Gurrado, Angela, additional, Hajiioannou, Jiannis, additional, Hakala, Tommi, additional, Harahap, Wirsma Arif, additional, Hargitai, Lindsay, additional, Hartl, Dana, additional, Hellmann, Andrzej, additional, Hlozek, Jiri, additional, Hoang, Van Trung, additional, Iacobone, Maurizio, additional, Innaro, Nadia, additional, Ioannidis, Orestis, additional, Jang, J H Isabelle, additional, Xavier-Junior, Jose Candido, additional, Jovanovic, Milan, additional, Kaderli, Reto Martin, additional, Kakamad, Fahmi, additional, Kaliszewski, Krzysztof, additional, Karamanliev, Martin, additional, Katoh, Hiroshi, additional, Košec, Andro, additional, Kovacevic, Bozidar, additional, Kowalski, Luiz Paulo, additional, Králik, Robert, additional, Yadav, Sanjay Kumar, additional, Kumorová, Adriána, additional, Lampridis, Savvas, additional, Lasithiotakis, Konstantinos, additional, Leclere, Jean-Christophe, additional, Leong, Eugene Kwong Fei, additional, Leow, Melvin Khee-Shing, additional, Lim, James Y, additional, Lino-Silva, Leonardo S, additional, Liu, Shirley Yuk Wah, additional, Llorach, Núria Perucho, additional, Lombardi, Celestino Pio, additional, López-Gómez, Javier, additional, Lori, Eleonora, additional, Quintanilla-Dieck, Lourdes, additional, Lucchini, Roberta, additional, Madani, Amin, additional, Manatakis, Dimitrios, additional, Markovic, Ivan, additional, Materazzi, Gabriele, additional, Mazeh, Haggi, additional, Mercante, Giuseppe, additional, Meyer-Rochow, Goswin Yason, additional, Mihaljevic, Olgica, additional, Miller, Julie A, additional, Minuto, Michele, additional, Monacelli, Massimo, additional, Mulita, Francesk, additional, Mullineris, Barbara, additional, Muñoz-de-Nova, José Luis, additional, Muradás Girardi, Fábio, additional, Nader, Saki, additional, Napadon, Tangjaturonrasme, additional, Nastos, Constantinos, additional, Offi, Chiara, additional, Ronen, Ohad, additional, Oragano, Luigi, additional, Orois, Aida, additional, Pan, Yongqin, additional, Panagiotidis, Emmanouil, additional, Panchangam, Ramakanth Bhargav, additional, Papavramidis, Theodosios, additional, Parida, Pradipta Kumar, additional, Paspala, Anna, additional, Pérez, Òscar Vidal, additional, Petrovic, Sabrina, additional, Raffaelli, Marco, additional, Ramacciotti, Constanza Fernanda, additional, Ratia Gimenez, Tomas, additional, Rivo Vázquez, Ángel, additional, Roh, Jong-Lyel, additional, Rossi, Leonardo, additional, Sanabria, Alvaro, additional, Santeerapharp, Alena, additional, Semenov, Arseny, additional, Seneviratne, Sanjeewa, additional, Serdar, Altinay, additional, Sheahan, Patrick, additional, Sheppard, Sean C, additional, Slotcavage, Rachel L, additional, Smaxwil, Constantin, additional, Kim, Soo Young, additional, Sorrenti, Salvatore, additional, Spartalis, Eleftherios, additional, Sriphrapradang, Chutintorn, additional, Testini, Mario, additional, Turk, Yigit, additional, Tzikos, George, additional, Vabalayte, Kristina, additional, Vargas-Osorio, Kelly, additional, Vázquez Rentería, Rafael Sebastián, additional, Velázquez-Fernández, David, additional, Vithana, Sanura Malinda Pallegoda, additional, Yücel, Levent, additional, Yulian, Erwin Danil, additional, Zahradnikova, Petra, additional, Zarogoulidis, Paul, additional, Ziablitskaia, Evgeniia, additional, Zolotoukho, Anna, additional, Calò, Pietro Giorgio, additional, Abdallah, A, additional, Abentroth, AL, additional, Acheimastos, V, additional, Agunaoun, M, additional, Al Bisher, HM, additional, Al Ghuzlan, A, additional, Alakus, H, additional, Alkan, M, additional, Almaraz Almaraz, MC, additional, Amram, K, additional, Anesidis, S, additional, Anestiadou, E, additional, Angelucci, D, additional, Ansaldo, GL, additional, Antonopoulou, MI, additional, Arciniegas, M, additional, Armellin, C, additional, Arredondo Saldaña, G, additional, Astl, J, additional, Athanasakis, E, additional, Avenia, S, additional, Aydın, H, additional, Baba, B, additional, Babala, J, additional, Banús, MV, additional, Barba-Valadez, LA, additional, Barcons, SV, additional, Battafarano, F, additional, Bayat, A, additional, Bella, RMC, additional, Benariba, F, additional, Bernardi, S, additional, Bignami, EG, additional, Bitenc, M, additional, Bitsianis, S, additional, Bolaños de la Torre, JDD, additional, Bonati, E, additional, Bonetti, T, additional, Borges, FA, additional, Bouchagier, K, additional, Boudina, M, additional, Bourial, A, additional, Breuskin, I, additional, Brock, P, additional, Bruns, C, additional, Burlacu, MC, additional, Burton, T, additional, Buta, M, additional, Buzanakov, D, additional, Caliseo, C, additional, Callanan, D, additional, Calu, V, additional, Cameselle-Teijeiro, JM, additional, Camilo-Junior, DJ, additional, Canberk, S, additional, Candalise, V, additional, Candanedo-Gonzalez, F, additional, Carrillo Lizarazo, LJ, additional, Carvalho, GB, additional, Casallas, D, additional, Casolino, C, additional, Castellani, L, additional, Castillo Morales, C, additional, Chambon, G, additional, Chatzipavlidou, V, additional, Chernikov, R, additional, Chorti, A, additional, Chow, TCM, additional, Chrisoulidou, A, additional, Chrysos, E, additional, Conrado-Neto, S, additional, Cordova García, D, additional, Corigliano, A, additional, Crocco, A, additional, Cuesta, A, additional, Čukman, M, additional, Curto, LS, additional, Damilano, RA, additional, D'Anna, R, additional, De, M, additional, De Virgilio, A, additional, Dellaportas, D, additional, Demarquet, L, additional, Devresse, A, additional, Di Meo, G, additional, Diaz Pedrero, R, additional, Dimitrov, D, additional, Dmitry, Z, additional, Domínguez Garijo, P, additional, Dulgeroglu, O, additional, Dural, AC, additional, Eksi, A, additional, El Hammoumi, M, additional, El Kaoui, H, additional, Eleni, G, additional, Elliyanti, A, additional, Ersöz, Ş, additional, Escobar-Jiménez, M, additional, Fedorova, L, additional, Feeley, L, additional, Fernández Rodríguez, E, additional, Ferreli, F, additional, Filoia, A, additional, Fingeret, A, additional, Francescato, A, additional, Gaino, F, additional, Galiandro, F, additional, Gallegos-Hernández, JF, additional, Garas, G, additional, García Lorenzo, F, additional, García-Chávez, JP, additional, Gaudiello, M, additional, Gay, S, additional, Gerasimos, S, additional, Gerek, M, additional, Gervasi, R, additional, Giordano, A, additional, Gjeloshi, B, additional, Gocký, L, additional, Golubinskaya, E, additional, González Romero, S, additional, González-Mínguez, C, additional, Goran, M, additional, Gosman, A, additional, Granados Garcia, M, additional, Greco, E, additional, Grünbart, M, additional, Grützmann, R, additional, Guerlain, J, additional, Guirao, XG, additional, Guzey, D, additional, Hajjij, A, additional, Hamdy, O, additional, Hameed, MS, additional, Hauth, LA, additional, Hernández-Acevedo, JD, additional, Hernandez-Carrillo, JF, additional, Hevilla Sánchez, F, additional, Hoi, H, additional, Hongkwon, K, additional, Hu Zhu, R, additional, Huang, E, additional, Hyeung Kyoo, K, additional, Ignjatovic, V, additional, Ioannidis, A, additional, Iossa, A, additional, Işık, A, additional, James, D, additional, Jung Hoon, L, additional, Kara, H, additional, Karajovic, J, additional, Kartini, D, additional, Khambri, D, additional, Kholová, I, additional, Kisiel, M, additional, Knežević, M, additional, Koh, YQ, additional, Konca, C, additional, Kosmidis, C, additional, Kotsovolis, G, additional, Kowalski, LP, additional, Kralik, R, additional, Kuczma, P, additional, Kuravi, BG, additional, Kurnia, A, additional, Kyriaki, V, additional, Lai, CM, additional, Lallemant, B, additional, Lardhi, AA, additional, Leboulleux, S, additional, Lee, JW, additional, Lelli, G, additional, Leutner, M, additional, Lim, MY, additional, Lim, CM, additional, Llanos, A, additional, Lo, X, additional, Loderer, T, additional, López-Corrales, MA, additional, Ludwig, M, additional, Magnabosco, FF, additional, Maheo, C, additional, Maia, AL, additional, Makay, O, additional, Maksimova, P, additional, Mallick, S, additional, Mallouk, C, additional, Mamani, Z, additional, Mandal, S, additional, Manyalich Blasi, M, additional, Marincola, G, additional, Marulanda, M, additional, Mavromati, M, additional, Mayilvaganan, S, additional, Metso, S, additional, Micalizzi, A, additional, Michalopoulos, A, additional, Min-Su, K, additional, Miron, A, additional, Mishra, AK, additional, Misso, C, additional, Mittermair, C, additional, Morosán Allo, Y, additional, Mourad, M, additional, Moysidis, M, additional, Nabhan, F, additional, Nasiri, R, additional, Nastos, C, additional, Ngiam, KY, additional, Nomine-Criqui, C, additional, Ntziovara, AM, additional, Nuño Vázquez-Garza, JM, additional, Nutautiene, V, additional, Obtulovičová, K, additional, O'Keeffe, L, additional, Okudur, NO, additional, Ossola, P, additional, Ovejero Merino, E, additional, Ozdemir, M, additional, Pangonis, A, additional, Panigoro, SS, additional, Panuzi, A, additional, Papaconstantinou, D, additional, Pardo Matamoros, N, additional, Paschou, S, additional, Pasculli, A, additional, Paterakis, K, additional, Peiris, K, additional, Pennestrì, F, additional, Peppa, M, additional, Perdikaris, P, additional, Perdikaris, I, additional, Pérez-Soto, RH, additional, Piana, S, additional, Piccoli, M, additional, Pietrasanta, D, additional, Placentino, G, additional, Pliakos, I, additional, Polistena, A, additional, Pongtippan, A, additional, Potard, G, additional, Quinn, V, additional, Rahul, P, additional, Ramos, T, additional, Rankin, A, additional, Ratnayake, P, additional, Reuto-Castillo, J, additional, Ridolfo, A, additional, Rios-Valencia, J, additional, Riss, P, additional, Rival, E, additional, Rivillas, J, additional, Roi, D, additional, Rollo, EM, additional, Romanchishen, A, additional, Romito, M, additional, Rotnagl, J, additional, Rovcanin, B, additional, Russo, G, additional, Sabol, M, additional, Saki, S, additional, Saleh, S, additional, Salih, A, additional, Saltiki, A, additional, Salvador-Camarmo, G, additional, Samal, DK, additional, Sánchez-Flores, S, additional, Sapalidis, K, additional, Sarin, D, additional, Sarin, H, additional, Savkovic, N, additional, Scheffel, RS, additional, Scheinpflug, AL, additional, Scheuba, C, additional, Scheyer, N, additional, Schmidt, M, additional, Senashova, O, additional, Serafini, E, additional, Serrano Arévalo, ML, additional, Shank, J, additional, Shindo, ML, additional, Shoshkova, M, additional, Shvan, M, additional, Sičák, M, additional, Silva, TG, additional, Simó Guerrero, O, additional, Skuletic, V, additional, Slijepcevic, N, additional, Slovic, Z, additional, Soares, P, additional, Somova, A, additional, Soto, S, additional, Spiezia, S, additional, Stankovic, V, additional, Stephenson, KJ, additional, Straub, E, additional, Summa, M, additional, Surani, S, additional, Syed, AA, additional, Symeonidis, S, additional, Taciak, A, additional, Tarallo, M, additional, Tarle, A, additional, Tasis, N, additional, Tausanovic, K, additional, Tchabashvili, L, additional, Thierry, M, additional, Tokarczyk, U, additional, Toma, EA, additional, Topuz, S, additional, Torresan, F, additional, Uras, C, additional, Vaccaro, C, additional, Valdés de Anca, Á, additional, Valentini, M, additional, Varaldo, E, additional, Vartanian, JG, additional, Verras, GI, additional, Vithanage, A, additional, Wijayalathge, H, additional, Wiriyaamornchai, P, additional, Wong, YLC, additional, Wongwattana, P, additional, Xenaki, S, additional, Xie, S, additional, Xu, M, additional, Yang, W, additional, Yilmaz, S, additional, Yılmaz, YF, additional, Yotsov, T, additional, Zahid, MT, additional, and Zielke, A, additional

Published
2023
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39. LBA5 A phase II study of neoadjuvant SHR-1701 with or without chemotherapy (chemo) followed by surgery or radiotherapy (RT) in stage III unresectable NSCLC (uNSCLC)

Author

Wu, Y.-L., primary, Zhou, Q., additional, Pan, Y., additional, Yang, X., additional, Zhao, Y., additional, Han, G., additional, Pang, Q., additional, Zhang, Z., additional, Wang, Q., additional, Yao, J., additional, Wang, H., additional, Yang, W., additional, Liu, B., additional, Chen, Q., additional, Du, X., additional, Cai, K., additional, Li, B., additional, Shuang, J., additional, Song, L., additional, and Shi, W., additional

Published
2022
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44. Comparison of an Auto-Segmentation Model Using a Dual-Path Convolutional Neural Network to Intra- and Inter-Operator High-Risk Clinical Target Volumes for Tandem-and-Ovoid Brachytherapy

Author

Vassantachart, A., primary, Cao, Y., additional, Ragab, O.M., additional, Bian, S.X., additional, Mitra, P., additional, Xu, Z., additional, Gallogly, A., additional, Cui, J., additional, Shen, Z.L., additional, Balik, S., additional, Gribble, M., additional, Chang, E.L., additional, Fan, Z., additional, and Yang, W., additional

Published
2022
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45. Alterations of circulating bacterial DNA in colorectal cancer and adenoma: A proof-of-concept study

Author

Xue Wu, Ran Cao, Ao Wang, Xiangxing Kong, Kefeng Ding, Ying Yuan, Wei Lu, Kaihua Liu, Yeting Hu, Qian Xiao, Hua Bao, Xiaonan Wang, Yang W. Shao, and Shu Zheng

Subjects
Adenoma, Adult, DNA, Bacterial, Male, 0301 basic medicine, Cancer Research, medicine.medical_specialty, Colorectal cancer, Colorectal adenoma, Bacterial genome size, Biology, Gut flora, Proof of Concept Study, Gastroenterology, Diagnosis, Differential, Feces, 03 medical and health sciences, 0302 clinical medicine, Predictive Value of Tests, Internal medicine, Biomarkers, Tumor, medicine, Humans, Mass Screening, Early Detection of Cancer, Aged, Aged, 80 and over, Middle Aged, medicine.disease, biology.organism_classification, Healthy Volunteers, Gastrointestinal Microbiome, 030104 developmental biology, ROC Curve, Oncology, Metagenomics, Case-Control Studies, 030220 oncology & carcinogenesis, Female, Colorectal Neoplasms, Cell-Free Nucleic Acids, Bacterial dna
Abstract

The gut microbiota is closely associated with colorectal neoplasia. While most metagenomics studies utilized fecal samples, circulating bacterial DNA in colorectal neoplasia patients remained unexplored. This proof-of-concept study aims to characterize alterations of circulating bacterial DNA in colorectal neoplasia patients. We performed WGS of plasma samples from 25 colorectal cancer (CRC) patients, 10 colorectal adenoma (CRA) patients and 22 healthy controls (HC). Bacterial relative abundance was measured by removing the host genome and mapping reads into bacterial genomes. By diversity analysis, we found plasma samples required less sample size to approach saturation than fecal samples, and species diversity in HC was slightly higher compared with CRC/CRA patients. The majority of circulating bacterial DNA came from bacterial genera which commonly associated with gastrointestine and oral tract. By differential analysis, a total of 127 significant species between CRC patients and HC were identified, on which basis 28 species with top predictive ability were selected and showed promise in preliminary discrimination between CRC/CRA and HC. In CRA patients, relative abundance of the selected 28 species more closely resembled those in CRC patients than HC. By comparing with fecal metagenomics studies, we found there was moderate positive correlation between fold changes of the overlapped fecal and circulating bacterial DNA. Finally, species correlation analysis revealed that CRC and HC displayed distinct patterns of species association. In conclusion, this study demonstrated alterations of circulating bacterial DNA in colorectal neoplasia patients, which had the potential to become non-invasive biomarkers for colorectal neoplasia screening and early diagnosis.

Published
2021
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46. 1744P Camrelizumab plus nab-paclitaxel in platinum-resistant patients with unresectable locally advanced or metastatic urothelial carcinoma: A multicentre, single-arm, phase II study

Author

Li, H., primary, Chen, M., additional, Xue, C., additional, Li, L., additional, Hu, A., additional, Yang, W., additional, Zheng, Z., additional, Ni, M., additional, Zhang, L., additional, Zeng, Y., additional, Peng, J., additional, Yao, K., additional, Zhou, F., additional, Liu, Z., additional, An, X., additional, and Shi, Y., additional

Published
2022
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48. The influence of alcohol, carbonate and polyethers as oxygenated fuels on the soot characteristics from a CI engine

Author

Tan, YR, Zhu, Q, Zong, Y, Lai, J, Salamanca, M, Akroyd, J, Yang, W, Kraft, M, Akroyd, Jethro [0000-0002-2143-8656], and Apollo - University of Cambridge Repository

Subjects
CI engine, Fuel Technology, Soot, General Chemical Engineering, Organic Chemistry, Energy Engineering and Power Technology, Polyoxymethylene dimethyl ether (PODE), Particulate matter, Particle size distribution (PSD)
Published
2023
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49. A metal ion-dependent conformational switch modulates activity of the Plasmodium M17 aminopeptidase.

Author

Webb, CT, Yang, W, Riley, BT, Hayes, BK, Sivaraman, KK, Malcolm, TR, Harrop, S, Atkinson, SC, Kass, I, Buckle, AM, Drinkwater, N, McGowan, S, Webb, CT, Yang, W, Riley, BT, Hayes, BK, Sivaraman, KK, Malcolm, TR, Harrop, S, Atkinson, SC, Kass, I, Buckle, AM, Drinkwater, N, and McGowan, S

Abstract

The metal-dependent M17 aminopeptidases are conserved throughout all kingdoms of life. This large enzyme family is characterized by a conserved binuclear metal center and a distinctive homohexameric arrangement. Recently, we showed that hexamer formation in Plasmodium M17 aminopeptidases was controlled by the metal ion environment, although the functional necessity for hexamer formation is still unclear. To further understand the mechanistic role of the hexameric assembly, here we undertook an investigation of the structure and dynamics of the M17 aminopeptidase from Plasmodium falciparum, PfA-M17. We describe a novel structure of PfA-M17, which shows that the active sites of each trimer are linked by a dynamic loop, and loop movement is coupled with a drastic rearrangement of the binuclear metal center and substrate-binding pocket, rendering the protein inactive. Molecular dynamics simulations and biochemical analyses of PfA-M17 variants demonstrated that this rearrangement is inherent to PfA-M17, and that the transition between the active and inactive states is metal dependent and part of a dynamic regulatory mechanism. Key to the mechanism is a remodeling of the binuclear metal center, which occurs in response to a signal from the neighboring active site and serves to moderate the rate of proteolysis under different environmental conditions. In conclusion, this work identifies a precise mechanism by which oligomerization contributes to PfA-M17 function. Furthermore, it describes a novel role for metal cofactors in the regulation of enzymes, with implications for the wide range of metalloenzymes that operate via a two-metal ion catalytic center, including DNA processing enzymes and metalloproteases.

Published
2022

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