Search

Your search keyword '"Long, Qi"' showing total 2,758 results
Start Over Author "Long, Qi"
2,758 results on '"Long, Qi"'

301. Supplementary Table 9 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

302. Supplementary Figure 3 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

303. Supplementary Figure 2 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

304. Supplementary Figure Legends 1-4 from A Randomized Clinical Trial of the Effects of Supplemental Calcium and Vitamin D3 on Markers of Their Metabolism in Normal Mucosa of Colorectal Adenoma Patients

Author

Ahearn, Thomas U., primary, McCullough, Marjorie L., primary, Flanders, W. Dana, primary, Long, Qi, primary, Sidelnikov, Eduard, primary, Fedirko, Veronika, primary, Daniel, Carrie R., primary, Rutherford, Robin E., primary, Shaukat, Aasma, primary, and Bostick, Roberd M., primary

Published
2023
Full Text
View/download PDF

305. Supplementary Table 2 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

306. Supplementary Table 8 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

307. Supplementary References from A Randomized Clinical Trial of the Effects of Supplemental Calcium and Vitamin D3 on Markers of Their Metabolism in Normal Mucosa of Colorectal Adenoma Patients

Author

Ahearn, Thomas U., primary, McCullough, Marjorie L., primary, Flanders, W. Dana, primary, Long, Qi, primary, Sidelnikov, Eduard, primary, Fedirko, Veronika, primary, Daniel, Carrie R., primary, Rutherford, Robin E., primary, Shaukat, Aasma, primary, and Bostick, Roberd M., primary

Published
2023
Full Text
View/download PDF

308. Supplementary Figure 1 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

309. Supplementary Figures 1-4 from A Randomized Clinical Trial of the Effects of Supplemental Calcium and Vitamin D3 on Markers of Their Metabolism in Normal Mucosa of Colorectal Adenoma Patients

Author

Ahearn, Thomas U., primary, McCullough, Marjorie L., primary, Flanders, W. Dana, primary, Long, Qi, primary, Sidelnikov, Eduard, primary, Fedirko, Veronika, primary, Daniel, Carrie R., primary, Rutherford, Robin E., primary, Shaukat, Aasma, primary, and Bostick, Roberd M., primary

Published
2023
Full Text
View/download PDF

310. Supplementary Table 7 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

311. Supplementary Table 3 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

312. Supplementary Table 5 from Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Author

Long, Qi, primary, Xu, Jianpeng, primary, Osunkoya, Adeboye O., primary, Sannigrahi, Soma, primary, Johnson, Brent A., primary, Zhou, Wei, primary, Gillespie, Theresa, primary, Park, Jong Y., primary, Nam, Robert K., primary, Sugar, Linda, primary, Stanimirovic, Aleksandra, primary, Seth, Arun K., primary, Petros, John A., primary, and Moreno, Carlos S., primary

Published
2023
Full Text
View/download PDF

314. Long-term Effect of Machine Learning–Triggered Behavioral Nudges on Serious Illness Conversations and End-of-Life Outcomes Among Patients With Cancer

Author

Manz, Christopher R., primary, Zhang, Yichen, additional, Chen, Kan, additional, Long, Qi, additional, Small, Dylan S., additional, Evans, Chalanda N., additional, Chivers, Corey, additional, Regli, Susan H., additional, Hanson, C. William, additional, Bekelman, Justin E., additional, Braun, Jennifer, additional, Rareshide, Charles A. L., additional, O’Connor, Nina, additional, Kumar, Pallavi, additional, Schuchter, Lynn M., additional, Shulman, Lawrence N., additional, Patel, Mitesh S., additional, and Parikh, Ravi B., additional

Published
2023
Full Text
View/download PDF

315. Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?

Author

Tan, Amelia L.M., primary, Getzen, Emily J., additional, Hutch, Meghan R., additional, Strasser, Zachary H., additional, Gutiérrez-Sacristán, Alba, additional, Le, Trang T., additional, Dagliati, Arianna, additional, Morris, Michele, additional, Hanauer, David A., additional, Moal, Bertrand, additional, Bonzel, Clara-Lea, additional, Yuan, William, additional, Chiudinelli, Lorenzo, additional, Das, Priam, additional, Zhang, Harrison G., additional, Aronow, Bruce J., additional, Avillach, Paul, additional, Brat, Gabriel.A., additional, Cai, Tianxi, additional, Hong, Chuan, additional, La Cava, William G., additional, Hooi Will Loh, He, additional, Luo, Yuan, additional, Murphy, Shawn N., additional, Yuan Hgiam, Kee, additional, Omenn, Gilbert S., additional, Patel, Lav P., additional, Jebathilagam Samayamuthu, Malarkodi, additional, Shriver, Emily R., additional, Shakeri Hossein Abad, Zahra, additional, Tan, Byorn W.L., additional, Visweswaran, Shyam, additional, Wang, Xuan, additional, Weber, Griffin M., additional, Xia, Zongqi, additional, Verdy, Bertrand, additional, Long, Qi, additional, Mowery, Danielle L., additional, and Holmes, John H., additional

Published
2023
Full Text
View/download PDF

317. MISNN: Multiple Imputation via Semi-parametric Neural Networks

Author

Bu, Zhiqi, Dai, Zongyu, Zhang, Yiliang, Long, Qi, Bu, Zhiqi, Dai, Zongyu, Zhang, Yiliang, and Long, Qi

Abstract

Multiple imputation (MI) has been widely applied to missing value problems in biomedical, social and econometric research, in order to avoid improper inference in the downstream data analysis. In the presence of high-dimensional data, imputation models that include feature selection, especially $\ell_1$ regularized regression (such as Lasso, adaptive Lasso, and Elastic Net), are common choices to prevent the model from underdetermination. However, conducting MI with feature selection is difficult: existing methods are often computationally inefficient and poor in performance. We propose MISNN, a novel and efficient algorithm that incorporates feature selection for MI. Leveraging the approximation power of neural networks, MISNN is a general and flexible framework, compatible with any feature selection method, any neural network architecture, high/low-dimensional data and general missing patterns. Through empirical experiments, MISNN has demonstrated great advantages over state-of-the-art imputation methods (e.g. Bayesian Lasso and matrix completion), in terms of imputation accuracy, statistical consistency and computation speed.

Published
2023

318. Fair Canonical Correlation Analysis

Author

Zhou, Zhuoping, Tarzanagh, Davoud Ataee, Hou, Bojian, Tong, Boning, Xu, Jia, Feng, Yanbo, Long, Qi, Shen, Li, Zhou, Zhuoping, Tarzanagh, Davoud Ataee, Hou, Bojian, Tong, Boning, Xu, Jia, Feng, Yanbo, Long, Qi, and Shen, Li

Abstract

This paper investigates fairness and bias in Canonical Correlation Analysis (CCA), a widely used statistical technique for examining the relationship between two sets of variables. We present a framework that alleviates unfairness by minimizing the correlation disparity error associated with protected attributes. Our approach enables CCA to learn global projection matrices from all data points while ensuring that these matrices yield comparable correlation levels to group-specific projection matrices. Experimental evaluation on both synthetic and real-world datasets demonstrates the efficacy of our method in reducing correlation disparity error without compromising CCA accuracy., Comment: Accepted for publication at NeurIPS 2023, 31 Pages, 14 Figures

Published
2023

319. Fully convolutional network for rice seedling and weed image segmentation at the seedling stage in paddy fields.

Author

Xu Ma, Xiangwu Deng, Long Qi, Yu Jiang, Hongwei Li, Yuwei Wang, and Xupo Xing

Subjects
Medicine, Science
Abstract

To reduce the cost of production and the pollution of the environment that is due to the overapplication of herbicide in paddy fields, the location information of rice seedlings and weeds must be detected in site-specific weed management (SSWM). With the development of deep learning, a semantic segmentation method with the SegNet that is based on fully convolutional network (FCN) was proposed. In this paper, RGB color images of seedling rice were captured in paddy field, and ground truth (GT) images were obtained by manually labeled the pixels in the RGB images with three separate categories, namely, rice seedlings, background, and weeds. The class weight coefficients were calculated to solve the problem of the unbalance of the number of the classification category. GT images and RGB images were used for data training and data testing. Eighty percent of the samples were randomly selected as the training dataset and 20% of samples were used as the test dataset. The proposed method was compared with a classical semantic segmentation model, namely, FCN, and U-Net models. The average accuracy rate of the SegNet method was 92.7%, whereas the average accuracy rates of the FCN and U-Net methods were 89.5% and 70.8%, respectively. The proposed SegNet method realized higher classification accuracy and could effectively classify the pixels of rice seedlings, background, and weeds in the paddy field images and acquire the positions of their regions.

Published
2019
Full Text
View/download PDF

320. Analysis of truck-related crashes of freeways in China

Author

Ting Xu, Rui-sen Jiang, Lei Zhao, Long Qi, and Yu Zhang

Subjects
Mechanical engineering and machinery, TJ1-1570
Abstract

Truck-related crashes result in tremendous lives and property loss and become a serious safety issue in China. The goal of this article is to identify the influential factors for severity of truck-related crashes using data from Jingjintang freeways in China and to design an ordered probit model to explore their relationship. Records including crashes, traffic flow attributes, and geometric design features ranging from 2009 to 2012 were collected from Jingjintang freeway. Crashes are divided into three severity levels: slight injury, injury, and fatal injury. The injury crashes is ranking the first place occupying 64.37%. Truck-related crashes are likely to occur when truck percentage is around 20% and 80%. The speed of traffic flow decreases with the more appearance of trucks. The ordered probit model is developed to estimate the impacts of influential factors on injury severity of truck-related crashes. Marginal effects for each level of injury severity are calculated. The results reveal that truck-involving crashes are highly sensitive to factors such as time of day, truck percentage, average slope, operating speed, speed difference, and exposure variable. The average slope of road segment and speed gaps has the greatest impact on all severity levels of crashes.

Published
2019
Full Text
View/download PDF

326. Efficacy and safety of PD-1/PD-L1 inhibitor combined with chemotherapy versus chemotherapy alone in the treatment of advanced gastric or gastroesophageal junction adenocarcinoma: a systematic review and meta-analysis

Author

Bo-Wei Liu, Qi-Xing Shang, Yu-Shang Yang, and Long-Qi Chen

Subjects
Cancer Research, Oncology
Abstract

BackgroundThere is increasing evidence that immunotherapy (programmed cell death-1 (PD-1) inhibitor) combined with chemotherapy is superior to chemotherapy alone in neoadjuvant therapy for patients with previously untreated, unresectable advanced, or metastatic esophageal adenocarcinoma (EAC)/gastric/gastroesophageal junction adenocarcinoma (GEA). However, the results of recent studies have been contradictory. Therefore, the aim of this article is to evaluate the efficacy and safety of PD-1 inhibitors combined with chemotherapy in neoadjuvant therapy through meta-analysis.MethodWe comprehensively reviewed the literature and clinical randomized controlled trials (RCTs) by February 2022 by searching Medical Subject Headings (MeSH) and keywords such as “esophageal adenocarcinoma” or “immunotherapy” in several databases, including the Embase, Cochrane, PubMed, and ClinicalTrials.gov websites. Two authors independently selected studies, extracted data, and assessed the risk of bias and quality of evidence by using standardized Cochrane Methods procedures. The primary outcomes were 1-year overall survival (OS) and 1-year progression-free survival (PFS), estimated by calculating the 95% confidence interval (CI) for the combined odds ratio (OR) and hazard ratio (HR). Secondary outcomes estimated using OR were disease objective response rate (DORR) and incidence of adverse events.ResultsFour RCTs with a total of 3,013 patients researching the efficacy of immunotherapy plus chemotherapy versus chemotherapy alone on gastrointestinal cancer were included in this meta-analysis. The results showed that immune checkpoint inhibitor plus chemotherapy treatment was associated with an increased risk of PFS (HR = 0.76 [95% CI: 0.70–0.83]; p < 0.001), OS (HR = 0.81 [95% CI: 0.74–0.89]; p < 0.001), and DORR (relative ratio (RR) = 1.31 [95% CI: 1.19–1.44]; p < 0.0001) when compared with chemotherapy alone in advanced, unresectable, and metastatic EAC/GEA. However, immunotherapy combined with chemotherapy increased the incidence of adverse reactions such as alanine aminotransferase elevation (OR = 1.55 [95% CI: 1.17–2.07]; p = 0.003) and palmar-plantar erythrodysesthesia (PPE) syndrome (OR = 1.30 [95% CI: 1.05–1.63]; p = 0.02). Nausea (OR = 1.24 [95% CI: 1.07–1.44]; p = 0.005) and white blood cell count decreased (OR = 1.40 [95% CI: 1.13–1.73]; p = 0.002), and so on. Fortunately, toxicities were within acceptable limits. Meanwhile, for patients with a combined positive score (CPS) ≥1, compared with chemotherapy alone, immunotherapy combined with chemotherapy had a better overall survival rate (HR = 0.81 [95% CI: 0.73–0.90]; p = 0.0001).ConclusionOur study shows that immunotherapy plus chemotherapy has an obvious benefit for patients with previously untreated, unresectable advanced, or metastatic EAC/GEA when compared with chemotherapy alone. However, a high risk of adverse reactions may occur during immunotherapy plus chemotherapy, and more studies focusing on the treatment strategies of untreated, unresectable advanced, or metastatic EAC/GEA are warranted.Systematic review registrationwww.crd.york.ac.uk, identifier CRD42022319434.

Published
2023
Full Text
View/download PDF

330. Automated Counting Grains on the Rice Panicle Based on Deep Learning Method

Author

Ruoling Deng, Ming Tao, Xunan Huang, Kemoh Bangura, Qian Jiang, Yu Jiang, and Long Qi

Subjects
grain detection, primary branch, convolutional neural network, image, rice, Chemical technology, TP1-1185
Abstract

Grain number per rice panicle, which directly determines grain yield, is an important agronomic trait for rice breeding and yield-related research. However, manually counting grains of rice per panicle is time-consuming, laborious, and error-prone. In this research, a grain detection model was proposed to automatically recognize and count grains on primary branches of a rice panicle. The model used image analysis based on deep learning convolutional neural network (CNN), by integrating the feature pyramid network (FPN) into the faster R-CNN network. The performance of the grain detection model was compared to that of the original faster R-CNN model and the SSD model, and it was found that the grain detection model was more reliable and accurate. The accuracy of the grain detection model was not affected by the lighting condition in which images of rice primary branches were taken. The model worked well for all rice branches with various numbers of grains. Through applying the grain detection model to images of fresh and dry branches, it was found that the model performance was not affected by the grain moisture conditions. The overall accuracy of the grain detection model was 99.4%. Results demonstrated that the model was accurate, reliable, and suitable for detecting grains of rice panicles with various conditions.

Published
2021
Full Text
View/download PDF

336. Size measurement and filled/unfilled detection of rice grains using backlight image processing.

Author

Xiao Feng, Zhiqi Wang, Zhiwei Zeng, Yuhao Zhou, Yunting Lan, Wei Zou, Hao Gong, and Long Qi

Subjects
IMAGE processing, PLANT breeding, MEASUREMENT errors, RICE, RICE breeding, PHYSICAL measurements, GRAIN
Abstract

Measurements of rice physical traits, such as length, width, and percentage of filled/unfilled grains, are essential steps of rice breeding. A new approach for measuring the physical traits of rice grains for breeding purposes was presented in this study, utilizing image processing techniques. Backlight photography was used to capture a grayscale image of a group of rice grains, which was then analyzed using a clustering algorithm to differentiate between filled and unfilled grains based on their grayscale values. The impact of backlight intensity on the accuracy of the method was also investigated. The results show that the proposed method has excellent accuracy and high efficiency. The mean absolute percentage error of the method was 0.24% and 1.36% in calculating the total number of grain particles and distinguishing the number of filled grains, respectively. The grain size was also measured with a little margin of error. The mean absolute percentage error of grain length measurement was 1.11%, while the measurement error of grain width was 4.03%. The method was found to be highly accurate, non-destructive, and costeffective when compared to conventional methods, making it a promising approach for characterizing physical traits for crop breeding. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

337. NIR-II fluorescence and PA imaging guided activation of STING pathway in photothermal therapy for boosting cancer immunotherapy by theranostic thermosensitive liposomes.

Author

Long, Qi, Yang, Yuliang, Liao, Fangling, Chen, Haoting, He, Dongyue, Li, Shengliang, Li, Pengcheng, Guo, Weisheng, and Xiao, Yafang

Abstract

Photothermal immunotherapy has shown great potential for efficient cancer treatment. However, the immunosuppressive tumor microenvironment forms a heavy barrier for photothermal-induced anti-tumor immunity by inhibiting dendritic cell (DC) maturation and cytotoxic T cell response. Moreover, the lack of reliable spatiotemporal imaging modalities makes photothermal immunotherapy difficult to guide tumor ablation and monitor therapeutic outcomes in real time. Herein, we designed a theranostic thermosensitive liposome (PLDD) as a versatile nanoplatform to boost the adaptive anti-tumor immunity of photothermal immunotherapy and to achieve multiple bioimaging modalities in a real-time manner. PLDD contains two major functional components: a multifunctional photothermal agent (DTTB) and an immune potentiator STING pathway agonist (DMXAA). Upon irradiation, the heat generated by DTTB induced the immunogenic cell death (ICD) of the tumor and dissociated the structure of thermosensitive liposome to release DMXAA, which ultimately activated the STING pathway and promoted the ICD-induced immune response by increasing DC cell maturation and T cell recruitment. Moreover, the DTTB in PLDD displayed excellent second near-infrared (NIR-II) fluorescence and photoacoustic (PA) dual-modal imaging, which provided omnibearing information on the tumor and guided the subsequent therapeutic operation. Therefore, this versatile PLDD with light-triggered promotion of anti-tumor immunity and multiple spatiotemporal imaging profiles holds great potential for the future development of cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

338. CEDAR: communication efficient distributed analysis for regressions.

Author

Chang, Changgee, Bu, Zhiqi, and Long, Qi

Subjects
REGRESSION analysis, ELECTRONIC health records, LEAKS (Disclosure of information), MISSING data (Statistics), CEDAR
Abstract

Electronic health records (EHRs) offer great promises for advancing precision medicine and, at the same time, present significant analytical challenges. Particularly, it is often the case that patient‐level data in EHRs cannot be shared across institutions (data sources) due to government regulations and/or institutional policies. As a result, there are growing interests about distributed learning over multiple EHRs databases without sharing patient‐level data. To tackle such challenges, we propose a novel communication efficient method that aggregates the optimal estimates of external sites, by turning the problem into a missing data problem. In addition, we propose incorporating posterior samples of remote sites, which can provide partial information on the missing quantities and improve efficiency of parameter estimates while having the differential privacy property and thus reducing the risk of information leaking. The proposed approach, without sharing the raw patient level data, allows for proper statistical inference. We provide theoretical investigation for the asymptotic properties of the proposed method for statistical inference as well as differential privacy, and evaluate its performance in simulations and real data analyses in comparison with several recently developed methods. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

340. A deep learning approach reveals unexplored landscape of viral expression in cancer

Author

Elbasir, Abdurrahman, primary, Ye, Ying, additional, Schäffer, Daniel E., additional, Hao, Xue, additional, Wickramasinghe, Jayamanna, additional, Tsingas, Konstantinos, additional, Lieberman, Paul M., additional, Long, Qi, additional, Morris, Quaid, additional, Zhang, Rugang, additional, Schäffer, Alejandro A., additional, and Auslander, Noam, additional

Published
2023
Full Text
View/download PDF

341. The compact Casπ (Cas12l) ‘bracelet’ provides a unique structural platform for DNA manipulation

Author

Sun, Ao, primary, Li, Cheng-Ping, additional, Chen, Zhihang, additional, Zhang, Shouyue, additional, Li, Dan-Yuan, additional, Yang, Yun, additional, Li, Long-Qi, additional, Zhao, Yuqian, additional, Wang, Kaichen, additional, Li, Zhaofu, additional, Liu, Jinxia, additional, Liu, Sitong, additional, Wang, Jia, additional, and Liu, Jun-Jie Gogo, additional

Published
2023
Full Text
View/download PDF

343. Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: an international multi-centre observational cohort study

Author

Tan, Byorn W.L., primary, Tan, Bryce W.Q., additional, Tan, Amelia L.M., additional, Schriver, Emily R., additional, Gutiérrez-Sacristán, Alba, additional, Das, Priyam, additional, Yuan, William, additional, Hutch, Meghan R., additional, García Barrio, Noelia, additional, Pedrera Jimenez, Miguel, additional, Abu-el-rub, Noor, additional, Morris, Michele, additional, Moal, Bertrand, additional, Verdy, Guillaume, additional, Cho, Kelly, additional, Ho, Yuk-Lam, additional, Patel, Lav P., additional, Dagliati, Arianna, additional, Neuraz, Antoine, additional, Klann, Jeffrey G., additional, South, Andrew M., additional, Visweswaran, Shyam, additional, Hanauer, David A., additional, Maidlow, Sarah E., additional, Liu, Mei, additional, Mowery, Danielle L., additional, Batugo, Ashley, additional, Makoudjou, Adeline, additional, Tippmann, Patric, additional, Zöller, Daniela, additional, Brat, Gabriel A., additional, Luo, Yuan, additional, Avillach, Paul, additional, Bellazzi, Riccardo, additional, Chiovato, Luca, additional, Malovini, Alberto, additional, Tibollo, Valentina, additional, Samayamuthu, Malarkodi Jebathilagam, additional, Serrano Balazote, Pablo, additional, Xia, Zongqi, additional, Loh, Ne Hooi Will, additional, Chiudinelli, Lorenzo, additional, Bonzel, Clara-Lea, additional, Hong, Chuan, additional, Zhang, Harrison G., additional, Weber, Griffin M., additional, Kohane, Isaac S., additional, Cai, Tianxi, additional, Omenn, Gilbert S., additional, Holmes, John H., additional, Ngiam, Kee Yuan, additional, Aaron, James R., additional, Agapito, Giuseppe, additional, Albayrak, Adem, additional, Albi, Giuseppe, additional, Alessiani, Mario, additional, Alloni, Anna, additional, Amendola, Danilo F., additional, Angoulvant, François, additional, Anthony, Li L.L.J., additional, Aronow, Bruce J., additional, Ashraf, Fatima, additional, Atz, Andrew, additional, Panickan, Vidul Ayakulangara, additional, Azevedo, Paula S., additional, Balshi, James, additional, Beaulieu-Jones, Brett K., additional, Beaulieu-Jones, Brendin R., additional, Bell, Douglas S., additional, Bellasi, Antonio, additional, Benoit, Vincent, additional, Beraghi, Michele, additional, Bernal-Sobrino, José Luis, additional, Bernaux, Mélodie, additional, Bey, Romain, additional, Bhatnagar, Surbhi, additional, Blanco-Martínez, Alvar, additional, Boeker, Martin, additional, Booth, John, additional, Bosari, Silvano, additional, Bourgeois, Florence T., additional, Bradford, Robert L., additional, Bréant, Stéphane, additional, Brown, Nicholas W., additional, Bruno, Raffaele, additional, Bryant, William A., additional, Bucalo, Mauro, additional, Bucholz, Emily, additional, Burgun, Anita, additional, Cannataro, Mario, additional, Carmona, Aldo, additional, Cattelan, Anna Maria, additional, Caucheteux, Charlotte, additional, Champ, Julien, additional, Chen, Jin, additional, Chen, Krista Y., additional, Cimino, James J., additional, Colicchio, Tiago K., additional, Cormont, Sylvie, additional, Cossin, Sébastien, additional, Craig, Jean B., additional, Cruz-Bermúdez, Juan Luis, additional, Cruz-Rojo, Jaime, additional, Daniar, Mohamad, additional, Daniel, Christel, additional, Devkota, Batsal, additional, Dionne, Audrey, additional, Duan, Rui, additional, Dubiel, Julien, additional, DuVall, Scott L., additional, Esteve, Loic, additional, Estiri, Hossein, additional, Fan, Shirley, additional, Follett, Robert W., additional, Ganslandt, Thomas, additional, García-Barrio, Noelia, additional, Garmire, Lana X., additional, Gehlenborg, Nils, additional, Getzen, Emily J., additional, Geva, Alon, additional, González, Tomás González, additional, Gradinger, Tobias, additional, Gramfort, Alexandre, additional, Griffier, Romain, additional, Griffon, Nicolas, additional, Grisel, Olivier, additional, Guzzi, Pietro H., additional, Han, Larry, additional, Haverkamp, Christian, additional, Hazard, Derek Y., additional, He, Bing, additional, Henderson, Darren W., additional, Hilka, Martin, additional, Honerlaw, Jacqueline P., additional, Huling, Kenneth M., additional, Issitt, Richard W., additional, Jannot, Anne Sophie, additional, Jouhet, Vianney, additional, Kavuluru, Ramakanth, additional, Keller, Mark S., additional, Kennedy, Chris J., additional, Kernan, Kate F., additional, Key, Daniel A., additional, Kirchoff, Katie, additional, Krantz, Ian D., additional, Kraska, Detlef, additional, Krishnamurthy, Ashok K., additional, L'Yi, Sehi, additional, Le, Trang T., additional, Leblanc, Judith, additional, Lemaitre, Guillaume, additional, Lenert, Leslie, additional, Leprovost, Damien, additional, Liu, Molei, additional, Will Loh, Ne Hooi, additional, Long, Qi, additional, Lozano-Zahonero, Sara, additional, Lynch, Kristine E., additional, Mahmood, Sadiqa, additional, Makwana, Simran, additional, Mandl, Kenneth D., additional, Mao, Chengsheng, additional, Maram, Anupama, additional, Maripuri, Monika, additional, Martel, Patricia, additional, Martins, Marcelo R., additional, Marwaha, Jayson S., additional, Masino, Aaron J., additional, Mazzitelli, Maria, additional, Mazzotti, Diego R., additional, Mensch, Arthur, additional, Milano, Marianna, additional, Minicucci, Marcos F., additional, Ahooyi, Taha Mohseni, additional, Moore, Jason H., additional, Moraleda, Cinta, additional, Morris, Jeffrey S., additional, Moshal, Karyn L., additional, Mousavi, Sajad, additional, Murad, Douglas A., additional, Murphy, Shawn N., additional, Naughton, Thomas P., additional, Breda Neto, Carlos Tadeu, additional, Newburger, Jane, additional, Njoroge, Wanjiku F.M., additional, Norman, James B., additional, Obeid, Jihad, additional, Okoshi, Marina P., additional, Olson, Karen L., additional, Orlova, Nina, additional, Ostasiewski, Brian D., additional, Palmer, Nathan P., additional, Paris, Nicolas, additional, Pedrera-Jiménez, Miguel, additional, Pfaff, Ashley C., additional, Pfaff, Emily R., additional, Pillion, Danielle, additional, Pizzimenti, Sara, additional, Priya, Tanu, additional, Prokosch, Hans U., additional, Prudente, Robson A., additional, Prunotto, Andrea, additional, Quirós-González, Víctor, additional, Ramoni, Rachel B., additional, Raskin, Maryna, additional, Rieg, Siegbert, additional, Roig-Domínguez, Gustavo, additional, Rojo, Pablo, additional, Rubio-Mayo, Paula, additional, Sacchi, Paolo, additional, Sáez, Carlos, additional, Salamanca, Elisa, additional, Sanchez-Pinto, L. Nelson, additional, Sandrin, Arnaud, additional, Santhanam, Nandhini, additional, Santos, Janaina C.C., additional, Sanz Vidorreta, Fernando J., additional, Savino, Maria, additional, Schubert, Petra, additional, Schuettler, Juergen, additional, Scudeller, Luigia, additional, Sebire, Neil J., additional, Serrano-Balazote, Pablo, additional, Serre, Patricia, additional, Serret-Larmande, Arnaud, additional, Shah, Mohsin, additional, Hossein Abad, Zahra Shakeri, additional, Silvio, Domenick, additional, Sliz, Piotr, additional, Son, Jiyeon, additional, Sonday, Charles, additional, Sperotto, Francesca, additional, Spiridou, Anastasia, additional, Strasser, Zachary H., additional, Tan, Byorn W.L., additional, Tanni, Suzana E., additional, Taylor, Deanne M., additional, Terriza-Torres, Ana I., additional, Toh, Emma M.S., additional, Torti, Carlo, additional, Trecarichi, Enrico M., additional, Vallejos, Andrew K., additional, Varoquaux, Gael, additional, Vella, Margaret E., additional, Vie, Jill-Jênn, additional, Vitacca, Michele, additional, Wagholikar, Kavishwar B., additional, Waitman, Lemuel R., additional, Wang, Xuan, additional, Wassermann, Demian, additional, Wolkewitz, Martin, additional, Wong, Scott, additional, Xiong, Xin, additional, Ye, Ye, additional, Yehya, Nadir, additional, Zachariasse, Joany M., additional, Zahner, Janet J., additional, Zambelli, Alberto, additional, Zuccaro, Valentina, additional, and Zucco, Chiara, additional

Published
2023
Full Text
View/download PDF

348. Towards a primate single-cell atlas

Author

Xiao, Zhang, Guang-Yao, Lai, Giacomo, Volpe, Lei, Han, Patrick H, Maxwell, Long-Qi, Liu, Miguel A, Esteban, and Yi-Wei, Lai

Subjects
Primates, Ecology, Animals, Brain, Animal Science and Zoology, Ecology, Evolution, Behavior and Systematics
Published
2022

349. Rxn Rover: automation of chemical reactions with user-friendly, modular software

Author

Kevin Basemann, Theresa L. Windus, Zachery Crandall, and Long Qi

Subjects
Fluid Flow and Transfer Processes, User Friendly, Chemistry (miscellaneous), business.industry, Computer science, Process Chemistry and Technology, Chemical Engineering (miscellaneous), business, Software engineering, Automation, Modular software, Catalysis
Abstract

Automation of chemical reactions through tools such as Rxn Rover in research and development is an enabling technology to reduce cost and waste management in technology transformations towards renewable feedstocks and energy in the chemical industry.

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results