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5. Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department

Author

Ram-Mohan, Nikhil, Rogers, Angela J, Blish, Catherine A, Nadeau, Kari C, Zudock, Elizabeth J, Kim, David, Quinn, James V, Sun, Lixian, Liesenfeld, Oliver, Group, The Stanford COVID-19 Biobank Study, Yang, Samuel, follows:, The additional author members of the Stanford COVID-19 Biobank Study Group are as, Hashemi, Marjan M, Tjandra, Kristel C, Newberry, Jennifer A, Blomkalns, Andra L, O’Hara, Ruth, Ashley, Euan, Mann, Rosen, Visweswaran, Anita, Ranganath, Thanmayi, Roque, Jonasel, Manohar, Monali, Din, Hena Naz, Kumar, Komal, Jee, Kathryn, Noon, Brigit, Anderson, Jill, Fay, Bethany, Schreiber, Donald, Zhao, Nancy, Vergara, Rosemary, McKechnie, Julia, Wilk, Aaron, de la Parte, Lauren, Dantzler, Kathleen Whittle, Ty, Maureen, Kathale, Nimish, Rustagi, Arjun, Martinez-Colon, Giovanny, Ivison, Geoff, Pi, Ruoxi, Lee, Maddie, Brewer, Rachel, Hollis, Taylor, Baird, Andrea, Ugur, Michele, Bogusch, Drina, Nahass, Georgie, Haider, Kazim, Tran, Kim Quyen Thi, Simpson, Laura, Tal, Michal, Chang, Iris, Do, Evan, Fernandes, Andrea, Lee, Allie, Ahuja, Neera, Snow, Theo, and Krempski, James

Subjects
Microbiology, Biological Sciences, Lung, Emerging Infectious Diseases, Vaccine Related, Infectious Diseases, Clinical Research, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, 4.1 Discovery and preclinical testing of markers and technologies, Infection, Good Health and Well Being, Humans, Female, Middle Aged, Male, COVID-19, SARS-CoV-2, Coinfection, RNA, Messenger, Bacteria, Bacterial Infections, Stanford COVID-19 Biobank Study Group, bacterial superinfection, coinfection, diagnosis, emergency department, host response classifier, mortality prediction, prognosis
Abstract

Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial coinfection, and determining illness severity since current practices require separate workflows. Here, we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and bacterial coinfections and predicting clinical severity of COVID-19. A total of 161 patients with PCR-confirmed COVID-19 (52.2% female; median age, 50.0 years; 51% hospitalized; 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene blood RNA), and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrollment, and the remaining patients oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial coinfection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e., Clostridioides difficile colitis (n = 1), urinary tract infection (n = 1), and clinically diagnosed bacterial infections (n = 3), for a specificity of 99.4%. Two of 101 (2.8%) patients in the IMX-SEV-3 "Low" severity classification and 7/60 (11.7%) in the "Moderate" severity classification died within 30 days of enrollment. IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19 and bacterial coinfections and predicted patients' risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management, including more accurate treatment decisions and optimized resource utilization. IMPORTANCE We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection. This will negate the need for empirical use of broad-spectrum antibiotics and allow for antibiotic use stewardship. Additionally, accurate classification of the severity of infection and the prediction of 30-day severe outcomes will allow for appropriate allocation of hospital resources.

Published
2022

21. Self-repairing high entropy oxides

Author

Liu, Zongwen, Huang, Pengru, Sun, Lixian, Liu, Yanping, Qu, Jiangtao, Cairney, Julie, Zheng, Zhong, Wang, Zhiming M., Khan, Naveed A., Lai, Zhiping, Fu, Li, Teng, Bing, Zhou, Cuifeng, Zhao, Hong, Xu, Fen, Xiong, Pan, Zhu, Junwu, Yuan, Peng, Tsoutas, Kosta, Akhavan, Behnam, Bilek, Marcela M., Ringer, Simon P., and Novoselov, Kostya S.

Subjects
Condensed Matter - Materials Science
Abstract

All biological organisms, from plants to living creatures, can heal minor wounds and damage. The realization of a similar self-healing capacity in inorganic materials has been a design target for many decades. This would represent a breakthrough in materials engineering, enabling many novel technological applications, since such materials would be able to resist damage caused by electromagnetic irradiation and/or mechanical impact. Here we demonstrate that a high-entropy oxide is intrinsically capable of undergoing an autonomous self-repairing process. Transmission electron microscopy revealed that the spinel structure of (AlCoCrCu0.5FeNi)3O4 can regrow and repair itself at the atomic level when damaged. Density functional theory calculations reveal that the extra enthalpy stored in the high entropy material during fabrication can be released to effectively heal macroscopic defects by regrowing into a partially ordered state. This extraordinary self-repairing phenomenon makes this new material highly desirable as a coating, enabling structures used in harsh environments to better withstand damage, such as cosmic irradiation in space, nuclear irradiation in nuclear power facilities, or tribological damage. Most importantly, our results set the general design principles for the synthesis of self-repairing materials., Comment: 12 pages,4 figures

Published
2021

42. Risk factors of paclitaxel-induced peripheral neuropathy in patients with breast cancer: a prospective cohort study

Author

Sun Lixian, Yu Xiaoqian, Guo Luyan, Zhou Lizhi, Du Rui, Yao Hongyue, Zhao Caijie, and Yuan Fenghui

Subjects
paclitaxel, peripheral neuropathy, breast cancer, chemotherapy, risk factor, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

ObjectiveChemotherapy-induced peripheral neuropathy (CIPN) is a common and severe adverse reaction in taxane-based chemotherapy. This study aimed to analyze the risk factors of peripheral neuropathy in patients with breast cancer receiving paclitaxel chemotherapy to provide a reference for the early prevention of CIPN.MethodsWe included 350 patients with breast cancer who received chemotherapy for the first time at the Tangshan People’s Hospital between August 2022 and June 2023 and were followed for at least 3 months after the end of chemotherapy. The incidence of CIPN in patients with breast cancer was calculated, and risk factors for CIPN were analyzed using logistic regression analysis.ResultsThe incidence rate of CIPN was 79.1%. Multifactor logistic regression analysis indicated that age ≥45 years [odds ratio (OR)=5.119, 95% confidence interval (CI)=1.395–18.780] and ≥60 years (OR=9.366, 95% CI=1.228–71.421), history of hypertension (OR=3.475, 95% CI=1.073–11.250), cumulative dose of chemotherapy drugs >900 mg (OR=4.842, 95% CI=1.961–5.946), vitamin D deficiency (OR=6.214, 95% CI=2.308–16.729), abnormal alanine aminotransferase (OR=3.154, 95% CI=1.010–9.844), anemia before chemotherapy (OR=2.770, 95% CI=1.093–7.019), infusion duration of chemotherapy drugs >30 min (OR=3.673, 95% CI=1.414–9.539), body mass index ≥24 kg/m2 (OR=8.139, 95% CI=1.157–57.240), mild depression (OR=4.546, 95% CI=1.358–15.223), and major depression (OR=4.455, 95% CI=1.237–16.037) increased the risk of CIPN. Having a regular caregiver (OR=0.223, 95% CI=0.087–0.573), high levels of physical activity (OR=0.071, 95% CI=0.008–0.647), and strong social support (OR=0.048, 95% CI=0.003–0.682) were protective factors against CIPN.ConclusionClinical attention should be paid to patients with these risk factors, and active and effective preventive measures should be taken to reduce the occurrence of CIPN and improve the quality of life.

Published
2024
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