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5. Recyclable high-strength polybutadiene-based rubber with self-healing and shape memory properties via dynamic boronic ester and Diels-Alder chemistry

Author

Shengao Yang, Yan Wang, Fang Wang, Kaiyi Zhang, Xinxin Lv, Hao Teng, Rui Zheng, Faliang Luo, and Qian Xing

Subjects
crosslinking, rubber, self-healing, shape memory polymer, recycling, Materials of engineering and construction. Mechanics of materials, TA401-492, Chemical technology, TP1-1185
Abstract

Dynamic cross-linked networks (DCNs) endow thermoset rubber with self-healability and recyclability to extend its lifetime and alleviate environmental pollution. However, the contradiction between high self-healing and mechanical properties in DCNs rubber is always difficult to be resolved. Herein, we used boronic ester (BO) and Diels-Alder dynamic covalent bonds (DA) to synthesize polybutadiene-based dual networks rubber (PB-BO-DA) via thiol-ene reaction. This approach achieved a tensile strength of 16.46 MPa and 99% self-healing efficiency, facilitated by extensive intermolecular interactions (π-π packing and N-B coordination) and fully dynamic cross-linking. In addition, multiple dynamic cross-linked networks (MDCNs) polybutadiene-based rubber also show excellent shape memory ability and recyclability. This strategy might open a helpful pathway to fabricate intelligent multifunctional polymers with high strength and high self-healing efficiency.

Published
2025
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6. Preoperative CT-based morphological heterogeneity for predicting survival in patients with colorectal cancer liver metastases after surgical resection: a retrospective study

Author

Qian Xing, Yong Cui, Ming Liu, Xiao-Lei Gu, Xiao-Ting Li, Bao-Cai Xing, and Ying-Shi Sun

Subjects
Colorectal cancer, Liver metastases, Heterogeneity, Prognosis, CT, Medical technology, R855-855.5
Abstract

Abstract Objective To explore the value of preoperative CT-based morphological heterogeneity (MH) for predicting local tumor disease-free survival (LTDFS) and progression-free survival (PFS) in patients with colorectal cancer liver metastases (CRLM). Methods The latest CT data of 102 CRLM patients were retrospectively analyzed. The morphological score of each liver metastasis was obtained, and the morphological heterogeneity difference (MHD) was calculated. The receiver operating characteristic (ROC) curve was drawn, and the cutoff value was found. The Kaplan-Meier method was used to draw survival curves of patients with or without MH. The Cox regression analysis was used to build the model with MH and clinical characteristics for predicting PFS. Results In 78 patients without MH, median PFS was 9.0 months (95% CI:6.5–11.5), while in 24 patients with MH, median PFS was 6.0 months (95% CI:4.0-8.1), indicating that MH significantly affected PFS (p = 0.001). MH affected PFS in both the chemotherapy group and the chemotherapy combined with targeted therapy group (p = 0.005, p = 0.043). MH, preoperative carcinoembryonic antigen (CEA) and chemotherapy after surgery were independent predictors for postoperative PFS in patients with CRLM. Conclusion Preoperative CT-based MH had good efficacy for predicting LTDFS and PFS of CRLM patients after surgical resection, regardless of preoperative treatment. MH is one of the independent predictors of PFS.

Published
2024
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7. HateModerate: Testing Hate Speech Detectors against Content Moderation Policies

Author

Zheng, Jiangrui, Liu, Xueqing, Yang, Guanqun, Haque, Mirazul, Qian, Xing, Rathnasuriya, Ravishka, Yang, Wei, and Budhrani, Girish

Subjects
Computer Science - Software Engineering, Computer Science - Computation and Language
Abstract

To protect users from massive hateful content, existing works studied automated hate speech detection. Despite the existing efforts, one question remains: do automated hate speech detectors conform to social media content policies? A platform's content policies are a checklist of content moderated by the social media platform. Because content moderation rules are often uniquely defined, existing hate speech datasets cannot directly answer this question. This work seeks to answer this question by creating HateModerate, a dataset for testing the behaviors of automated content moderators against content policies. First, we engage 28 annotators and GPT in a six-step annotation process, resulting in a list of hateful and non-hateful test suites matching each of Facebook's 41 hate speech policies. Second, we test the performance of state-of-the-art hate speech detectors against HateModerate, revealing substantial failures these models have in their conformity to the policies. Third, using HateModerate, we augment the training data of a top-downloaded hate detector on HuggingFace. We observe significant improvement in the models' conformity to content policies while having comparable scores on the original test data. Our dataset and code can be found in the attachment., Comment: NAACL 2024 Finding

Published
2023

8. Drivers of innovation value: simulation for new drug pricing evaluation based on system dynamics modelling

Author

Qian Xing, Wendi Cheng, Wei Wang, Chunlin Jin, and Haiyin Wang

Subjects
system dynamics, drug prices, innovation premium, value-based pricing, pricing evaluation, Therapeutics. Pharmacology, RM1-950
Abstract

ObjectivesPaying for the innovative value of drugs is an important means of mitigating healthcare system duplication and enhancing patient health. Assessing and exploiting the factors influencing innovation premium to forecast trends and shortcomings within the pharmaceutical innovation ecosystem.MethodsUtilizing system dynamics, this research constructs a decision evaluation system for new drug pricing in Japan. It integrates various decision-making factors across dimensions such as value premium, marketability premium, pediatric premium, and SAKIGAKE premium, employing Vensim PLE software for simulation purposes.ResultsUnder the current policy framework, pharmaceutical innovation is on the rise, with significant policy effects observable after 5 years. The most substantial growth in value occurs in medications for rare diseases and niche markets, with effects varying in the short to medium term and stabilizing over the long term. Sensitivity analysis highlights that factors like combination therapies, faster mechanisms of action, and novel therapeutic parts notably influence the value dimension. Other significant factors include obtaining national certifications, addressing indications lacking standard treatments, and demonstrating superior efficacy. The study also identifies underexploited opportunities related to the use of evidence in pricing decisions.ConclusionClinical outcomes are pivotal in shaping drug pricing, influencing both patient and healthcare provider preferences, and thereby affecting market uptake and competitive dynamics. Regulatory frameworks that prioritize unmet medical needs or superior drug efficacy are essential. Future enhancements to the model should incorporate more real-world evidence and expand regulatory considerations to better reflect the dynamic nature of the healthcare sector and support equitable, outcome-based drug pricing.

Published
2025
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21. The relation between FT3 and long-term fatigue in patients with COVID-19

Author

Shuo Dong, FanRui Ding, Yuan Wang, Shuo Liu, Ran Bai, YuanYuan Liu, Yin Zhao, YueRan Zhu, MengXue Liu, Yuenan Liu, and Qian Xing

Subjects
SARS-CoV-2, COVID-19, thyroid hormone, fatigue, risk factor, Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

BackgroundUnder the current pandemic of Corona Virus Disease 2019 (COVID-19), The relationship between fatigue and COVID-19 has been found. Infection with COVID-19 is associated with fatigue long after the acute phase of COVID-19. Understanding the association of thyroid hormones levels with post-COVID condition, such as fatigue, is necessary to improve quality of life.MethodsThis population-based cohort study was conducted in Dalian, China, from December 2022, to March 2023, using a Yidu Core platform in the First Affiliated Hospital of Dalian Medical University, that integrates medical records, laboratory tests, and all diagnosis and treatment information based on patients in hospital. Eligible individuals were 40 patients with COVID-19, Divided them into fatigue group and non-fatigue group following up by telephone using the FS-14 scale after 6 months. The primary outcomes were the diagnoses of fatigue. The association between thyroid hormones levels and post-COVID condition, such as fatigue, was assessed using logistic regression analysis.ResultsCompared with the non-fatigue group, the FT3 level in fatigue group was lower (p

Published
2024
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22. Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder

Author

Adamson, Chris, Adler, Sophie, Alexander-Bloch, Aaron F., Anagnostou, Evdokia, Anderson, Kevin M., Areces-Gonzalez, Ariosky, Astle, Duncan E., Auyeung, Bonnie, Ayub, Muhammad, Bae, Jong Bin, Ball, Gareth, Baron-Cohen, Simon, Beare, Richard, Bedford, Saashi A., Benegal, Vivek, Bethlehem, Richard A.I., Beyer, Frauke, Blangero, John, Cábez, Manuel Blesa, Boardman, James P., Borzage, Matthew, Bosch-Bayard, Jorge F., Bourke, Niall, Bullmore, Edward T., Calhoun, Vince D., Chakravarty, Mallar M., Chen, Christina, Chertavian, Casey, Chetelat, Gaël, Chong, Yap S., Corvin, Aiden, Costantino, Manuela, Courchesne, Eric, Crivello, Fabrice, Cropley, Vanessa L., Crosbie, Jennifer, Crossley, Nicolas, Delarue, Marion, Delorme, Richard, Desrivieres, Sylvane, Devenyi, Gabriel, Di Biase, Maria A., Dolan, Ray, Donald, Kirsten A., Donohoe, Gary, Dorfschmidt, Lena, Dunlop, Katharine, Edwards, Anthony D., Elison, Jed T., Ellis, Cameron T., Elman, Jeremy A., Eyler, Lisa, Fair, Damien A., Fletcher, Paul C., Fonagy, Peter, Franz, Carol E., Galan-Garcia, Lidice, Gholipour, Ali, Giedd, Jay, Gilmore, John H., Glahn, David C., Goodyer, Ian M., Grant, P.E., Groenewold, Nynke A., Gudapati, Shreya, Gunning, Faith M., Gur, Raquel E., Gur, Ruben C., Hammill, Christopher F., Hansson, Oskar, Hedden, Trey, Heinz, Andreas, Henson, Richard N., Heuer, Katja, Hoare, Jacqueline, Holla, Bharath, Holmes, Avram J., Huang, Hao, Ipser, Jonathan, Jack, Clifford R., Jr., Jackowski, Andrea P., Jia, Tianye, Jones, David T., Jones, Peter B., Kahn, Rene S., Karlsson, Hasse, Karlsson, Linnea, Kawashima, Ryuta, Kelley, Elizabeth A., Kern, Silke, Kim, Ki-Woong, Kitzbichler, Manfred G., Kremen, William S., Lalonde, François, Landeau, Brigitte, Lerch, Jason, Lewis, John D., Li, Jiao, Liao, Wei, Liston, Conor, Lombardo, Michael V., Lv, Jinglei, Mallard, Travis T., Marcelis, Machteld, Mathias, Samuel R., Mazoyer, Bernard, McGuire, Philip, Meaney, Michael J., Mechelli, Andrea, Misic, Bratislav, Morgan, Sarah E., Mothersill, David, Ortinau, Cynthia, Ossenkoppele, Rik, Ouyang, Minhui, Palaniyappan, Lena, Paly, Leo, Pan, Pedro M., Pantelis, Christos, Park, Min Tae M., Paus, Tomas, Pausova, Zdenka, Paz-Linares, Deirel, Binette, Alexa Pichet, Pierce, Karen, Qian, Xing, Qiu, Anqi, Raznahan, Armin, Rittman, Timothy, Rodrigue, Amanda, Rollins, Caitlin K., Romero-Garcia, Rafael, Ronan, Lisa, Rosenberg, Monica D., Rowitch, David H., Salum, Giovanni A., Satterthwaite, Theodore D., Schaare, H. Lina, Schabdach, Jenna, Schachar, Russell J., Schöll, Michael, Schultz, Aaron P., Seidlitz, Jakob, Sharp, David, Shinohara, Russell T., Skoog, Ingmar, Smyser, Christopher D., Sperling, Reisa A., Stein, Dan J., Stolicyn, Aleks, Suckling, John, Sullivan, Gemma, Thyreau, Benjamin, Toro, Roberto, Traut, Nicolas, Tsvetanov, Kamen A., Turk-Browne, Nicholas B., Tuulari, Jetro J., Tzourio, Christophe, Vachon-Presseau, Étienne, Valdes-Sosa, Mitchell J., Valdes-Sosa, Pedro A., Valk, Sofie L., van Amelsvoort, Therese, Vandekar, Simon N., Vasung, Lana, Vértes, Petra E., Victoria, Lindsay W., Villeneuve, Sylvia, Villringer, Arno, Vogel, Jacob W., Wagstyl, Konrad, Wang, Yin-Shan S., Warfield, Simon K., Warrier, Varun, Westman, Eric, Westwater, Margaret L., Whalley, Heather C., White, Simon R., Witte, A. Veronica, Yang, Ning, Yeo, B.T. Thomas, Yun, Hyuk Jin, Zalesky, Andrew, Zar, Heather J., Zettergren, Anna, Zhou, Juan H., Ziauddeen, Hisham, Zimmerman, Dabriel, Zugman, Andre, Zuo, Xi-Nian N., Ho, Natalie C.W., Nogovitsyn, Nikita, Metzak, Paul, Ballester, Pedro L., Hassel, Stefanie, Rotzinger, Susan, Poppenk, Jordan, Lam, Raymond W., Taylor, Valerie H., Milev, Roumen, Frey, Benicio N., Harkness, Kate L., Addington, Jean, and Kennedy, Sidney H.

Published
2024
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32. Supine transfer test-induced changes in cardiac index predict fluid responsiveness in patients without intra-abdominal hypertension

Author

Zhiyong Zhao, Zhongwei Zhang, Jing Liu, Zhili Xia, Qian Xing, Yaodong Zhang, Yijun Zheng, Lihua Shen, Qionghua Lin, Danyan Gu, Pengmei Wang, Shan Zhang, Fangfang Li, and Biao Zhu

Subjects
Fluid responsiveness, Supine transfer, Cardiac index, Intra-abdominal hypertension, Anesthesiology, RD78.3-87.3
Abstract

Abstract Background The reversible maneuver that mimics the fluid challenge is a widely used test for evaluating volume responsiveness. However, passive leg raising (PLR) does have certain limitations. The aim of the study is to determine whether the supine transfer test could predict fluid responsiveness in adult patients with acute circulatory failure who do not have intra-abdominal hypertension, by measuring changes in cardiac index (CI). Methods Single-center, prospective clinical study in a 25-bed surgery intensive care unit at the Fudan University Shanghai Cancer Center. Thirty-four patients who presented with acute circulatory failure and were scheduled for fluid therapy. Every patient underwent supine transfer test and fluid challenge with 500 mL saline for 15–30 min. There were four sequential steps in the protocol: (1) baseline-1: a semi-recumbent position with the head of the bed raised to 45°; (2) supine transfer test: patients were transferred from the 45° semi-recumbent position to the strict supine position; (3) baseline-2: return to baseline-1 position; and (4) fluid challenge: administration of 500 mL saline for 15–30 min. Hemodynamic parameters were recorded at each step with arterial pulse contour analysis (ProAQT/Pulsioflex). A fluid responder was defined as an increase in CI ≥ 15% after fluid challenge. The receiver operating characteristic curve and gray zone were defined for CI. Results Seventeen patients were fluid challenge. The r value of the linear correlations was 0.73 between the supine transfer test- and fluid challenge-induced relative CI changes. The relative changes in CI induced by supine transfer in predicting fluid responsiveness had an area under the receiver operating characteristic curve of 0.88 (95% confidence interval 0.72–0.97) and predicted a fluid responder with 76.5% (95% confidence interval 50.1–93.2) sensitivity and 88.2% (95% confidence interval 63.6–98.5) specificity, at a best threshold of 5.5%. Nineteen (55%) patients were in the gray zone (CI ranging from -3 and 8 L/min/m2). Conclusion The supine transfer test can potentially assist in detecting fluid responsiveness in patients with acute circulatory failure without intra-abdominal hypertension. Nevertheless, the small threshold and the 55% gray zone were noteworthy limitation. Trial registration Predicting fluid responsiveness with supine transition test (ChiCTR2200058264). Registered 2022–04-04 and last refreshed on 2023–03-26, https://www.chictr.org.cn/showproj.html?proj=166175 .

Published
2023
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