| 1. |
- Chen, Haiyang, et al.
(författare)
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Heterogeneous Nucleating Agent for High-Boiling-Point Nonhalogenated Solvent-Processed Organic Solar Cells and Modules
- 2024
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Ingår i: Advanced Materials. - : WILEY-V C H VERLAG GMBH. - 0935-9648 .- 1521-4095.
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Tidskriftsartikel (refereegranskat)abstract
- High-boiling-point nonhalogenated solvents are superior solvents to produce large-area organic solar cells (OSCs) in industry because of their wide processing window and low toxicity; while, these solvents with slow evaporation kinetics will lead excessive aggregation of state-of-the-art small molecule acceptors (e.g. L8-BO), delivering serious efficiency losses. Here, a heterogeneous nucleating agent strategy is developed by grafting oligo (ethylene glycol) side-chains on L8-BO (BTO-BO). The formation energy of the obtained BTO-BO; while, changing from liquid in a solvent to a crystalline phase, is lower than that of L8-BO irrespective of the solvent type. When BTO-BO is added as the third component into the active layer (e.g. PM6:L8-BO), it easily assembles to form numerous seed crystals, which serve as nucleation sites to trigger heterogeneous nucleation and increase nucleation density of L8-BO through strong hydrogen bonding interactions even in high-boiling-point nonhalogenated solvents. Therefore, it can effectively suppress excessive aggregation during growth, achieving ideal phase-separation active layer with small domain sizes and high crystallinity. The resultant toluene-processed OSCs exhibit a record power conversion efficiency (PCE) of 19.42% (certificated 19.12%) with excellent operational stability. The strategy also has superior advantages in large-scale devices, showing a 15.03-cm2 module with a record PCE of 16.35% (certificated 15.97%). The heterogeneous nucleating agent (BTO-BO) is developed to suppress the excessive aggregation of L8-BO in high-boiling-point nonhalogenated solvents processing, achieving the active layer with high crystallinity and nano-scaled phase separation morphology. The resultant OSCs achieve record power conversion efficiencies of 19.42% (0.062-cm2) and 16.35% (15. 03-cm2) with excellent operational stabilities. image
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| 2. |
- Huang, Yuting, et al.
(författare)
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Host-Guest Strategy Enabling Nonhalogenated Solvent Processing for High-Performance All-Polymer Hosted Solar Cells
- 2023
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Ingår i: Chinese journal of chemistry. - : WILEY-V C H VERLAG GMBH. - 1001-604X .- 1614-7065. ; 41:9, s. 1066-1074
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Tidskriftsartikel (refereegranskat)abstract
- The power conversion efficiencies (PCEs) of all-polymer solar cells (all-PSCs), usually processed from low-boiling-point and toxic solvents, have reached high values of 18%. However, poor miscibility and uncontrollable crystallinity in polymer blends lead to a notable drop in the PCEs when using green solvents, limiting the practical development of all-PSCs. Herein, a third component (guest) BTO was employed to optimize the miscibility and enhance the crystallinity of PM6/PY2Se-F host film processed from green solvent toluene (TL), which can effectively suppress the excessive aggregation of PY2Se-F and facilitate a nano-scale interpenetrating network morphology for exciton dissociation and charge transport. As a result, TL-processed all-polymer hosted solar cells (all-PHSCs) exhibited an impressive PCE of 17.01%. Moreover, the strong molecular interaction between the host and guest molecules also enhances the thermal stability of the devices. Our host-guest strategy provides a unique approach to developing high-efficiency and stable all-PHSCs processed from green solvents, paving the way for the industrial development of all-PHSCs.
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| 3. |
- Li, Qin, et al.
(författare)
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Dynamics inside the cancer cell attractor reveal cell heterogeneity, limits of stability, and escape
- 2016
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 113:10, s. 2672-2677
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Tidskriftsartikel (refereegranskat)abstract
- The observed intercellular heterogeneity within a clonal cell population can be mapped as dynamical states clustered around an attractor point in gene expression space, owing to a balance between homeostatic forces and stochastic fluctuations. These dynamics have led to the cancer cell attractor conceptual model, with implications for both carcinogenesis and new therapeutic concepts. Immortalized and malignant EBV-carrying B-cell lines were used to explore this model and characterize the detailed structure of cell attractors. Any subpopulation selected from a population of cells repopulated the whole original basin of attraction within days to weeks. Cells at the basin edges were unstable and prone to apoptosis. Cells continuously changed states within their own attractor, thus driving the repopulation, as shown by fluorescent dye tracing. Perturbations of key regulatory genes induced a jump to a nearby attractor. Using the Fokker-Planck equation, this cell population behavior could be described as two virtual, opposing influences on the cells: one attracting toward the center and the other promoting diffusion in state space (noise). Transcriptome analysis suggests that these forces result from high-dimensional dynamics of the gene regulatory network. We propose that they can be generalized to all cancer cell populations and represent intrinsic behaviors of tumors, offering a previously unidentified characteristic for studying cancer.
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| 4. |
- Xie, Sisi, et al.
(författare)
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Dietary ketone body-escalated histone acetylation in megakaryocytes alleviates chemotherapy-induced thrombocytopenia
- 2022
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Ingår i: Science Translational Medicine. - : AMER ASSOC ADVANCEMENT SCIENCE. - 1946-6234 .- 1946-6242. ; 14:673
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Tidskriftsartikel (refereegranskat)abstract
- Chemotherapy-induced thrombocytopenia (CIT) is a severe complication in patients with cancer that can lead to impaired therapeutic outcome and survival. Clinically, therapeutic options for CIT are limited by severe adverse effects and high economic burdens. Here, we demonstrate that ketogenic diets alleviate CIT in both animals and humans without causing thrombocytosis. Mechanistically, ketogenic diet-induced circulating beta-hydroxybutyrate (beta-OHB) increased histone H3 acetylation in bone marrow megakaryocytes. Gain- and loss-of-function experiments revealed a distinct role of 3-beta-hydroxybutyrate dehydrogenase (BDH)-mediated ketone body metabolism in promoting histone acetylation, which promoted the transcription of platelet biogenesis genes and induced thrombocytopoiesis. Genetic depletion of the megakaryocyte-specific ketone body transporter monocarboxylate transporter 1 (MCT1) or pharmacological targeting of MCT1 blocked beta-OHB-induced thrombocytopoiesis in mice. A ketogenesis-promoting diet alleviated CIT in mouse models. Moreover, a ketogenic diet modestly increased platelet counts without causing thrombocytosis in healthy volunteers, and a ketogenic lifestyle inversely correlated with CIT in patients with cancer. Together, we provide mechanistic insights into a ketone body-MCT1-BDH-histone acetylation-platelet biogenesis axis in megakaryocytes and propose a non-toxic, low-cost dietary intervention for combating CIT.
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| 5. |
- Yu, Wenjin, et al.
(författare)
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Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid
- 2022
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Ingår i: Frontiers in Oncology. - : Frontiers Media SA. - 2234-943X. ; 12, s. 1-11
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Tidskriftsartikel (refereegranskat)abstract
- Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope.Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage.Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly.Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists.Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.
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| 6. |
- Yu, Zhang, et al.
(författare)
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Distinction between bacterial and viral infections by serum measurement of human neutrophil lipocalin (HNL) and the impact of antibody selection
- 2016
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Ingår i: JIM - Journal of Immunological Methods. - : Elsevier BV. - 0022-1759 .- 1872-7905. ; 432, s. 82-86
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Tidskriftsartikel (refereegranskat)abstract
- The distinction between acute infections of bacterial or viral causes is clinically important, but often very difficult even for experienced doctors. Previous studies indicated that serum measurements of HNL (Human Neutrophil Lipocalin) might be a superior diagnostic means in this regard, but also indicated that the antibody conformation of the HNL assay might have an impact on the diagnostic performance. The aim of the present report was to examine this further. Methods: Several different (n = 24) HNL ELISA assays were developed using different combinations of monoclonal and polyclonal HNL antibodies. Sera were collected from healthy persons (n = 188) and from 155 patients with acute infections.before any antibiotics treatment. The patients were diagnosed as having bacterial (n = 69) or viral causes (n = 86) of their infections. Plasma and serum were also examined by Western blotting using HNL-specific polyclonal antibodies. Results: The optimal assay format for the distinction between bacterial and viral infection resulted in an area under the receiver operating characteristics curve (AuROC) for S-HNL of 0.98. (95% CI 0.94-1.00) as compared to 0.83 (0.76-0.88) for blood neutrophil counts and 0.69 (0.61-0.76) for S-CRP. Results also showed that different assay formats of HNL identified monomeric and dimeric HNL differently, the monomeric HNL being elevated in viral infections and the dimeric HNL being elevated in bacterial infections. Conclusion: We conclude that serum theasurement of HNL is a superior diagnostic means to distinguish between acute infections caused by bacteria or virus. For optimal clinical performance the immunoassay should address conformational epitopes in the dimeric HNL.
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