Browsing by Author "Wang S"
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- ItemAssessment of clinical feasibility:offline adaptive radiotherapy for lung cancer utilizing kV iCBCT and UNet++ based deep learning model.(Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine, 2024-11-29) Zeng H; Chen Q; E X; Feng Y; Lv M; Zeng S; Shen W; Guan W; Zhang Y; Zhao R; Wang S; Yu JBackground Lung cancer poses a significant global health challenge. Adaptive radiotherapy (ART) addresses uncertainties due to lung tumor dynamics. We aimed to investigate a comprehensively and systematically validated offline ART regimen with high clinical feasibility for lung cancer. Methods This study enrolled 102 lung cancer patients, who underwent kV iterative cone-beam computed tomography (iCBCT). Data collection included iCBCT and planning CT (pCT) scans. Among these, data from 70 patients were employed for training the UNet++ based deep learning model, while 15 patients were allocated for testing the model. The model transformed iCBCT into adaptive CT (aCT). Clinical radiotherapy feasibility was verified in 17 patients. The dosimetric evaluation encompassed GTV, organs at risk (OARs), and monitor units (MU), while delivery accuracy was validated using ArcCHECK and thermoluminescent dosimeter (TLD) detectors. Results The UNet++ based deep learning model substantially improved image quality, reducing mean absolute error (MAE) by 70.05%, increasing peak signal-to-noise ratio (PSNR) by 17.97%, structural similarity (SSIM) by 7.41%, and the Hounsfield Units (HU) of aCT approaching a closer proximity to pCT compared to kV iCBCT. There were no significant differences observed in the dosimetric parameters of GTV and OARs between the aCT and pCT plans, confirming the accuracy of the dose maps in ART plans. Similarly, MU manifested no notable disparities, underscoring the consistency in treatment efficiency. Gamma passing rates for intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans derived from aCT and pCT exceeded 98%, while the deviations in TLD measurements (within 2% to 7%) also exhibited no significant differences, thus corroborating the precision of dose delivery. Conclusion An offline ART regimen utilizing kV iCBCT and UNet++ based deep learning model is clinically feasible for lung cancer treatment. This approach provides enhanced image quality, comparable treatment plans to pCT, and precise dose delivery.
- ItemChinese Students Abroad during the COVID Crisis: Challenges and Opportunities(21st Century Global Dynamics Initiative at the Orfalea Center of the University of California, Santa Barbara, 25/09/2020) Qi GY; Wang S; Dai CCOVID-19 is a human crisis that has hit international education particularly hard. International students have been directly affected by air travel cancellations and quarantine measures which have made border-crossing almost impossible. Like many, they are victims of this crisis—particularly those from China, who constitute the largest market within the global international education sector. Chinese international students have faced a double stigmatization since the outbreak of COVID-19. First, they have been discriminated against by the “Chinese virus” stigma while they were overseas in the early stage of the pandemic. Second, they have been targeted in multiple ways by the anti-China politics triggered by the coronavirus. Given the fluidity of the crisis and the impacts of COVID-19 on Chinese international students, it is worth discussing their plight. Policymakers need to think carefully about the new dynamics of international education in terms of the huge market share of Chinese international students as related to new destination options and changing international education policies that may further affect Chinese students now and during the post-pandemic recovery.
- ItemComparative study on the rheological properties of myofibrillar proteins from different kinds of meat(Elsevier Ltd, 2022-01) Wang H; Yang Z; Yang H; Xue J; Li Y; Wang S; Ge L; Shen Q; Zhang MIn this study, the gel properties of myofibrillar proteins (MPs) from four meat sources (fish, beef, sheep, and pork) were compared. Oscillatory rheology measurements including temperature sweep, frequency sweep, and strain sweep were conducted to characterise the small and large deformation rheological properties of the MPs. In addition, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and scanning electron microscopy (SEM) were used to evaluate differences in the molecular weight distribution as well as the microstructures in gel among different MPs. Frequency sweep measurements showed that all MP gels were weak gels. MPs extracted from pork exhibited the highest gel strength and most compact gel structure, whereas those from fish exhibited the lowest gel strength and loosest gel structure. In addition, the MP extracted from pork (PSM) had the highest content of myosin heavy chain (MHC) and actin. In conclusion, the MPs extracted from fish source and mammalian sources varied significantly in terms of rheological properties and microstructural characteristics. These results provided useful information for developing mixed gel products with different gel strengths.
- ItemFungi regulate the response of the N2O production process to warming and grazing in a Tibetan grassland(Copernicus Publications on behalf of the European Geosciences Union, 2018-07-20) Zhong L; Wang S; Xu X; Wang Y; Rui Y; Zhou X; Shen Q; Wang J; Jiang L; Luo C; Gu T; Ma W; Chen G; Kuzyakov YLack of understanding of the effects of warming and winter grazing on soil fungal contribution to the nitrous oxide (N2O) production process has limited our ability to predict N2O fluxes under changes in climate and land use management, because soil fungi play an important role in driving terrestrial N cycling. A controlled warming and winter grazing experiment that included control (C), winter grazing (G), warming (W) and warming with winter grazing (WG) was conducted to investigate the effects of warming and winter grazing on soil N2O production potential in an alpine meadow on the Tibetan Plateau. Our results showed that soil bacteria and fungi contributed 46 ± 2% and 54 ± 2% to nitrification, and 37 ± 3% and 63 ± 3% to denitrification in the control treatment, respectively. We conclude that soil fungi could be the main source of N2O production potential for the Tibetan alpine grasslands. In our results, neither warming nor winter grazing affected the activity of enzymes responsible for overall nitrification and denitrification. However, warming significantly increased the enzyme activity of bacterial nitrification and potential of N2O production from denitrification to 53 ± 2% and 55 ± 3%, respectively, but decreased them to 47 ± 2% and 45 ± 3%, respectively. Winter grazing had no such effects. Warming and winter grazing may not affect the soil N2O production potential, but climate warming can alter biotic pathways responsible for N2O production process. These findings confirm the importance of soil fungi in the soil N2O production process and how they respond to environmental and land use changes in alpine meadow ecosystems. Therefore, our results provide some new insights into ecological controls on the N2O production process and contribute to the development of an ecosystem nitrogen cycle model.
- ItemIntegrative analysis identifies two molecular and clinical subsets in Luminal B breast cancer(Elsevier Inc, 2023-09-15) Wang H; Liu B; Long J; Yu J; Ji X; Li J; Zhu N; Zhuang X; Li L; Chen Y; Liu Z; Wang S; Zhao SComprehensive multiplatform analysis of Luminal B breast cancer (LBBC) specimens identifies two molecularly distinct, clinically relevant subtypes: Cluster A associated with cell cycle and metabolic signaling and Cluster B with predominant epithelial mesenchymal transition (EMT) and immune response pathways. Whole-exome sequencing identified significantly mutated genes including TP53, PIK3CA, ERBB2, and GATA3 with recurrent somatic mutations. Alterations in DNA methylation or transcriptomic regulation in genes (FN1, ESR1, CCND1, and YAP1) result in tumor microenvironment reprogramming. Integrated analysis revealed enriched biological pathways and unexplored druggable targets (cancer-testis antigens, metabolic enzymes, kinases, and transcription regulators). A systematic comparison between mRNA and protein displayed emerging expression patterns of key therapeutic targets (CD274, YAP1, AKT1, and CDH1). A potential ceRNA network was developed with a significantly different prognosis between the two subtypes. This integrated analysis reveals a complex molecular landscape of LBBC and provides the utility of targets and signaling pathways for precision medicine.
- ItemMercury records from natural archives reveal ecosystem responses to changing atmospheric deposition.(Oxford University Press, 2024-11-19) Chen Q; Wu Q; Cui Y; Wang SGlobal ecosystems face mercury contamination, yet long-term data are scarce, hindering understanding of ecosystem responses to atmospheric Hg input changes. To bridge the data gap and assess ecosystem responses, we compiled and compared a mercury accumulation database from peat, lake, ice and marine deposits worldwide with atmospheric mercury deposition modelled by GEOS-Chem, focusing on trends, magnitudes, spatial-temporal distributions and impact factors. The mercury fluxes in all four deposits showed a 5- to 9-fold increase over 1700-2012, with lake and peat mercury fluxes that generally mirrored atmospheric deposition trends. Significant decreases in lake and peat mercury fluxes post-1950 in Europe evidenced effective environmental policies, whereas rises in East Asia, Africa and Oceania highlighted coal-use impacts, inter alia. Conversely, mercury fluxes in marine and high-altitude ecosystems did not align well with atmospheric deposition, emphasizing natural influences over anthropogenic impacts. Our study underscores the importance of these key regions and ecosystems for future mercury management.
- ItemPotential rapid intraoperative cancer diagnosis using dynamic full-field optical coherence tomography and deep learning: A prospective cohort study in breast cancer patients(Elsevier B V on behalf of the Science China Press, 2024-06-15) Zhang S; Yang B; Yang H; Zhao J; Zhang Y; Gao Y; Monteiro O; Zhang K; Liu B; Wang SAn intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&E) histology, such as frozen section, are time-, resource-, and labor-intensive, and involve specimen-consuming concerns. Here, we report a near-real-time automated cancer diagnosis workflow for breast cancer that combines dynamic full-field optical coherence tomography (D-FFOCT), a label-free optical imaging method, and deep learning for bedside tumor diagnosis during surgery. To classify the benign and malignant breast tissues, we conducted a prospective cohort trial. In the modeling group (n = 182), D-FFOCT images were captured from April 26 to June 20, 2018, encompassing 48 benign lesions, 114 invasive ductal carcinoma (IDC), 10 invasive lobular carcinoma, 4 ductal carcinoma in situ (DCIS), and 6 rare tumors. Deep learning model was built up and fine-tuned in 10,357 D-FFOCT patches. Subsequently, from June 22 to August 17, 2018, independent tests (n = 42) were conducted on 10 benign lesions, 29 IDC, 1 DCIS, and 2 rare tumors. The model yielded excellent performance, with an accuracy of 97.62%, sensitivity of 96.88% and specificity of 100%; only one IDC was misclassified. Meanwhile, the acquisition of the D-FFOCT images was non-destructive and did not require any tissue preparation or staining procedures. In the simulated intraoperative margin evaluation procedure, the time required for our novel workflow (approximately 3 min) was significantly shorter than that required for traditional procedures (approximately 30 min). These findings indicate that the combination of D-FFOCT and deep learning algorithms can streamline intraoperative cancer diagnosis independently of traditional pathology laboratory procedures.
- ItemSensory Profile of Kombucha Brewed with New Zealand Ingredients by Focus Group and Word Clouds(MDPI (Basel, Switzerland), 2021-06-23) Alderson H; Liu C; Mehta A; Gala HS; Mazive NR; Chen Y; Zhang Y; Wang S; Serventi L; Viejo CG; Fuentes SKombucha is a yeast and bacterially fermented tea that is often described as having an acetic, fruity and sour flavour. There is a particular lack of sensory research around the use of Kombucha with additional ingredients such as those from the pepper family, or with hops. The goal of this project was to obtain a sensory profile of Kombucha beverages with a range of different ingredients, particularly of a novel Kombucha made with only Kawakawa (Piper excelsum) leaves. Other samples included hops and black pepper. Instrumental data were collected for all the Kombucha samples, and a sensory focus group of eight semi-trained panellists were set up to create a sensory profile of four products. Commercially available Kombucha, along with reference training samples were used to train the panel. Kawakawa Kombucha was found to be the sourest of the four samples and was described as having the bitterest aftertaste. The instrumental results showed that the Kawakawa Kombucha had the highest titratable acidity (1.55 vs. 1.21–1.42 mL) as well as the highest alcohol percentage (0.40 vs. 0.15–0.30%). The hops sample had the highest pH (3.72 vs. 3.49–3.54), with the lowest titratable acidity (1.21), and, from a basic poll, was the most liked of the samples. Each Kombucha had its own unique set of sensory descriptors with particular emphasis on the Kawakawa product, having unique mouthfeel descriptors as a result of some of the compounds found in Kawakawa. This research has led to a few areas that could be further studied, such as the characteristics of the Piperaceae family under fermentation and the different effects or the foaminess of the Kawakawa Kombucha, which is not fully explained.
- ItemSupplying silicon alters microbial community and reduces soil cadmium bioavailability to promote health wheat growth and yield(Elsevier, 30/06/2021) Song A; Li Z; Wang E; Xu D; Wang S; Bi J; Wang H; Jeyakumar P; Li Z; Fan FSoil amendments of black bone (BB), biochar (BC), silicon fertilizer (SI), and leaf fertilizer (LF) play vital roles in decreasing cadmium (Cd) availability, thereby supporting healthy plant growth and food security in agroecosystems. However, the effect of their additions on soil microbial community and the resulting soil Cd bioavailability, plant Cd uptake and health growth are still unknown. Therefore, in this study, BB, BC, SI, and LF were selected to evaluate Cd amelioration in wheat grown in Cd-contaminated soils. The results showed that relative to the control, all amendments significantly decreased both soil Cd bioavailability and its uptake in plant tissues, promoting healthy wheat growth and yield. This induced-decrease effect in seeds was the most obvious, wherein the effect was the highest in SI (52.54%), followed by LF (43.31%), and lowest in BC (35.24%) and BB (31.98%). Moreover, the induced decrease in soil Cd bioavailability was the highest in SI (29.56%), followed by BC (28.85%), lowest in LF (17.55%), and BB (15.30%). The significant effect in SI likely resulted from a significant increase in both the soil bioavailable Si and microbial community (Acidobacteria and Thaumarchaeota), which significantly decreased soil Cd bioavailability towards plant roots. In particular, a co-occurrence network analysis indicated that soil microbes played a substantial role in rice yield under Si amendment. Therefore, supplying Si alters the soil microbial community, positively and significantly interacting with soil bioavailable Si and decreasing Cd bioavailability in soils, thereby sustaining healthy crop development and food quality.
