Making “cold” tumors “hot”- radiotherapy remodels the tumor immune microenvironment of pancreatic cancer to benefit from immunotherapy: a case report

Immune checkpoint inhibitors have limited efficacy in metastatic pancreatic cancer due to the complex tumor immune microenvironment (TIME). Studies have shown that radiotherapy can cause cell lesions to release tumor antigens and then take part in the remodeling of the tumor environment and the induction of ectopic effects via regional and systemic immunoregulation. Here, we reported a case of advanced metastatic pancreatic cancer treated with immunotherapy combined with chemotherapy and radiotherapy and a sharp shift of the TIME from T3 to T2 was also observed. One hepatic metastasis within the planning target volume (PTV) was evaluated complete response (CR), the other one was evaluated partial response (PR) and 2 hepatic metastases outside the PTV were surprisingly considered PR. In the study, we found that immunotherapy combined with chemotherapy and radiotherapy achieved significant therapeutic benefits, which may provide a new strategy for the treatment of advanced pancreatic cancer

The factors impacting the use of navigation systems: A study based on the technology acceptance model

Navigation&nbsp;systems&nbsp;are important in daily driving situations.&nbsp;The&nbsp;user experience&nbsp;of&nbsp;using&nbsp;navigation&nbsp;systems&nbsp;can influence drivers&rsquo; attitudes towards them and their intentions to&nbsp;use&nbsp;them.&nbsp;The&nbsp;objective&nbsp;of&nbsp;this paper was to identify&nbsp;the&nbsp;mechanisms underlying&nbsp;the&nbsp;use&nbsp;of&nbsp;navigation&nbsp;systems&nbsp;and analyse&nbsp;the&nbsp;psychological&nbsp;factors&nbsp;that influence drivers&rsquo;&nbsp;use&nbsp;of&nbsp;navigation&nbsp;systems.&nbsp;The&nbsp;technology&nbsp;acceptance&nbsp;model&nbsp;(TAM) was&nbsp;used&nbsp;to explore&nbsp;the&nbsp;factors&nbsp;impacting&nbsp;navigation&nbsp;system&nbsp;usage, and related&nbsp;factors&nbsp;such as trust and professional driver status were also considered.&nbsp;Using&nbsp;data collected from 372 drivers in China,&nbsp;the&nbsp;study&nbsp;demonstrated that two dimensions&nbsp;of&nbsp;the&nbsp;TAM, perceived&nbsp;usefulness&nbsp;(PU) and perceived ease&nbsp;of&nbsp;use&nbsp;(PEOU), as well as trust, were positively related to&nbsp;the&nbsp;intention to&nbsp;use&nbsp;navigation&nbsp;systems. Meanwhile, these positive associations were mediated by drivers&rsquo; attitudes towards&nbsp;navigation&nbsp;systems. Furthermore, professional drivers showed different trends from nonprofessional drivers in terms&nbsp;of&nbsp;the&nbsp;path from PEOU and trust to positive attitudes.</p

How dyadic emotional transmission shapes teacher-student relationship: effects of emotional convergence on cohesion in teacher-student interaction

Understanding the dynamics of teacher-student relationships is crucial, and emotional exchange plays a pivotal role in this process. This study aims to investigate the predictive mechanisms underlying affective and physiological responses synchrony, specifically focusing on positive emotional convergence and its impact on emotional cohesion during teacher-student interactions. To achieve this, we implemented a novel reading-following paradigm to induce teacher-student interaction within an actual classroom setting. Galvanic skin response (GSR) signals were collected using wrist-worn wearable devices from both teachers and students during class. Following each session, teachers and students individually completed questionnaires to evaluate the quality of their interaction and the cohesion between them. Results indicate that the reading-following paradigm facilitated creative emotional convergence between teachers and students. Moreover, a positive association was observed between teacher-student interaction and teacher-student cohesion, mediated by affective responses synchrony and physiological coupling between teachers and students. Additionally, the influence of teacher-student interaction on affective responses synchrony was moderated by physiological predictability. The implications of these findings for future research and their potential application in the classroom setting are discussed.</p

Why people like using bikesharing: Factors influencing bikeshare use in a Chinese sample

Bikesharing refers to a short-term bicycle rental service for pedestrians provided by enterprises or the government. The aim of this study was to evaluate the public attitude toward bikesharing and factors influencing intention to use bikeshare services. 334 participants from Beijing, China, completed a questionnaire including the Big Five Inventory, the Traffic Climate Scale, and measurements of attitude toward and intention to use bikesharing. The results showed that attitude toward bikesharing was positively predicted by extroversion, the functionality of the traffic climate, social support and personal preference. Additionally, social support, personal preference and attitude toward bikesharing positively predicted the intention to use bikesharing. Young people were more willing to use bikesharing services. This study provides a framework for bikeshare usage and the related influencing factors. Related suggestions and strategies from policymaking and marketing perspectives are proposed to encourage more residents to adopt bikesharing. Some of the limitations and possible extensions of this field are discussed

The Prediction of Wheat Yield in the North China Plain by Coupling Crop Model with Machine Learning Algorithms

The accuracy prediction for the crop yield is conducive to the food security in regions and/or nations. To some extent, the prediction model for crop yields combining the crop mechanism model with statistical regression model (SRM) can improve the timeliness and robustness of the final yield prediction. In this study, the accumulated biomass (AB) simulated by the Agricultural Production Systems sIMulator (APSIM) model and multiple climate indices (e.g., climate suitability indices and extreme climate indices) were incorporated into SRM to predict the wheat yield in the North China Plain (NCP). The results showed that the prediction model based on the random forest (RF) algorithm outperformed the prediction models using other regression algorithms. The prediction for the wheat yield at SM (the period from the start of grain filling to the milky stage) based on RF can obtain a higher accuracy (r = 0.86, RMSE = 683 kg ha−1 and MAE = 498 kg ha−1). With the progression of wheat growth, the performances of yield prediction models improved gradually. The prediction of yield at FS (the period from flowering to the start of grain filling) can achieve higher precision and a longer lead time, which can be viewed as the optimum period providing the decent performance of the yield prediction and about one month’s lead time. In addition, the precision of the predicted yield for the irrigated sites was higher than that for the rainfed sites. The APSIM-simulated AB had an importance of above 30% for the last three prediction events, including FIF event (the period from floral initiation to flowering), FS event (the period from flowering to the start of grain filling) and SM event (the period from the start of grain filling to the milky stage), which ranked first in the prediction model. The climate suitability indices, with a higher rank for every prediction event, played an important role in the prediction model. The winter wheat yield in the NCP was seriously affected by the low temperature events before flowering, the high temperature events after flowering and water stress. We hope that the prediction model can be used to develop adaptation strategies to mitigate the negative effects of climate change on crop productivity and provide the data support for food security

Climate Change Impact on Yield and Water Use of Rice–Wheat Rotation System in the Huang-Huai-Hai Plain, China

Global climate change has had a significant impact on crop production and agricultural water use. Investigating different future climate scenarios and their possible impacts on crop production and water consumption is critical for proposing effective responses to climate change. In this study, based on daily downscaled climate data from 22 Global Climate Models (GCMs) provided by Coupled Model Intercomparison Project Phase 6 (CMIP6), we applied the well-validated Agricultural Production Systems sIMulator (APSIM) to simulate crop phenology, yield, and water use of the rice–wheat rotation at four representative stations (including Hefei and Shouxian stations in Anhui province and Kunshan and Xuzhou stations in Jiangsu province) across the Huang-Huai-Hai Plain, China during the 2041–2070 period (2050s) under four Shared Socioeconomic Pathways (i.e., SSP126, SSP245, SSP370, and SSP585). The results showed a significant increase in annual mean temperature (Temp) and solar radiation (Rad), and annual total precipitation (Prec) at four investigated stations, except Rad under SSP370. Climate change mainly leads to a consistent advance in wheat phenology, but inconsistent trends in rice phenology across four stations. Moreover, the reproductive growth period (RGP) of wheat was prolonged while that of rice was shorted at three of four stations. Both rice and wheat yields were negatively correlated with Temp, but positively correlated with Rad, Prec, and CO2 concentration ([CO2]). However, crop ET was positively correlated with Rad, but negatively correlated with [CO2], as elevated [CO2] decreased stomatal conductance. Moreover, the water use efficiency (WUE) of rice and wheat was negatively correlated with Temp, but positively correlated with [CO2]. Overall, our study indicated that the change in Temp, Rad, Prec, and [CO2] have different impacts on different crops and at different stations. Therefore, in the impact assessment for climate change, it is necessary to explore and analyze different crops in different regions. Additionally, our study helps to improve understanding of the impacts of climate change on crop production and water consumption and provides data support for the sustainable development of agriculture

Identification and Quality Evaluation of Raw and Processed Asarum Species Using Microscopy, DNA Barcoding, and Gas Chromatography-Mass Spectrometry

Asarum (Aristolochiaceae) is one of the common herbs used to relieve exterior syndromes. Some volatile components of Asarum which have toxic effect may cause adverse reactions such as headache, general tension, unconsciousness, and respiratory paralysis. Therefore, Asarum is normally processed to reduce such toxicity and adverse effects. The bioactive ingredients contained in different Asarum herbs vary significantly; this variation may be attributed to their differences in species, origins, or processing methods. In this study, 16 batches of Asarum herbs were collected, and their species were identified using DNA barcoding, which is a method for distinguishing plant species, coupled with microscopy. A gas chromatography-mass spectrometry (GC-MS) method for simultaneous determination of 10 compounds was established to evaluate the contents of raw and processed Asarum herbs. Multivariate analysis was then applied to compare different batches of herbs based on the GC-MS data. DNA barcoding identified the herbs as being derived from four sources, and herbs from different origins showed different microscopic features. The results demonstrated that most of the samples were clearly clustered into distinct groups that corresponded to species types. All raw and processed samples were classified by partial least squares discriminant analysis (PLS-DA) based on the 10 analyzed compounds. The findings suggested that safrole and methyleugenol with a variable importance in the project (VIP) > 1 are unique compounds that can be used to differentiate between Asarum species. Safrole, methyleugenol, and 2,6,6-trimethylcyclohepta-2,4-dien-1-one were identified as significant constituents, the presence of which can be used to differentiate between raw and processed Asarum samples. These results indicate that species and processing methods show important effects on the composition of Asarum herbs