Sentiment Analysis and Effect of COVID-19 Pandemic using College SubReddit Data

Background: The COVID-19 pandemic has affected our society and human well-being in various ways. In this study, we investigate how the pandemic has influenced people's emotions and psychological states compared to a pre-pandemic period using real-world data from social media. Method: We collected Reddit social media data from 2019 (pre-pandemic) and 2020 (pandemic) from the subreddits communities associated with eight universities. We applied the pre-trained Robustly Optimized BERT pre-training approach (RoBERTa) to learn text embedding from the Reddit messages, and leveraged the relational information among posted messages to train a graph attention network (GAT) for sentiment classification. Finally, we applied model stacking to combine the prediction probabilities from RoBERTa and GAT to yield the final classification on sentiment. With the model-predicted sentiment labels on the collected data, we used a generalized linear mixed-effects model to estimate the effects of pandemic and in-person teaching during the pandemic on sentiment. Results: The results suggest that the odds of negative sentiments in 2020 (pandemic) were 25.7% higher than the odds in 2019 (pre-pandemic) with a $p$-value $<0.001$; and the odds of negative sentiments associated in-person learning were 48.3% higher than with remote learning in 2020 with a $p$-value of 0.029. Conclusions: Our study results are consistent with the findings in the literature on the negative impacts of the pandemic on people's emotions and psychological states. Our study contributes to the growing real-world evidence on the various negative impacts of the pandemic on our society; it also provides a good example of using both ML techniques and statistical modeling and inference to make better use of real-world data

Has Sentiment Returned to the Pre-pandemic Level? A Sentiment Analysis Using U.S. College Subreddit Data from 2019 to 2022

As impact of COVID-19 pandemic winds down, both individuals and society gradually return to pre-pandemic activities. This study aims to explore how people's emotions have changed from the pre-pandemic during the pandemic to post-emergency period and whether it has returned to pre-pandemic level. We collected Reddit data in 2019 (pre-pandemic), 2020 (peak pandemic), 2021, and 2022 (late stages of pandemic, transitioning period to post-emergency period) from subreddits in 128 universities/colleges in the U.S., and a set of school-level characteristics. We predicted two sets of sentiments from a pre-trained Robustly Optimized BERT pre-training approach (RoBERTa) and graph attention network (GAT) that leverages both rich semantic and relational information among posted messages and then applied a logistic stacking method to obtain the final sentiment classification. After obtaining sentiment label for each message, we used a generalized linear mixed-effects model to estimate temporal trend in sentiment from 2019 to 2022 and how school-level factors may affect sentiment. Compared to the year 2019, the odds of negative sentiment in years 2020, 2021, and 2022 are 24%, 4.3%, and 10.3% higher, respectively, which are all statistically significant(adjusted $p$<0.05). Our study findings suggest a partial recovery in the sentiment composition in the post-pandemic-emergency era. The results align with common expectations and provide a detailed quantification of how sentiments have evolved from 2019 to 2022

Study on the Effect of PIWIL2 Expression on EMT of Breast Cancer Stem Cells and Its Mechanism

Objective: This study mainly elaborated the specific molecular mechanisms of breast cancer metastasis and EMT, which has important clinical value in judging the prognosis and treatment of breast cancer patients. Methods: A total of 493 patients with breast cancer were studied. The expression of PIWIL2 gene was analyzed by immunohistochemistry and section analysis, and the correlation between gene expression and clinicopathological parameters and prognosis of the patients was investigated. TGF-β1 was used to induce breast cancer cells, and EMT model was constructed at the same time to compare the changes of EMT model cells in the control group and obervation group. The expression of PIWIL2 gene in EMT model was detected by Western bloting. After transfection and RNA interference, PIWIL2 expression was silenced. At the same time, the morphological changes of the cells after the reduction of PIWIL2 gene expression were observed through microscope. The gene changes related to EMT were detected by RT-PCR and Western bloting. The expression of PIWIL2 gene was decreased by invasion test. And the expression of breast cell invasiveness and other related expressions such as MMP-13, MMP-9, VEGF shall also be decreased. The effect of MAPKERK and P13K/AKT pathway on the regulation of PIWIL2 expression was studied by obseving the cellular mophology through the microscope. And RT-PCR and Western bloting were used to detect the expression, including Snail, Vimentin and SIug. The effects of PIWIL2 and the downstream transcription factor SIug in ER pathway in breast cancer cells were analyzed by light microscopy, RT-PCR, Western bloting and Transwell invasion experiment. Results: PIWIL2 expression was negatively correlated with its survival rate in estrogen receptor a negative patients, while was not directly related to estrogen receptor positive patients. After the induction of TGF-β1 in MCF-7 breast cancer cells, the cells were spindle shaped and would lose the intercellular adhesion. With the development of EMT, the inhibition of PIWIL2 gene expression would block the effect of TGF-β1 on EMT in MCF-7 cell lines. The changes of EMT-related genes expression can be shown by RT-PCR and Western Bloting. SiRNA sclienced the Piwi12 expression, which will decrease the cellular invasiveness. At the same time, such matrix metalloproteinase as MMP9 and MMP13 and the mRNA transcription vascular endothelial growth factor was significantly down-regulated. After silencing the expression of SIug, all EMT of TGF-β1 gene will be inhibited, and the estrogen a signal pathway can inhibit the expression of PIWIL2 and the downstream transcription factor SIug. Slug is a common downstream transcription factor of estrogen a and PIWIL2, which also serves as an important bridge connecting estrogen a and Piwi12. It can accept Piwi12 and estrogen a to inhibit or stimulate signals, and then effectively regulate the EMT of breast cancer cells. In addition, ER signal can also participate in the expression of Piwi12 and antagonize Piwi12 to promote EMT

Seismic Fragility Analysis of Base Isolated Structure Subjected to Near-fault Ground Motions

In order to better evaluate the performance of the base isolated structure under the near-fault earthquakes, this paper takes into consideration an existing engineering case study in China as the prototype, and uses OpenSEES platform to establish the nonlinear finite element model of the base isolated structure. The nonlinear response of the isolated structure under the near-fault earthquake is analyzed. The incremental dynamic analysis (IDA) method is used to calculate the damage probability of the structure under the near-fault earthquake, and the fragility curve of the base isolated structure is established. The fragility equation is obtained by nonlinear regression, and the error of fragility equation is analyzed. The results show that the maximum value of the inter-story drift of the upper structure under the action of near-fault earthquake is significantly greater than that under the action of far-fault earthquake. With the increase of seismic intensity, the damage probability of base isolated structure increases nonlinearly, and the maximum response value of horizontal displacement of bearing and inter-story drift of superstructure increases generally. In addition, the exceeding probability of the fragility curve based on PSDA is greater than that based on EDP criterion. When the sample points of the two methods are the same, the exceeding probability points calculated based on PSDA can be regarded as accurate values. The&nbsp;fragility curve based on PSDA may overestimate the exceeding probability to some extent, and the overestimation may be enlarged with the increase of failure stage

Effect of secondary currents on the flow and turbulence in partially filled pipes

Large-eddy simulations of turbulent flow in partially filled pipes are conducted to investigate the effect of secondary currents on the friction factor, first- and second-order statistics and large-scale turbulent motion. The method is validated first and simulated profiles of the mean streamwise velocity, normal stresses and turbulent kinetic energy (TKE) are shown to be in good agreement with experimental data. The secondary flow is stronger in half- and three-quarters full pipes compared with quarter full or fully filled pipe flows, respectively. The origin of the secondary flow is examined by both the TKE budget and the steamwise vorticity equation, providing evidence that secondary currents originate from the corner between the free surface and the pipe walls, which is where turbulence production is larger than the sum of the remaining terms of the TKE budget. An extra source of streamwise vorticity production is found at the free surface near the centreline bisector, due to the two-component asymmetric turbulence there. The occurrence of dispersive stresses (due to secondary currents) reduces the contribution of the turbulent shear stress to the friction factor, which results in a reduction of the total friction factor of flows in half and three-quarters full pipes in comparison to a fully filled pipe flow. Furthermore, the presence of significant secondary currents inhibits very-large-scale motion (VLSM), which in turn reduces the strength and scales of near-wall streaks. Subsequently, near-wall coherent structures generated by streak instability and transient growth are significantly suppressed. The absence of VLSM and less coherent near-wall turbulence structures is supposedly responsible for the drag reduction in partially filled pipe flows relative to a fully filled pipe flow at an equivalent Reynolds number

Berberine induces caspase-independent cell death in colon tumor cells through activation of apoptosis-inducing factor

Berberine, an isoquinoline alkaloid derived from plants, is a traditional medicine for treating bacterial diarrhea and intestinal parasite infections. Although berberine has recently been shown to suppress growth of several tumor cell lines, information regarding the effect of berberine on colon tumor growth is limited. Here, we investigated the mechanisms underlying the effects of berberine on regulating the fate of colon tumor cells, specifically the immorto Min mouse colonic epithelial (IMCE) cells carrying the Apcmin mutation, and of normal colon epithelial cells, namely young adult mouse colon (YAMC) epithelial cells. Berberine decreased colon tumor colony formation in agar, and induced cell death and LDH release in a time- and concentration-dependent manner in IMCE cells. In contrast, YAMC cells were not sensitive to berberine-induced cell death. Berberine did not stimulate caspase activation, and PARP cleavage and berberine-induced cell death were not affected by a caspase inhibitor in IMCE cells. Rather, berberine stimulated a caspase-independent cell death mediator, apoptosis-inducing factor (AIF) release from mitochondria and nuclear translocation in a ROS production-dependent manner. Amelioration of berberine-stimulated ROS production or suppression of AIF expression blocked berberine-induced cell death and LDH release in IMCE cells. Furthermore, two targets of ROS production in cells, cathepsin B release from lysosomes and PARP activation were induced by berberine. Blockage of either of these pathways decreased berberine-induced AIF activation and cell death in IMCE cells. Thus, berberine-stimulated ROS production leads to cathepsin B release and PARP activation-dependent AIF activation, resulting in caspase-independent cell death in colon tumor cells. Notably, normal colon epithelial cells are less susceptible to berberine-induced cell death, which suggests the specific inhibitory effects of berberine on colon tumor cell growth