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As the incidence of postoperative pain in patients with biliary and pancreatic diseases has gradually increased, how to control postoperative pain has received increasing research attention. By reading pain management guidelines and multidisciplinary communication and cooperation, clinical pharmacists designed multi-mode analgesia regimens based on surgical types, in order to provide strong evidence for the effectiveness and safety of postoperative analgesia regimens and better serve patients.Data from biliary or pancreatic surgery performed at Nanjing Drum Tower Hospital from 2019 to 2021 were collected. Take October 2020 as the time point to compare the outcomes before and after the implementation of the path-based postoperative analgesic regimens. The primary outcomes were NRS pain scores, sleep quality, and incidence of adverse reactions. Length of stay was a secondary outcome.A total of 268 and 239 patients were enrolled in the study and control groups, respectively. Four path-based postoperative analgesic management regimens significantly reduced patients' static and dynamic NRS scores in the 24 h (p 0.05). The patients' sleep quality were better than controls (p 0.05). The incidence of adverse reactions and the length of stay in the study group were numerically lower than controls. Moderate analysis indicated that four analgesia regimens are more precise and better meet actual clinical needs.Effective and safe postoperative pain management is particularly important for clinical purposes. Path-based postoperative analgesia regimens based on different types of surgery overcome the disadvantages of overly broad and generalized traditional guidelines, which play an important role in providing personalized and precise clinical services. Further, study findings provide evidence that four path-based analgesic regimens can reduce postoperative pain and reduce the length of hospital stay, which may provide a better direction for clinical postoperative pain management.

The lane-changing behavior is one of the important causes in traffic accident in congest traffic, and many behaviors of change lane affect volume of traffic. When autonomous driving vehicles are running on road with human-driven vehicles, the effects of change lane on traffic are different. In all human-driven vehicles traffic, the vehicle behaviors of changing lane are more competent. When autonomous driving vehicles are running in mixed traffic, the behaviors of changing lane decrease and the volume of traffic increases. However, a few studies have involved the relationship between traffic volume and lane-change behavior. In a sense, the study of this relationship is good for understanding the operation mechanism of mixed traffic. In this paper, we proposed the linear regression model to describe the relationship between traffic volume and lane-change behavior. The model can be used to establish the basic graph model. Here, we used empirical, simulation, and data-driven methods to obtain data and established a multiple linear regression model. First, we empirically study the continuous traffic with all human-driven vehicles. Then, the corresponding simulation model is established, and the availability of the simulation model is proved by data comparison with empirical study. Finally, 9 rounds of simulation experiments are carried out with the established simulation model. The number of autonomous driving vehicles in each round of simulation experiment increases by 10%. Then, we analyze the data of the behaviors of changing lane and the volume of traffic from simulation experiments. The following was found: (1) an increase in autonomous driving vehicle leads to an increase in traffic volume and a slight decrease in lane changing behaviors; (2) the influence of different proportions of autonomous vehicles on the traffic volume of lanes at different locations is slightly different; and (3) the relationships among the rate of vehicles entering lane, the rate of vehicles exiting lane together, and the volume of traffic show obvious linear relationships with the increase in autonomous driving vehicles. We used multiple linear regression models to carry out description, and the obtained parameter value intervals are close under different operating ratios of autonomous vehicles. To sum up, on multilane roads, especially 4-lane urban expressways, autonomous driving vehicles join in the traffic, which can effectively increase the volume of traffic of each lane while reducing vehicle behaviors of changing lane. The relationships between vehicle behaviors of changing lane and the traffic volume in mixed traffic show linear relationships with the increase in autonomous driving vehicles. In the future, we will further study whether this relationship model can be used in discrete traffic flow.

Modelling the mixed traffic flows of autonomous vehicles (AVs) and human-driven vehicles (HVs) on highways is challenging. Randomness, fluctuations, and congestion exist in the mixed traffic flows. This paper extends the current literature by proposing an M/G(n)/c/c state-dependent queuing model operating in a random environment. The fluctuating traffic demand is addressed by arrival rates modulated by the random environment. Meanwhile, a Markovian arrival process (MAP) is incorporated to describe the platoons. We investigate the performance of the mixed traffic flow under the I policy (AVs and HVs travel together in all lanes) and the D policy (one lane is designated to AVs). Numerical experiments reveal the following interesting findings: (1) the fluctuation degree of traffic demand, the traffic intensity, and the penetration rate of AVs play essential roles in determining the performance of mixed traffic flows. (2) The I policy should always be adopted if the travel time is more valuable. In terms of output rate, the choice between the I and the D policies depends on the traffic intensity, SCV of arrival rates and penetration rate. (3) A larger penetration rate is required to completely eliminate congestion on a longer highway segment.

Robust optimal design of circulation systems (e.g., roads for vehicles or corridors for pedestrians) relies on an accurate steady-state traffic flow model that considers the effect of randomly changing environmental factors (e.g., daily periodicity and weather). Most analytical models assume that the customer interarrival time and service time of circulation facilities follow the exponential distribution with fixed rate parameters, which is unrealistic in most cases. In this paper, we develop a stationary PH i /PH i , n / C / C state-dependent queuing model in a randomly changing environment (RE), which is represented by a Markov chain. The model simultaneously considers the general randomness of arrival and service, the randomly varying rate parameters, and the state-dependent service (the travel time increases with the number of customers). The existing matrix analytic scheme (MAS) algorithm is extended to solve the proposed model because it avoids the explicit calculation of probability distributions. The space complexity of the algorithm is only linear in the number of RE states and is independent of the enormous (four-dimensional) state space of the Markov process. Its time complexity is a linear function of the product of the queue capacity and the number of RE states. Our model is validated versus simulation estimates. The obtained conditional performance measures can accurately capture the queue accumulation and dissipation and reveal the effect of randomly changing environments. Numerical experiments provide some interesting findings. (1) The proposed stationary model coincides with the transient M( t )/G x / C / C fluid queuing model under special conditions. (2) Under high traffic intensities, increasing the randomness in the duration time of the RE state leads to an obvious growth in the conditional queue length. (3) An increase in the facility length leads to an increase or a decrease in the average output rate, depending on whether the congestion dissipates effectively in one cycle. (4) A larger width is required to obtain the maximum average output rate for traffic demand with a greater nonuniformity.

Zonal jets and inertia–gravity waves are ubiquitous on planets such as Earth, Jupiter and Saturn. Motivated by the modification of energy flux of balanced flow by inertia–gravity waves, this paper studies the impact of near-inertial waves (NIWs) on zonal jets on a $\beta$ -plane. Using a two-dimensional quasi-geostrophic and NIW coupled system on a $\beta$ -plane (Xie & Vanneste, J. Fluid Mech., vol. 774, 2015, pp. 143–169), we find NIWs catalytically impact several features of zonal jets. The NIWs inhibit jet formation due to the waves’ catalytic induction of downscale mean energy flux. As the strength of NIWs increases, a critical point exists beyond which zonal jets are annihilated. The jet spacing is captured by the Rhines scale $L\sim \sqrt {U/\beta }$ with $U$ estimated from the upscale energy flux induced by the mean flow alone, which again shows that the NIWs’ impact is catalytic. Also, the temporal asymmetry of NIWs leads to the spatial asymmetry of jet dynamics. The jet profiles are asymmetric with a stronger shear on the left flank. And similar to the left turning of vortex dipole under the impact of NIWs, the NIW-modified jets migrate poleward. The NIWs also show a catalytic role in jet migration: the net momentum flux directly induced by NIWs is of secondary importance in the zonal mean momentum dynamics and impedes jet migration, while the advective effect of NIW-modified mean flow dominates the jet migration velocity.

We explore the spatial-temporal structure functions of Burgers turbulence driven by a temporal Ornstein-Uhlenbeck (OU) process, where the characteristic time scale of the OU process is much larger than that of the energy flux across spatial scales. Based on the K\'arm\'an-Howarth-Monin equation, we obtain an expression for the third-order spatial-temporal structure function away from the dissipation scale. This expression combines Kolmogorov's exact result of spatial structure function and the exponential temporal decay of the external force. We numerically justify this expression and find that the high-order structure functions also decay exponentially, however, the dependence of decay rates on order is different for the odd- and even-order structure functions. Comparing the OU-driven Burgers turbulence with that driven by temporal white noise, their spatial structure functions are identical when the energy injection rates are the same, which justifies Kolmogorov's theory, but these two systems' temporal structure functions differ. Also, the velocity pdf in the OU-driven Burgers turbulence shows a bimodal distribution, contradicting the near-Gaussian distribution in white-noise-driven turbulence., Comment: 18 pages, 9 figures

Exposure to audiovisual input has been recognised as an engaging approach for implicit vocabulary learning. Recent studies have compared the effectiveness of different types of subtitling in enhancing viewers' learning gains in single word vocabulary, but research on multiword vocabulary , especially collocations, remains limited. The present study aims to examine which type of subtitling (i.e., English–Chinese subtitles or English-only subtitles) is more effective in L2 implicit collocation learning, and it attempts to identify Chinese L2 learners’ learning difficulties when acquiring collocations. Experiments and interviews were conducted with 66 Chinese undergraduates to investigate their acquisition, in terms of both form recognition and meaning recall. Results indicate that compared with English-only subtitles, the effectiveness of English–Chinese subtitles in enhancing the acquisition of L2 collocation meaning is more significant, although English-only subtitles can be more helpful in reinforcing collocation forms. The results of the interviews also suggest that participants are more likely to encounter difficulties with contextually marked phrasal verbs and idioms, and affective filters should be considered when analysing individual differences. The findings support the use of L1 in subtitles to improve the learning efficiency of vocabulary meaning, as well as to help teachers identify the sources of students’ learning difficulties.

Applying Chinese medicine (CM) is an important strategy for malignant tumor treatment in China. One of the significant characteristics of CM is to treat diseases based on syndrome differentiation. For Western medicine, it is of important clinical significance to formulate guidelines for the diagnosis and treatment of cancer patients based on the characteristics of disease differentiation. In Chinese clinical practice, the combination of disease differentiation and syndrome differentiation is an important feature for cancer treatment in the past. Currently, molecular profiling and genomic analysis-based precision medicine optimizes the anticancer drug design and holds the greatest success in treating cancer patients. Therefore, we want to know which populations of cancer patients can benefit more from CM treatment if the theory of precision medicine is applied to CM clinical practice. So, we developed a novel diagnostic and therapeutic strategy "disease-syndrome differentiation-genomic profiling-prescriptions" for cancer patients by CM syndrome differentiation and precision medicine. As a result, this strategy has greatly enhanced the anti-tumor efficacy of CM and improved clinical outcomes for cancer patients with some gene mutations. Our idea will hopefully establish a novel approach for the inheritance and innovation of CM.

Body temperature is an important indicator of health monitoring. However, since animals are covered with fur, it is difficult to obtain their accurate body temperature with the traditional infrared measurement technology. To deal with this problem, this research proposes a non-contact real-time monitoring system using an infrared method combined with object detection. The system is developed based on general infrared thermal imaging technology and an infrared thermal imaging module with an image tracking algorithm. YOLO is used to detect animals, and a thermal imaging camera is used to measure the body surface temperature of animals. The result shows that the proposed system can accurately measure the body temperature of animals without being influenced by animals’ fur. In the future, it can be applied to monitor the body temperature of sick animals in veterinary hospitals.

Suppl Figure legends

NO-mediated regulation of PDL-1 in cancer cells.

Lack of LDH-A results in M1 polarization and suppression of tumor growth.

mRNA expression of activation markers and cytokines in CD8 T cells.

Supplementary Figures 1-7 and Supplementary Figure legends

Co-culture of RAW macrophages and cancer cells.

Immunometabolism is emerging as a critical determinant of cancer pathophysiology. In this study, we explored the contributions of macrophage-expressed lactate dehydrogenase-A (LDH-A) to tumor formation in a K-Ras murine model of lung carcinoma. Myeloid-specific deletion of LDH-A promoted accumulation of macrophages with a CD86high and MCP-1high M1-like phenotype that suppressed tumor growth. This phenotypic effect was accompanied by reduced VEGF expression and angiogenesis, diminished numbers of PD-L1+ cancer cells, increased numbers of CD3+ T cells, and activation status of CD8+ T cells. Furthermore, it was associated with more pronounced antitumor T-cell immunity via induction of IL17 and IFNγ-producing CD8+ T (Tc17 and Tc1) cells, likely via suppression of lactate-driven PD-L1 expression. Our results suggest that expressions of LDH-A and lactate by macrophage in the tumor microenvironment are major drivers of T-cell immunosuppression, strongly supporting the concept of targeting stromal LDH-A as an effective strategy to blunt tumoral immune escape. Cancer Res; 77(13); 3632–43. ©2017 AACR.

Expression of CD86 and PDL-1 in macrophages lacking LDH-A.

LDH-A in macrophages controls expression of HO-1.

Background Super-enhancers (SEs), driving high-level expression of genes with tumor-promoting functions, have been investigated recently. However, the roles of super-enhancer-associated lncRNAs (SE-lncRNAs) in tumors remain undetermined, especially in gliomas. We here established a SE-lncRNAs expression-based prognostic signature to choose the effective treatment of glioma and identify a novel therapeutic target. Methods Combined analysis of RNA sequencing (RNA-seq) data and ChIP sequencing (ChIP-seq) data of glioma patient-derived glioma stem cells (GSCs) screened SE-lncRNAs. Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets served to construct and validate SE-lncRNA prognostic signature. The immune profiles and potential immuno- and chemotherapies response prediction value of the signature were also explored. Moreover, we verified the epigenetic activation mechanism of LINC00945 via the ChIP assay, and its effect on glioma was determined by performing the functional assay and a mouse xenograft model. Results 6 SE-lncRNAs were obtained and identified three subgroups of glioma patients with different prognostic and clinical features. A risk signature was further constructed and demonstrated to be an independent prognostic factor. The high-risk group exhibited an immunosuppressive microenvironment and was higher enrichment of M2 macrophage, regulatory T cells (Tregs), and Cancer-associated fibroblasts (CAFs). Patients in the high-risk group were better candidates for immunotherapy and chemotherapeutics. The SE of LINC00945 was further verified via ChIP assay. Mechanistically, BRD4 may mediate epigenetic activation of LINC00945. Additionally, overexpression of LINC00945 promoted glioma cell proliferation, EMT, migration, and invasion in vitro and xenograft tumor formation in vivo. Conclusion Our study constructed the first prognostic SE-lncRNA signature with the ability to optimize the choice of patients receiving immuno- and chemotherapies and provided a potential therapeutic target for glioma.

LDH-A deletion resets tumor microenvironment.

Background Litaf protein is a newly discovered inflammatory protein, whether it is involved in the formation of atherosclerosis remains unclear; Methods Ten C57BL/6J mice and ten C57BL/6J mice with knockout of Litaf gene (C57BL/6J− Litaf−) were purchased from Animal Culture Center of Huazhong University of Science and Technology divided into two groups: control group and Litaf−/− group. Animals were given a normal diet and euthanized after 16-week culture. Mice, heart and whole aorta were isolated, and the aortic root of the mouse was taken for frozen sections; used for oil red staining and immunohistochemical staining (α-actin, CD68, Masson), and then compared the oil red staining area and the positive proportion of immunohistochemical staining in each group; at the same time, a sufficient amount of mouse blood was collected for extraction Plasma protein and RNA, monitoring the expression of inflammation-related proteins by Western and RT-PCR. Results Oil red staining of the aortic root sections of the mice in each group showed that the area of atherosclerotic plaques in Litaf−/− group was less than control group (P −/− group was higher than that in the control group, while the results were opposite after Masson stainning(P −/− group were lower than those in the control group (P

Introduction: Dimethyl phthalate (DMP) which has been widely detected in water is neurotoxic to humans and should be effectively eliminated. Persulfate-based advanced oxidation processes are considered to be reliable methods aiming at emerging contaminants degradation, while an efficient catalyst is urgently needed for the activation of the reaction. As a typical 2D material, 1T-MoS2 is expected to be applied to the activation of persulfate owing to its abundant active sites and excellent electrical conductivity. In practical applications, 1T-MoS2 has the phenomenon of reunion which affects the exposure of its catalytic sites.Methods: Therefore, in this study, we used waste cow manure as a raw material to prepare biochar and achieved high exposure of 1T-MoS2 activation sites by loading 1T-MoS2 onto the surface of cow manure biochar through hydrothermal synthesis. The prepared composite catalytic material CMB@1T-MoS2 was used to activate PMS for the degradation of DMP.Results: It was found that CMB@1T-MoS2 has better effect than CMB or 1T-MoS2 alone for the degradation of DMP, reaching 77.65% at pH = 3. Under alkaline conditions, the degradation rate of DMP was reduced due to the inhibition of the catalytic process. Among the different coexisting anions, HCO-3 interfered and inhibited the degradation process the most, leading to the lowest degradation rate of DMP with 42.45%.Discussion: The quenching experiments and EPR analysis showed that SO-4• and •OH were the main ROS in the CMB@1T-MoS2/PMS process. This study promotes the resourceful use of cow manure and is expected to provide a novel persulfate-based advanced oxidation process catalyzed by CMB@1T-MoS2 for the elimination of DMP in an aqueous environment.

Background Idiopathic pulmonary fibrosis (IPF) is a condition that may cause persistent pulmonary damage. The transformation of pericytes into myofibroblasts has been recognized as a key player during IPF progression. This study aimed to investigate the functions of lncRNA growth arrest-specific transcript 5 (GAS5) in myofibroblast transformation during IPF progression. Methods We created a mouse model of pulmonary fibrosis (PF) via intratracheal administration of bleomycin. Pericytes were challenged with exogenous transforming growth factor-β1 (TGF-β1). To determine the expression of target molecules, we employed quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemical and immunofluorescence staining. The pathological changes in the lungs were evaluated via H&E and Masson staining. Furthermore, the subcellular distribution of GAS5 was examined using FISH. Dual-luciferase reporter assay, ChIP, RNA pull-down, and RIP experiments were conducted to determine the molecular interaction. Results GAS5 expression decreased whereas PDGFRα/β expression increased in the lungs of IPF patients and mice with bleomycin-induced PF. The in vitro overexpression of GAS5 or silencing of PDGFRα/β inhibited the TGF-β1-induced differentiation of pericytes to myofibroblasts, as evidenced by the upregulation of pericyte markers NG2 and desmin as well as downregulation of myofibroblast markers α-SMA and collagen I. Further mechanistic analysis revealed that GAS5 recruited KDM5B to promote H3K4me2/3 demethylation, thereby suppressing PDGFRα/β expression. In addition, KDM5B overexpression inhibited pericyte–myofibroblast transformation and counteracted the promotional effect of GAS5 knockdown on pericyte–myofibroblast transformation. Lung fibrosis in mice was attenuated by GAS5 overexpression but promoted by GAS5 deficiency. Conclusion GAS5 represses pericyte–myofibroblast transformation by inhibiting PDGFRα/β expression via KDM5B-mediated H3K4me2/3 demethylation in IPF, identifying GAS5 as an intervention target for IPF.

Background: Gliomas are the most common malignant tumor of the central nervous system(CNS). Dysregulated pseudogene expression was significantly associated with the prognosis of glioma patients. However, the role of abnormal methylation of pseudogenes in glioma prognosis has not yet been studied. This study aimed to develop a novel six-methylated pseudogenes signature to predict the prognosis of glioma patients. Methods: Based on lasso regression analysis, a risk signature for six methylated pseudogenes was constructed. Next, a prognostic nomogram including grade, age, gender, and radiation was constructed. Besides, the immune cell infiltration analyses of patients based on the six-methylated pseudogenes were performed. Meanwhile, consensus cluster analysis of six methylated pseudogenes identified two glioma patient subgroups. Furthermore, GO, KEGG and GSEA were used to analyze related genes. Finally, the ability of glioma to proliferate, migrate and invade was used to verify subsequent functions. Results: In this study, six gene models consisting of methylated pseudogenes were identified and validated, and showed strong prognostic power in the training dataset, validation dataset, and entire dataset. The calibration diagram showed good predictive performance. In addition, the proportion of B cells and CD4+T cells was significantly higher in the high-risk group, while the proportion of mono cells was lower. By silencing the expression of SBF1P1 and SUMO1P1, the ability of glioma to proliferate, migrate, and invade can be inhibited. Conclusions: The six-methylated pseudogene signature may be a novel predictor for prognostic assessment of glioma patients, which could accurately predict patient prognosis.

Background: Long non-coding RNAs (lncRNAs) are tissue-specific expression patterns and dysregulated in cancer, how they are regulated is still unclear. We aimed to investigate the functions of glioma-specific lncRNA LIMD1-AS1 activated by super-enhancer (SE) and identify the potential mechanisms. Methods: To investigate the clinical significance of LIMD1-AS1, we analyzed its expression levels in a publicly available dataset and 43 glioma samples from our cohort. Functional assays, including the CCK8, colony formation, and transwell assays, were used to determine the oncogenic role of LIMD1-AS1 in human glioma progression. Furthermore, RNA pull-down, mass spectrometry, Chromatin immunoprecipitation, dCas9-KRAB interference, and Dual-Luciferase Reporter Assays were used to determine the mechanism of LIMD1-AS1 in glioma progression. Animal experiments were used to determine the role of LIMD1-AS1 in glioma tumorigenicity in vivo. Results: In this paper, we identified a SE-driven lncRNA, LIMD1-AS1, which is expressed at significantly higher levels in glioma than in normal brain tissue. High LIMD1-AS1 levels were significantly associated with a shorter survival time of glioma patients. LIMD1-AS1 overexpression significantly enhanced glioma cells proliferation, colony formation, migration, and invasion, whereas LIMD1-AS1 knockdown inhibited their proliferation, colony formation, migration and invasion, and the xenograft tumor growth of glioma cells in vivo. Mechanically, inhibition of CDK7 significantly attenuates MED1 recruitment to the super-enhancer of LIMD1-AS1, and then decreases the expression of LIMD1-AS1. Most importantly, LIMD1-AS1 could directly bind to HSPA5, leading to the activation of interferon signaling. Conclusions: Our findings support the idea that CDK7 mediated-epigenetically activation of LIMD1-AS1 plays a crucial role in glioma progression, and provides a promising therapeutic approach for patients with glioma.

Near-inertial waves (NIWs), pervasive and dominating the mixing process in the upper ocean, are observed to concentrate in anticyclones. Based on the NIW amplitude equation derived by Young & Ben Jelloul, which captures dispersion and effects of vortical flow’s advection and refraction, this work analytically and numerically studies the influence of scale on the concentration of NIWs. For a sinusoidal background shear flow, the exact solutions expressed as periodic Mathieu functions are approximated by a Gaussian envelope with Hermite polynomial oscillations to determine the distance to the anticyclones. Two dimensionless parameters control NIW’s dynamics: (i) h/Ψ, where h is a constant capturing the strength of wave dispersion and Ψ is the magnitude of the background streamfunction capturing the ratio of dispersion to refraction; (ii) LΨ/LM, the ratio between the spatial scales of background flow and NIWs, where LΨ and LM, respectively, captures the relative strength between advection and refraction. The refraction by the background flow leads to the concentration in the regions with negative vorticity, dispersion controls the variance of the wave packet, and the advection shifts the center of NIWs away from the peak of negative vorticity, which is scale-dependent. When the refraction effect dominates, i. e., small LΨ/LM, NIWs concentrate in anticyclones, and this concentration becomes stronger as h/Ψ decreases; when the advection effect dominates, i.e., large LΨ/LM, the NIW’s concentration is less obvious. Numerical simulations with backgrounds of sinusoidal shear, vortex quadrupoles and random vortices confirm these results. Considering the similarity between the NIW amplitude equation and the Schrödinger equation, we propose a new perspective that the combined effect of uncertainty relation and energy conservation leads to large-scale NIW’s concentration in anticyclones.

To investigate the regulatory effect and mechanism of circular RNA PVT1 (circPVT1) in proliferation and chemoresistance of osteosarcoma (OS) cells.The expression of circPVT1 in human OS and adjacent normal tissues was detected. The correlation between circPVT1 expression and clinical features of OS was analyzed. The expressions of circPVT1 and miR-24-3p in OS cells resistant to cisplatin, doxorubicin or methotrexate and parental OS cells were detected after cell transfection. CCK-8 and colony formation assay assessed the viability and proliferative ability of OS cells. qRT-PCR and Western blotting measured the expression of KLF8. Dual-luciferase reporter and RNA pull-down assays verified the targeting relationships of circPVT1/miR-24-3p and miR-24-3p/KLF8.CircPVT1 was over-expressed in OS tissues and cells, and correlated with clinical features of OS. Over-expressed circPVT1 reduced the survival of OS patients. CircPVT1 was up-regulated in chemoresistant OS cells compared to their parental cells. CircPVT1 inhibition suppressed the proliferation and chemoresistance of OS cells. MiR-24-3p was under-expressed in OS cells and further down-regulated in chemoresistant cells. CircPVT1 could bind and down-regulate miR-24-3p. MiR-24-3p overexpression inhibited the proliferation and chemoresistance of OS cells. KLF8 was over-expressed in OS cells and further up-regulated in chemoresistant cells. MiR-24-3p negatively regulated the expression of KLF8.CircPVT1 mediates proliferation and chemoresistance of OS cells via the miR-24-3p/KLF8 axis. The findings may provide guidance for clinical treatment of OS.

In mixed traffic with autonomous vehicles, the relationship between speed and lane-changing behavior is an important basis for mixed traffic control. In this study, we use empirical, simulation, and data-driven methods to study the relationship between speed and lane change rates in mixed traffic under different autonomous vehicle penetration rates. We use the empirical data to establish the corresponding road simulation models. Based on the simulation model, the traffic flow simulation experiments under the conditions of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90% penetration rate of autonomous vehicles were carried out. The analysis of the simulation results found that: (1) the penetration of autonomous vehicles into the road has a positive impact on the lanes far away from the entrance and exit, while the impact on the lanes closer to the entrance and exit is not obvious. (2) Lane-changing behavior has effectively decreased with the penetration of autonomous vehicles, but it is not obvious when the penetration rate exceeds 10%, and there is no significant drop in the lane connecting the entrance and exit. (3) There is a linear relationship between speed and lane-changing rate. Under different penetration rates, the data-driven analysis is used to perform multiple linear regressions, and the regression formula fits are all above 0.7. Based on the above findings, the linear formula of the fitting is proposed, and the value interval of the parameters in different states is given as well. Due to the small changes in the parameter values under different permeability conditions, the model has a certain degree of stability. The speed-lane change rate model proposed in this study can better describe the relationship between the speed of the ring-shaped urban expressway and the lane-changing behavior in the mixed traffic environment with the larger traffic flow.