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Abstract Hepatocellular carcinoma (HCC) is the primary malignant tumor of the liver. c-Myc is one of the most common oncogenes in clinical settings, and amplified levels of c-Myc are frequently found in HCC. Histone deacetylase inhibitors (HDACi), such as Trichostatin A (TSA), hold enormous promise for the treatment of HCC. However, the potential and mechanism of TSA in the treatment of c-Myc-induced HCC are unclear. In this study, we investigated the effects of TSA treatment on a c-Myc-induced HCC model in mice. TSA treatment delayed the development of HCC, and liver function indicators such as ALT, AST, liver weight ratio, and spleen weight ratio demonstrated the effectiveness of TSA treatment. Oil red staining further demonstrated that TSA attenuated lipid accumulation in the HCC tissues of mice. Through mRNA sequencing, we identified that TSA mainly affected cell cycle and fatty acid degradation genes, with alcohol dehydrogenase 4 (ADH4) potentially being the core molecular downstream target. QPCR, immunohistochemistry, and western blot analysis revealed that ADH4 expression was repressed by c-Myc and restored after TSA treatment both in vitro and in vivo. Furthermore, we observed that the levels of total NAD+ and NADH, NAD+, NAD+/NADH, and ATP concentration increased after c-Myc transfection in liver cells but decreased after TSA intervention. The levels of phosphorylated protein kinase B (p-AKT) and p-mTOR were identified as targets regulated by TSA, and they governed the ADH4 expression and the downstream regulation of total NAD+ and NADH, NAD+, NAD+/NADH, and ATP concentration. Overall, our study suggests that TSA has a therapeutic effect on c-Myc-induced HCC through the AKT-mTOR-ADH4 pathway. These findings provide valuable insights into the potential treatment of HCC using TSA and shed light on the underlying molecular mechanisms involved.

Abstract Pancreatic cancer (PC) is a deadly disease, and its post‐transcriptional gene regulation mechanism remains unclear. The abundant extracellular matrix (ECM) in PC plays an important role in tumor progression. This study is the first to focus on the role of N6‐methyladenosine (m6A) RNA methylation, an emerging post‐transcriptional regulatory mechanism, in the regulation of the ECM in PC. Here, we found that ADAMTS2, COL12A1, and THBS2 were associated with the prognosis of PC by comprehensive analysis of differentially expressed genes from two independent GEO expression profile datasets and m6A‐related genes in RMVar database (PAAD). GO and KEGG enrichment analysis found that these m6A‐related targets are chiefly functionally concentrated in the ECM region and participate in ECM signal transduction. Correlation analysis revealed that these genes can be regulated by the demethylase FTO. Cell biology function assays showed that knockdown of FTO‐inhibited PC cell abilities to migrate and invade in vitro. qRT‐PCR and MeRIP experiments showed that after knockdown of FTO, the mRNA levels of ADAMTS2, COL12A1, and THBS2 and their m6A modification levels were significantly reduced. These results indicate that m6A RNA demethylation is associated with the regulation of ECM in PC. In conclusion, m6A RNA demethylase FTO regulates ECM‐related genes and promotes PC cell abilities to migrate and invade, our work provides a new perspective on the molecular mechanism of PC progression.

Alzheimer’s disease is characterized by sustained neuroinflammation leading to memory loss and cognitive decline. The past decade has witnessed tremendous efforts in Alzheimer’s disease research; however, no effective treatment is available to prevent disease progression. An increasing body of evidence suggests that neuroinflammation plays an important role in Alzheimer’s disease pathogenesis, alongside the classical pathological hallmarks such as misfolded and aggregated proteins (e.g., amyloid-beta and tau). Firstly, this review summarized the clinical and pathological characteristics of Alzheimer’s disease. Secondly, we outlined key aspects of glial cell-associated inflammation in Alzheimer’s disease pathogenesis and provided the latest evidence on the roles of microglia and astrocytes in Alzheimer’s disease pathology. Then, we revealed the double-edged nature of inflammatory cytokines and inflammasomes in Alzheimer’s disease. In addition, the potential therapeutic roles of innate immunity and neuroinflammation for Alzheimer’s disease were also discussed through these mechanisms. In the final section, the remaining key problems according to the current research status were discussed.

Pancreatic cancer (PC) is one of the most fatal cancers with a very poor prognosis. Here, we found that N6-methyladenosine (m6A) RNA demethylase fat mass and obesity-related protein (FTO) promote the growth, migration and invasion of PC. FTO expression level is increased in human PC and is associated with poor prognosis of PC patients. Knockdown of FTO increases m6A methylation of TFPI-2 mRNA in PC cells, thereby increasing mRNA stability via the m6A reader YTHDF1, resulting in up-regulation of TFPI-2 expression, and inhibits PC proliferation, colony formation, sphere formation, migration and invasion in vitro, as well as tumour growth in vivo. Rescue assay further confirms that FTO facilitates cancer progression by reducing the expression of TFPI-2. Mechanistically, FTO promotes the progression of PC at least partially through reducing m6A/YTHDF1 mediated TFPI-2 mRNA stability. Our findings reveal that FTO, as an m6A demethylase, plays a critical role in promoting PC growth, migration and invasion, suggesting that FTO may be a potential therapeutic target for treating PC.

Objectives This study aimed to conduct a thorough analysis of fluid retention-associated adverse events (AEs) associated with BCR::ABL inhibitors.Design A retrospective pharmacovigilance study.Setting Food and Drug Administration Adverse Event Reporting System (FAERS) database for BCR::ABL inhibitors was searched from 1 January 2004 to 30 September 2021.Main outcome measures Reporting OR (ROR) and 95% CI were used to detect the signals. ROR was calculated by dividing the odds of fluid retention event reporting for the target drug by the odds of fluid retention event reporting for all other drugs. The signal was considered positive if the lower limit of 95% CI of ROR was >1. The analysis was run only considering coupled fluid retention events/BCR::ABL inhibitors with at least three cases.Results A total of 97 823 reports were identified in FAERS. Imatinib had the most fluid retention signals, followed by dasatinib and nilotinib, while bosutinib and ponatinib had fewer signals. Periorbital oedema (ROR=24.931, 95% CI 22.404 to 27.743), chylothorax (ROR=161.427, 95% CI 125.835 to 207.085), nipple swelling (ROR=48.796, 95% CI 26.270 to 90.636), chylothorax (ROR=35.798, 95% CI 14.791 to 86.642) and gallbladder oedema (ROR=77.996, 95% CI 38.286 to 158.893) were the strongest signals detected for imatinib, dasatinib, nilotinib, bosutinib and ponatinib, respectively. Pleural effusion, pericardial effusion and pulmonary oedema were detected for all BCR::ABL inhibitors, with dasatinib having the highest RORs for pleural effusion (ROR=37.424, 95% CI 35.715 to 39.216), pericardial effusion (ROR=14.146, 95% CI 12.649 to 15.819) and pulmonary oedema (ROR=11.217, 95% CI 10.303 to 12.213). Patients aged ≥65 years using dasatinib, imatinib, nilotinib or bosutinib had higher RORs for pleural effusion, pericardial effusion and pulmonary oedema. Patients aged ≥65 years and females using imatinib had higher RORs for periorbital oedema, generalised oedema and face oedema.Conclusions This pharmacovigilance study serves as a clinical reminder to physicians to be more vigilant for fluid retention-associated AEs with BCR::ABL inhibitors.

Rutin, a flavonoid found in fruits and vegetables, is a potential anticancer compound with strong anticancer activity. Therefore, electrochemical sensor was developed for the detection of rutin. In this study, CoWO4 nanosheets were synthesized via a hydrothermal method, and porous carbon (PC) was prepared via high-temperature pyrolysis. Successful preparation of the materials was confirmed, and characterization was performed by transmission electron microscopy, scanning electron microscopy, and X-ray photoelectron spectroscopy. A mixture of PC and CoWO4 nanosheets was used as an electrode modifier to fabricate the electrochemical sensor for the electrochemical determination of rutin. The 3D CoWO4 nanosheets exhibited high electrocatalytic activity and good stability. PC has a high surface-to-volume ratio and superior conductivity. Moreover, the hydrophobicity of PC allows large amounts of rutin to be adsorbed, thereby increasing the concentration of rutin at the electrode surface. Owing to the synergistic effect of the 3D CoWO4 nanosheets and PC, the developed electrochemical sensor was employed to quantitively determine rutin with high stability and sensitivity. The sensor showed a good linear range (5–5000 ng/mL) with a detection limit of 0.45 ng/mL. The developed sensor was successfully applied to the determination of rutin in crushed tablets and human serum samples.

Abstract Chinese medicine (CM) has a long history in the treatment of psoriasis, and its different understanding angle and treatment mode from modern medicine have unique wisdom. In this article, we consulted a large number of literatures and collected data in order to systematically clarify how CM understands psoriasis, including the classification and judgment of syndrome types, the diagnosis and thinking of etiology and pathogenesis, the application of treatment ideas, principles, methods and various prescriptions, and suggestions on patient care, so as to provide a clear CM treatment process and experience for the world clinic. In addition, we analyzed the efficacy and safety through clinical data, and summarize the methods and prescriptions worthy of promotion, so as to provide reference for doctors to prescribe prescriptions and medication. Finally, we found that compared with modern medicine, CM has unique advantages in the treatment of psoriasis, including the uniqueness of syndrome classification, the abundantly and flexibility of treatment ideas. Not only many famous doctors have studied the ideas in ancient books, but also made great efforts to innovate, which has left a lot of valuable experiences for clinical practice. Moreover, a large number of treatment methods, prescriptions and medicines have achieved high effectiveness and safety in clinical practices for many years, which has been proved to be worthy of clinical reference and in-depth research. In addition, we also think about the deficiencies of CM in the treatment of psoriasis and the direction of breakthrough combined with modern medicine. The treatment of psoriasis with CM is worth popularizing, and we hope it can benefit more patients.

Abstract Background Long non-coding RNAs (lncRNA) are reported to influence colorectal cancer (CRC) progression. Currently, the functions of the lncRNA ZNF561 antisense RNA 1 (ZNF561-AS1) in CRC are unknown. Methods ZNF561-AS1 and SRSF6 expression in CRC patient samples and CRC cell lines was evaluated through TCGA database analysis, western blot along with real-time PCR. SRSF6 expression in CRC cells was also examined upon ZNF561-AS1 depletion or overexpression. Interaction between miR-26a-3p, miR-128-5p, ZNF561-AS1, and SRSF6 was examined by dual luciferase reporter assay, as well as RNA binding protein immunoprecipitation (RIP) assay. Small interfering RNA (siRNA) mediated knockdown experiments were performed to assess the role of ZNF561-AS1 and SRSF6 in the proliferative actives and apoptosis rate of CRC cells. A mouse xenograft model was employed to assess tumor growth upon ZNF561-AS1 knockdown and SRSF6 rescue. Results We find that ZNF561-AS1 and SRSF6 were upregulated in CRC patient tissues. ZNF561-AS1 expression was reduced in tissues from treated CRC patients but upregulated in CRC tissues from relapsed patients. SRSF6 expression was suppressed and enhanced by ZNF561-AS1 depletion and overexpression, respectively. Mechanistically, ZNF561-AS1 regulated SRSF6 expression by sponging miR-26a-3p and miR-128-5p. ZNF561-AS1-miR-26a-3p/miR-128-5p-SRSF6 axis was required for CRC proliferation and survival. ZNF561-AS1 knockdown suppressed CRC cell proliferation and triggered apoptosis. ZNF561-AS1 depletion suppressed the growth of tumors in a model of a nude mouse xenograft. Similar observations were made upon SRSF6 depletion. SRSF6 overexpression reversed the inhibitory activities of ZNF561-AS1 in vivo, as well as in vitro. Conclusion In summary, we find that ZNF561-AS1 promotes CRC progression via the miR-26a-3p/miR-128-5p-SRSF6 axis. This study reveals new perspectives into the role of ZNF561-AS1 in CRC.

Marine alkaloids have novel structures and antitumor activities. Therefore, we synthesized rhopaladins’ analogs from marine alkaloids rhopaladins A-D and modified their structures to synthesize 4-benzylidene-5-pyrrolidone derivatives. Among the compounds, (2E, 4E)-4-(4-chlorobenzylidene)-2-(4-chlorostyryl)-N-cyclohexyl-1-(4-fluorophenyl)-5-oxopyrrolidine-2-carboxamide (RPDPRH) has high efficiency and less hepatotoxicity, with IC50 values of 4.66, 6.42, 17.66, 15.2, 12.36, 22.4, and 243.2 μM in vitro anti-proliferative activity testing against cervical cancer C-33A, CaSki, SiHa, and HeLa cells, human hepatocarcinoma HepG2 and 7402 cells, and human normal liver LO2 cells, respectively. In particular, RPDPRH has similar activity to cisplatin on human hepatocarcinoma cells, and cisplatin served as a positive control in our study. Next, the apoptosis of HepG2 and 7402 cells induced by RPDPRH at different concentrations was detected by Annexin V/PI flow cytometry. Moreover, the expression of apoptotic proteins was detected by Western blot analysis. Finally, the results showed that RPDPRH could induce apoptosis of hepatocarcinoma cells by regulating Bax and Bcl-2 expressions. In summary, our results indicate that RPDPRH has the potential to serve as an antitumor agent and plays a significant role in future studies.

Lung cancer is a malignant tumor with high incidence and mortality in the world, which seriously threatens people’s safety and health. Early diagnosis of lung cancer is the key part in the process of prevention and treatment of lung cancer. It can improve the survival of patients with lung cancer. Exosomes are closely related to the invasion and metastasis process of tumor, it plays an important role in the development of lung cancer. Biomarkers based on exosomes have become a powerful diagnostic tool of lung cancer. Exosomes are lipid bilayer vesicles with uniform size and diameter of 30 nm-200 nm secreted by cells. Exosomes contain different types of nucleic acids and proteins. These nucleic acids and proteins are derived from their parent cells (including parent cancer cells), which have a wide range of physiological functions, including immune regulation, intercellular communication and other physiological activities. Biomacromolecules in exosomes, such as single-stranded RNA, long noncoding RNA, microRNA, protein and lipids, which can provide valuable genetic information for early clinical diagnosis of lung cancer. This review described the origin, structural characteristics, extraction methods, biological characteristics of exosomes and the relationships of exosomes in the early diagnosis of lung cancer.

Mixed use has been extensively applied as an urban planning principle and hinders the study of single urban functions. To address this problem, it is worth decomposing the mixed use. Inspired by the concept of spectral unmixing in remote sensing applications, this paper proposes a framework for mixed-use decomposition based on big geo-data. Mixed-use decomposition in terms of human activities differs from traditional land use research, and it is more reasonable to infer the actual urban function of land. The framework consists of four steps, namely temporal activity signature extraction, urban function base curve extraction, mixed-use decomposition, and result validation. First, the temporal activity signatures (TASs) of each zone are extracted as the proxy of human activity patterns. Second, the diurnal TASs of routine activities are extracted as urban function base curves (i.e. endmembers). Third, a linear decomposition model is used to decompose the mixed use and obtain multiple results (urban function composition, dynamic activity proportions, and the mixing index). Finally, result validation strategies are concluded. This framework offers method extensibility and has few requirements for the input data. It is validated by means of a case study of Beijing, based on a social media check-in dataset.

Recently, miRNAs have become a promising biomarker for disease diagnostics. miRNA-145 is closely related to strokes. The accuracy determination of miRNA-145 (miR-145) in stroke patients still remains challenging due to its heterogeneity and low abundance, as well as the complexity of the blood matrix. In this work, we developed a novel electrochemical miRNA-145 biosensor via subtly coupling the cascade strand displacement reaction (CSDR), exonuclease III (Exo III), and magnetic nanoparticles (MNPs). The developed electrochemical biosensor can quantitatively detect miRNA-145 ranging from 1 × 102 to 1 × 106 aM with a detection limit as low down as 100 aM. This biosensor also exhibits excellent specificity to distinguish similar miRNA sequences even with single-base differences. It has been successfully applied to distinguish healthy people from stroke patients. The results of this biosensor are consistent with the results of the reverse transcription quantitative polymerase chain reaction (RT-qPCR). The proposed electrochemical biosensor has great potential applications for biomedical research on and clinical diagnosis of strokes.

Exosomal MicroRNA-21 (miRNA-21, miR-21) is significantly up-regulated in blood samples of patients with lung cancer. Exosomal-derived miR-21 can be used as a promising biomarker for the early diagnosis of lung cancer. This paper develops a fluorescent biosensor based on the combination of magnetic nanoparticles (MNPs), cascade strand displacement reaction (CSDR) and CRISPR/Cas12a to detect the exosomal miR-21 from lung cancer. The powerful separation performance of MNPs can eliminate the potential interference of matrix and reduce the background signal, which is very beneficial for the improvement of specificity and sensitivity. The CSDR can specifically transform one miR-21 into plenty of DNA which can specifically trigger the trans-cleavage nuclease activity of Cas12a, resulting in the cleavage of ssDNA bi-labeled with fluorescent and a quencher. Under the optimized experimental conditions, the developed fluorescence biosensor exhibited high sensitivity and specificity towards the determination of exosomal-derived miR-21 with a linear range from 10 to 1 × 105 fM and a low detection limit of about 0.89 fM. Most importantly, this method can be successfully applied to distinguish the exosomal miR-21 from the lung cancer patients and the healthy people.

A novel process ‘coalescence-airflotation-carrier preferential adsorption’ utilising an oil-water separation flotation column with a unique structure was used in the oil-water separation field. The oil-water separation flotation column contains the cyclonic separation and airflotation separation which has advantages in oily sewage treatment, especially in polymer-flooding-drive oily sewage treatment. In this paper, different dimensions of flotation column with 1 m3 d−1, 30 m3 d−1 and 2,000 m3 d−1 oil-water separation systems were investigated. In addition, several operating parameters which impact separation, such as feeding speed, aeration rate, circulating pressure, adsorbents consumption and frother consumption were also investigated. The optimum operating parameters determined for 1 m3 d−1 the oil-water separation flotation column were a feeding speed of 0.042 m3 h−1, an aeration rate of 0.10 m3 h−1, a coal consumption of 4 (g coal)·(g oil)−1, a frother consumption of 10 mg L−1, and a circulating pressure of 0.12 MPa. The novel process cost reduced 55.8% than conventional two-stage airflotation process. In the 2,000 m3 d−1 oil-water separation experiment, the oil concentration and the oil removal efficiency of outlet are 23.39 mgL−1, 97.70%, respectively. Sediment is not produced during the oily sewage treatment using the novel process and flotation column.

Massive flows that represent the individual level of movements and communications can be easily obtained in the age of big data. Generalizing spatial and temporal flow patterns from such data is essential to demonstrate spatial connections and mobility trends. Clustering approaches provide effective methods to handle data sets that contain massive individual-level flows. However, existing flow clustering studies obscure the geometric properties of flow data, such as direction and length, which significantly indicate movement trends. In addition, temporal information is often ignored because previous approaches have mainly focused on the perspective of spatial clusters of flow data, resulting in a loss of temporal patterns. In this paper, we introduce new spatial and temporal similarity measurements between flows and propose a new clustering approach of flow data based on a stepwise strategy. This method can identify clusters from distinct flow distributions and discover significant spatio-temporal trends from large flow data. Simulated experiments with synthetic flows and a case study using Beijing taxi trip data are conducted to validate the usefulness of the proposed method.

The protection of water resources is of paramount importance to human beings’ practical lives. Monitoring and improving water quality nowadays has become an important topic. In this study, a novel Bayesian probabilistic neural network (BPNN) improved from ordinary Bayesian probability methods has been developed to quantitatively predict water quality parameters including phosphorus, nitrogen, chemical oxygen demand (COD), biochemical oxygen demand (BOD), and chlorophyll a. The proposed method, based on conventional Bayesian probability methods, involves feature engineering and deep neural networks. Additionally, it extracts significant information for each endmember from combinations of spectra by feature extraction, with spectral unmixing based on mathematical and statistical analysis, and calculates each of the water quality parameters. The experimental results show the great performance of the proposed model with all coefficient of determination R 2 over 0.9 greater than the values (0.6–0.8) from conventional methods, which are greater than ordinary Bayesian probability analysis. The mean percent of absolute error (MPAE) is taken into account as an important statistical criterion to evaluate model performance, and our results show that MPAE ranges from 4% (nitrogen) to 10% (COD). The root mean squared errors (RMSEs) of phosphorus, nitrogen, COD, BOD, and chlorophyll-a (Chla) are 0.03 mg/L, 0.28 mg/L, 3.28 mg/L, 0.49 mg/L, and 0.75 μg/L, respectively. In comparison with other deep learning methods, this study takes a relatively small amount of data as training data to train the proposed model and the proposed model is then tested on the same amount of testing data, achieving a greater performance. Thus, the proposed method is time-saving and more effective. This study proposes a more compatible and effective method to assist with decomposing combinations of hyperspectral signatures in order to calculate the content level of each water quality parameter. Moreover, the proposed method is practically applied to hyperspectral image data on board an unmanned aerial vehicle in order to monitor the water quality on a large scale and trace the location of pollution sources in the Maozhou River, Guangdong Province of China, obtaining well-explained and significant results.

Protection of water environments is an important part of overall environmental protection; hence, many people devote their efforts to monitoring and improving water quality. In this study, a self-adapting selection method of multiple artificial neural networks (ANNs) using hyperspectral remote sensing and ground-measured water quality data is proposed to quantitatively predict water quality parameters, including phosphorus, nitrogen, biochemical oxygen demand (BOD), chemical oxygen demand (COD), and chlorophyll a. Seventy-nine ground measured data samples are used as training data in the establishment of the proposed model, and 30 samples are used as testing data. The proposed method based on traditional ANNs of numerical prediction involves feature selection of bands, self-adapting selection based on multiple selection criteria, stepwise backtracking, and combined weighted correlation. Water quality parameters are estimated with coefficient of determination R 2 ranging from 0.93 (phosphorus) to 0.98 (nitrogen), which is higher than the value (0.7 to 0.8) obtained by traditional ANNs. MPAE (mean percent of absolute error) values ranging from 5% to 11% are used rather than root mean square error to evaluate the predicting precision of the proposed model because the magnitude of each water quality parameter considerably differs, thereby providing reasonable and interpretable results. Compared with other ANNs with backpropagation, this study proposes an auto-adapting method assisted by the above-mentioned methods to select the best model with all settings, such as the number of hidden layers, number of neurons in each hidden layer, choice of optimizer, and activation function. Different settings for ANNS with backpropagation are important to improve precision and compatibility for different data. Furthermore, the proposed method is applied to hyperspectral remote sensing images collected using an unmanned aerial vehicle for monitoring the water quality in the Shiqi River, Zhongshan City, Guangdong Province, China. Obtained results indicate the locations of pollution sources.

Objective: A model of Near Infrared Diffuse Reflectance Spectroscopy (NIR-DRS) was established for the first time to determine the content of Shengmaxinside I in the honey-fried processing of Rhizoma Cimicifugae. Methods: Shengmaxinside I content was determined by high-performance liquid chromatography (HPLC), and the data of the honey-fried processing of Rhizoma Cimicifugae samples from different batches of different origins by NIR-DRS were collected by TQ Analyst 8.0. Partial Least Squares (PLS) analysis was used to establish a near-infrared quantitative model. Results: The determination coefficient R2 was 0.9878. The Cross-Validation Root Mean Square Error (RMSECV) was 0.0193%, validating the model with a validation set. The Root Mean Square Error of Prediction (RMSEP) was 0.1064%. The ratio of the standard deviation for the validation samples to the standard error of prediction (RPD) was 5.5130. Conclusion: This method is convenient and efficient, and the experimentally established model has good prediction ability, and can be used for the rapid determination of Shengmaxinside I content in the honey-fried processing of Rhizoma Cimicifugae.

With millions of people traveling to unfamiliar cities to spend holidays, travel recommendation becomes necessary to assist tourists in planning their trips more efficiently. Serving as a prerequisite to travel recommender systems, understanding tourist behavior patterns is therefore of great importance. Recently, geo-tagged photos on social media platforms like Flickr have provided a rich data source that captures location histories of tourists and reflects their preferences. This article utilizes geo-tagged photos from Flickr to extract trajectories of tourists and then extends the concept of motifs from topological spaces, to temporal spaces and to semantic spaces, for detecting tourist mobility patterns. By representing trajectories in terms of three distinct types of travel motif and further using them to measure user similarity, typical tourist travel behavior patterns associated with distinct sightseeing tastes/preferences are identified and analyzed for tourism recommendation. Our empirical results confirm that the proposed analytical framework is effective to uncover meaningful tourist behavior patterns.

BACKGROUND: High-intensity focused ultrasound (HIFU) is a widely applied to treatment for unresectable hepatocellular carcinoma. However, insufficient HIFU can result in rapid progression of the residual tumor. The mechanism of such rapid growth of the residual tumor after HIFU ablation is poorly understood. OBJECTIVE: The aim of this study was to investigate the dynamic angiogenesis of residual tumor, and the temporal effect and mechanism of the HIF-1, 2α in the residual tumor angiogenesis. METHODS: Xenograft tumors of HepG2 cells were created by subcutaneously inoculating nude mice (athymic BALB/c nu/nu mice) with hepatoma cells. About thirty days after inoculation, all mice (except control group) were treated by HIFU and assigned randomly to 7 groups according to various time intervals (1st, 3rd, 5th day (d) and 1st, 2nd, 3rd, 4th week (w)). The residual tumor tissues were obtained from the experimental groups at various time points. Protein levels of HIF-1α, HIF-2α, VEGF-A, and EphA2 were quantified by immunohistochemistry analysis and Western Blot assays, and mRNA levels measured by Q-PCR. Microvascular density was calculated with counting of CD31 positive vascular endothelial cells by immunohistochemical staining. RESULTS: Compared with the control group, protein and mRNA levels of HIF-1α reached their highest levels on the 3rd day (P

Most existing human mobility literature focuses on exterior characteristics of movements but neglects activities, the driving force that underlies human movements. In this research, we combine activity-based analysis with a movement-based approach to model the intra-urban human mobility observed from about 15 million check-in records during a yearlong period in Shanghai, China. The proposed model is activity-based and includes two parts: the transition of travel demands during a specific time period and the movement between locations. For the first part, we find the transition probability between activities varies over time, and then we construct a temporal transition probability matrix to represent the transition probability of travel demands during a time interval. For the second part, we suggest that the travel demands can be divided into two classes, locationally mandatory activity (LMA) and locationally stochastic activity (LSA), according to whether the demand is associated with fixed location or not. By judging the combination of predecessor activity type and successor activity type we determine three trip patterns, each associated with a different decay parameter. To validate the model, we adopt the mechanism of an agent-based model and compare the simulated results with the observed pattern from the displacement distance distribution, the spatio-temporal distribution of activities, and the temporal distribution of travel demand transitions. The results show that the simulated patterns fit the observed data well, indicating that these findings open new directions for combining activity-based analysis with a movement-based approach using social media check-in data.

Background/Aim: Gout, characterized by acute inflammatory symptoms and monosodium urate crystal deposits in joints, is prevalent among males and the elderly. Total knee arthroplasty (TKA) is a common treatment for knee osteoarthritis (OA), but its impact on the risk of developing gout is unclear. This study examined the risk of gout in patients undergoing TKA. Patients and Methods: Utilizing the TriNetX research network, a retrospective cohort study was conducted on OA patients without prior gout. The TKA cohort was compared to a non-TKA control group using propensity score matching to balance covariates. The primary outcome was the incidence of gout over a five-year follow-up period. Results: The study included 38,834 matched pairs of TKA and non-TKA patients. TKA patients had a 15.6% higher risk of developing gout (HR=1.156; 95%CI=1.042-1.284) compared to controls. Sensitivity analyses confirmed the increased risk across various models and follow-up durations. Conclusion: TKA is associated with a higher risk of developing gout, particularly in females and older adults. Clinicians should monitor and manage gout risk in TKA patients, emphasizing preventive measures and early intervention. Further research is needed to understand the underlying mechanisms and improve patient care post-TKA. [ABSTRACT FROM AUTHOR]