AKR1C1 overexpression attenuates the inhibitory effect of glycyrrhizic acid on gastric cancer cell proliferation and migration

Purpose: To investigate the involvement of aldo-keto reductase family 1 member C1 (AKR1C1) in glycyrrhizic acid-mediated gastric cancer.Methods: Immunohistochemistry, quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR), and western blot were used to assess AKR1C1 expression in gastric cancer. Cell proliferation was assessed using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) and colony formation assay. Apoptosis was evaluated by flow cytometry. Transwell and wound healing assays were performed to investigate cell invasion and migration, respectively.Results: AKR1C1 was significantly upregulated in gastric cancer tissues and cells (p < 0.01). AKR1C1 knockdown suppressed cell proliferation, migration, and invasion of gastric cancer, but promoted cell apoptosis. Glycyrrhizic acid treatment reduced AKR1C1 expression in gastric cancer cells (p < 0.05). AKR1C1 overexpression attenuated the glycyrrhizic acid-induced increase in gastric cancer cell apoptosis as well as the decrease in cell proliferation, migration, and invasion.Conclusion: AKR1C1 contributes to gastric cancer cell proliferation and metastasis and counteracts the suppressive effects of glycyrrhizic acid on gastric cancer cell proliferation and metastasis

Analysis of a Single Hemodialysis on Phosphate Removal of the Internal Fistula Patients by Mathematical and Statistical Methods

Chronic kidney disease related mineral and bone disease (CKD-MBD) is a worldwide challenge in hemodialysis patients. In china, the number of dialysis patients is growing but few data are available about their bone disorders. In the current study, we aimed to evaluate the effect of clinical factors on the serum phosphorus clearance in the 80 maintenance hemodialysis (MHD) patients. Six clinical factors were identified for their association with the serum phosphorus clearance using the analysis of Spearman’s single linear correlation, including predialysis serum phosphate level, CRR, membrane surface area of the dialyzer, effective blood flow rate, the blood chamber volume, and hematocrit. In an overall multivariate analysis, pre-P, CRR, membrane SA, and Qb were identified as independent risk factors associated with the serum phosphorus clearance. In conclusion, HD could effectively clear serum phosphorus. The analysis of CRR might help to estimate serum phosphorus reduction ratio

Mechanisms Of Cannabinoid Cb 2 Receptor-Mediated Reduction Of Dopamine Neuronal Excitability In Mouse Ventral Tegmental Area

Background: We have recently reported that activation of cannabinoid type 2 receptors (CB 2 Rs)reduces dopamine (DA)neuron excitability in mouse ventral tegmental area (VTA). Here, we elucidate the underlying mechanisms. Methods: Patch-clamp recordings were performed in mouse VTA slices and dissociated single VTA DA neurons. Findings: Using cell-attached recording in VTA slices, bath-application of CB 2 R agonists (JWH133 or five other CB 2 R agonists)significantly reduced VTA DA neuron action potential (AP)firing rate. Under the patch-clamp whole-cell recording model, JWH133 (10 μM)mildly reduced the frequency of miniature excitatory postsynaptic currents (mEPSCs)but not miniature inhibitory postsynaptic currents (mIPSCs). JWH133 also did not alter evoked EPSCs or IPSCs. In freshly dissociated VTA DA neurons, JWH133 reduced AP firing rate, delayed AP initiation and enhanced AP after-hyperpolarization. In voltage-clamp recordings, JWH133 (1 μM)enhanced M-type K + currents and this effect was absent in CB 2−/− mice and abolished by co-administration of a selective CB 2 R antagonist (10 μM, AM630). CB 2 R-mediated inhibition in VTA DA neuron firing can be mimicked by M-current opener (10 μM retigabine)and blocked by M-current blocker (30 μM XE991). In addition, enhancement of neuronal cAMP by forskolin (10 μM)reduced M-current and increased DA neuron firing rate. Finally, pharmacological block of synaptic transmission by NBQX (10 μM), D-APV (50 μM)and picrotoxin (100 μM)in VTA slices failed to prevent CB 2 R-mediated inhibition, while intracellular infusion of guanosine 5\u27-O-2-thiodiphosphate (600 μM, GDP-β-S)through recording electrode to block postsynaptic G-protein function prevented JWH133-induced reduction in AP firing. Interpretation: Our results suggest that CB 2 Rs modulate VTA DA neuron excitability mainly through an intrinsic mechanism, including a CB 2 R-mediated reduction of intracellular cAMP, and in turn enhancement of M-type K + currents. Fund: This research was supported by the Barrow Neuroscience Foundation, the BNI-BMS Seed Fund, and CNSF (81771437)

Blood arsenic exposure levels of preschool children and dietary factors analysis

Objective To explore the blood arsenic exposure levels of preschool children and analyze the factors of blood arsenic. Methods By the multi-stage cluster and simple randomized method, six districts of Shanghai City was chosen and the preschool children in the selected village were asked to fill in the questionnaire and have blood sampling. Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect blood arsenic, of which the data was analyzed by multiple linear regression models. Marine fish, freshwater fish, freshwater shrimp and shellfish were grouped as follows: ≤3 times per month, 1-3 times per week, and 4-6 times per week. Rice, noodles and milk were grouped as <50, 50-100, and ≥100 g/d. Results 2 263 preschool children were recruited. The range of blood arsenic was 0.12-27.94 μg/L. The median (P25, P75) were 2.26 (1.63, 3.09) μg/L. Statistical analysis showed that the more intake of rice, wheaten food, and sea fish and shrimp, the more arsenic in children’s blood (P<0.05). Whereas highter intake of freshwater fish and shrimp group showed decreased blood arsenic (P<0.05). Conclusion Most preschool children’s blood arsenic levels (92.4%, 2 091/2 263) were at normal level (<5 μg/L). There was a positive correlation between blood arsenic concentration and the intake of rice, wheaten food, and sea fish and shrimp, while negative correlation with high freshwater fish and shrimp consumption

Acquired reactive perforating collagenosis triggered by trauma with eosinophilia: a case report and literature review

Acquired reactive perforating collagenosis (ARPC) is a rare dermatological disorder condition defined by the perforation of altered collagen fibers through the epidermis. The presence of underlying conditions such as diabetes or renal disease is helpful in the ARPC diagnosis. Although skin rashes related to ARPC have been reported, the exact causative factors and mechanisms remain unclear. Here, we present a unique case of ARPC triggered by trauma in a 67-year-old male without concurrent systemic alterations. The diagnosis of ARPC with eosinophilia was made following comprehensive diagnostic testing, including clinical presentation, histological results, and blood tests, ruling out other possible diseases. Intriguingly, the histopathological examination revealed collagen penetration into the epidermis at different tissue sections. In addition, we reviewed existing literature on ARPC, which documented the causation. To help confirm the diagnosis, clinicians have to pay attention to traumatic triggers for ARPC and its rare manifestation with eosinophilia

Study on the substitutability of nighttime light data for SDG indicators: a case study of Yunnan Province

Introdution: One crucial method to attain Sustainable Development Goals (SDGs) involves timely adjustment of development policies, promoting the realization of SDGs through a time-series assessment of the degree of accomplishment. In practical applications, data acquisition is a significant constraint in evaluating the SDGs, not only in China but across the globe. Hence, expanding data channels and exploring the feasibility of various data sources for sustainable development assessment are effective strategies to tackle the challenge of data acquisition.Methods: In light of this issue, this study selected Nighttime Light Data, a remote sensing data source closely linked to human social activities, as an alternative data source. Using Yunnan Province as an example, 16 localized indicators of social, economic, and environmental types were chosen. These indicators were then subjected to a correlation analysis with the Total Nighttime Light Index (TNLI). The relationships between different types of indicators and TNLI were analyzed at both temporal and spatial scales, thus identifying the indicators for which TNLI could serve as a suitable substitute measure.Results: The study indicates that when the SDG indicators are classified into economic, social and environmental categories, the total value of nighttime light presents a significant correlation and substitutability with economic indicators; significantly correlated with some social indicators, it can reveal the weak links in the development of underdeveloped areas; it is not significantly correlated with environmental indicators, while a trend correlation exists, which can provide some reference values.Discussion: This study has demonstrated the feasibility of using Nighttime Light Data for sustainable development assessment. It provides a novel evaluation method for countries that, despite a lack of resources for conducting sustainable development assessments, have a greater need for such assessments due to their lower economic development. Furthermore, a multitude of assessment methods can be developed based on Nighttime Light Data

The PFILSTM model: a crack recognition method based on pyramid features and memory mechanisms

Crack detection is a crucial task for the structural health diagnosis of buildings. The current widely used manual inspection methods have inherent limitations and safety hazards, while traditional digital image processing methods require manual feature extraction and also have substantial limitations. In this paper, we propose a crack recognition method based on pyramid features and memory mechanisms that leverages a U-shaped network, long short-term memory mechanisms, and a pyramid feature design to address the recognition accuracy, robustness, and universality issues with deep learning-based crack detection methods in recent years. Experiments were conducted on four publicly available datasets and one private dataset. Compared with the commonly used FCN8s, SegNet, UNet, and DeepLabv3+ models and other related studies using the same evaluation criteria and datasets, our proposed model shows better overall performance in terms of all metrics evaluated

Screening of the Key Genes and Signalling Pathways for Diabetic Nephropathy Using Bioinformatics Analysis

BackgroundThis study aimed to identify biological markers for diabetic nephropathy (DN) and explore their underlying mechanisms.MethodsFour datasets, GSE30528, GSE47183, GSE104948, and GSE96804, were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the “limma” package, and the “RobustRankAggreg” package was used to screen the overlapping DEGs. The hub genes were identified using cytoHubba of Cytoscape. Logistic regression analysis was used to further analyse the hub genes, followed by receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes. Correlation analysis and enrichment analysis of the hub genes were performed to identify the potential functions of the hub genes involved in DN.ResultsIn total, 55 DEGs, including 38 upregulated and 17 downregulated genes, were identified from the three datasets. Four hub genes (FN1, CD44, C1QB, and C1QA) were screened out by the “UpSetR” package, and FN1 was identified as a key gene for DN by logistic regression analysis. Correlation analysis and enrichment analysis showed that FN1 was positively correlated with four genes (COL6A3, COL1A2, THBS2, and CD44) and with the development of DN through the extracellular matrix (ECM)–receptor interaction pathway.ConclusionsWe identified four candidate genes: FN1, C1QA, C1QB, and CD44. On further investigating the biological functions of FN1, we showed that FN1 was positively correlated with THBS2, COL1A2, COL6A3, and CD44 and involved in the development of DN through the ECM–receptor interaction pathway. THBS2, COL1A2, COL6A3, and CD44 may be novel biomarkers and target therapeutic candidates for DN