Gastric cancer cell lines induced by trichostatin A

AIM： To explore the effect of trichostatin A （TSA） on apoptosis and acetylated histone H3 levels in gastric cancer cell lines BGC-823 and SGC-7901. METHODS： The effect of TSA on growth inhibition and apoptosis was examined by MTT, fluorescence microscopy and PI single-labeled flow cytometry. The acetylated histone H3 level was detected by Western blot. RESULTS： TSA induced apoptosis in gastric cancer cell lines BGC-823 and SGC-7901 was in a dose and time-dependent manner. Apoptotic cells varied significantly between TSA treated groups （37.5 ng/mL 72 h for BGC-823 cell line and 75 ng/mL 72 h for SGC-7901 cell line） and control group （0.85 ± 0.14 vs 1.14 ± 0.07, P = 0.02; 0.94 ± 0.07 vs 1.15 ± 0.06, P = 0.02）. Morphologic changes of apoptosis, including nuclear chromatin condensation and fluorescence strength, were observed under fluorescence microscopy. TSA treatment in BGC-823 and SGC-7901 cell lines obviously induced cell apoptosis, which was demonstrated by the increased percentage of sub-G1 phase cells, the reduction of Gl-phase cells and the increase of apoptosis rates in flow cytometric analysis. The result of Western blot showed that the expression of acetylated histone H3 increased in BGC-823 and SGC-7901 TSA treatment groups as compared with the control group.CONCLUSION： TSA can induce cell apoptosis in BGC-823 and SGC-7901 cell lines. The expression of acetylated histone H3 might be correlated with apoptosis.

Development and external validation of models to predict acute respiratory distress syndrome related to severe acute pancreatitis

BACKGROUND Acute respiratory distress syndrome(ARDS)is a major cause of death in patients with severe acute pancreatitis(SAP).Although a series of prediction models have been developed for early identification of such patients,the majority are complicated or lack validation.A simpler and more credible model is required for clinical practice.AIM To develop and validate a predictive model for SAP related ARDS.METHODS Patients diagnosed with AP from four hospitals located at different regions of China were retrospectively grouped into derivation and validation cohorts.Statistically significant variables were identified using the least absolute shrinkage and selection operator regression method.Predictive models with nomograms were further built using multiple logistic regression analysis with these picked predictors.The discriminatory power of new models was compared with some common models.The performance of calibration ability and clinical utility of the predictive models were evaluated.RESULTS Out of 597 patients with AP,139 were diagnosed with SAP(80 in derivation cohort and 59 in validation cohort)and 99 with ARDS(62 in derivation cohort and 37 in validation cohort).Four identical variables were identified as independent risk factors for both SAP and ARDS:heart rate[odds ratio(OR)=1.05;95%CI:1.04-1.07;P<0.001;OR=1.05,95%CI:1.03-1.07,P<0.001],respiratory rate(OR=1.08,95%CI:1.0-1.17,P=0.047;OR=1.10,95%CI:1.02-1.19,P=0.014),serum calcium concentration(OR=0.26,95%CI:0.09-0.73,P=0.011;OR=0.17,95%CI:0.06-0.48,P=0.001)and blood urea nitrogen(OR=1.15,95%CI:1.09-1.23,P<0.001;OR=1.12,95%CI:1.05-1.19,P<0.001).The area under receiver operating characteristic curve was 0.879(95%CI:0.830-0.928)and 0.898(95%CI:0.848-0.949)for SAP prediction in derivation and validation cohorts,respectively.This value was 0.892(95%CI:0.843-0.941)and 0.833(95%CI:0.754-0.912)for ARDS prediction,respectively.The discriminatory power of our models was improved compared with that of other widely used models and the calibration ability and clinical utility of the prediction models performed adequately.CONCLUSION The present study constructed and validated a simple and accurate predictive model for SAPrelated ARDS in patients with AP.

Minimally invasive treatment of forearm double fracture in adult using Acumed forearm intramedullary nail: A case report

BACKGROUND Currently,open reduction internal fixation is the conventional surgical method for treatment of double ulna and radius fracture.However,open reduction is associated with a high risk of complications.This case of forearm double fracture involved a patient treated using an Acumed intramedullary nail.The patient experienced good follow-up outcomes.The Acumed forearm intramedullary nail enables early functional exercise and hastens healing of the fracture.Few studies have reported on the use of this approach for the treatment of fractures.CASE SUMMARY A 23-year-old male patient was admitted to hospital after 5 h of pain,swelling,and limited activity of left forearm caused by a careless fall.Physical examination showed stable basic vital signs,swelling of the left forearm,and severe pain when pressing on the injured part of the forearm.Further,friction was felt at the broken end of the bone;the skin was not punctured.Movement of the left hand was normal,and the left radial artery pulse was normal.Three-dimensional computed tomography examination showed an ulna fracture of the left forearm and comminuted fracture of the radius.The fracture was located in the upper third of the radius,with significant displacement on the fracture side.Clinical diagnosis further confirmed the left radius comminuted fracture and ulna fracture.After analyzing the fracture pattern,age,and other patient characteristics,we chose an Acumed nail for treatment and achieved good follow-up outcomes.CONCLUSION Acumed forearm intramedullary nail for fixation of ulna and radius fracture reduced complication risk and resulted in good follow-up outcomes.

Model comparison of dark energy models using deep network

This work uses a combination of a variational auto-encoder and generative adversarial network to compare different dark energy models in light of observations, e.g., the distance modulus from type Ia supernovae. The network finds an analytical variational approximation to the true posterior of the latent parameters in the models, yielding consistent model comparison results with those derived by the standard Bayesian method, which suffers from a computationally expensive integral over the parameters in the product of the likelihood and the prior. The parallel computational nature of the network together with the stochastic gradient descent optimization technique leads to an efficient way to compare the physical models given a set of observations. The converged network also provides interpolation for a dataset, which is useful for data reconstruction.

Forecast of cosmological constraints with type Ia supernovae from the Chinese Space Station Telescope

The 2-m aperture Chinese Space Station Telescope(CSST),which observes at wavelengths ranging from 255 to 1000 nm,is expected to start science operations in 2024.An ultra-deep field observation program covering approximately 10 deg2is proposed with supernovae(SNe) and other transients as one of its primary science drivers.This paper presents the simulated detection results of type Ⅰa supernovae(SNe Ⅰa) and explores the impact of new datasets on the determinations of cosmological parameters.The simulated observations are conducted with an exposure time of 150 s and cadences of 10,20,and 30 d.The survey mode covering a total of 80 observations but with a random cadence in the range of 4 to 14 d is also explored.Our simulation results indicate that the CSST can detect up to ~1800 SNe la at z <1.3.The simulated SNe la are then used to constrain the cosmological parameters.The constraint on can be improved by 37.5% using the 10-d cadence sample in comparison with the Pantheon sample.A deeper measurement simulation with a 300 s exposure time together with the Pantheon sample improves the current constraints on Ωmby 58.3% and ω by 47.7%.Taking future lager sets of nearby SN Ⅰa sample form ground-based surveys(i.e.,N~3400) into consideration,the constraints on ω can be improved by 59.1%.The CSST ultra-deep field observation program is expected to discover large amounts of SNe la over a broad redshift span and enhance our understanding of the nature of dark energy.