Effects of Antimicrobial Peptide Revealed by Simulations: Translocation, Pore Formation, Membrane Corrugation and Euler Buckling

We explore the effects of the peripheral and transmembrane antimicrobial peptides on the lipid bilayer membrane by using the coarse grained Dissipative Particle Dynamics simulations. We study peptide/lipid membrane complexes by considering peptides with various structure, hydrophobicity and peptide/lipid interaction strength. The role of lipid/water interaction is also discussed. We discuss a rich variety of membrane morphological changes induced by peptides, such as pore formation, membrane corrugation and Euler buckling

Design of a new type of safety protection device for gas bottle cabinet

Aiming at the problem of explosion caused by leakage of flammable and explosive gas cylinder, a new type of safety protection device for gas bottle cabinet is designed to solve this problem. The design of this new type of gas bottle cabinet safety protection device is to use GSM voice, short message control technology, sensor technology, wifi technology, plc control technology and so on, to monitor the gas in the gas bottle cabinet in real time. Once the gas in the cylinder leaks and the concentration of the leakage gas reaches the set alarm concentration, the alarm will occur, and the exhaust fan will start to discharge the leakage gas and send an alarm message to the pre-set mobile phone at the same time

Knockdown of PAICS inhibits malignant proliferation of human breast cancer cell lines

Abstract Background Phosphoribosylaminoimidazole carboxylase, phosphoribosylaminoimidazole succinocarboxamide synthetase (PAICS), an enzyme required for de novo purine biosynthesis, is associated with and involved in tumorigenesis. This study aimed to evaluate the role of PAICS in human breast cancer, which remains the most frequently diagnosed cancer and the leading cause of cancer-related death among women in less developed countries. Results Lentivirus-based short hairpin RNA targeting PAICS specifically depleted its endogenous expression in ZR-75-30 and MDA-MB-231 breast cancer cells. Depletion of PAICS led to a significant decrease in cell viability and proliferation. To ascertain the mechanisms through which PAICS modulates cell proliferation, flow cytometry was performed, and it was confirmed that G1-S transition was blocked in ZR-75-30 cells through PAICS knockdown. This might have occurred partly through the suppression of Cyclin E and the upregulation of Cyclin D1, P21, and CDK4. Moreover, PAICS knockdown obviously promoted cell apoptosis in ZR-75-30 cells through the activation of PARP and caspase 3 and downregulation of Bcl-2 and Bcl-xl expression in ZR-75-30 cells. Conclusions These findings demonstrate that PAICS plays an essential role in breast cancer proliferation in vitro, which provides a new opportunity for discovering and identifying novel effective treatment strategies

An Interference-Resistant and Low-Consumption Lip Recognition Method

Lip movements contain essential linguistic information. It is an important medium for studying the content of the dialogue. At present, there are many studies on how to improve the accuracy of lip language recognition models. However, there are few studies on the robustness and generalization performance of the model under various disturbances. Specific experiments show that the current state-of-the-art lip recognition model significantly drops in accuracy when disturbed and is particularly sensitive to adversarial examples. This paper substantially alleviates this problem by using Mixup training. Taking the model subjected to negative attacks generated by FGSM as an example, the model in this paper achieves 85.0% and 40.2% accuracy on the English dataset LRW and the Mandarin dataset LRW-1000, respectively. The correct recognition rates are improved by 9.8% and 8.3%, compared with the current advanced lip recognition models. The positive impact of Mixup training on the robustness and generalization of lip recognition models is demonstrated. In addition, the performance of the lip recognition classification model depends more on the training parameters, which increase the computational cost. The InvNet-18 network in this paper reduces the consumption of GPU resources and the training time while improving the model accuracy. Compared with the standard ResNet-18 network used in mainstream lip recognition models, the InvNet-18 network in this paper has more than three times lower GPU consumption and 32% fewer parameters. After detailed analysis and comparison in various aspects, it is demonstrated that the model in this paper can effectively improve the model’s anti-interference ability and reduce training resource consumption. At the same time, the accuracy is comparable with the current state-of-the-art results

An Interference-Resistant and Low-Consumption Lip Recognition Method

Lip movements contain essential linguistic information. It is an important medium for studying the content of the dialogue. At present, there are many studies on how to improve the accuracy of lip language recognition models. However, there are few studies on the robustness and generalization performance of the model under various disturbances. Specific experiments show that the current state-of-the-art lip recognition model significantly drops in accuracy when disturbed and is particularly sensitive to adversarial examples. This paper substantially alleviates this problem by using Mixup training. Taking the model subjected to negative attacks generated by FGSM as an example, the model in this paper achieves 85.0% and 40.2% accuracy on the English dataset LRW and the Mandarin dataset LRW-1000, respectively. The correct recognition rates are improved by 9.8% and 8.3%, compared with the current advanced lip recognition models. The positive impact of Mixup training on the robustness and generalization of lip recognition models is demonstrated. In addition, the performance of the lip recognition classification model depends more on the training parameters, which increase the computational cost. The InvNet-18 network in this paper reduces the consumption of GPU resources and the training time while improving the model accuracy. Compared with the standard ResNet-18 network used in mainstream lip recognition models, the InvNet-18 network in this paper has more than three times lower GPU consumption and 32% fewer parameters. After detailed analysis and comparison in various aspects, it is demonstrated that the model in this paper can effectively improve the model’s anti-interference ability and reduce training resource consumption. At the same time, the accuracy is comparable with the current state-of-the-art results

Experimental and numerical study on AlGaInAs/AlGaAs distributed feedback lasers with GaInP gratings

Ridge-waveguide AlGaInAs/AlGaAs distributed feedback lasers with lattice-matched GaInP gratings were fabricated and their light-current characteristics, spectrum and far-field characteristics were measured. On the basis of our experimental results we analyze the effect of the electron stopper layer on light-current performance using the commercial laser simulation software PICS3D. The simulator is based on the self-consistent solution of drift diffusion equations, the Schrodinger equation, and the photon rate equation. The simulation results suggest that, with the use of a 80 nm-width p-doped Al0.6GaAs electron stopper layer, the slope efficiency can be increased and the threshold current can be reduced by more than 10 mA

Systematic review and meta-analysis : impact of anti-viral therapy on portal hypertensive complications in HBV patients with advanced chronic liver disease

Background: The efficacy of nucleos(t)ide analogs (NAs) in non-cirrhotic chronic hepatitis B (CHB) patients is well-established. However, their impact on complications of portal hypertension in advanced chronic liver disease (ACLD) is less well characterized. Methods: MEDLINE/PubMed, EMBASE, Web of Science, Cochrane Central Register of Controlled Trials, and abstracts of major international hepatology meetings were searched for publications from Jan 1, 1995 to Nov 30, 2021. Randomized control trials and observational studies reporting the efficacy of NAs in ACLD patients were eligible. Pooled risk ratios (RRs) for outcomes of interest were calculated with a random-effect or fixed-effect model, as appropriate. Results: Thirty-nine studies including 14,212 ACLD patients were included. NA treatment was associated with reduced risks of overall hepatic decompensation events (RR, 0.51; 95% confidence interval [CI]: 0.37–0.71), such as variceal bleeding (RR, 0.44; 95% CI: 0.26–0.74) and ascites (RR, 0.10; 95% CI: 0.01–1.59), on a trend-wise level. Moreover, the risks of hepatocellular carcinoma (HCC) (RR, 0.48; 95% CI: 0.30–0.75) and liver transplantation/death (RR, 0.36; 95% CI: 0.25–0.53) were also reduced by NA treatment and the first-line NAs were superior to non-first-line NAs in improving these outcomes (RR, 0.85; 95% CI: 0.75–0.97 and RR, 0.85; 95% CI: 0.73–0.99, respectively). Conclusion: NA therapy lowers the risk of portal hypertension-related complications, including variceal bleeding, HCC, and liver transplantation/death

Systematic review and meta-analysis: impact of anti-viral therapy on portal hypertensive complications in HBV patients with advanced chronic liver disease

Background: The efficacy of nucleos(t)ide analogs (NAs) in non-cirrhotic chronic hepatitis B (CHB) patients is well-established. However, their impact on complications of portal hypertension in advanced chronic liver disease (ACLD) is less well characterized. Methods: MEDLINE/PubMed, EMBASE, Web of Science, Cochrane Central Register of Controlled Trials, and abstracts of major international hepatology meetings were searched for publications from Jan 1, 1995 to Nov 30, 2021. Randomized control trials and observational studies reporting the efficacy of NAs in ACLD patients were eligible. Pooled risk ratios (RRs) for outcomes of interest were calculated with a random-effect or fixed-effect model, as appropriate. Results: Thirty-nine studies including 14,212 ACLD patients were included. NA treatment was associated with reduced risks of overall hepatic decompensation events (RR, 0.51; 95% confidence interval [CI]: 0.37–0.71), such as variceal bleeding (RR, 0.44; 95% CI: 0.26–0.74) and ascites (RR, 0.10; 95% CI: 0.01–1.59), on a trend-wise level. Moreover, the risks of hepatocellular carcinoma (HCC) (RR, 0.48; 95% CI: 0.30–0.75) and liver transplantation/death (RR, 0.36; 95% CI: 0.25–0.53) were also reduced by NA treatment and the first-line NAs were superior to non-first-line NAs in improving these outcomes (RR, 0.85; 95% CI: 0.75–0.97 and RR, 0.85; 95% CI: 0.73–0.99, respectively). Conclusion: NA therapy lowers the risk of portal hypertension-related complications, including variceal bleeding, HCC, and liver transplantation/death