Construction and evaluation of prognostic models of ECMO in elderly patients with cardiogenic shock based on BP neural network, random forest, and decision tree.

OBJECTIVE: To analyze the predictive effect of a back propagation (BP) neural network, random forest (RF) and decision tree model on the prognosis of elderly patients with cardiogenic shock after extracorporeal membrane oxygenation (ECMO). METHODS: This is a retrospective analysis of the clinical data of elderly patients with cardiogenic shock (258 cases) who underwent ECMO in People's Hospital of Guangxi Zhuang Autonomous Region from January 2016 to January 2022. All patients were followed up for 6 months after ECMO treatment. The prognosis was evaluated, and the prognostic factors were analyzed. BP neural network, RF and decision tree were used to establish predictive models, and the predictive performance of the models was evaluated. RESULTS: Among the 258 elderly patients with cardiogenic shock, 52 (20.16%) died 6 months after the ECMO treatment. Based on BP neural network, RF, and decision tree, predictive models for the prognosis and death of elderly patients with cardiogenic shock were constructed. A test set was used to predict the performance of the three models. The results showed that the predictive performances of the three models were all more than 80.00%. The accuracy, sensitivity, and specificity of the RF model were 0.987, 1.000, and 0.929 respectively, which were higher than those of the decision tree model. The area under the receiver operating characteristic curve (AUC) of the RF model was 1.000, which was higher than 0.916 for the decision tree model. DeLong test showed that there was a significant difference in the AUC of the RF model compared to the decision tree test set (D=-2.063, P=0.042 < 0.05). CONCLUSION: The predictive performance is good in all the three models, which have a high application value for prognosis of ECMO in elderly patients with cardiogenic shock. In clinical practice, predictive models should be selected according to the actual situation, so clinicians and patients can make decisions.

An engineered (CAGA)12-EGFP cell-based biosensor for high-content and accurate detection of active TGF-ß.

Transforming growth factor-ß (TGF-ß) regulates multiple fundamental physiological processes and is closely related to severe diseases such as cancer, fibrosis, immune disorders and cardiovascular diseases. TGF-ß is thus an important biomarker for clinical diagnosis and prognosis, and a crucial target for therapeutics development. Here we describe a high-content, serum-free, easy-to-use, and cost-effective (CAGA)12-EGFP cell-based biosensor for accurate measurements of active TGF-ß. Together with non-destructive and continuous measurement protocol and data processing method established here, the biosensor is capable of detecting active TGF-ß1 in the range of 0.024-6.25 ng/mL concentration with >91% accuracy and high repeatability. Overall, the engineered (CAGA)12-EGFP biosensor is a powerful tool for detection of active TGF-ß and for mechanistic study of the TGF-ß pathway. The greatly reduced cost and operating simplicity also makes it a highly potent in vitro platform for high-throughput screening of anti-TGF-ß therapeutics.

Specificity of TGF-ß1 signal designated by LRRC33 and integrin αVß8.

Myeloid lineage cells present the latent form of transforming growth factor-ß1 (L-TGF-ß1) to the membrane using an anchor protein LRRC33. Integrin αVß8 activates extracellular L-TGF-ß1 to trigger the downstream signaling functions. However, the mechanism designating the specificity of TGF-ß1 presentation and activation remains incompletely understood. Here, we report cryo-EM structures of human L-TGF-ß1/LRRC33 and integrin αVß8/L-TGF-ß1 complexes. Combined with biochemical and cell-based analyses, we demonstrate that LRRC33 only presents L-TGF-ß1 but not the -ß2 or -ß3 isoforms due to difference of key residues on the growth factor domains. Moreover, we reveal a 2:2 binding mode of integrin αVß8 and L-TGF-ß1, which shows higher avidity and more efficient L-TGF-ß1 activation than previously reported 1:2 binding mode. We also uncover that the disulfide-linked loop of the integrin subunit ß8 determines its exquisite affinity to L-TGF-ß1. Together, our findings provide important insights into the specificity of TGF-ß1 signaling achieved by LRRC33 and integrin αVß8.

Observation of Unusual Thermoresponsive Volume Phase Transition Behavior of Cubic Poly(N-isopropylacrylamide) Microgels.

Here, we report the observation of an unusual thermoresponsive volume phase transition behavior of cubic poly(N-isopropylacrylamide) (PNIPAM) microgels. Cubic PNIPAM microgels with a mean edge size of 125 ± 41 nm were synthesized via electrochemical-initiated radical polymerization with a photovoltaic cell as power supply. In turbidity and laser light scattering studies on dilute aqueous dispersions of these cubic microgels, both the light attenuation and hydrodynamic radius variations with temperature reveal an additional transition at about 25.0 °C, besides the widely reported volume phase transition at the PNIPAM LCST that is typically found for (quasi-)spherical microgels. This unusual thermoresponsive volume phase transition behavior of the cubic microgels can be elucidated by using a core-corona model, with the contribution from each part varying at different temperatures. The finding is also checked by thermal analysis.

Nature of the Synergistic Effect of N and S Co-Doped Graphene for the Enhanced Simultaneous Determination of Toxic Pollutants.

N-doped graphene (NG), S-doped graphene (SG), and N and S co-doped graphene nanocatalysts with different doping sequences (N-SG and S-NG) are successfully synthesized by a facile low-temperature hydrothermal method. By changing the synthetic sequence, S-NG significantly increases the electron transport rate of the sensor and the electrocatalytic ability compared to NG, SG, and N-SG due to the optimal proportion of doping element content and suitable N- and S-bonding configurations. The origin of the synergistic effect of N and S co-doped graphene is confirmed. Traces of S doping greatly enhance the electrochemical performance. The large volume of S-Ox groups may prevent the analytes from approaching the catalytic sites of the sensing materials due to a steric hindrance effect. S-NG, which possesses less S-Ox groups, exhibits better performance than N-SG. Pyridinic N plays an important role in enhancing the electrochemical activity and conductivity. The simultaneous determination of aniline (AN), p-phenylenediamine (PPD), and nitrobenzene (NB) as typical toxic pollutants is performed by employing the S-NG nanoarchitecture. The detection limits (S/N = 3) for AN, PPD, and NB are 0.023, 0.051, and 0.216 µM, respectively. In addition, the S-NG sensors also have excellent anti-interference, stability, and reproducibility. The precise control and synthesis of multiheteroatoms into graphene represent a promising strategy to enhance the electrocatalytic performance in energy and environmental fields.

Hierarchical Self-Assembly of Cyclodextrin and Dimethylamino-Substituted Arylene-Ethynylene on N-doped Graphene for Synergistically Enhanced Electrochemical Sensing of Dihydroxybenzene Isomers.

An electrochemically active sensing nanomaterial (denoted as CD-MPEA-NG) has been successfully constructed by an hierarchical self-assembly of cyclodextrin (CD) and N,N-dimethyl-4-(phenylethynyl)aniline (MPEA) on N-doped graphene (NG) in a low-temperature hydrothermal process. The unique nanostructure of the high-performance CD-MPEA-NG was confirmed by utilizing Fourier transform infrared spectra, an X-ray diffractometer, and differential pulse voltammetry (DPV), etc. In particular, the method of density functional theory with dispersion energy (DFT-D) of wB97XD/LanL2DZ was employed to optimize and describe the face-to-face packing structure of heterodimers of NG and MPEA. The CD-MPEA-NG sensor exhibits highly sensitive performance toward dihydroxybenzene isomers, without relying on expensive noble metal or a complicated preparation process. The experimental results demonstrate that given the synergistic effect of NG and MPEA as a coupled sensing platform, CD as a supramolecular cavity can significantly enhance the electrochemical response. The detection limits (S/N = 3) for catechol (CT), resorcinol (RS), and hydroquinone (HQ) are 0.008, 0.018, and 0.011 µM by DPV, respectively. Besides, the CD-MPEA-NG sensor shows a superb anti-interference, reproducibility, and stability, and satisfactory recovery aimed at detecting isomers in Nanjing River water. The encouraging performance as well as simplified preparation approach strongly support the CD-MPEA-NG sensor is a fascinating electrode to develop as a seamless and sensitive electroanalytical technique.

Variations of antioxidant properties and NO scavenging abilities during fermentation of tea.

Tea is known as one of the most popular beverages in the world, which is believed to be beneficial for health. The main components in tea will change a lot depending on the different processes of fermentation, and thus the effects of different teas on human health may differ. The aim of this study is to explore the varied abilities of reactive oxygen species (ROS) and nitric oxide (NO) scavenging during the fermentation of tea. In this study, we conducted the in vitro experiments which involved some reaction systems indicating the abilities of scavenging ROS and NO. We also investigated the effects of tea and their components (catechins, theabrownins, caffeine) on the intracellular levels of ROS and NO, using Raw 264.7 cells as the model. We found that regardless of whether it was out of cell system or in Raw 264.7 cells, the abilities of scavenging ROS would decrease during the fermentation of tea. Further, the post-fermented pu-erh tea showed the best effect on inhibiting the lipopolysaccharide (LPS)-induced production of NO. These findings indicated that the fermentation process caused a change of the components which might be due to the changes of their antioxidant properties and NO scavenging abilities.