The use of machine learning to predict the effects of cryoprotective agents on the GelMA-based bioinks used in extrusion cryobioprinting

Cryobioprinting has tremendous potential to solve problems to do with lack of shelf availability in traditional bioprinting by combining extrusion bioprinting and cryopreservation.In order to ensure the viability of cells in the frozen state and avoid the possible toxicity of dimethyl sulfoxide(DMSO),DMSO-free bioink design is critical for achieving successful cryobioprinting.A nontoxic gelatin methacryloyl-based bioink used in cryobioprinting is composed of cryoprotective agents(CPAs)and a buffer solution.The selection and ratio of CPAs in the bioink directly affect the survival of cells in the frozen state.However,the development of universal and efficient cryoprotective bioinks requires extensive experimentation.We first compared two commonly used CPA formulations via experiments in this study.Results show that the effect of using ethylene glycol as the permeable CPA was 6.07%better than that of glycerol.Two datasets were obtained and four machinelearning models were established to predict experimental outcomes.The predictive powers of multiple linear regression(MLR),decision tree(DT),random forest(RF),and artificial neural network(ANN)approaches were compared,suggesting an order of ANN>RF>DT>MLR.The final selected ANN model was then applied to another dataset.Results reveal that this machine-learning method can accurately predict the effects of cryoprotective bioinks composed of different CPAs.Outcomes also suggest that the formulations presented here have universality.Our findings are likely to greatly accelerate research and development on the use of bioinks for cryobioprinting.

Numerical study on maldistribution of gas-solid flow in multiple-branching limestone-conveying pipelines of circulating fluidized bed

As one of the most important auxiliary systems of a circulating fluidized bed boiler,the limestone pneumatic conveying system is of great significance to its operation.Maldistribution of powder in the different injecting ports seriously limits inner-furnace desulfurization performance owing to inefficient mixing of limestone powder and SO2.The gas-solid flow characteristics of an industrial-scale multiple-branching limestone-conveying pipeline system of a 200 MW circulating fluidized bed boiler were studied using a computational particle fluid dynamics method.The maldistribution intensity was studied under different operating conditions of air velocity and particle mass flow rate.Simulation results indicated that when the air velocity increased,the maldistribution was mitigated,but when the particle mass flow rate increased,the maldistribution strengthened.To solve this problem,two improved schemes were proposed:adding a deflector at different angles and changing the height of pipeline distributor.According to the simulation,the maldistribution could be efficiently mitigated using a distributor height in the range of 100-120 mm and a deflector angle of 10°-30°.

Opalski综合征合并小脑梗死血管内介入治疗一例

Opalski综合征是一种较为少见的特殊类型的脑干综合征,是伴有同侧肢体无力的延髓背外侧(Wallenberg)梗死的一种变异体,由法国人Opalski于1946年首次发现并命名。临床上不易识别,首诊此类患者,因患者同侧肢体偏瘫,不符合Wallenberg综合征的表现,尤其是合并其他部位梗死时,容易误诊。目前该类患者在治疗上多以内科药物保守治疗为主,血管内介入治疗较为少见。因此,为能尽早识别Opalski综合征以及尽早让患者得到有效救治,降低致残率及致死率,现将西电集团医院收治的1例合并小脑枕叶梗死的Opalski综合征病例报道如下。