The reprogramming of somatic cells with defined factors, which converts cells from one lineage into cells of another, has greatly reshaped our traditional views on cell identity and cell fate ...determination. Direct reprogramming (also known as transdifferentiation) refers to cell fate conversion without transitioning through an intermediary pluripotent state. Given that the number of cell types that can be generated by direct reprogramming is rapidly increasing, it has become a promising strategy to produce functional cells for therapeutic purposes. This Review discusses the evolution of direct reprogramming from a transcription factor-based method to a small-molecule-driven approach, the recent progress in enhancing reprogrammed cell maturation, and the challenges associated with in vivo direct reprogramming for translational applications. It also describes our current understanding of the molecular mechanisms underlying direct reprogramming, including the role of transcription factors, epigenetic modifications, non-coding RNAs, and the function of metabolic reprogramming, and highlights novel insights gained from single-cell omics studies.
Abstract
In order to effectively improve the economic benefits of large-scale fracturing of the single well in tight reservoirs, avoid investment risks and raise development effects, research on the ...forecast means of large-scale multi-branch fracturing capacity is carried out. Large-scale fracturing has high costs and high investment risks, it is necessary to conduct relatively accurate forecast for the capacity after fracturing to reduce investment risks. On the basis of the single-well capacity data of 78 large-scale fracturing wells that have been put into production in the Hailar Basin, the geological, development and engineering factors affecting capacity were deeply analyzed and summarized. According to different applicable conditions, the theoretical derivation and polynomial linear regression methods are used; two different capacity forecast models of tight reservoir are given. These two forecast models are used, the error of capacity forecast results after fracturing is less than 15%, and the accuracy can meet the actual application requirements of the mine, therefore, this forecast method provides a powerful technical support for the promotion of large-scale fracturing technology and reducing economic risks.
Lithium (Li) metal battery is considered the most promising next‐generation battery due to its low potential and high theoretical capacity. However, Li dendrite growth causes serious safety problems. ...Herein, the 15‐Crown‐5 (15‐C‐5) is reported as an electrolyte additive based on solvation shell regulation. The strong complex effect between Li+ ion and 15‐C‐5 can reduce the concentration of Li ions on the electrode surface, thus changing the nucleation, and repressing the growth of Li dendrites in the plating process. Significantly, the strong coordination of Li+/15‐C‐5 would be able to make them aggregate around the Li crystal surface, which could form a protective layer and favor the formation of a smooth and dense solid electrolyte interphase with high toughness and Li+ ion conductivity. Therefore, the electrolyte system with 2.0 wt% 15‐C‐5 achieves excellent electrochemical performance with 170 cycles at 1.0 mA cm−2 with capacity of 0.5 mA h cm−2 in symmetric Li|Li cells. The obviously enhanced cycle and rate performance are also achieved in Li|LiNi0.6Co0.2Mn0.2O2 (NCM622) full cells. The 15‐C‐5 demonstrates to be a promising additive for the electrolytes toward safe and efficient Li metal batteries.
Owing to the strong coordination ability, 15‐Crown‐5 (15‐C‐5) ether can coordinate with Li+ to form a Li+/15‐C‐5 protective layer in Li surface and favor the formation of smooth and dense solid electrolyte interphase films with high Li+ conductivity. This is found to be effective to enable high‐performance electrolytes for Li metal batteries with a life span of 170 cycles.
Pervious concrete is an environmentally friendly material that improves water permeability, skid resistance, and sound absorption characteristics. Permeability is the most important functional ...performance for the pervious concrete while limited studies have been conducted to predict permeability based on mix-design parameters. This study proposed a method to combine the beetle antennae search (BAS) and random forest (RF) algorithm to predict the permeability of pervious concrete. Based on the 36 samples designed in the laboratory and 4 key influencing variables, the permeability of pervious concrete can be obtained by varying mix-design parameters by RF. BAS algorithm was used to tune the hyperparameters of RF, which were then verified by the so-called 10-fold cross-validation. Furthermore, the model to combine the BAS and RF was validated by the correlation parameters. The results showed that the hyperparameters of RF can be tuned by the BAS efficiently; the BAS can combine the conventional RF algorithm to construct the evolved model to predict the permeability of pervious concrete; the cement/aggregate ratio was the most significant variable to determine the permeability, followed by the coarse aggregate proportions.
Gastric cancer is the fourth most common malignancy and the third leading cause of cancer-related deaths worldwide. Advanced gastric cancer patients can notably benefit from chemotherapy including ...adriamycin, platinum drugs, 5-fluorouracil, vincristine, and paclitaxel as well as targeted therapy drugs. Nevertheless, primary drug resistance or acquisition drug resistance eventually lead to treatment failure and poor outcomes of the gastric cancer patients. The detailed mechanisms involved in gastric cancer drug resistance have been revealed. Interestingly, different noncoding RNAs (ncRNAs), such as microRNAs (miRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs), are critically involved in gastric cancer development. Multiple lines of evidences demonstrated that ncRNAs play a vital role in gastric cancer resistance to chemotherapy reagents and targeted therapy drugs. In this review, we systematically summarized the emerging role and detailed molecular mechanisms of ncRNAs impact drug resistance of gastric cancer. Additionally, we propose the potential clinical implications of ncRNAs as novel therapeutic targets and prognostic biomarkers for gastric cancer.
Cloning of multiple genes in a single vector has greatly facilitated both basic and translational studies that require co-expression of multiple factors or multi-units of complex protein. Many ...strategies have been adopted, among which 2A "self-cleaving" peptides have garnered increased interest for their polycistronic nature, small size and high "cleavage" efficiency. However, broad application of 2 A peptides is limited by the lack of systematic comparison of different 2As alone or in combination. Here we characterized the effect of varying gene position and 2As on the expression of proteins encoded in bi-, tri-, or quad-cistronic constructs. Using direct cardiac reprogramming as an example, we further determined the effect of varied 2As on the efficiency of fluorescent cell labeling and cell fate conversion. We found that the expression of fluorophores decreased as it was moved towards the end of the construct while reprogramming was most efficient with the fluorophore at the second position. Moreover, quad-cistronic TPE2A constructs resulted in more efficient reprogramming than 3P2A or PTE2A constructs. We expect that the bi-, tri-, and quad-cistronic vectors constructed here and our results on protein expression ratios from different 2A constructs could serve to guide future utilization of 2A peptides in basic research and clinical applications.
The adult human heart has limited regenerative capacity. As such, the massive cardiomyocyte loss due to myocardial infarction leads to scar formation and adverse cardiac remodeling, which ultimately ...results in chronic heart failure. Direct cardiac reprogramming that converts cardiac fibroblast into functional cardiomyocyte-like cells (also called iCMs) holds great promise for heart regeneration. Cardiac reprogramming has been achieved both in vitro and in vivo by using a variety of cocktails that comprise transcription factors, microRNAs, or small molecules. During the past several years, great progress has been made in improving reprogramming efficiency and understanding the underlying molecular mechanisms. Here, we summarize the direct cardiac reprogramming methods, review the current advances in understanding the molecular mechanisms of cardiac reprogramming, and highlight the novel insights gained from single-cell omics studies. Finally, we discuss the remaining challenges and future directions for the field.
Generation of induced cardiac myocytes (iCMs) directly from fibroblasts offers great opportunities for cardiac disease modeling and cardiac regeneration. A major challenge of iCM generation is the ...low conversion rate of fibroblasts to fully reprogrammed iCMs, which could in part be attributed to unbalanced expression of reprogramming factors Gata4 (G), Mef2c (M), and Tbx5 (T) using the current gene delivery approach.
We aimed to establish a system to express distinct ratios of G, M, T proteins in fibroblasts and determine the effect of G, M, T stoichiometry on iCM reprogramming.
We took advantage of the inherent feature of the polycistronic system and generated all possible combinations of G, M, T with identical 2A sequences in a single transgene. We demonstrated that each splicing order of G, M, T gave rise to distinct G, M, T protein expression levels. Combinations that resulted in higher protein level of Mef2c with lower levels of Gata4 and Tbx5 significantly enhanced reprogramming efficiency compared with separate G, M, T transduction. Importantly, after further optimization, the MGT vector resulted in more than 10-fold increase in the number of mature beating iCM loci. Molecular characterization revealed that more optimal G, M, T stoichiometry correlated with higher expression of mature cardiac myocyte markers.
Our results demonstrate that stoichiometry of G, M, T protein expression influences the efficiency and quality of iCM reprogramming. The established optimal G, M, T expression condition will provide a valuable platform for future iCM studies.
To estimate the compressive strength of cement-based materials with mining waste, the dataset based on a series of experimental studies was constructed. The support vector machine (SVM), decision ...tree (DT), and random forest (RF) models were developed and compared. The beetle antennae search (BAS) algorithm was employed to tune the hyperparameters of the developed machine learning models. The predictive performances of the three models were compared by the evaluation of the values of correlation coefficient (R) and root mean square error (RMSE). The results showed that the BAS algorithm can effectively tune these artificial intelligence models. The SVM model can obtain the minimum RMSE, while the BAS algorithm is inefficient in DT and RF models. The SVM, DT, and RF models can be used to predict the compressive strength of cement-based materials using solid mining waste as aggregate effectively and accurately, with high R values and lower RMSE values. The RF algorithm can obtain the highest value of R and the lowest value of RMSE, demonstrating the highest accuracy. The solid mining waste to cement ratio is the most important variable to affect the compressive strength. Curing time was also an important parameter in the compressive strength of cemented materials, followed by the water-solid ratio of mining waste and fine sand ratio.
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