Increased recruitment of endogenous stem cells and chondrogenic differentiation by a composite scaffold containing bone marrow homing peptide for cartilage regeneration

Even small cartilage defects could finally degenerate to osteoarthritis if left untreated, owing to the poor self-healing ability of articular cartilage. Stem cell transplantation has been well implemented as a common approach in cartilage tissue engineering but has technical complexity and safety concerns. The stem cell homing-based technique emerged as an alternative promising therapy for cartilage repair to overcome traditional limitations. In this study, we constructed a composite hydrogel scaffold by combining an oriented acellular cartilage matrix (ACM) with a bone marrow homing peptide (BMHP)-functionalized self-assembling peptide (SAP). We hypothesized that increased recruitment of endogenous stem cells by the composite scaffold could enhance cartilage regeneration. Methods: To test our hypothesis, in vitro proliferation, attachment and chondrogenic differentiation of rabbit mesenchymal stem cells (MSCs) were tested to confirm the bioactivities of the functionalized peptide hydrogel. The composite scaffold was then implanted into full-thickness cartilage defects on rabbit knee joints for cartilage repair, in comparison with microfracture or other sample groups. Stem cell recruitment was monitored by dual labeling with CD29 and CD90 under confocal microcopy at 1 week after implantation, followed by chondrogenic differentiation examined by qRT-PCR. Repaired tissue of the cartilage defects was evaluated by histological and immunohistochemistry staining, microcomputed tomography (micro-CT) and magnetic resonance imaging (MRI) at 3 and 6 months post-surgery. Macroscopic and histological scoring was done to evaluate the optimal in vivo repair outcomes of this composite scaffold. Results: The functionalized SAP hydrogels could stimulate rabbit MSC proliferation, attachment and chondrogenic differentiation during in vitro culture. At 7 days after implantation, increased recruitment of MSCs based on CD29(+)/CD90(+) double-positive cells was found in vivo in the composite hydrogel scaffold, as well as upregulation of cartilage-associated genes (aggrecan, Sox9 and type II collagen). After 3 and 6 months post-surgery, the articular cartilage defect in the composite scaffold-treated group was fully covered with cartilage-like tissue with a smooth surface, which was similar to the surrounding native cartilage, according to the results of histological and immunohistochemistry staining, micro-CT and MRI analysis. Macroscopic and histological scoring confirmed that the quality of cartilage repair was significantly improved with implantation of the composite scaffold at each timepoint, in comparison with microfracture or other sample groups. Conclusion: Our findings demonstrated that the composite scaffold could enhance endogenous stem cell homing and chondrogenic differentiation and significantly improve the therapeutic outcome of chondral defects. The present study provides a promising approach for in vivo cartilage repair without cell transplantation. Optimization of this strategy may offer great potential and benefits for clinical application in the future

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Daily flow prediction of the Huayuankou hydrometeorological station based on the coupled CEEMDAN–SE–BiLSTM model

Abstract Enhancing flood forecasting accuracy, promoting rational water resource utilization and management, and mitigating river disasters all hinge on the crucial role of improving the accuracy of daily flow prediction. The coupled model of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Sample Entropy (SE), and Bidirectional Long Short-Term Memory (BiLSTM) demonstrates higher stability when faced with nonlinear and non-stationary data, stronger adaptability to various types and lengths of time series data by utilizing sample entropy, and significant advantages in processing sequential data through the BiLSTM network. In this study, in the context of predicting daily flow at the Huayuankou Hydrological Station in the lower reaches of the Yellow River, a coupled CEEMDAN–SE–BiLSTM model was developed and utilized. The results showed that the CEEMDAN–SE–BiLSTM coupled model achieved the utmost accuracy in prediction and optimal fitting performance. Compared with the CEEMDAN–SE–LSTM, CEEMDAN–BiLSTM, and BiLSTM coupled models, the root mean square error (RMSE) of this model is reduced by 42.77, 182.02, and 193.71, respectively; the mean absolute error (MAE) is reduced by 37.62, 118.60, and 126.67, respectively; and the coefficient of determination (R2) is increased by 0.0208, 0.1265, 0.1381

Assessing effect of best management practices in unmonitored watersheds using the coupled SWAT-BiLSTM approach

Abstract In order to enhance the simulation of BMPs (Best Management Practices) reduction effects in unmonitored watersheds, in this study, we combined the physically-based hydrological model Soil & Water Assessment Tool (SWAT) and the data-driven model Bi-directional Long Short-Term Memory (Bi-LSTM), using the very-high-resolution (VHR) Land Use and Land Cover (LULC) dataset SinoLC-1 as data input, to evaluate the feasibility of constructing a water environment model for the Ba-River Basin (BRB) in central China and improving streamflow prediction performance. In the SWAT-BiLSTM model, we calibrated the top five SWAT parameters sorted by P-Value, allowing SWAT to act as a transfer function to convert meteorological data into base flow and storm flow, serving as the data input for the Bi-LSTM model. This optimization improved the Bi-LSTM's learning process for the relationship between the target and explanatory variables. The daily streamflow prediction results showed that the hybrid model had 9 regions rated as "Very good," 2 as "Good," 2 as "Satisfactory," and 1 as "Unsatisfactory" among the 14 regions. The model achieved an NSE of 0.86, R2 of 0.85, and PBIAS of −2.71% for the overall daily streamflow prediction performance during the verification period of the BRB. This indicates that the hybrid model has high predictive accuracy and no significant systematic bias, providing a sound hydrodynamic environment for water quality simulation. The simulation results of different BMPs scenarios showed that in the scenarios with only one BMP measure, stubble mulch had the best reduction effect, with average reductions of 17.83% for TN and 36.17% for TP. In the scenarios with a combination of multiple BMP measures, the combination of stubble mulch, soil testing and formula fertilization, and vegetative filter strip performed the best, achieving average reductions of 42.71% for TN and 50.40% for TP. The hybrid model provides a novel approach to simulate BMPs' reduction effects in regions without measured hydrological data and has the potential for wide application in BMP-related decision-making

Construction and application of urban water system connectivity evaluation index system based on PSR-AHP-Fuzzy evaluation method coupling

The connectivity of urban water systems can enhance the connectivity of regional rivers, lakes, and water systems, which can improve the regional water environment and water ecology to a certain extent, and enhance the water disaster prevention capability. To scientifically evaluate the effect of water system connectivity in the comprehensive urban water system management project. In this study, a regional waterlogging model based on the coupling of ArcGis and SWMM is established. At the same time, the evaluation index system of water system connectivity effect of regional town water system comprehensive management project was constructed regarding PSR (“Pressure-Status-Response”) theory with structural connectivity, hydraulic connectivity and ecological and environmental improvement as the criteria, and the fuzzy evaluation method was used for analysis and evaluation. The results show that the improvement in the water environment is obvious after the water system is connected. The total length and area of rivers in the study area increased by 68.98% and 57.51%, respectively. River network density increased from 0.66 km/km2 to 0.69 km/km2, an increase of 4.55%; the regional water surface rate increased from 2.22% to 3.51%, an increase of 58.11%; the river frequency increased from 0.15/km2 to 0.29/km2, an increase of 93.33%. The water exchange capacity increased by 37.5% and the flow rate increased by 30%. All water systems have a better degree of connectivity and a better structure of river network water system. The decay rate of point source pollution increased by 40.61%, the water quality of rivers reached V standard, and the area covered by green areas increased to 32.29%. The evaluation grade of hydraulic characteristics and ecological environment indexes was “excellent”. The total evaluation set D=[0.5417,0.0791,0.2125,0] for the effect of water system connection in the study area. According to the principle of maximum affiliation, the improvement effect of the water system connection project in the study area is “excellent”

Rainfall prediction in coastal hilly areas based on VMD–RSA–DNC

Highly accurate rainfall prediction can provide a reliable scientific basis for human production and life. For the characteristics of occasional and sudden changes of rainfall in coastal hilly areas, this article chooses four cities in the eastern Zhejiang province as the object of the study and establishes a rainfall prediction model based on variational mode decomposition (VMD), reptile search algorithm (RSA), and differentiable neural computer (DNC). The VMD algorithm reduces the complexity of the sequence data; RSA is used to find the best-fit function; and DNC combines the advantages of the recurrent neural network and computational processing to improve the problem of memory forgetting of long short-term memory. To verify the prediction accuracy of the model, the prediction results are compared with the other three models, and the results show that the VMD–RSA–DNC model has the best prediction with the maximum and minimum relative errors of 9.62 and 0.17%, respectively, the average root-mean-square error of 5.43, the average mean absolute percentage error of 3.59%, and the average Nash–Sutcliffe efficiency of 0.95 for predicting four cities in the coastal hilly area. This study provides a new reference method for the construction of rainfall prediction models. HIGHLIGHTS Optimization of the differentiable neural computer (DNC) controller with reptile search algorithm (RSA) has a solid theoretical basis.; The coastal hilly area where plum rains and typhoons exist is selected for the study, and the prediction effect is better.; The coupled variational mode decomposition (VMD)–RSA–DNC model has higher prediction accuracy compared with other models.

Assessing the response of non-point source nitrogen pollution to land use change based on SWAT model

In recent years, with the growth of the population and the continuous expansion of agricultural land, non-point source (NPS) pollution has gradually become the primary cause of deteriorating water quality in the aquatic environment. Compared to point source pollution, NPS pollution is more diffuse, complex in its mechanisms, and challenging to pinpoint its sources. This study utilized the SWAT-Land Use Update Tool (SWAT-LUT) to dynamically update multi-year land use and land cover (LULC) data into the SWAT model to investigate the differences in nitrogen pollution sources in Jincheng City under different LULC scenarios. Two models were constructed in this study: SWAT-UNI, which utilized static 1997 LULC data, and SWAT-MULTI, which incorporated dynamic LULC data from 1997 to 2022. During the calibration period, SWAT achieved R2 and NSE values exceeding 0.82 for the daily streamflow simulation results, and these values remained above 0.76 during the validation period. Additionally, the Patch-generating Land Use Simulation (PLUS) model was employed to forecast the land use evolution in Jincheng City from 2022 to 2032 to explore the future response of NPS nitrogen pollution. From 1997 to 2022, significant changes were observed in agricultural land, forested land, and grassland areas within Jincheng City. Agricultural land and forested land increased by 3.29% and 4.71% of the total area of Jincheng City, respectively, while grassland decreased by 10.4%. In the prediction of land use evolution from 2022 to 2032, the evolutionary trends remained similar to previous patterns, albeit with a slightly decelerated pace. Simulation results indicated that the top three sources of nitrogen pollution in Jincheng City's water bodies in 1997 were atmospheric deposition (39.8%), nitrogen fertilizer application (29.8%), and soil nitrogen reservoirs (21.4%). With the continuous expansion of agricultural land, nitrogen pollution from nitrogen fertilizer application accounted for 35.6% of the TN (Total Nitrogen) load in water bodies in 2022, surpassing atmospheric deposition to become the dominant factor. The contribution of soil nitrogen reservoirs to nitrogen pollution in water bodies within Jincheng City showed a continuous upward trend over the twenty-five years, resulting in a total nitrogen load of 565.1 tons in 2022, ranking second and becoming a crucial aspect in pollution control efforts. Regarding seasonal distribution, the crop growing season (March to September) was identified as the critical period for controlling nitrogen pollution from nitrogen fertilizer application, while the autumn and winter seasons were crucial for controlling nitrogen pollution from atmospheric deposition and soil nitrogen reservoirs. The predictive results for future NPS nitrogen pollution indicate a continual increase in annual TN inflow into the river from nitrogen fertilizer application and soil nitrogen reservoirs, reaching 1841.6 tons in 2032, accounting for 65.2% of the total inflow. This research contributes to supporting decision-making for NPS pollution control measures in Jincheng City

Transcriptome Sequencing Reveals Pathways Related to Proliferation and Differentiation of Shitou Goose Myoblasts

Chinese Shitou goose is a type of large goose with high meat yield. Understanding the genetic regulation of muscle development in Shitou goose would be beneficial to improve the meat production traits of geese. Muscle development is regulated by genes related to myoblast proliferation and differentiation. In this study, the RNA-seq method was used to construct the mRNA and lncRNA expression profiles of Shitou goose myoblasts and myotubes. A total of 1664 differentially expressed (DE) mRNAs and 244 DE-lncRNAs were identified. The alternative mRNA splicing in proliferation and differentiation stages was also analyzed. Notably, pathways enriched in DE-mRNAs, DE-splicing transcripts, and DE-lncRNAs all point to the Wnt signaling pathway, indicating that the Wnt signaling is a key regulatory pathway of muscle development in Shitou goose. We also constructed the interactive network of DE-lncRNAs and DE-mRNAs and revealed some key genes of lncRNAs regulating the proliferation and differentiation of myoblasts. These results provide new insights for the study of the muscle development of the Shitou goose

Exotic Hydrogen Bonding in Compressed Ammonia Hydrides

Hydrogen-rich compounds attract significant fundamental and practical interest for their ability to accommodate diverse hydrogen bonding patterns and their promise as superior energy storage materials. Here, we report on an intriguing discovery of exotic hydrogen bonding in compressed ammonia hydrides and identify two novel ionic phases in an unusual stoichiometry NH7. The first is a hexagonal R3̅m phase containing NH3–H+–NH3, H–, and H2 structural units stabilized above 25 GPa. The exotic NH3–H+–NH3 unit comprises two NH3 molecules bound to a proton donated from a H2 molecule. Above 60 GPa, the structure transforms to a tetragonal P41212 phase comprising NH4+, H–, and H2 units. At elevated temperatures, fascinating superionic phases of NH7 with part-solid and part-liquid structural forms are identified. The present findings advance fundamental knowledge about ammonia hydrides at high pressure with broad implications for studying planetary interiors and superior hydrogen storage materials