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As the most prevalent and reversible internal epigenetic modification in eukaryotic mRNAs, N6-methyladenosine (m6A) post-transcriptionally regulates the processing and metabolism of mRNAs involved in diverse biological processes. m6A modification is regulated by m6A writers, erasers, and readers. Emerging evidence suggests that m6A modification plays essential roles in modulating the cell-fate transition of embryonic stem cells. Mechanistic investigation of embryonic stem cell maintenance and differentiation is critical for understanding early embryonic development, which is also the premise for the application of embryonic stem cells in regenerative medicine. This review highlights the current knowledge of m6A modification and its essential regulatory contribution to the cell fate transition of mouse and human embryonic stem cells.

Single-phase body-centered cubic (BCC) lightweight Ti–V–Nb–Zrx solid-solution alloys were fabricated by reducing the Zr concentration within the range of 0–5 at% to improve the mechanical properties of equimolar TiVNbZr alloy at elevated temperatures. The fabricated Zrx alloys indeed exhibited greater strength above 800 °C than TiVNbZr, but some special mechanical responses occurred at 800 °C: (ⅰ) superficial cracks with different lengths and amounts along the high-angle grain boundaries (HAGBs) on the compressed sample surface, and (ⅱ) near-brittle fracture of the tensile stress-strain curves. Based on the analysis of the deformed and undeformed surface, local stress concentration and phase transformation were responsible for the cracks and difference in compression behavior, and atmospheric oxygen, deformation localization and phase transformation were mainly responsible for the tensile fracture difference at 800 °C. Phase transformation promote stress dispersion, combined with better oxidation resistance, which make the Zr-containing alloys fractured via the transgranular mode in tensile test. In particular, the Zr3 alloy exhibited work hardening and tensile ductility. Based on the tensile and compression properties of the Zrx alloys, it was found that at RT and 600 °C, atomic size difference (δ) governed alloy strength; from 800 to 1000 °C, δ and melting temperature (Tm) co-operatively governed alloy strength; at 1200 °C, alloy strength was independent of δ, but dependent on Tm. The fabricated Ti–V–Nb–Zrx alloys have medium mechanical properties but a small strength loss at high temperatures, and are suitable for various RT deformation processing methods.

BackgroundAfter the implementation of 2- and 3-child policies, the rising proportion of high-age and high-risk pregnancies put enormous pressure on maternal and child health (MCH) services for China. This populous nation with an increasing population flow imperatively required the support of large-scale information systems for management. Municipal MCH information systems were commonly applied in developed cities of eastern provinces in China. However, implementation of provincial MCH information systems in relatively low-income areas is lacking. In 2020, the implementation of a regional maternal and child information system (RMCIS) in Inner Mongolia filled this gap. ObjectiveThis paper aimed to demonstrate the construction process and evaluate the implementation effect of an RMCIS in improving the regional MCH in Inner Mongolia. MethodsWe conducted a descriptive study for the implementation of an RMCIS in Inner Mongolia. Based on the role analysis and information reporting process, the system architecture design had 10 modules, supporting basic health care services, special case management, health support, and administration and supervision. Five-color management was applied for pregnancy risk stratification. We collected data on the construction cost, key characteristics of patients, and use count of the main services from January 1, 2020, to October 31, 2022, in Inner Mongolia. Descriptive analysis was used to demonstrate the implementation effects of the RMCIS. ResultsThe construction and implementation of the RMCIS cost CNY 8 million (US $1.1 million), with a duration of 13 months. Between 2020 and 2022, the system recorded 221,772 registered pregnant women, with a 44.75% early pregnancy registry rate and 147,264 newborns, covering 278 hospitals and 225 community health care centers in 12 cities. Five-color management of high-risk pregnancies resulted in 76,975 (45.45%) pregnancies stratified as yellow (general risk), 36,627 (21.63%) as orange (relatively high risk), 156 (0.09%) as red (high risk), and 3888 (2.30%) as purple (infectious disease). A scarred uterus (n=28,159, 36.58%), BMI≥28 (n=14,164, 38.67%), aggressive placenta praevia (n=32, 20.51%), and viral hepatitis (n=1787, 45.96%) were the top factors of high-risk pregnancies (yellow, orange, red, and purple). In addition, 132,079 pregnancies, including 65,018 (49.23%) high-risk pregnancies, were registered in 2022 compared to 32,466 pregnancies, including 21,849 (67.30%) high-risk pregnancies, registered in 2020. ConclusionsThe implementation of an RMCIS in Inner Mongolia achieved the provincial MCH data interconnection for basic services and obtained both social and economic benefits, which could provide valuable experience to medical administration departments, practitioners, and medical informatics constructors worldwide.

Natural products synthesized by plants have substantial industrial and medicinal values and are therefore attracting increasing interest in various related industries. Among the key enzyme families involved in the biosynthesis of natural products, uridine diphosphate-dependent glycosyltransferases (UGTs) play a crucial role in plants. In recent years, significant efforts have been made to elucidate the catalytic mechanisms and substrate recognition of plant UGTs and to improve them for desired functions. In this review, we presented a comprehensive overview of all currently published structures of plant UGTs, along with in-depth analyses of the corresponding catalytic and substrate recognition mechanisms. In addition, we summarized and evaluated the protein engineering strategies applied to improve the catalytic activities of plant UGTs, with a particular focus on high-throughput screening methods. The primary objective of this review is to provide readers with a comprehensive understanding of plant UGTs and to serve as a valuable reference for the latest techniques used to improve their activities.

Peritoneal fibrosis (PF) is the main reason leading to declining efficiency and ultrafiltration failure of peritoneum, which restricts the application of peritoneal dialysis (PD). We aimed to investigate the effects and mechanisms of miR-122-5p on the PF. Sprague-Dawley (SD) rats were infused with glucose-based standard PD fluid to establish PF model. HE staining was performed to evaluate the extent of PF. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) and fluorescence in situ hybridization (FISH) were performed to measure the expression level of miR-122-5p. Western blot was used to test the expression of transforming growth factor (TGF)-β1, platelet-derived growth factor (PDGF)-A, Fibronectin 1 (FN1), extracellular matrix protein 1 (ECM1), Smad5, α-smooth muscle actin (SMA), collagen type 1(COL-1), Vimentin, E-Cadherin, Wnt1, β-catenin, p-β-catenin, c-Myc, c-Jun, and Cyclin D1. Immunohistochemistry (IHC) staining was used to detect type I collagen alpha 1 (Col1α1), α-SMA, and E-Cadherin expression. We found PF was glucose concentration-dependently enhanced in peritoneum of PD rat. The PD rats showed increased miR-122-5p and decreased Smad5 expression. MiR-122-5p silencing improved PF and epithelial–mesenchymal transition (EMT) process in PD rats. MiR-122-5p silencing attenuated the activity of the Wnt/β-catenin signaling pathway. Importantly, dual-luciferase reporter assay showed Smad5 was a target gene of miR-122-5p. Smad5 overexpression significantly reversed the increases of PF and EMT progression induced by miR-122-5p overexpression. Moreover, miR-122-5p mimic activated Wnt/β-catenin activity, which was blocked by Smad5 overexpression. Overall, present results demonstrated that miR-122-5p overexpression showed a deterioration effect on PD-related PF by targeting Smad5 to activate Wnt/β-catenin pathway.

Abstract Background The main focus of in silico drug repurposing, which is a promising area for using artificial intelligence in drug discovery, is the prediction of drug–disease relationships. Although many computational models have been proposed recently, it is still difficult to reliably predict drug–disease associations from a variety of sources of data. Results In order to identify potential drug–disease associations, this paper introduces a novel end-to-end model called Graph convolution network based on a multimodal attention mechanism (GCMM). In particular, GCMM incorporates known drug–disease relations, drug–drug chemical similarity, drug–drug therapeutic similarity, disease–disease semantic similarity, and disease–disease target-based similarity into a heterogeneous network. A Graph Convolution Network encoder is used to learn how diseases and drugs are embedded in various perspectives. Additionally, GCMM can enhance performance by applying a multimodal attention layer to assign various levels of value to various features and the inputting of multi-source information. Conclusion 5 fold cross-validation evaluations show that the GCMM outperforms four recently proposed deep-learning models on the majority of the criteria. It shows that GCMM can predict drug–disease relationships reliably and suggests improvement in the desired metrics. Hyper-parameter analysis and exploratory ablation experiments are also provided to demonstrate the necessity of each module of the model and the highest possible level of prediction performance. Additionally, a case study on Alzheimer’s disease (AD). Four of the five medications indicated by GCMM to have the highest potential correlation coefficient with AD have been demonstrated through literature or experimental research, demonstrating the viability of GCMM. All of these results imply that GCMM can provide a strong and effective tool for drug development and repositioning.

Abstract Background The shared care pathway for ADHD is a program developed in Canada with two main strategies: (a) implement a shared care pathway between general practitioners (GPs) and specialists, and (b) step up or down care so that the patient is treated at the most appropriate level of care, depending on the complexity or outcome of their illness. The current study aims to identify the challenges and facilitators of implementing this program in a Chinese mental health service setting. Methods Two focus groups were conducted using semi-structured interviews with a total of 7 health care providers in Beijing. An adapted grounded theory methodology using open-ended, axial and selective coding was used for data analysis. Results We identified three main levels related to barriers and facilitators: (1) a sociocultural level of patients' and health care providers' perspectives; (2) a structural level related to internal and external organizational environments; (3) and the level of the intervention itself with its characteristics. The project is generally aligned with the mandates and goals of the health system, but two of the main obstacles are the varying qualifications of physicians in hospitals of different levels, implying different needs and flexible and adapted training programs, and the lack of appropriate patient referral systems between the different hospital levels. Conclusion Our study highlights the importance of consultation to obtain a "lay of the land" for deciding on the implementation steps of an a priori well accepted model of care.

Environmental, Social, and Governance (ESG) is changing from a concept to corporate soft power. Can this improve corporate performance in capital markets? There is little literature linking environmental, Social, and Governance performance to stock liquidity. Therefore, It is of urgent theoretical and practical importance to study the impact of environmental, Social, and Governance performance on stock liquidity. Using Chinese A-share listed companies from 2015 to 2020 as a sample to empirically examine the impact of environmental, Social, and Governance performance on stock liquidity and its mechanism. We find that environmental, Social, and Governance performance has a significant positive impact on listed companie’s stock liquidity. This conclusion was validated after conducting a series of robustness tests. Mechanism analysis shows that environmental, Social, and Governance performance can promote stock liquidity by reducing agency costs, increasing the proportion of foreign ownership, and improving corporate reputation. The heterogeneity analysis shows that environmental, Social, and Governance performance in state-owned enterprises, heavily polluting enterprises, and enterprises in areas with low degrees of marketisation has a more significant positive promoting effect on stock liquidity. This study expands the research on environmental, Social, and Governance performance and has implications for promoting the development of environmental, Social, and Governance practices.

Quorum sensing (QS) is considered to be a promising regulation method for biological wastewater treatment (WWT) due to its regulation in extracellular substances (EPS) production, biofilm formation, granulation, colonization and bacterial activity and stability. Recently, autoinducer-2 (AI-2), a kind of interspecies communication QS signal molecule, is being increasingly reported for its roles in regulating bacterial gene expression and aggregation. Consequently, AI-2 mediated QS system is considered as a promising regulatory approach in WWT processes. This article systematically reviews the effects of AI-2-mediated QS system on bacterial behavior and its high potential for real-world applications in different WWT systems. Given the extensive presence of AI-2, AI-2 mediated QS could cooperate with other signal molecules in WWT processes, which suggests that the interactions among multiple signal molecules might be underestimated in the previous studies. The differences between AI-2 and AHL signaling molecules are also compared. Furthermore, the attempts at AI-2 regulated QS in pollution control of different WWT systems are summarized, while some challenges and defects still require targeted research in the future. HIGHLIGHTS The AI-2 mediated QS is a potential regulatory approach in WWT processes.; The differences between AI-2 and AHL signaling molecules are compared.; The interaction among multiple signal molecules might be underestimated in the previous studies.; Possible applications of QQ mechanism based on AI-2 need to be further studied.;

Hepatocellular carcinoma (HCC) is the most common liver tumor, with a continually rising incidence. The curative treatment for HCC is surgical resection or liver transplantation; however, only a small portion of patients are eligible due to local tumor burden or underlying liver dysfunction. Most HCC patients receive nonsurgical liver-directed therapies (LDTs), including thermal ablation, transarterial chemoembolization (TACE), transarterial radioembolization (TARE), and external beam radiation therapy (EBRT). Stereotactic ablative body radiation (SABR) is a specific type of EBRT that can precisely deliver a high dose of radiation to ablate tumor cells using a small number of treatments (or fractions, typically 5 or less). With onboard MRI imaging, MRI-guided SABR can improve therapeutic dose while minimizing normal tissue exposure. In the current review, we discuss different LDTs and compare them with EBRT, specifically SABR. The emerging MRI-guided adaptive radiation therapy has been reviewed, highlighting its advantages and potential role in HCC management.

Quorum sensing (QS) is a communication mode between microorganisms to regulate bacteria ecological relations and physiological behaviors, thus achieve the physiological function that single bacteria cannot complete. This phenomenon plays important roles in the formation of biofilm and granular sludge, and may be related to enhancement of some functional bacteria activity in wastewater treatment systems. There is a need to better understand bacterial QS in engineered reactors, and to assess how designs and operations might improve the removal efficiency. This article reviewed the recent advances of QS in several environmental systems and mainly analyzed the regulation mechanism of QS-based strategies for biofilm, granular sludge, functional bacteria, and biofouling control. The co-existences of multiple signal molecules in wastewater treatment (WWT) processes were also summarized, which provide basis for the future research on the QS mechanism of multiple signal molecules' interaction in WWT. This review would present some prospects and suggestions which are of practical significance for further application.

Due to the limitations of welding complexity and machining error, traditional manual teaching and offline programming are not intelligent enough and have weak adaptability to workpiece. At present, the 2D perception visual welding guidance programming method is commonly used which cannot accurately locate and model the complicated 3D spatial curve welding seam. The 2D perception method can hardly meet the requirements of welding process. In this paper, a welding seam perception method based on a line structure-light sensor was proposed, which optimizes the generation of the weld seam trajectory, and builds a highly adaptable intelligent guidance programming system for welding robots. Firstly, 3D modeling perception of welding parts is realized through eye-in-hand system of robot, which solves the problem that offline programming system cannot be applied when the welding model is not precise enough or partly miss. Secondly, aiming at solving extraction problem of common types of 3D space curve welding seam, corresponding types of weld extraction algorithms are proposed according to the characteristics of different types of welds under the general process of weld extraction. These methods not only can directly extract the weld from the ordered point cloud with high precision and resolution, but also are less affected by the welding environment, which solve the problem of low perception accuracy of complex curved welds in 3D space. Then, on the basis of welding seam extraction, NURBS curves are used to realize the optimal generation of weld trajectory. Finally, the feasibility and effectiveness of all the methods proposed in this paper are verified by a large number of experiments.

Wind turbine fault diagnosis and early warning are important to reduce wind farm operation and maintenance costs and improve power generation efficiency. In this paper, we take the Supervisory Control and Data Acquisition (SCADA) data as the research object and research wind turbine health data purification, fault diagnosis model building, and unit operation status monitoring from a completely data-driven perspective. Firstly, for the problem that Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm cannot identify high-density anomalous data. An anomaly data processing scheme combining a density clustering algorithm and normal power interval estimation is proposed. The accuracy of extracting health data from wind turbines is improved. Secondly, to address the problem that the eXtreme Gradient Boosting (XGBoost) algorithm has more hyperparameters, we propose an optimization scheme based on the Bayesian Optimization Algorithm (BOA) and tree model for feature weight measurement, which improves the efficiency and accuracy of intuitive mapping from SCADA system monitoring data to fault features. Finally, a wind turbine condition monitoring scheme based on the information fusion of multi-characteristic monitoring parameters is designed. The wind turbine condition monitoring scheme proposed in this paper can warn generator system failure 3.67 hours, gearbox system failure 5.17 hours in advance, and hydraulic system failure 2.33 hours in advance.

Effective early warning of wind turbine failures is of great significance to reduce the operation and maintenance costs of wind farms and improve power generation efficiency. At present, most wind farms are installed with supervisory control and data acquisition (SCADA) system, and SCADA data contains a lot of hidden information, which can be used for fault early warning. This paper uses the generator temperature and gearbox oil temperature in the SCADA data as the entry point for fault warning. Firstly, the eXtreme gradient boosting (XGBoost) algorithm is used to establish the normal temperature regression prediction model of wind turbine components. Then, the residual between the predicted value and the actual value is calculated, and the change trend of the residual is monitored by the principle of exponentially weighted moving-average (EWMA) control chart. Finally, by setting an appropriate threshold, the variation trend of the residual is judged to determine the occurrence and development of the fault. This paper uses two fault detection methods: fixed threshold and dynamic threshold based on adaptive algorithm, and compares the advantages and disadvantages of the two methods. Based on the SCADA data of a wind farm in Inner Mongolia (China), this paper designs the fault early warning test of the wind turbine generator and gearbox. The experimental results show that for the generator, the fixed fault threshold method can give the fault alarm 3 hours in advance, while the dynamic fault threshold determination method can give fault alarm 4.25 hours in advance. For gearbox, the fixed fault threshold method can give the fault alarm 2 hours in advance, while the dynamic threshold fault diagnosis method can send out the fault alarm 2.75 hours in advance.

Background/introduction: Chickenpox is a common viral infection caused by Varicella-zoster virus (VZV). Pneumonia is an infrequent complication of chickenpox infection. Rarely, multiple calcified pulmonary nodules can be the sequela of healed VZV pneumonia. Case presentation: A middle-aged female individual was found to have diffuse incidental pulmonary micronodules. By further history inquiry and diagnosis of exclusion, her pulmonary micronodules were determined to be likely associated with prior VZV infection. Conclusions: VZV infection can cause calcified pulmonary nodules related to granuloma, and gold standard diagnosis is surgical lung biopsy with VZV PCR. However, diagnosis of exclusion is a reasonable approach to reach a presumptive diagnosis. Familiarity with this entity can potentially avoid invasive procedures in selected patients.

Aim: The current treatments of toxic epidermal necrolysis (TEN) are limited to the discontinuation of a suspect medication and supportive measures. We conducted a retrospective study to evaluate the efficacy of adding continuous venovenous hemofiltration (CVVH) and hemoperfusion (HP) to the conventional treatment for TEN. Methods: TEN patients who were admitted to our center between January 2008 and May 2016 were considered as candidates. The included patients were divided into the CVVH&HP group (n = 34) and the conventional group (n = 34) according to their accepted therapies during hospital stay. Results: The patients in the conventional group had a significantly reduced 28-day survival proportion compared with patients in the CVVH&HP group (73.5 versus 91.2%, p = .047). The adjusted results demonstrated that the conventional group had a significantly higher risk of 28-day mortality as well. Moreover, patients in the CVVH&HP group were associated with significantly shorter hospital stay, rash, fever, and antibiotic durations. However, the addition of CVVH&HP to conventional treatment did not significantly increase the in-hospital cost. Conclusions: In conclusion, CVVH&HP might be a safe and effective adjuvant therapy for TEN. Further well-designed studies are warranted to obtain robust evidence.

The development of industry 4.0 has put forward higher requirements for modern milling technology. Monitoring the degree of milling tool wear during machine tool processing can improve product quality and reduce production losses. In the machining process of machine tools, many kinds of tools are usually used, and the signal characteristics of various sensors of different tools are different. Therefore, before the tool wear assessment, this paper identified the tool type according to the spindle current data. After the tool type recognition, this paper evaluates the tool wear degree according to the tool force data, vibration data, acoustic emission signal, and other multi-sensor data. Firstly, the Elman neural network and Adaboost algorithm are combined to construct the Elman_Adaboost strong predictor. Then, the variance and mean of seven sensor data were selected as the characteristic quantities to input the strong predictor. Finally, three wear quantities were obtained to measure the wear degree of the tool. The method proposed in this paper is implemented by Matlab, and the validity of this method is verified using the competition data provided by PHM (Prognostics and Health Management) Society. The results show that the average evaluation accuracy of the same tool wear is more than 92%, and that of the similar tool wear is more than 85%.

Hiking is a popular recreational activity and to cater to public demand, it is apt to increase the number of hiking trails. Various methodologies have been proposed to evaluate the suitability of forest trails to be constructed as hiking trails, but they can be costly and require relevant knowledge in analyzing digital information through a high-throughput dataset. Therefore, there is a need to come up with a simple method to obtain first-hand information on the trail condition, particularly considering the aspects of safety and suitability to hikers, using both on-ground and aerial observations. In this study, we introduce a new assessment approach to analyze and select old forest trails to be reconstructed as new hiking trails. This is useful for park managers who prioritize safety, comfort, and aesthetic features of the recreation site for their visitors. Trail condition assessment was carried out along the trail whereby a 2×2 m sampling plot was constructed at every 100 m. Aerial drone survey was conducted to produce an ortho-mosaic that revealed the percentage of exposed trail from above. Potential phytotourism products and scenic spots were identified and recorded for their locations along the trail to promote the aesthetic value of the recreation site. A strength distribution plot was prepared based on the trail condition, canopy coverage, and aesthetic features along the trail that were categorized using three altitude ranges (n ≤ 150 m, 150 < n < 250 m, n ≥ 250 m a.s.l.). This is to assess the trade-offs in safety, comfort, and aesthetic features along the trail. The development of this methodology offers a direct and cost-effective, yet informative approach to evaluate the quality of a potential hiking trail, thus could effectively aid in the promotion of nature-based tourism.

To determine whether and how the patterns of breast cancer-specific mortality (BCSM) changed along with time periods.We used the Surveillance, Epidemiology and End Results registry to identify 228209 female patients diagnosed with invasive breast cancer between 1990 and 2000 (cohort 1 [C1], 112981) and between 2001 and 2005 (cohort 2 [C2], 115228). BCSM was compared in two cohorts using Cox proportional hazard regression models. We analysed the relative hazard ratios (HRs) and absolute BCSM rates by flexible parametric survival modelling.The patterns of BCSM were similar between the two cohorts, with the peak of mortality presenting in the first 2-3 years after diagnosis, and mortality rate significantly decreased in C2 in all cases. In C2, the annual BCSM rate of all cases was 9.64 (per 1000 persons per year) in year 10 with a peak rate of 23.34 in year 2. In ER-negative and high-risk patients, marked survival improvements were achieved mostly in the first 5 years, while in ER-positive and low-risk patients, survival improvements were less but constant up to 10 years.There has been a significant improvement of BCSM with substantially decreased mortality within 5 years. The current pattern of BCSM and its changing feature differs according to ER status. Our findings have some clinical implications both for treatment decisions and adjuvant treatment trial design.