Ultrasonic-assisted preparation of SBS modified asphalt: Cavitation bubble numerical simulation and rheological properties.

SBS (styrene-butadiene-styrene block copolymer) is currently the most widely used asphalt modifier, and SBS modified asphalt is usually prepared by high-speed shearing. This paper combines the cavitation effect of ultrasonic to assist in the preparation of SBS modified asphalt, and conducts numerical simulation and rheological properties research on the cavitation bubbles in the molten SBS modified asphalt fluid. The cavitation bubbles in the modified asphalt fluid will expand and contract as the pressure changes inside and outside the bubbles. When the cavitation bubble is compressed to the minimum and the pressure inside the bubble reaches 1.94 × 105Pa, the direction of the velocity vector near the cavitation bubble will change with the expansion and compression of the bubble. The expansion-contraction process of a single cavitation bubble can release 6.41 × 10-7J of energy, thus breaking the long bonds in asphalt and generating a large number of free radicals react with the unsaturated C = C bonds in the SBS molecules. According to the preparation process of modified asphalt, the influence of ultrasonic wave on rheological property of modified asphalt was studied through experiments. The results show that ultrasonic treatment can enhance the elasticity of asphalt and improve the temperature sensitivity of asphalt. With the increase of ultrasonic treatment time, the anti-rutting deformation ability of SBS modified asphalt is greatly improved. At the same temperature, the recovery rate of asphalt also increases with the increase of ultrasonic treatment time, and the non-recoverable compliance (Jnr) decreases Combined with the numerical simulation of cavitation bubbles, the ultrasonic process is added to asphalt production, which is of great significance for the green production of modified asphalt and the improvement of the rheological properties of modified asphalt.

Academic resilience in nusing students: a concept analysis.

BACKGROUND: Academic resilience is a crucial concept for nursing students to cope with academic challenges. Currently, there is significant variation in the description of the concept attributes of academic resilience among nursing students, which impedes the advancement of academic research. Therefore, it is essential to establish a clear definition of the concept of academic resilience for nursing students. PURPOSE: The purpose of this paper is to report the results of concept analysis of academic resilience of nursing students. METHODS: The Rodgers evolutionary concept analysis was employed to test the attributes, antecedents, consequences and related concepts of academic resilience of nursing students. Walker and Avant's method was utilized to construct a model case and provide empirical referents. RESULTS: The findings indicate that the attributes of nursing students' academic resilience include self-efficacy, self-regulation and recovery, and the antecedents include internal factors and external environmental factors. The consequences include adaptability, career maturity, adversity quotient level, probability of academic success, a sense of belonging to school and low levels of psychological distress. CONCLUSION: The systematic understanding of academic resilience among nursing students provides a pathway for nursing educators and students to enhance academic resilience, promote academic success, and establish a foundation for the training of more qualified nurses.

Small water body significantly contributes to nitrous oxide emissions in China's aquaculture.

Aquaculture systems are expected to act as potential hotspots for nitrous oxide (N2O) emissions, largely attributed to substantial nutrient loading from aquafeed applications. However, the specific patterns and contributions of N2O fluxes from these systems to the global emissions inventory are not well characterized due to limited data. This study investigates the patterns of N2O flux across 127 freshwater systems in China to elucidate the role of aquaculture ponds and lakes/reservoirs in landscape N2O emission. Our findings show that the average N2O flux from aquaculture ponds was 3.63 times higher (28.73 µg N2O m-2 h-1) than that from non-aquaculture ponds. Additionally, the average N2O flux from aquaculture lakes/reservoirs (15.65 µg N2O m-2 h-1) increased 3.05 times compared to non-aquaculture lakes/reservoirs. The transition from non-aquaculture to aquaculture practices has resulted in a net annual increase of 7589 ± 2409 Mg N2O emissions in China's freshwater systems from 2003 to 2022, equivalent to 20% of total N2O emissions from China's inland water. Particularly, the robust negative regression relationship between N2O emission intensity and water area suggests that small ponds are hotspots of N2O emissions, a result of both elevated nutrient concentrations and more vigorous biogeochemical cycles. This indicates that N2O emissions from smaller aquaculture ponds are larger per unit area compared to equivalent larger water bodies. Our findings highlight that N2O emissions from aquaculture systems can not be proxied by those from natural water bodies, especially small water bodies exhibiting significant but largely unquantified N2O emissions. In the context of the rapid global expansion of aquaculture, this underscores the critical need to integrate aquaculture into global assessments of inland water N2O emissions to advance towards a low-carbon future.

Spatiotemporal transcriptomic landscape of rice embryonic cells during seed germination.

Characterizing cellular features during seed germination is crucial for understanding the complex biological functions of different embryonic cells in regulating seed vigor and seedling establishment. We performed spatially enhanced resolution omics sequencing (Stereo-seq) and single-cell RNA sequencing (scRNA-seq) to capture spatially resolved single-cell transcriptomes of germinating rice embryos. An automated cell-segmentation model, employing deep learning, was developed to accommodate the analysis requirements. The spatial transcriptomes of 6, 24, 36, and 48 h after imbibition unveiled both known and previously unreported embryo cell types, including two unreported scutellum cell types, corroborated by in situ hybridization and functional exploration of marker genes. Temporal transcriptomic profiling delineated gene expression dynamics in distinct embryonic cell types during seed germination, highlighting key genes involved in nutrient metabolism, biosynthesis, and signaling of phytohormones, reprogrammed in a cell-type-specific manner. Our study provides a detailed spatiotemporal transcriptome of rice embryo and presents a previously undescribed methodology for exploring the roles of different embryonic cells in seed germination.

Nutrient requirements determined by grain yield and protein content to optimize N, P, and K fertilizer management in China.

Nutrient requirement for crop growth, defined as the amount of nutrient that crops take up from soil to produce a specific grain yield, is a key parameter in determining fertilizer application rate. However, existing studies primarily focus on identifying nitrogen (N), phosphorus (P), and potassium (K) requirements solely in relation to grain yield, neglecting grain protein content, a crucial index for wheat grain quality. Addressing this gap, we conducted multi-site, multi-cultivar, and multi-year field trials across three ecological regions of China from 2016 to 2020 to elucidate variations in nutrient requirements for grain yield and grain protein. The research findings revealed that wheat grain yield ranged from 4.1 to 9.3 Mg ha-1 (average 6.9 Mg ha-1) and grain protein content ranged from 98 to 157 g kg-1 (average 127 g kg-1) across the three regions. Notably, the N requirement exhibited a nonlinear correlation with the wheat grain yield but a linear increase with increasing grain protein, while the P and K requirements positively correlated with grain yield and protein content. Regression models were formulated to determine the nutrient requirements (MENR), enabling the prediction of N, P, and K requirements for leading cultivars with varying grain yields and protein contents. Implementing nutrient requirements based on MENR projections resulted in substantial reductions in fertilizer rates: 22.0 kg ha-1 N (10.7 %), 9.9 kg ha-1 P (20.2 %), and 8.1 kg ha-1 K (16.3 %). This translated to potential savings of 0.4 Mt. N, 0.23 Mt. P, and 0.17 Mt. K, consequently mitigating 5.5 Mt. CO2 greenhouse-gas emission and yielding an economic benefit of 0.8 billion US$ annually in China. These findings underscore the significance of considering grain yield and protein content in estimating nutrient requirements for fertilizer recommendations to realize high-yielding, high-protein wheat production, and minimize overfertilization and associated environmental risks.

Semisynthesis and antitumor activity of endertiin B and related triterpenoids from Ganoderma lucidum.

Ganoderma lucidum, a fungus used in traditional Chinese medicine, is known for its medicinal value attributed to its active components called Ganoderma triterpenoids (GTs). However, the limited isolation rate of these GTs has hindered their potential as promising drug candidates. Therefore, it is imperative to achieve large-scale preparation of GTs. In this study, four GTs were effectively synthesised from lanosterol. The antitumor activity of these GTs was evaluated in vivo. Endertiin B exhibited potent inhibitory activity against breast cancer cells (9.85 ± 0.91 µM and 12.12 ± 0.95 µM). Further investigations demonstrated that endertiin B significantly upregulated p21 and p27 and downregulated cyclinD1 expression, arresting the cell cycle at the G0/G1 phase and inducing apoptosis by decreasing BCL-2 and increasing BAX and BAK levels. Additionally, endertiin B was found to reduce the expression of proteins associated with the PI3K-AKT signaling pathway. To summarize, endertiin B effectively inhibited cell proliferation by blocking the cell cycle and inducing apoptosis through the PI3K-AKT pathway.

A scoping review of hospital to home transitional care programmes for stroke survivors.

AIM: The study was aimed at exploring the current scope of hospital to home transitional care programmes for stroke survivors. BACKGROUND: Stroke survivors face the dilemma of solving many complex problems that leave survivors at high risk for readmission as they discharge from hospital. The transitional care model has proved to be effective in reducing readmissions and mortality, thereby improving health outcomes and enhancing patient satisfaction for survivors with stroke. DESIGN: A scoping review. METHODS: Conducted in accordance with the Joanna Briggs Institute (JBI) Methodology for Scoping Reviews. DATA SOURCES: A comprehensive search was conducted in nine databases, including PubMed, Web of Science, Cochrane Library, EMBASE, CINAHL, Medline, China Knowledge Net-work, Wanfang Database and China Biomedical Literature Database (SinoMed) from January 2014 to June 2023. RESULTS: Title and abstract screening was performed on 10,171 articles resulting in 287 articles for full-text screening. Full-text screening yielded 49 articles that met inclusion criteria. CONCLUSION: This study identified transitional care programmes for stroke survivors, as well as areas for future consideration to be explored in more depth to help improve transitional care for stroke survivors as they transition from hospital to home. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study demonstrates that multidisciplinary collaboration becomes an integral part of the transitional care model for stroke survivors, which provides comprehensive and precise medical care to them. REPORTING METHOD: PRISMA checklist for scoping reviews. PATIENT AND PUBLIC CONTRIBUTION: No patient or public contribution was part of this study.

[Construction of a predictive model of death for sepsis-associated acute kidney injury].

OBJECTIVE: To establish a predictive model nomogram for 30-day death in patients with sepsis-associated acute kidney injury (SA-AKI) by using the data from the large international database, the Electronic Intensive Care Unit-Collaborative Research Database (eICU-CRD), and to validate its predictive performance. METHODS: A retrospective cohort study was conducted using data from the eICU-CRD. Data of SA-AKI patients were screened from the eICU-CRD database, including demographic characteristics, medical history, SA-AKI type, Kidney Disease: Improving Global Outcomes (KDIGO)-AKI staging, severity of illness scores, vital signs, laboratory indicators, and treatment measures; with admission time as the observation start point, death as the outcome event, and a follow-up time of 30 days. Relevant variables of patients with different 30-day prognoses were compared. Univariate Logistic regression analysis and multivariate Logistic regression forward likelihood ratio analysis were used to screen for risk factors associated with 30-day death in SA-AKI patients, and a predictive model nomogram was constructed. Receiver operator characteristic curve (ROC curve), calibration curve, and Hosmer-Lemeshow test were used to validate the predictive performance of the model. RESULTS: A total of 201 SA-AKI patients' data were finally enrolled, among which 51 survived for 30 days and 150 died, with a mortality of 74.63%. Compared with the survival group, patients in the death group were older [years old: 68 (60, 78) vs. 59 (52, 69), P < 0.01], had lower body weight, proportion of transient SA-AKI, platelet count (PLT) and blood glucose [body weight (kg): 79 (65, 95) vs. 91 (71, 127), proportion of transient SA-AKI: 61.33% (92/150) vs. 82.35% (42/51), PLT (×109/L): 207 (116, 313) vs. 260 (176, 338), blood glucose (mmol/L): 5.5 (4.4, 7.1) vs. 6.4 (5.1, 7.6), all P < 0.05] and higher proportion of persistent SA-AKI, sequential organ failure assessment (SOFA) score, lactic acid (Lac), and total bilirubin [TBil; proportion of persistent SA-AKI: 38.67% (58/150) vs. 17.65% (9/51), SOFA score: 7 (5, 22) vs. 5 (2, 7), Lac (mmol/L): 0.4 (0.2, 0.7) vs. 0.3 (0.2, 0.4), TBil (µmol/L): 41.0 (17.1, 51.3) vs. 18.8 (17.1, 34.2), all P < 0.05]. Univariate Logistic regression analysis showed that age [odds ratio (OR) = 1.035, 95% confidence interval (95%CI) was 1.013-1.058, P = 0.002], body weight (OR = 0.987, 95%CI was 0.977-0.996, P = 0.007), persistent SA-AKI (OR = 2.942, 95%CI was 1.333-6.491, P = 0.008), SOFA score (OR = 1.073, 95%CI was 1.020-1.129, P = 0.006), PLT (OR = 0.998, 95%CI was 0.996-1.000, P = 0.034), Lac (OR = 1.142, 95%CI was 1.009-1.292, P = 0.035), TBil (OR = 1.422, 95%CI was 1.070-1.890, P = 0.015) were associated with 30-day death risk in SA-AKI patients. Multivariate Logistic regression forward likelihood ratio analysis showed that age (OR = 1.051, 95%CI was 1.023-1.079, P = 0.000), body weight (OR = 0.985, 95%CI was 0.974-0.995, P = 0.005), cardiovascular disease (OR = 9.055, 95%CI was 1.037-79.084, P = 0.046), persistent SA-AKI (OR = 3.020, 95%CI was 1.258-7.249, P = 0.013), SOFA score (OR = 1.076, 95%CI was 1.013-1.143, P = 0.017), and PLT (OR = 0.997, 95%CI was 0.995-1.000, P = 0.030) were independent risk factors for 30-day death in SA-AKI patients. Based on the above risk factors, a predictive model nomogram for 30-day death in SA-AKI patients was constructed. ROC curve analysis showed that the area under the ROC curve (AUC) of the model was 0.798 (95%CI was 0.722-0.873), with a sensitivity of 86.7% and a specificity of 62.7%. Calibration curve showed that the fitted curve was close to the standard line, indicating that the predicted probability was close to the actual probability, suggesting good predictive performance of the model. Hosmer-Lemeshow test showed χ 2 = 6.393, df = 8, P = 0.603 > 0.05, suggesting that the model could fit the observed data well. The quality of model fitting was judged by the accuracy of model prediction. The results showed that the prediction accuracy rate of the model was 95.3%, and the overall prediction accuracy rate of the model was 81.6%, indicating good model fitting. CONCLUSIONS: A predictive model for 30-day death in SA-AKI patients based on risk factors can be successfully constructed, and the model has high accuracy, sensitivity, reliability, and certain specificity, which can help to early identify high-risk patients for death and adopt more proactive treatment strategies.

FMNL2 regulates actin for endoplasmic reticulum and mitochondria distribution in oocyte meiosis.

During mammalian oocyte meiosis, spindle migration and asymmetric cytokinesis are unique steps for the successful polar body extrusion. The asymmetry defects of oocytes will lead to the failure of fertilization and embryo implantation. In present study, we reported that an actin nucleating factor Formin-like 2 (FMNL2) played critical roles in the regulation of spindle migration and organelle distribution in mouse and porcine oocytes. Our results showed that FMNL2 mainly localized at the oocyte cortex and periphery of spindle. Depletion of FMNL2 led to the failure of polar body extrusion and large polar bodies in oocytes. Live-cell imaging revealed that the spindle failed to migrate to the oocyte cortex, which caused polar body formation defects, and this might be due to the decreased polymerization of cytoplasmic actin by FMNL2 depletion in the oocytes of both mice and pigs. Furthermore, mass spectrometry analysis indicated that FMNL2 was associated with mitochondria and endoplasmic reticulum (ER)-related proteins, and FMNL2 depletion disrupted the function and distribution of mitochondria and ER, showing with decreased mitochondrial membrane potential and the occurrence of ER stress. Microinjecting Fmnl2-EGFP mRNA into FMNL2-depleted oocytes significantly rescued these defects. Thus, our results indicate that FMNL2 is essential for the actin assembly, which further involves into meiotic spindle migration and ER/mitochondria functions in mammalian oocytes.

Mechanisms underlying aryl hydrocarbon receptor-driven divergent macrophage function.

Macrophages play an essential role in the innate immune system by differentiating into functionally diverse subsets in order to fight infection, repair damaged tissues, and regulate inappropriate immune responses. This functional diversity stems from their ability to adapt and respond to signals in the environment, which is in part mediated through aryl hydrocarbon receptor (AHR)-signaling. AHR, an environmental sensor, can be activated by various ligands, ranging from environmental contaminants to microbially derived tryptophan metabolites. This review discusses what is currently known about how AHR-signaling influences macrophage differentiation, polarization, and function. By discussing studies that are both consistent and divergent, our goal is to highlight the need for future research on the mechanisms by which AHR acts as an immunological switch in macrophages. Ultimately, understanding the contexts in which AHR-signaling promotes and/or inhibits differentiation, proinflammatory functions, and immunoregulatory functions, will help uncover functional predictions of immunotoxicity following exposure to environmental chemicals as well as better design AHR-targeted immunotherapies.

Probability-Distribution-Configurable True Random Number Generators Based on Spin-Orbit Torque Magnetic Tunnel Junctions.

The incorporation of randomness into stochastic computing can provide ample opportunities for applications such as simulated annealing, non-polynomial hard problem solving, and Bayesian neuron networks. In these cases, a considerable number of random numbers with an accurate and configurable probability distribution function (PDF) are indispensable. Preferably, these random numbers are provided at the hardware level to improve speed, efficiency, and parallelism. In this paper, how spin-orbit torque magnetic tunnel junctions (SOT-MTJs) with high barriers are suitable candidates for the desired true random number generators is demonstrated. Not only do these SOT-MTJs perform excellently in speed and endurance, but their randomness can also be conveniently and precisely controlled by a writing voltage, which makes them a well-performed Bernoulli bit. By utilizing these SOT-MTJ-based Bernoulli bits, any PDF, including Gaussian, uniform, exponential, Chi-square, and even arbitrarily defined distributions can be realized. These PDF-configurable true random number generators can then promise to advance the development of stochastic computing and broaden the applications of the SOT-MTJs.

The Therapeutic Potential of Four Main Compounds of Zanthoxylum nitidum (Roxb.) DC: A Comprehensive Study on Biological Processes, Anti-Inflammatory Effects, and Myocardial Toxicity.

Zanthoxylum nitidum (Roxb.) DC. (Z. nitidum) is a traditional Chinese medicinal plant that is indigenous to the southern regions of China. Previous research has provided evidence of the significant anti-inflammatory, antibacterial, and anticancer properties exhibited by Z. nitidum. The potential therapeutic effects and cardiac toxicity of Z. nitidum remain uncertain. The aim of this research was to investigate the potential therapeutic properties of the four main compounds of Z. nitidum in cardiovascular diseases, their impact on the electrical activity of cardiomyocytes, and the underlying mechanism of their anti-inflammatory effects. We selected the four compounds from Z. nitidum with a high concentration and specific biological activity: nitidine chloride (NC), chelerythrine chloride (CHE), magnoflorine chloride (MAG), and hesperidin (HE). A proteomic analysis was conducted on the myocardial tissues of beagle dogs following the administration of NC to investigate the role of NC in vivo and the associated biological processes. A bioinformatic analysis was used to predict the in vivo biological processes that MAG, CHE, and HE were involved in. Molecular docking was used to simulate the binding between compounds and their targets. The effect of the compounds on ion channels in cardiomyocytes was evaluated through a patch clamp experiment. Organ-on-a-chip (OOC) technology was developed to mimic the physiological conditions of the heart in vivo. Proteomic and bioinformatic analyses demonstrated that the four compounds of Z. nitidum are extensively involved in various cardiovascular-related biological pathways. The findings from the patch clamp experiments indicate that NC, CHE, MAG, and HE elicit a distinct activation or inhibition of the IK1 and ICa-L in cardiomyocytes. Finally, the anti-inflammatory effects of the compounds on cardiomyocytes were verified using OOC technology. NC, CHE, MAG, and HE demonstrate anti-inflammatory effects through their specific interactions with prostaglandin-endoperoxide synthase 2 (PTGS2) and significantly influence ion channels in cardiomyocytes. Our study provides a foundation for utilizing NC, CHE, MAG, and HE in the treatment of cardiovascular diseases.

Work status among middle-aged and older individuals in China: the effects on physical and mental health.

Objective: China's middle-aged and older population is a rich source of human capital. Therefore, considering the health of this group is important when creating and using human resources. Methods: Using data from the nationwide China Health and Retirement Longitudinal Study (CHARLS) 2018 baseline survey of 19,000 adults ages 45 years and older, this study was an objective investigation of the effects of work on the physical and mental health of middle-aged and older adults. We conducted several types of analyses using details of participants' lifestyles and demographic characteristics (living environment, education, financial level, and access to medical services) with work (i.e., employment or volunteer work) as a primary input component of health production to examine their effects on the health status of middle-aged and older individuals. Results: Six primary outcomes were identified: (1) Employment positively affects both the physical and mental health of middle-aged and older people; (2) Employment can influence the physical and mental health of middle-aged and older people through income, cognitive level, and social support networks; (3) Compared to non-self-employment, self-employment dramatically worsens physical health but has no apparent detrimental effects on mental health. Compared to non-agricultural employment, agricultural labor affects both physical and mental health. (4) Employment has more positive physical and mental health effects in Individuals with higher rather than lower levels of education. (5) Employment opportunities in the eastern region are more likely to promote better physical health than those in the central and western regions of China, although the effects on mental health are negative. (6) When considering groups at different ages of the lifespan, the 60-65-year-old group, who are just entering retirement probably benefit more from continuing work. Conclusion: We provide some recommendations to encourage middle-aged and older people to work and utilize their experience, which will enhance their physical and mental well-being and help them in realize their own value and social integration.

Restricted Boltzmann Machines Implemented by Spin-Orbit Torque Magnetic Tunnel Junctions.

Artificial intelligence has surged forward with the advent of generative models, which rely heavily on stochastic computing architectures enhanced by true random number generators with adjustable sampling probabilities. In this study, we develop spin-orbit torque magnetic tunnel junctions (SOT-MTJs), investigating their sigmoid-style switching probability as a function of the driving voltage. This feature proves to be ideally suited for stochastic computing algorithms such as the restricted Boltzmann machines (RBM) prevalent in pretraining processes. We exploit SOT-MTJs as both stochastic samplers and network nodes for RBMs, enabling the implementation of RBM-based neural networks to achieve recognition tasks for both handwritten and spoken digits. Moreover, we further harness the weights derived from the preceding image and speech training processes to facilitate cross-modal learning from speech to image generation. Our results clearly demonstrate that these SOT-MTJs are promising candidates for the development of hardware accelerators tailored for Boltzmann neural networks and other stochastic computing architectures.

Professional values education for undergraduate nursing students: developing a framework based on the professional values growth theory.

BACKGROUND: Education has been recognised as necessary in forming and internalising professional values. The system and instructors' content in existing educational institutions focus on developing students' knowledge, skills and practices. Still, the development of values has yet to achieve significant effects, leading to a crisis in students' professional identity. AIMS: To construct a professional values growth theory for undergraduate nursing students and develop a corresponding education framework. METHODS: Through the review, some databases(PubMed、CINAHL、Web of Science、Wiley and Google Scholars)were searched using a systematic search strategy to collect relevant literature on professional values education. Based on the nursing professional values growth theory (Li and Li, Nursing Ethics In press, 2022), a theory of professional values growth of nursing undergraduates was developed using the method of theory derivation. Two rounds of expert meetings were conducted to review and revise an education framework of professional values of nursing undergraduates derived from that theory. FINDINGS: A total of 10 studies were included. The contents of two themes were analysed: theories and models and the current status of the professional values development of nursing students. The resulting professional values growth theory for undergraduate nursing students consists of five parts: key aspects, decisive opportunities, drivers, embodiment (humanistic sentiments, moral emotions), and outcomes. A total of five experts in the relevant fields were invited to this study. After two rounds of expert meetings, an education framework for undergraduate nursing students was finally developed, which consists of four parts: education objectives, education process and content, environment and conditions, and evaluation. CONCLUSION: The education framework developed in this study has practical implications for the development of professional values of undergraduate nursing students, providing educational strategies and methods for the growth and internalisation of professional values of undergraduate nursing students.

Outcomes of Heart Transplantation From Donation After Circulatory Death: An Up-to-Date Systematic Meta-analysis.

BACKGROUND: Donation after circulatory death (DCD) heart transplantation (HTx) significantly expands the donor pool and reduces waitlist mortality. However, high-level evidence-based data on its safety and effectiveness are lacking. This meta-analysis aimed to compare the outcomes between DCD and donation after brain death (DBD) HTxs. METHODS: Databases, including MEDLINE, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials, were systematically searched for randomized controlled trials and observational studies reporting the outcomes of DCD and DBD HTxs published from 2014 onward. The data were pooled using random-effects models. Risk ratios (RRs) with 95% confidence intervals (CIs) were used as the summary measures for categorical outcomes and mean differences were used for continuous outcomes. RESULTS: Twelve eligible studies were included in the meta-analysis. DCD HTx was associated with lower 1-y mortality rate (DCD 8.13% versus DBD 10.24%; RR = 0.75; 95% CI, 0.59-0.96; P = 0.02) and 5-y mortality rate (DCD 14.61% versus DBD 20.57%; RR = 0.72; 95% CI, 0.54-0.97; P = 0.03) compared with DBD HTx. CONCLUSIONS: Using the current DCD criteria, HTx emerges as a promising alternative to DBD transplantation. The safety and feasibility of DCD hearts deserve further exploration and investigation.

Self-controlled in silico gene knockdown strategies to enhance the sustainable production of heterologous terpenoid by Saccharomyces cerevisiae.

Microbial bioengineering is a growing field for producing plant natural products (PNPs) in recent decades, using heterologous metabolic pathways in host cells. Once heterologous metabolic pathways have been introduced into host cells, traditional metabolic engineering techniques are employed to enhance the productivity and yield of PNP biosynthetic routes, as well as to manage competing pathways. The advent of computational biology has marked the beginning of a novel epoch in strain design through in silico methods. These methods utilize genome-scale metabolic models (GEMs) and flux optimization algorithms to facilitate rational design across the entire cellular metabolic network. However, the implementation of in silico strategies can often result in an uneven distribution of metabolic fluxes due to the rigid knocking out of endogenous genes, which can impede cell growth and ultimately impact the accumulation of target products. In this study, we creatively utilized synthetic biology to refine in silico strain design for efficient PNPs production. OptKnock simulation was performed on the GEM of Saccharomyces cerevisiae OA07, an engineered strain for oleanolic acid (OA) bioproduction that has been reported previously. The simulation predicted that the single deletion of fol1, fol2, fol3, abz1, and abz2, or a combined knockout of hfd1, ald2 and ald3 could improve its OA production. Consequently, strains EK1∼EK7 were constructed and cultivated. EK3 (OA07△fol3), EK5 (OA07△abz1), and EK6 (OA07△abz2) had significantly higher OA titers in a batch cultivation compared to the original strain OA07. However, these increases were less pronounced in the fed-batch mode, indicating that gene deletion did not support sustainable OA production. To address this, we designed a negative feedback circuit regulated by malonyl-CoA, a growth-associated intermediate whose synthesis served as a bypass to OA synthesis, at fol3, abz1, abz2, and at acetyl-CoA carboxylase-encoding gene acc1, to dynamically and autonomously regulate the expression of these genes in OA07. The constructed strains R_3A, R_5A and R_6A had significantly higher OA titers than the initial strain and the responding gene-knockout mutants in either batch or fed-batch culture modes. Among them, strain R_3A stand out with the highest OA titer reported to date. Its OA titer doubled that of the initial strain in the flask-level fed-batch cultivation, and achieved at 1.23 ± 0.04 g L-1 in 96 h in the fermenter-level fed-batch mode. This indicated that the integration of optimization algorithm and synthetic biology approaches was efficiently rational for PNP-producing strain design.

Lysimachia capillipes Hemsl. saponins ameliorate colorectal cancer in mice via regulating gut microbiota and restoring metabolic profiles.

Lysimachia capillipes Hemsl., a traditional Chinese medicine (TCM), is commonly prescribed for its anti-inflammatory and anti-tumor properties. Pharmacological studies have demonstrated that Lysimachia capillipes Hemsl. saponins (LCS) are the primary bioactive component. However, its mechanism for treating colorectal cancer (CRC) is still unknown. Increasing evidence suggests a close relationship between CRC, intestinal flora, and host metabolism. Thus, this study aims to investigate the mechanism of LCS amelioration of CRC from the perspective of the gut microbiome and metabolome. As a result, seven gut microbiotas and fourteen plasma metabolites were significantly altered between the control and model groups. Among them, one gut microbiota genera (Monoglobus) and six metabolites (Ureidopropionic acid, Cytosine, L-Proline, 3-hydroxyanthranilic acid, Cyclic AMP and Suberic acid) showed the most pronounced callback trend after LCS administration. Subsequently, the correlation analysis revealed significant associations between 68 pairs of associated metabolites and gut microbes, with 13 pairs of strongly associated metabolites regulated by the LCS. Taken together, these findings indicate that the amelioration of CRC by LCS is connected to the regulation of intestinal flora and the recasting of metabolic abnormalities. These insights highlight the potential of LCS as a candidate drug for the treatment of CRC.