Ganoderma lucidum is a multi-purpose plant medicine that is homologous to functional food. The most attractive properties of G. lucidum are its immunomodulatory and antitumour activities, which are ...mainly attributed to the following two major active components: G. lucidum polysaccharides and G. lucidum triterpenoids (GLTs). GLTs are effective as supplemental therapies and improve health when combined with other medications to treat hepatitis, fatigue syndrome, and prostate cancer. However, research investigating the mechanism and application of G. lucidum or GLTs in the treatment of diseases remains preliminary in terms of both the utilization efficacy and product type. This review offers comprehensive insight into the pharmacological activities of GLTs and their potential applications in the development of functional foods and nutraceuticals. Specifically, 83 GLTs were selected, and their molecular structures and chemical formulas were described. We also describe 7 ganoderic acids that are currently at different stages of clinical trials (ganoderic acids A, C2, D, F, DM, X and Y). The related pharmacodynamic mechanisms and targeted signalling proteins were further analysed. Notably, the specific relationship between autophagy and apoptosis induced by ganoderic acid DM is summarized here for the first time.
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•The present review lists 83 species of Ganoderma lucidum triterpenoids (GLTs).•Seven GLTs and their SARs, pharmacological activities and mechanisms of action are described.•Specific relationship between autophagy and apoptosis induced by ganoderic acid DM is summarized for the first time.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Chemical reprogramming provides a powerful platform for exploring the molecular dynamics that lead to pluripotency. Although previous studies have uncovered an intermediate extraembryonic endoderm ...(XEN)-like state during this process, the molecular underpinnings of pluripotency acquisition remain largely undefined. Here, we profile 36,199 single-cell transcriptomes at multiple time points throughout a highly efficient chemical reprogramming system using RNA-sequencing and reconstruct their progression trajectories. Through identifying sequential molecular events, we reveal that the dynamic early embryonic-like programs are key aspects of successful reprogramming from XEN-like state to pluripotency, including the concomitant transcriptomic signatures of two-cell (2C) embryonic-like and early pluripotency programs and the epigenetic signature of notable genome-wide DNA demethylation. Moreover, via enhancing the 2C-like program by fine-tuning chemical treatment, the reprogramming process is remarkably accelerated. Collectively, our findings offer a high-resolution dissection of cell fate dynamics during chemical reprogramming and shed light on mechanistic insights into the nature of induced pluripotency.
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•Highly efficient chemical reprogramming enables single-cell transcriptomic analysis•scRNA-seq reconstructs reprogramming trajectories and major molecular events•An early embryonic-like gene network and epigenetic status drive CiPSC generation•Chemical reprogramming is accelerated by enhancing the 2C-like program
Single-cell RNA sequencing analysis of chemical reprogramming depicts its trajectory and highlights dynamic intermediate cellular programs resembling early embryonic signatures. Zhao et al. apply these insights to develop a faster reprogramming system.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Somatic cells can be reprogrammed into pluripotent stem cells (PSCs) by using pure chemicals, providing a different paradigm to study somatic reprogramming. However, the cell fate dynamics and ...molecular events that occur during the chemical reprogramming process remain unclear. We now show that the chemical reprogramming process requires the early formation of extra-embryonic endoderm (XEN)-like cells and a late transition from XEN-like cells to chemically-induced (Ci)PSCs, a unique route that fundamentally differs from the pathway of transcription factor-induced reprogramming. Moreover, precise manipulation of the cell fate transition in a step-wise manner through the XEN-like state allows us to identify small-molecule boosters and establish a robust chemical reprogramming system with a yield up to 1,000-fold greater than that of the previously reported protocol. These findings demonstrate that chemical reprogramming is a promising approach to manipulate cell fates.
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•An extraembryonic endoderm (XEN)-like state mediates the process of CiPSC generation•XEN-like cells are transcriptionally and functionally similar to in vivo counterpart•XEN cells are primed to express Oct4 and establish pluripotency•CiPSC induction is greatly enhanced by manipulating precisely with small molecules
In the process of chemical reprogramming from somatic cells to pluripotent stem cells, an intermediate extraembryonic endoderm (XEN)-like state is uncovered, allowing the development of a robust chemical reprogramming system by manipulating small molecules more precisely through this unique route.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Reliable assessment of satellite-based precipitation estimation (SPE) and production of more accurate precipitation data by data fusion is typically challenging in sparsely gauged and ungauged areas. ...Triple collocation (TC) is a novel assessment approach that does not require gauge observations; it provides a feasible solution for this problem. This study comprehensively validates the TC performance for assessing SPEs and performs data fusion of multiple SPEs using the TC-based merging (TCM) approach. The study area is the Tibetan Plateau (TP), a typical area lacking gauge observations. Three widely used SPEs are used: the integrated multi-satellite retrievals for global precipitation measurement (IMERG) “early run” product (IMERG-E), the precipitation estimation from remotely sensed information using artificial neural networks (PERSIANN) dynamic infrared (PDIR), and the Climate Prediction Center (CPC) morphing technique (CMORPH). Validation of the TC assessment approach shows that TC can effectively assess the SPEs’ accuracy, derive the spatial accuracy pattern of the SPEs, and reveal the accuracy ranking of the SPEs. TC can also detect the SPEs’ accuracy patterns, which are difficult to obtain from a traditional approach. The data fusion results of the SPEs show that TCM incorporates the regional advantages of the individual SPEs, providing more accurate precipitation data than the original SPEs, revealing that data fusion is reasonable and reliable in ungauged areas. In general, the TC approach performs well for the assessment and data fusion of SPEs, showing reasonable applicability in the TP and other areas lacking gauge data than other methods because it does not rely on gauge observations.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The acoustic tomography (AT) velocity field reconstruction technique has become a research hotspot in recent years due to its noninvasive nature, high accuracy, and real-time measurement advantages. ...However, most of the existing studies are limited to the reconstruction of the velocity field in a rectangular area, and there are very few studies on a circular area, mainly because the layout of acoustic transducers, selection of acoustic paths, and division of measured regions are more difficult in a circular area than in a rectangular area. Therefore, based on AT and using the reconstruction algorithm of the Markov function and singular value decomposition (MK-SVD), this paper proposes a measured regional division optimization algorithm for velocity field reconstruction in a circular area. First, an acoustic path distribution based on the multipath effect is designed to solve the problem of the limited emission angle of the acoustic transducer. On this basis, this paper proposes an adaptive optimization algorithm for measurement area division based on multiple sub-objectives. The steps are as follows: first, two optimization objectives, the condition number of coefficient matrix and the uniformity of acoustic path distribution, were designed. Then, the weights of each sub-objective are calculated using the coefficient of variation (CV). Finally, the measured regional division is optimized based on particle swarm optimization (PSO). The reconstruction effect of the algorithm and the anti-interference ability are verified through the reconstruction experiments of the model velocity field and the simulated velocity field.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Stress hyperglycemia is a physiological response of the body under stress to make adaptive adjustments in response to changes in the internal environment. The stress hyperglycemia ratio (SHR) is a ...new indicator after adjusting the basal blood glucose level of the population. Previous studies have shown that SHR is associated with poor prognosis in many diseases, such as cardiovascular and cerebrovascular diseases and delirium in elderly patients. However, there are currently no studies on the correlation between SHR and the general U.S.
The purpose of this study was to examine the association between SHR and adverse outcomes among adults in the United States in general.
Data on 13,315 follow-up cohorts were extracted from NHANES. The study population was divided into four groups according to quartiles of SHR. The primary outcomes were all-cause mortality and diabetes mellitus mortality. The relationship between SHR and outcomes was explored using restricted cubic splines, COX proportional hazards regression, Kaplan-Meier curves, and mediation effects. SHR is incorporated into eight machine learning algorithms to establish a prediction model and verify the prediction performance.
A total of 13,315 individual data were included in this study. Restricted cubic splines demonstrated a "U-shaped" association between SHR and all-cause mortality and diabetes mellitus mortality, indicating that increasing SHR is associated with an increased risk of adverse events. Compared with lower SHR, higher SHR was significantly associated with an increased risk of all cause mortality and diabetes mellitus mortality (HR > 1, P < 0.05). The mediating effect results showed that the positively mediated variables were segmented neutrophils and aspartate aminotransferase, and the negatively mediated variables were hemoglobin, red blood cell count, albumin, and alanine aminotransferase. The ROC of the eight machine learning algorithm models are XGBoost (0.8688), DT (0.8512), KNN (0.7966), RF (0.8417), Logistic regression (0.8633), ENET (0.8626), SVM (0.8327) and MLP (0.8662).
SHR can be used as a predictor of all cause mortality and diabetes mellitus mortality in the general adult population in the United States. Higher SHR is significantly associated with an increased risk of poor prognosis, especially in those aged < 65 years and in women.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Infective endocarditis (IE) is a disease with high in-hospital mortality. The objective of the present investigation was to develop and validate a nomogram that precisely anticipates in-hospital ...mortality in ICU individuals diagnosed with infective endocarditis.
Retrospectively collected clinical data of patients with IE admitted to the ICU in the MIMIC IV database were analyzed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify potential hazards. A logistic regression model incorporating multiple factors was established, and a dynamic nomogram was generated to facilitate predictions. To assess the classification performance of the model, an ROC curve was generated, and the AUC value was computed as an indicator of its diagnostic accuracy. The model was subjected to calibration curve analysis and the Hosmer-Lemeshow (HL) test to assess its goodness of fit. To evaluate the clinical relevance of the model, decision-curve analysis (DCA) was conducted.
The research involved a total of 676 patients, who were divided into two cohorts: a training cohort comprising 473 patients and a validation cohort comprising 203 patients. The allocation ratio between the two cohorts was 7:3. Based on the independent predictors identified through LASSO regression, the final selection for constructing the prediction model included five variables: lactate, bicarbonate, white blood cell count (WBC), platelet count, and prothrombin time (PT). The nomogram model demonstrated a robust diagnostic ability in both the cohorts used for training and validation. This is supported by the respective area under the curve (AUC) values of 0.843 and 0.891. The results of the calibration curves and HL tests exhibited acceptable conformity between observed and predicted outcomes. According to the DCA analysis, the nomogram model demonstrated a notable overall clinical advantage compared to the APSIII and SAPSII scoring systems.
The nomogram developed during the study proved to be highly accurate in forecasting the mortality of patients with IE during hospitalization in the ICU. As a result, it may be useful for clinicians in decision-making and treatment.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Over the past decades, sea ice in the polar regions has been significantly affecting local and even hemispheric climate through a positive ice albedo feedback mechanism. The role of fast ice, as ...opposed to drift ice, has not been well-studied due to its relatively small coverage over the earth. In this paper, the optical properties and surface energy balance of land fast ice in spring are studied using
in situ
observations in Barrow, Alaska. The results show that the albedo of the fast ice varied between 0.57 and 0.85 while the transmittance increased from 1.3×10
−3
to 4.1×10
−3
during the observation period. Snowfall and air temperature affected the albedo and absorbance of sea ice, but the transmittance had no obvious relationship with precipitation or snow cover. Net solar shortwave radiation contributes to the surface energy balance with a positive 99.2% of the incident flux, with sensible heat flux for the remaining 0.8%. Meanwhile, the ice surface loses energy through the net longwave radiation by 18.7% of the total emission, while the latent heat flux accounts for only 0.1%. Heat conduction is also an important factor in the overall energy budget of sea ice, contributing 81.2% of the energy loss. Results of the radiative transfer model reveal that the spectral transmittance of the fast ice is determined by the thickness of snow and sea ice as well as the amount of inclusions. As major inclusions, the ice biota and particulates have a significant influence on the magnitude and distribution of the spectral transmittance. Based on the radiative transfer model, concentrations of chlorophyll and particulate in the fast ice are estimated at 5.51 mg/m
2
and 95.79 g/m
2
, which are typical values in the spring in Barrow.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Sepsis is a severe form of systemic inflammatory response syndrome that is caused by infection. Sepsis is characterized by a marked state of stress, which manifests as nonspecific physiological and ...metabolic changes in response to the disease. Previous studies have indicated that the stress hyperglycemia ratio (SHR) can serve as a reliable predictor of adverse outcomes in various cardiovascular and cerebrovascular diseases. However, there is limited research on the relationship between the SHR and adverse outcomes in patients with infectious diseases, particularly in critically ill patients with sepsis. Therefore, this study aimed to explore the association between the SHR and adverse outcomes in critically ill patients with sepsis.
Clinical data from 2312 critically ill patients with sepsis were extracted from the MIMIC-IV (2.2) database. Based on the quartiles of the SHR, the study population was divided into four groups. The primary outcome was 28-day all-cause mortality, and the secondary outcome was in-hospital mortality. The relationship between the SHR and adverse outcomes was explored using restricted cubic splines, Cox proportional hazard regression, and Kaplan‒Meier curves. The predictive ability of the SHR was assessed using the Boruta algorithm, and a prediction model was established using machine learning algorithms.
Data from 2312 patients who were diagnosed with sepsis were analyzed. Restricted cubic splines demonstrated a "U-shaped" association between the SHR and survival rate, indicating that an increase in the SHR is related to an increased risk of adverse events. A higher SHR was significantly associated with an increased risk of 28-day mortality and in-hospital mortality in patients with sepsis (HR > 1, P < 0.05) compared to a lower SHR. Boruta feature selection showed that SHR had a higher Z score, and the model built using the rsf algorithm showed the best performance (AUC = 0.8322).
The SHR exhibited a U-shaped relationship with 28-day all-cause mortality and in-hospital mortality in critically ill patients with sepsis. A high SHR is significantly correlated with an increased risk of adverse events, thus indicating that is a potential predictor of adverse outcomes in patients with sepsis.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
► A novel airlift reactor enhanced by funnel internals at the top is developed in this study. ► A multiphase CFD model is developed for the hydrodynamics simulation in the studied reactor. ► CFD ...model can reproduce the experimental flow parameters well. ► The reactor can increase total gas holdup and reduce turbulent intensity, which make it more favorable to wastewater treatment.
Airlift reactors have been used widely in many industrial processes, but little work has been conducted on such reactors integrated with internals. In this study, a novel airlift reactor with a funnel internal was developed to achieve better flow conditions and advantages in biological processes. The CFD (computational fluid dynamics) simulation method was employed to investigate the effect of the funnel internals on hydrodynamic properties in the reactor. A CFD model was developed for gas–liquid two-phase flow simulation in a bench-scale reactor. Grid-independent simulation results were verified with global-scale experimental data. The results showed that the local or global gas holdup could be enhanced by 15% and that turbulent kinetic energy could be reduced by a maximum of 7.8% when the superficial gas velocity was 1cm/s. These features are beneficial for applications in stress-sensitive biological processes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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