Long-Term Benefits of Cenchrus fungigraminus Residual Roots Improved the Quality and Microbial Diversity of Rhizosphere Sandy Soil through Cellulose Degradation in the Ulan Buh Desert, Northwest China.

Long-term plant residue retention can effectively replenish soil quality and fertility. In this study, we collected rhizosphere soil from the residual roots of annual Cenchrus fungigraminus in the Ulan Buh Desert over the past 10 years. The area, depth, and length of these roots decreased over time. The cellulose content of the residual roots was significantly higher in the later 5 years (2018-2022) than the former 5 years (2013-2017), reaching its highest value in 2021. The lignin content of the residual roots did not differ across samples except in 2015 and reached its highest level in 2021. The total sugar of the residual roots in 2022 was 227.88 ± 30.69 mg·g-1, which was significantly higher than that in other years. Compared to the original sandy soil, the soil organic matter and soil microbial biomass carbon (SMBC) contents were 2.17-2.41 times and 31.52-35.58% higher in the later 3 years (2020-2022) and reached the highest values in 2020. The residual roots also significantly enhanced the soil carbon stocks from 2018-2022. Soil dehydrogenase, nitrogenase, and N-acetyl-ß-D-glucosidase (S-NAG) were significantly affected from 2019-2022. The rhizosphere soil community richness and diversity of the bacterial and fungal communities significantly decreased with the duration of the residual roots in the sandy soil, and there was a significant difference for 10 years. Streptomyces, Bacillus, and Sphigomonas were the representative bacteria in the residual root rhizosphere soil, while Agaricales and Panaeolus were the enriched fungal genera. The distance-based redundancy analysis and partial least square path model results showed that the duration of residual roots in the sandy soil, S-NAG, and SMBC were the primary environmental characteristics that shaped the microbial community. These insights provide new ideas on how to foster the exploration of the use of annual herbaceous plants for sandy soil improvement in the future.

Predictive factors for cerebrocardiac syndrome in patients with severe traumatic brain injury: a retrospective cohort study.

Background and objective: Cerebrocardiac syndrome (CCS) is a severe complication of severe traumatic brain injury (sTBI) that carries high mortality and disability rates. Early identification of CCS poses a significant clinical challenge. The main objective of this study was to investigate potential risk factors associated with the development of secondary CCS in patients with sTBI. It was hypothesized that elevated right heart Tei index (TI), lower Glasgow Coma Scale (GCS) scores, and elevated cardiac troponin-I (cTnI) levels would independently contribute to the occurrence of CCS in sTBI patients. Methods: A retrospective cohort study was conducted to identify risk factors for CCS secondary to sTBI. One hundred and fifty-five patients were enrolled with sTBI admitted to the hospital between January 2016 and December 2020 and divided them into a CCS group (n = 75) and a non-CCS group (n = 80) based on the presence of CCS. This study involved the analysis and comparison of clinical data from two patient groups, encompassing demographic characteristics, peripheral oxygen saturation (SPO2), neuron-specific enolase (NSE), cardiac troponin-I (cTnI), N-terminal pro-brain natriuretic peptide (NT-proBNP), optic nerve sheath diameter (ONSD), cardiac ultrasound, acute physiology and chronic health evaluation (APACHE II) scores, and GCS scores and so on. Multivariate logistic regression was employed to identify independent risk factors for CCS, and receiver operating characteristic (ROC) curves were used to assess their predictive value for CCS secondary to sTBI. Results: The study revealed that 48.4% of sTBI patients developed secondary CCS. In the multivariate analysis model 1 that does not include NT-proBNP and cTnI, ONSD (OR = 2.582, 95% CI: 1.054-6.327, P = 0.038), right heart Tei index (OR = 2.81, 95% CI: 1.288-6.129, P = 0.009), and GCS (OR = 0.212, 95% CI: 0.086-0.521, P = 0.001) were independent risk factors for secondary CCS in sTBI patients. In multivariate analysis model 2 that includes NT-proBNP and cTnI, cTnI (OR = 27.711, 95%CI: 3.086-248.795, P = 0.003), right heart Tei index (OR = 2.736, 95% CI: 1.056-7.091, P = 0.038), and GCS (OR = 0.147, 95% CI: 0.045-0.481, P = 0.002) were independent risk factors for secondary CCS in sTBI patients. The area under the ROC curve for ONSD, Tei index, GCS, and cTnI were 0.596, 0.613, 0.635, and 0.881, respectively. ONSD exhibited a positive predictive value (PPV) of 0.704 and a negative predictive value (NPV) of 0.634. The Tei index demonstrated a PPV of 0.624 and an NPV of 0.726, while GCS had a PPV of 0.644 and an NPV of 0.815. On the other hand, cTnI exhibited a significantly higher PPV of 0.936 and an NPV of 0.817. These findings indicate that the Tei index, GCS score, and cTnI possess certain predictive value for secondary CCS in patients with sTBI. Conclusions: The study provides valuable insights into the identification of independent risk factors for CCS secondary to sTBI. The findings highlight the significance of right heart Tei index, GCS score, and cTnI as potential predictive factors for CCS in sTBI patients. Further larger-scale studies are warranted to corroborate these findings and to provide robust evidence for the development of early intervention strategies aimed at reducing the incidence of CCS in this patient population.

Evaluate prognostic accuracy of SOFA component score for mortality among adults with sepsis by machine learning method.

INTRODUCTION: Sepsis has the characteristics of high incidence, high mortality of ICU patients. Early assessment of disease severity and risk stratification of death in patients with sepsis, and further targeted intervention are very important. The purpose of this study was to develop machine learning models based on sequential organ failure assessment (SOFA) components to early predict in-hospital mortality in ICU patients with sepsis and evaluate model performance. METHODS: Patients admitted to ICU with sepsis diagnosis were extracted from MIMIC-IV database for retrospective analysis, and were randomly divided into training set and test set in accordance with 2:1. Six variables were included in this study, all of which were from the scores of 6 organ systems in SOFA score. The machine learning model was trained in the training set and evaluated in the validation set. Six machine learning methods including linear regression analysis, least absolute shrinkage and selection operator (LASSO), Logistic regression analysis (LR), Gaussian Naive Bayes (GNB) and support vector machines (SVM) were used to construct the death risk prediction models, and the accuracy, area under the receiver operating characteristic curve (AUROC), Decision Curve Analysis (DCA) and K-fold cross-validation were used to evaluate the prediction performance of developed models. RESULT: A total of 23,889 patients with sepsis were enrolled, of whom 3659 died in hospital. Three feature variables including renal system score, central nervous system score and cardio vascular system score were used to establish prediction models. The accuracy of the LR, GNB, SVM were 0.851, 0.844 and 0.862, respectively, which were better than linear regression analysis (0.123) and LASSO (0.130). The AUROCs of LR, GNB and SVM were 0.76, 0.76 and 0.67, respectively. K-fold cross validation showed that the average AUROCs of LR, GNB and SVM were 0.757 ± 0.005, 0.762 ± 0.006, 0.630 ± 0.013, respectively. For the probability threshold of 5-50%, LY and GNB models both showed positive net benefits. CONCLUSION: The two machine learning-based models (LR and GNB models) based on SOFA components can be used to predict in-hospital mortality of septic patients admitted to ICU.

An application based on bioinformatics and machine learning for risk prediction of sepsis at first clinical presentation using transcriptomic data.

Background: Linking genotypic changes to phenotypic traits based on machine learning methods has various challenges. In this study, we developed a workflow based on bioinformatics and machine learning methods using transcriptomic data for sepsis obtained at the first clinical presentation for predicting the risk of sepsis. By combining bioinformatics with machine learning methods, we have attempted to overcome current challenges in predicting disease risk using transcriptomic data. Methods: High-throughput sequencing transcriptomic data processing and gene annotation were performed using R software. Machine learning models were constructed, and model performance was evaluated by machine learning methods in Python. The models were visualized and interpreted using the Shapley Additive explanation (SHAP) method. Results: Based on the preset parameters and using recursive feature elimination implemented via machine learning, the top 10 optimal genes were screened for the establishment of the machine learning models. In a comparison of model performance, CatBoost was selected as the optimal model. We explored the significance of each gene in the model and the interaction between each gene through SHAP analysis. Conclusion: The combination of CatBoost and SHAP may serve as the best-performing machine learning model for predicting transcriptomic and sepsis risks. The workflow outlined may provide a new approach and direction in exploring the mechanisms associated with genes and sepsis risk.

Angiotensin-Converting Enzyme 2 Inhibits Lipopolysaccharide-Caused Lung Fibrosis via Downregulating the Transforming Growth Factor ß-1/Smad2/Smad3 Pathway.

BACKGROUND: In our previous studies, angiotensin-converting enzyme 2 (ACE2) was shown to alleviate the severity of acute lung injury, but its effects on the development of lung injury-caused lung fibrosis have not been studied. METHODS: In the present study, the effects of ACE2 on lipopolysaccharide (LPS)-induced fibrosis in the lung were studied. The role of epithelial-mesenchymal transition (EMT) and that of the transforming growth factor ß-1 (TGF-ß1)/Smad2/Smad3 pathway in LPS-induced fibrosis in the lung were investigated. RESULTS: ACE2 expression in the mouse model of LPS-induced lung fibrosis was significantly increased. ACE2 activator diminazene aceturate (DIZE) significantly reduced pulmonary fibrosis, decreased alpha-smooth muscle actin expression, collagen I, hydroxyproline, and TGF-ß1 in the lung. DIZE significantly decreased TGF-ß1 expression and the activation of Smad2 and Smad3. ACE2 overexpression inhibited the LPS-induced EMT in MLE-12 cells (lung epithelial cells) and small interfering RNA treatment of ACE2 stimulated EMT. ACE2 overexpression also inhibited TGF-ß1 expression and activation of Smad2 and Smad3 in MLE-12 cells. Finally, after MLE-12 cells were treated with both ACE2 and TGF-ß1 plasmid, TGF-ß1 plasmid significantly abolished the effect of ACE2 plasmid on the EMT in MLE-12 cells. CONCLUSION: Combined with the in vivo study, it was revealed that ACE2 can suppress the TGF-ß1/Smad2/Smad3 pathway in lung type II epithelial cells, thus reversing their EMT and lung fibrosis. The present study provides basic research data for the application of ACE2 in lung injury-caused lung fibrosis treatment and clarifies the intervention mechanism of ACE2 in pulmonary fibrosis, which has potential value for clinical application. SIGNIFICANCE STATEMENT: Angiotensin-converting enzyme 2 (ACE2) can inhibit the epithelial-mesenchymal transition (EMT) in lung type II epithelial cells and lung fibrosis. ACE2 can regulate the transforming growth factor ß-1/Smad2/Smad3 pathway in lung type II epithelial cells, which may be the underlying mechanism of ACE2's effect on EMT and lung fibrosis.

Gestational chronic intermittent hypoxia induces hypertension, proteinuria, and fetal growth restriction in mice.

PURPOSE: Pregnant women are predisposed to obstructive sleep apnea (OSA). Based on the fact that OSA is an independent risk factor for hypertension among the general population, we hypothesized that chronic intermittent hypoxia (CIH), as a feature of OSA, may lead to preeclampsia. METHODS: Pregnant and non-pregnant C57BL/6 J mice were exposed to two conditions of chronic intermittent hypoxia: CIH1 (21-5% O2 alternations), CIH2 (21-10% O2 alternations), and room air until day 19. RESULTS: In non-pregnant mice, compared with their respective baseline values, systolic blood pressure (SBP) started to rise from day 14 in the CIH1 group, and SBP rose until day 19 in the CIH2 group. Compared with the pregnant mice exposed to room air, pregnant mice exposed to CIH1 maintained elevated SBP from day 14, accompanied by proteinuria, fetal and placental growth restriction, and a reduction in the number of fetuses. An imbalance between proangiogenic and antiangiogenic factors and impairment of vascular remodeling existed in the placenta of pregnant mice exposed to CIH1. Maternal serum levels of the soluble form of vascular endothelial growth factor receptor-1 were also significantly increased. Pregnant mice exposed to CIH2 seemed to have milder changes than pregnant mice exposed to CIH1. CONCLUSION: Our results demonstrated that gestational CIH may induce gestational hypertension, proteinuria, fetal and placental growth restriction as well as impairments in placental angiogenesis and vascular remodeling.

Low-dose urokinase thrombolytic therapy for patients with acute intermediate-high-risk pulmonary embolism: A retrospective cohort study.

INTRODUCTION: Patients at intermediate-high risk of developing a pulmonary embolism (PE) are very likely to experience adverse outcomes, such as cardiovascular instability and death. The role of thrombolytic therapy in intermediate-high-risk PE remains controversial. OBJECTIVES: This study aimed to determine the efficacy and safety of low-dose urokinase (UK) thrombolytic therapy for intermediate-high-risk PE. PATIENTS AND METHODS: This retrospective study included 81 consecutive patients with intermediate-high-risk PE from two centers. Patients received low-dose UK or low-molecular-weight heparin (anticoagulant therapy group). The efficacy outcomes were mortality, computed tomography pulmonary angiography (CTPA)-confirmed absorption, and dyspnea. Safety was assessed as the incidence of bleedings. RESULTS: The in-hospital mortality, 9-month mortality, and long-term mortality at the last follow-up were comparable for the low-dose UK group and the anticoagulant therapy group (6.45% vs. 0%, p = 0.144, 9.68% vs. 8.16%, p = 0.815, and 12.90% vs. 12.24%, p = 0.931, respectively). CTPA-confirmed absorption at one month after admission was higher in the low-dose UK group than in the anticoagulant therapy group (p = 0.016). The incidences of short-term dyspnea at discharge and long-term dyspnea at the last follow-up were lower in the low-dose UK group than in the anticoagulant therapy group (27.59% vs. 52%, p = 0.035, 33.33% vs. 58.14%, p = 0.043, respectively). No major bleeding occurred. The incidence of minor bleeding was not significantly different between the two groups (3.23% vs. 6%, p = 0.974). CONCLUSION: In intermediate-high-risk PE, a low-dose UK might increase CTPA-confirmed absorption and improve short-term and long-term dyspnea without affecting mortality or increasing the bleeding risk.

The predictive value of procalcitonin for early detection of infection in elderly type 2 diabetes mellitus.

OBJECTIVE: Aimed to investigate the predictive value of procalcitonin (PCT) in early detection of infections in elderly patients with type 2 diabetes, and to discover the optimum cut-off points of PCT. METHODS: A retrospective study was conducted with type 2 diabetic patients (≥65 years) with lung infection (LI), urinary tract infection (UTI) or skin and soft tissue infection (SSTI). The receiver operating characteristic (ROC) curves of the 3 markers (PCT, WBC count, and CRP) were constructed and compared to assess their accuracies in diagnosing. RESULTS: Among the three different groups with LI, UTI or SSTI, the area under the ROC curve (AUC) of PCT was 0.98 (95% confidence interval (CI): 0.96-0.99, p < 0.05) for the LI group, 0.98 (95% CI: 0.96-0.99, p < 0.05) for the UTI group, and 0.97 (95% CI: 0.94-1.00, p < 0.05) for the SSTI group. The optimum cut-off point of PCT level was 0.73 ng/mL (Sn 89.7%, Sp 97.7%) for the LI group, 1.48 ng/mL (Sn 88.9%, Sp 100%) for the UTI group, and 0.73 ng/mL (Sn 85.7%, Sp 97.7%) for the SSTI group. CONCLUSION: PCT demonstrated the strongest correlation with each of the infection types, indicating significant diagnostic value. Optimum cut-off points of PCT levels in elderly diabetes were higher.

Significance of Early Postoperative Arterial Lactic Acid, Inferior Vena Cava Variability, and Central Venous Pressure in Hypovolemic Shock.

INTRODUCTION: Up to one-third of patients admitted to the ICU are in circulatory shock, and early recognition of the condition is vital if subsequent tissue injuries are to be avoided. We would like to know what role the arterial lactic acid, inferior vena cava variability, and CVP (central venous pressure) play in the early stages of shock. METHODS: This is a retrospective study of patients who underwent surgical resuscitation in the Department of Critical Care Medicine. We use the ROC (receiver-operating characteristic) curve to evaluate the significance of each indicator in the diagnosis. For correlation analysis between groups, we first use linear regression for processing and then analysis with correlation. RESULTS: The ROC curve analysis shows that the area under the curve of the lactic acid group was 0.9272, the area under the curve of the inferior vena cava variability group was 0.8652, and the area under the curve of the CVP group was 0.633. Correlation analysis shows that the inferior vena cava variability and arterial lactic acid Pearson's r = 0.2863 and CVP and arterial lactic acid Pearson's r = 0.0729. CONCLUSION: The diagnostic value of arterial lactate is still very high and can still be used as an early warning indicator to help clinicians be alert to the microcirculatory disorders that have emerged quietly. The degree of inferior vena cava variability is linearly related to arterial lactic acid and can also be used as a reference indicator for early evaluation of shock. The diagnostic value of CVP is obviously lower.

Sepsis leads to thyroid impairment and dysfunction in rat model.

Sepsis was a systemic response to a local infection. Apoptosis was observed in the experimental sepsis. In this study, cecal ligation and puncture (CLP)-induced sepsis was established in rats. We found that sepsis decreased thyroid hormone levels, including triiodothyronine (T3), thyroxine (T4), free T3 (fT3), and free T4 (fT4). Besides, we detected the increasing expression level of Caspase-3 and increasing ratio of TUNEL positive cells in the thyroid after sepsis. Furthermore, a series of pathological ultrastructural changes were observed in thyroid follicular epithelial cells by CLP-induced sepsis. This study established a sepsis animal model and provided the cellular and molecular basis for decoding the pathological mechanism in thyroid with the occurrence of sepsis.

[Effects of different years of planting Pennisetum sp. on the plant- and insect diversity in Pennisetum sp. communities].

This paper studied the effects of 1-, 2- and 3 years of planting Pennisetum sp. on the plant- and insect diversity in the Pennisetum sp. communities, taking the barren mountain land without planting Pennisetum sp. as the control (CK). Compared with CK, the plant species richness in Pennisetum sp. communities with different years of planting was lower, but the coverage was higher. The coverage in the Pennisetum sp. community having been planted for 3 years was the highest, up to 91.6%, and 75.8% higher than the CK. The insect species richness in the Pennisetum sp. communities having been planted for 1, 2 and 3 years was 3.6, 5.3 and 5.6 times of the CK, respectively. The plant- and insect diversity indices, including Simpson index, Shannon index, evenness, Brillouin index, and McIntosh index for the Pennisetum sp. communities with different years of planting were significantly higher than the CK, which indicated that the growth of Pennisetum sp. could affect the plant- and insect diversity. With the increasing year of planting, the plant- and insect diversity in Pennisetum sp. communities tended to be stable.