Association Between Artificial Intelligence Based Chest Computed Tomography and Clinical/Laboratory Characteristics with Severity and Mortality in COVID-19 Hospitalized Patients.

Background: Some patients with COVID-19 rapidly develop respiratory failure or mortality, underscoring the necessity for early identification of those prone to severe illness. Numerous studies focus on clinical and lab traits, but only few attend to chest computed tomography. The current study seeks to numerically quantify pulmonary lesions using early-phase CT scans calculated through artificial intelligence algorithms in conjunction with clinical and laboratory helps clinicians to early identify the development of severe illness and death in a group of COVID-19 patients. Methods: From December 15, 2022, to January 30, 2023, 191 confirmed COVID-19 patients admitted to Xinhua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine were consecutively enrolled. All patients underwent chest CT scans and serum tests within 48 hours prior to admission. Variables significantly linked to critical illness or mortality in univariate analysis were subjected to multivariate logistic regression models post collinearity assessment. Adjusted odds ratio, 95% confidence intervals, sensitivity, specificity, Youden index, receiver-operator-characteristics (ROC) curves, and area under the curve (AUC) were computed for predicting severity and in-hospital mortality. Results: Multivariate logistic analysis revealed that myoglobin (OR = 1.003, 95% CI 1.001-1.005), APACHE II score (OR = 1.387, 95% CI 1.216-1.583), and the infected CT region percentage (OR = 113.897, 95% CI 4.939-2626.496) independently correlated with in-hospital COVID-19 mortality. Prealbumin stood as an independent safeguarding factor (OR = 0.965, 95% CI 0.947-0.984). Neutrophil counts (OR = 1.529, 95% CI 1.131-2.068), urea nitrogen (OR = 1.587, 95% CI 1.222-2.062), SOFA score(OR = 3.333, 95% CI 1.476-7.522), qSOFA score(OR = 15.197, 95% CI 3.281-70.384), PSI score(OR = 1.053, 95% CI 1.018-1.090), and the infected CT region percentage (OR = 548.221, 95% CI 2.615-114,953.586) independently linked to COVID-19 patient severity.

Piezo1 Knockout Improves Post-Stroke Cognitive Dysfunction by Inhibiting the Interleukin-6 (IL-6)/Glutathione Peroxidase 4 (GPX4) Pathway.

Background: Cerebral infarction often results in post-stroke cognitive impairment, which impairs the quality of life and causes long-term disability. Astrocytes, the most abundant glial cells in the central nervous system, have a crucial role in cerebral ischemia and neuroinflammation. We explored the possible advantages of interleukin-6 (IL-6), a powerful pro-inflammatory cytokine produced by astrocytes, for post-stroke cognitive function. Methods: Mendelian randomization was applied to analyze the GWAS database of stroke patients, obtaining a causal relationship between IL-6 and stroke. Further validation of this relationship and its mechanisms was conducted. Using a mouse model of cerebral infarction, we demonstrated a significant increase in IL-6 expression in astrocytes surrounding the ischemic lesion. This protective effect of Piezo1 knockout was attributed to the downregulation of matrix metalloproteinases and upregulation of tight junction proteins, such as occludin and zonula occludens-1 (ZO-1). Results: Two-step Mendelian randomization revealed that IL-6 exposure is a risk factor for stroke. Moreover, we conducted behavioral assessments and observed that Piezo1 knockout mice that received intranasal administration of astrocyte-derived IL-6 showed notable improvement in cognitive function compared to control mice. This enhancement was associated with reduced neuronal cell death and suppressed astrocyte activation, preserving ZO-1. Conclusion: Our study shows that astrocyte-derived IL-6 causes cognitive decline after stroke by protecting the blood-brain barrier. This suggests that piezo1 knockout may reduce cognitive impairment after brain ischemia. Further research on the mechanisms and IL-6 delivery methods may lead to new therapies for post-stroke cognition.

Hyperbaric oxygen therapy promotes the browning of white fat and contributes to the healing of diabetic wounds.

Non-healing wounds are one of the chronic complications of diabetes and have remained a worldwide challenge as one of the major health problems. Hyperbaric oxygen (HBO) therapy is proven to be very successful for diabetic wound treatment, for which the molecular basis is not understood. Adipocytes regulate multiple aspects of repair and may be therapeutic for inflammatory diseases and defective wound healing associated with aging and diabetes. Endothelial cell-derived extracellular vesicles could promote wound healing in diabetes. To study the mechanism by which HBO promotes wound healing in diabetes, we investigated the effect of HBO on fat cells in diabetic mice. A diabetic wound mouse model was established and treated with HBO. Haematoxylin and eosin (H&E) staining and immunofluorescence were used for the analysis of wound healing. To further explore the mechanism, we performed whole-genome sequencing on extracellular vesicles (EVs). Furthermore, we conducted in vitro experiments. Specifically, exosomes were collected from human umbilical vein endothelial cell (HUVEC) cells after HBO treatment, and then these exosomes were co-incubated with adipose tissue. The wound healing rate in diabetic mice treated with HBO was significantly higher. HBO therapy promotes the proliferation of adipose precursor cells. HUVEC-derived exosomes treated with HBO significantly promoted fat cell browning. These data clarify that HBO therapy may promote vascular endothelial cell proliferation and migration, and promote browning of fat cells through vascular endothelial cells derived exosomes, thereby promoting diabetic wound healing. This provides new ideas for the application of HBO therapy in the treatment of diabetic trauma.

Development of Biomarkers and Prognosis Model of Mortality Risk in Patients with COVID-19.

Background: As of 30 April 2023, the COVID-19 pandemic has resulted in over 6.9 million deaths worldwide. The virus continues to spread and mutate, leading to continuously evolving pathological and physiological processes. It is imperative to reevaluate predictive factors for identifying the risk of early disease progression. Methods: A retrospective study was conducted on a cohort of 1379 COVID-19 patients who were discharged from Xin Hua Hospital affiliated with Shanghai Jiao Tong University School of Medicine between 15 December 2022 and 15 February 2023. Patient symptoms, comorbidities, demographics, vital signs, and laboratory test results were systematically documented. The dataset was split into testing and training sets, and 15 different machine learning algorithms were employed to construct prediction models. These models were assessed for accuracy and area under the receiver operating characteristic curve (AUROC), and the best-performing model was selected for further analysis. Results: AUROC for models generated by 15 machine learning algorithms all exceeded 90%, and the accuracy of 10 of them also surpassed 90%. Light Gradient Boosting model emerged as the optimal choice, with accuracy of 0.928 ± 0.0006 and an AUROC of 0.976 ± 0.0028. Notably, the factors with the greatest impact on in-hospital mortality were growth stimulation expressed gene 2 (ST2,19.3%), interleukin-8 (IL-8,17.2%), interleukin-6 (IL-6,6.4%), age (6.1%), NT-proBNP (5.1%), interleukin-2 receptor (IL-2R, 5%), troponin I (TNI,4.6%), congestive heart failure (3.3%) in Light Gradient Boosting model. Conclusion: ST-2, IL-8, IL-6, NT-proBNP, IL-2R, TNI, age and congestive heart failure were significant predictors of in-hospital mortality among COVID-19 patients.

Intestinal Piezo1 aggravates intestinal barrier dysfunction during sepsis by mediating Ca2+ influx.

INTRODUCTION: Intestinal barrier dysfunction is a pivotal factor in sepsis progression. The mechanosensitive ion channel Piezo1 is associated with barrier function; however, its role in sepsis-induced intestinal barrier dysfunction remains poorly understood. METHODS: The application of cecal ligation and puncture (CLP) modeling was performed on both mice of the wild-type (WT) variety and those with Villin-Piezo1flox/flox genetic makeup to assess the barrier function using in vivo FITC-dextran permeability measurements and immunofluorescence microscopy analysis of tight junctions (TJs) and apoptosis levels. In vitro, Caco-2 monolayers were subjected to TNF-α incubation. Moreover, to modulate Piezo1 activation, GsMTx4 was applied to inhibit Piezo1 activation. The barrier function, intracellular calcium levels, and mitochondrial function were monitored using calcium imaging and immunofluorescence techniques. RESULTS: In the intestinal tissues of CLP-induced septic mice, Piezo1 protein levels were notably elevated compared with those in normal mice. Piezo1 has been implicated in the sepsis-mediated disruption of TJs, apoptosis of intestinal epithelial cells, elevated intestinal mucosal permeability, and systemic inflammation in WT mice, whereas these effects were absent in Villin-Piezo1flox/flox CLP mice. In Caco-2 cells, TNF-α prompted calcium influx, an effect reversed by GsMTx4 treatment. Elevated calcium concentrations are correlated with increased accumulation of reactive oxygen species, diminished mitochondrial membrane potential, and TJ disruption. CONCLUSIONS: Thus, Piezo1 is a potential contributor to sepsis-induced intestinal barrier dysfunction, influencing apoptosis and TJ modification through calcium influx-mediated mitochondrial dysfunction.

Association Between Nonthyroidal Illness Syndrome and Disseminated Intravascular Coagulation in Sepsis.

Purpose: Both nonthyroidal illness syndrome (NTIS) and disseminated intravascular coagulation (DIC) are commonly occurred in sepsis. The objective of this study is to evaluate the association between NTIS and DIC, as well as their impacts on the mortality in adults with sepsis. Patients and methods: A total of 1219 septic patients in two Chinese academic centers from October 2012 and October 2022 were enrolled in analysis. We conduct logistic regression models to analyze the independent risk factors for DIC. Modified Poisson regression models are used to estimate the relative risk (RR) of NTIS on the 28 days mortality in septic patients with DIC. Correlation analysis between thyroid function parameters and coagulation parameters is performed with Pearson coefficient be reported. Results: DIC is diagnosed on 388 (31.8%) of all the 1219 enrolled septic patients within 72 hours after admission. In multivariate logistic regression models, NTIS (OR 3.19; CI 2.31-4.46; p<0.001) is a statistically significant independent risk factor for DIC after adjustment for potential confounders. Twenty-eight days mortality is significantly higher in DIC patients complicated with NTIS compared with the other DIC patients (23.2% vs 14.0%, p=0.024). This result is also robust in different modified Poisson regression models (Model 1: RR 1.46; CI 1.25-1.70; p<0.001; Model 2: RR 1.35; CI 1.14-1.60; p<0.001; Model 3: RR 1.18; CI 1.02-1.37; p=0.026). Correlation analysis reveals that the thyroid function parameters of FT3, FT4 and TSH only have weak correlations with coagulation parameters of platelet count, fibrinogen, FDP, D-dimers, PT, APTT and INR in sepsis. Conclusion: NTIS is an independent risk factor for DIC in adults with sepsis. DIC patients complicated with NTIS have significantly higher severity and higher rate of mortality.

Blood Urea Nitrogen-to-Albumin Ratio May Predict Mortality in Patients with Traumatic Brain Injury from the MIMIC Database: A Retrospective Study.

Traumatic brain injury (TBI), a major global health burden, disrupts the neurological system due to accidents and other incidents. While the Glasgow coma scale (GCS) gauges neurological function, it falls short as the sole predictor of overall mortality in TBI patients. This highlights the need for comprehensive outcome prediction, considering not just neurological but also systemic factors. Existing approaches relying on newly developed biomolecules face challenges in clinical implementation. Therefore, we investigated the potential of readily available clinical indicators, like the blood urea nitrogen-to-albumin ratio (BAR), for improved mortality prediction in TBI. In this study, we investigated the significance of the BAR in predicting all-cause mortality in TBI patients. In terms of research methodologies, we gave preference to machine learning methods due to their exceptional performance in clinical support in recent years. Initially, we obtained data on TBI patients from the Medical Information Mart for Intensive Care database. A total of 2602 patients were included, of whom 2260 survived and 342 died in hospital. Subsequently, we performed data cleaning and utilized machine learning techniques to develop prediction models. We employed a ten-fold cross-validation method to obtain models with enhanced accuracy and area under the curve (AUC) (Light Gradient Boost Classifier accuracy, 0.905 ± 0.016, and AUC, 0.888; Extreme Gradient Boost Classifier accuracy, 0.903 ± 0.016, and AUC, 0.895; Gradient Boost Classifier accuracy, 0.898 ± 0.021, and AUC, 0.872). Simultaneously, we derived the importance ranking of the variable BAR among the included variables (in Light Gradient Boost Classifier, the BAR ranked fourth; in Extreme Gradient Boost Classifier, the BAR ranked sixth; in Gradient Boost Classifier, the BAR ranked fifth). To further evaluate the clinical utility of BAR, we divided patients into three groups based on their BAR values: Group 1 (BAR < 4.9 mg/g), Group 2 (BAR ≥ 4.9 and ≤10.5 mg/g), and Group 3 (BAR ≥ 10.5 mg/g). This stratification revealed significant differences in mortality across all time points: in-hospital mortality (7.61% vs. 15.16% vs. 31.63%), as well as one-month (8.51% vs. 17.46% vs. 36.39%), three-month (9.55% vs. 20.14% vs. 41.84%), and one-year mortality (11.57% vs. 23.76% vs. 46.60%). Building on this observation, we employed the Cox proportional hazards regression model to assess the impact of BAR segmentation on survival. Compared to Group 1, Groups 2 and 3 had significantly higher hazard ratios (95% confidence interval (CI)) for one-month mortality: 1.77 (1.37-2.30) and 3.17 (2.17-4.62), respectively. To further underscore the clinical potential of BAR as a standalone measure, we compared its performance to established clinical scores, like sequential organ failure assessment (SOFA), GCS, and acute physiology score III(APS-III), using receiver operator characteristic curve (ROC) analysis. Notably, the AUC values (95%CI) of the BAR were 0.67 (0.64-0.70), 0.68 (0.65-0.70), and 0.68 (0.65-0.70) for one-month mortality, three-month mortality, and one-year mortality. The AUC value of the SOFA did not significantly differ from that of the BAR. In conclusion, the BAR is a highly influential factor in predicting mortality in TBI patients and should be given careful consideration in future TBI prediction research. The blood urea nitrogen-to-albumin ratio may predict mortality in TBI patients.

Different subtypes of nonthyroidal illness syndrome on the prognosis of septic patients: a two-centered retrospective cohort study.

Background: Nonthyroidal illness syndrome (NTIS) is a common endocrine dysfunction predicting unfavorable outcomes in critical illness. The objective of the study is to evaluate the association between different NTIS subtypes with outcomes in septic patients. Methods: Septic patients in two Chinese academic centers from October 2012 and October 2022 are enrolled in analysis. Multivariable regressions are used to assess associations between NTIS and outcomes. Outcomes include in-hospital mortality, length of stay in hospital (LOS), non-invasive ventilation failure and weaning failure. Patients with NTIS are categorized into 4 types according to the different levels of FT4 and TSH. The association between different NTIS subtypes and mortality are further analyzed. Survival curve is plotted using the Kaplan-Meier method. Results: After screening, a total of 1226 septic patients with complete thyroid hormones result are eventually enrolled. Among them, 520 (42.4%) patients are diagnosed as NTIS. In multivariable regression analysis, NTIS is independently associated with increased 30-days mortality (OR=1.759, CI 1.009-3.104, p=0.047), but has no association with 60-days mortality (OR=1.524, CI 0.893-2.618, p=0.123), 90-days mortality (OR=1.411, CI 0.831-2.408, p=0.203), LOS, non-invasive ventilation failure or weaning failure. In NTIS subtypes, NTIS patients with low FT3 and TSH levels, regardless of the FT4 values, have significantly higher mortality than euthyroid patients (30-days mortality, OR= 6.488, CI 1.546-27.808, p=0.01; 60-days mortality, OR=3.973, CI 1.006-15.579, p=0.046; 90-days mortality, OR=3.849, CI 0.977-15.088, p=0.051). This result is consistent in patients with low FT3 and FT4 levels, regardless of the TSH values (30-days mortality, OR=3.349, CI 1.402-7.957, p=0.006; 60-days mortality, OR= 2.594, CI 1.122-5.930, p=0.024; 90-days mortality, OR=2.55, CI 1.110-5.804, p=0.025). There is no survival difference between NTIS patients with low FT3 only and euthyroid patients. Survival plot shows the worst prognosis is in NTIS patients with low FT3, FT4 and TSH level. Conclusions: NTIS is frequent in sepsis. A reduction of FT3 together with FT4 or TSH, but not FT3 only, is associated with an increased risk of mortality.

PAI-1 genetic polymorphisms influence septic patients' outcomes by regulating neutrophil activity.

BACKGROUND: Plasminogen activator inhibitor-1 (PAI-1) plays an important role in the pathophysiology of sepsis, but the exact mechanism remains debatable. In this study, we investigated the associations among the serum levels of PAI-1, the incidence of 4G/5G promoter PAI-1 gene polymorphisms, immunological indicators, and clinical outcomes in septic patients. METHODS: A total of 181 patients aged 18-80 years with sepsis between November 2016 and August 2018 in the intensive care unit in the Xinhua Hospital were recruited in this retrospective study, with 28-day mortality as the primary outcome. The initial serum level of PAI-1 and the presence of rs1799768 single nucleotide polymorphisms (SNPs) were examined. Univariate logistic regression and multivariate analyses were performed to determine the factors associated with different genotypes of PAI-1, serum level of PAI-1, and 28-day mortality. RESULTS: The logistic analysis suggested that a high serum level of PAI-1 was associated with the rs1799768 SNP of PAI-1 (4G/4G and 4G/5G) (Odds ratio [OR]: 2.49; 95% confidence interval [CI]: 1.09, 5.68). Furthermore, a high serum level of PAI-1 strongly influenced 28-day mortality (OR 3.36; 95% CI 1.51, 7.49). The expression and activation of neutrophils (OR 0.96; 95% CI 0.93, 0.99), as well as the changes in the expression patterns of cytokines and chemokine-associated neutrophils (OR: 1.00; 95% CI: 1.00, 1.00), were both regulated by the genotype of PAI-1. CONCLUSIONS: Genetic polymorphisms of PAI-1 can influence the serum levels of PAI-1, which might contribute to mortality by affecting neutrophil activity. Thus, patients with severe sepsis might clinically benefit from enhanced neutrophil clearance and the resolution of inflammation via the regulation of PAI-1 expression and activity.

Multidimensional analysis using low-dose computed tomography to evaluate the severity of Mycoplasma pneumoniae pneumonia in children.

Background: It is unclear whether local pathological pulmonary changes truly reflect the severity of childhood Mycoplasma pneumoniae infection, which is characterized by rapid progress and potential mortality. This study multi-dimensionally analyzed low-dose computed tomography findings to assess the severity of Mycoplasma pneumoniae infection and predict its progress in such patients. Methods: In all, 752 children with Mycoplasma pneumoniae pneumonia (MPP) who underwent low-dose computed tomography examinations from February 2016 to July 2020 were retrospectively enrolled to conduct a cohort study. Clinical and radiological variables were analyzed using univariate analysis, and radiological variables were further analyzed using multivariable logistic regression in severe cases. Then, the correlation between the key computed tomography features and clinical symptoms, laboratory indicators, and medical costs were assessed using the chi-squared and Kruskal-Wallis H tests. Kaplan-Meier curves and Cox regression models were created to evaluate the correlations between the key computed tomography features, fever duration, and the length of hospital stay. Results: Of the 752 included patients, 16.2% (122/752) developed severe MPP. Atelectasis, pleural effusion, and lung consolidation occurred in 9.7% (73/752), 15.8% (119/752), and 90.3% (679/752) of patients, respectively. In addition to pleural effusion, the number of lobes of lung consolidation was the highest risk feature of severe MPP. Patients with consolidation in 2, 3, and 4 lobes had a 1.0-, 3.1-, and 7.5-fold increased risk of severe MPP, compared with patients with consolidation in fewer than 1 lobe. The duration of fever prior to admission had no effect on the proportions of the lobar consolidation (P=0.14) but did have significant effect on the incidence of pleural effusion (P=0.004). Levels of inflammatory markers and medical costs rose consistently with the increase in the number of lobar consolidations (P<0.001). After adjustments for pleural effusion, 1, 2, 3, and 4 lobes of consolidation remained positively associated with fever duration [1 lobe: hazard ratio (HR) =1.55, 95% CI: 1.10-2.18; 2 lobes: HR =1.65, 95% CI: 1.13-2.42l; 3 lobes: HR =1.82, 95% CI: 1.11-2.98; 4 lobes: HR =2.87, 95% CI: 1.25-6.61] compared to 0 lobes of consolidation. Compared to 0 lobes of consolidation, 1, 2, 3, and 4 lobes of consolidation were also positively correlated with the length of hospital stay (1 lobe: HR =2.24, 95% CI: 1.73-2.89; 2 lobes: HR =2.56, 95% CI: 1.91-3.43; 3 lobes: HR =2.87, 95% CI: 1.90-4.32; 4 lobes: HR =4.12, 95% CI: 2.01-8.46). Conclusions: Lobar consolidation is a stable and reliable computed tomography feature that can be used to assess the severity of MPP in children. Quantitative analysis of lobar consolidation can comprehensively and accurately predict the progression of Mycoplasma pneumoniae. Low-dose computed tomography is recommended for children with severe MPP with complicated courses.

Association of Blood Glucose Variability with Sepsis-Related Disseminated Intravascular Coagulation Morbidity and Mortality.

Purpose: Sepsis-related disseminated intravascular coagulation (DIC) is closely associated with poor prognosis and high mortality. Higher blood glucose (BG) variability indicates an increased risk of mortality in sepsis; however, its relationship with sepsis-related DIC has not been investigated. This study aimed to determine the association between glucose variability and sepsis-related DIC. Patients and Methods: Patients with sepsis admitted to the intensive care unit were enrolled between October 2017 and January 2021. Baseline data and BG records from the first 72 h were collected. We calculated the glucose liability index (GLI), largest amplitude of glucose excursion, BG standard deviation, and coefficient of variation on days 1 and 3. The relationship between GLI and morbidity of sepsis-related DIC was explored using a competing risk model. In subgroup analysis, we divided patients with and without diabetes into three groups according to the BG range. Results: Of the 238 patients enrolled, 28.2% developed DIC during hospitalization (n=67). GLI on day 3 was found to have the closest relationship with DIC incidence as it has the largest area under the ROC curve and the highest associated odds ratio of death per unit change (GLI3-day: AUC=0.891 OR=1.84), also independently increased the occurrence of DIC after adjusting for the competing risk of death (sub-distribution hazard ratios=1.866, p<0.01). In subgroup analysis, patients with diabetes had worse outcomes under hypoglycemia than under hyperglycemia. Patients without diabetes having stable BG had the best outcomes. Conclusion: Our study suggested that a higher GLI in patients with sepsis at 72 h was independently associated with an increased risk of sepsis-related DIC, which was not associated with pre-existing diabetes.

Trimethylamine N-Oxide Promotes Cell Proliferation and Angiogenesis in Colorectal Cancer.

Background. Of all intestinal microbiome-derived metabolites, trimethylamine N-oxide (TMAO) has received increasing attention because of its potent role in colorectal cancer development. Accumulating evidence suggests that TMAO generated by the gut microbiota is a new and important player in the etiological process of colorectal cancer. Nevertheless, the carcinogenic mechanism of TMAO in colorectal cancer remains unclear. In this study, TMAO induced colorectal cancer cell proliferation and produced higher vascular endothelial growth factor A (VEGFA) levels in vitro. In vivo, after long-term choline feeding in tumor-bearing mice, circulating TMAO levels, tumor volume, new blood vessel formation, and VEGFA and CD31 amounts were increased significantly. This study revealed that TMAO exerts oncogenic effects by promoting cell proliferation and angiogenesis in colorectal cancer.

A novel electrochemical biosensor based on MIL-101-NH2 (Cr) combining target-responsive releasing and self-catalysis strategy for p53 detection.

A novel electrochemical biosensor was constructed to detect p53 gene based on MIL-101-NH2 (Cr) by combining target-responsive releasing and self-catalysis strategy. MIL-101-NH2 (Cr) with suitable pore structure was used to encapsulate methylene blue (MB) as signal probe. The hairpin DNA (HP) containing rich-G sequences was used as gatekeeper to seal up the pores and avoid MB leakage through covalent immobilization. The p53 gene could hybridize with the loop portion of HP for the formation of dsDNA, which had the specific nicking site of the nicking endonuclease (Nt.BstNBI). Then Nt.BstNBI recognized the specific recognition site and cleaved HP to open the pore for releasing of MB. Meanwhile, the cleavage of HP released the target DNA to trigger the target recycling for signal amplification. More importantly, the plentiful rich-G sequences were exposed to form Hemin/G-quadruplex DNAzymes, which could unite MIL-101-NH2 (Cr) to catalyze redox reaction of MB released by itself for signal amplification. The biosensor for p53 had wide linear range from 1 × 10-14 to 1 × 10-7 M and a low detection limit of 1.4 × 10-15 M. The combination of target-responsive releasing and self-catalysis strategy provided a promising way for constructing ultrasensitive and simple biosensor.

Multi-omic Profiling Reveals that Intra-abdominal-Hypertension-Induced Intestinal Damage Can Be Prevented by Microbiome and Metabolic Modulations with 5-Hydroxyindoleacetic Acid as a Diagnostic Marker.

Emerging evidence shows that modulation of the microbiome can suppress intra-abdominal hypertension (IAH)-induced intestinal barrier damage through the regulation of amino acid (AA) biosynthesis. Here, we investigated the protective effects of orally gavaged Lactobacillus acidophilus L-92 (L92) and a mixture of AA in rats with induced IAH. The results showed that both L92 and AA pretreatments effectively mitigated IAH-induced intestinal damage. Interestingly, L92 but not AA prevented metagenomic changes induced by IAH. Bacteroides fragilis, Bacteroides eggerthii, Bacteroides ovatus, Faecalibacterium prausnitzii, Prevotella, and extensively altered functional pathways were associated with L92-mediated host protection. Metabolomic profiling revealed that tryptophan metabolism was involved in both L92- and AA-mediated gut protection. The tryptophan metabolite 5-hydroxyindoleacetic acid (5-HIAA) is a sensitive biomarker for IAH in rats and patients with either gut-derived sepsis (n = 41) or all-source sepsis (n = 293). In conclusion, we show that microbiome and metabolic modulations can effectively prevent IAH-induced intestinal damage and that 5-HIAA is a potential metabolic marker for IAH and sepsis. IMPORTANCE Gut protection through modulation of the microbiome for critically ill patients has been gaining much attention recently. Intra-abdominal hypertension (IAH) is a prevailing clinical feature of acute gastrointestinal injuries in critically ill patients, characterized by nonspecific intestinal barrier damage. Prolonged IAH can induce or aggravate the development of sepsis and multiorgan dysfunctions. Therefore, the prevention of IAH-induced damage in rats through microbiome and metabolic interventions by commercially available L92 and AA treatments and the identification of 5-HIAA as an important marker for IAH/sepsis have important clinical implications for the treatment and early diagnosis of critically ill patients.

Predictors for mortality and recovery in patients with acute renal injury receiving continuous renal replacement therapy.

OBJECTIVE: Despite continuous renal replacement therapy (CRRT) has been widely used in critically ill patients with acute kidney injury (AKI), the prognosis and recovery of renal function in these patients are still poor. Therefore, we aimed to identify the prognostic factors for the mortality and recovery of renal function in patients with AKI receiving CRRT. METHODS: A total of 125 patients with AKI, treated with CRRT in the emergency intensive care unit (EICU) in an academic teaching hospital from January 2014 to December 2018 were enrolled in this retrospective study. The clinical data of these patients were collected. Univariate regression analysis and multivariate regression analysis were conducted to identify the predictors for the mortality and recovery of renal function. RESULTS: The median age was 68.0 (56.5-79.0) years old, and from which 69.6% were males. Sixty-four patients (51.2%) survived and 50 patients (40%) recovered their renal function. Multivariate regression analysis showed that the independent risk factors for mortality were male (odds ratio [OR]:3.771, 95% confidence interval [CI]:1.063-13.372, p = 0.04), Acute Physiology and Chronic Health Evaluation (APACHE) II score (OR: 1.187, 95% CI: 1.050-1.341, p = 0.006), mechanical ventilation (OR: 6.266, 95% CI: 1.771-22.167, p = 0.004) and vasopressor use (OR: 5.224, 95% CI: 1.546-17.657, p = 0.008). Moreover, the independent predictors for not recovering of renal function were male (OR: 3.440, 95% CI: 1.271-9.311, p = 0.015), pre-existing comorbidity of hypertension (OR: 4.207, 95% CI: 1.609-11.000, p = 0.003) and vasopressor use (OR: 5.280, 95% CI: 2.018-13.811, p = 0.001). CONCLUSIONS: Male, high APACHE II score, mechanical ventilation and vasopressor use were closely associated with the increased mortality, while male, pre-existing history of hypertension, and vasopressor use were the independent predictors for non-recovery of renal function.

MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum.

BACKGROUND: Gravid patients at high risk with placenta accreta spectrum (PAS) face life-threatening risk at delivery. Intraoperative risk assessment for patients is currently insufficient. We aimed to develop an assessment system of intraoperative risks through MRI-based radiomics. METHODS: A total of 131 patients enrolled were randomly grouped according to a ratio of 7:3. Clinical data were analyzed retrospectively. Radiomic features were extracted from sagittal Fast Imaging Employing State-sate Acquisition images. Univariate and multivariate regression analyses were performed to build models using R software. A receiver operating characteristic curve and decision curve analysis (DCA) were performed to determine the predictive performance of models. RESULTS: Six radiomic features and two clinical variables were used to construct the combined model for selection of removal protocols of the placenta, with an area under the curve (AUC) of 0.90 and 0.91 in the training and test cohorts, respectively. Nine radiomic features and two clinical variables were obtained to establish the combined model for prediction of intraoperative blood loss, with an AUC of 0.90 and 0.88 in the both cohorts, respectively. The DCA confirmed the clinical utility of the combined model. CONCLUSION: The analysis of combined MRI-based radiomics with clinics could be clinically beneficial for patients.

Initial CT-based radiomics nomogram for predicting in-hospital mortality in patients with traumatic brain injury: a multicenter development and validation study.

OBJECTIVE: To develop and validate a radiomic prediction model using initial noncontrast computed tomography (CT) at admission to predict in-hospital mortality in patients with traumatic brain injury (TBI). METHODS: A total of 379 TBI patients from three cohorts were categorized into training, internal validation, and external validation sets. After filtering the unstable features with the minimum redundancy maximum relevance approach, the CT-based radiomics signature was selected by using the least absolute shrinkage and selection operator (LASSO) approach. A personalized predictive nomogram incorporating the radiomic signature and clinical features was developed using a multivariate logistic model to predict in-hospital mortality in patients with TBI. The calibration, discrimination, and clinical usefulness of the radiomics signature and nomogram were evaluated. RESULTS: The radiomic signature consisting of 12 features had areas under the curve (AUCs) of 0.734, 0.716, and 0.706 in the prediction of in-hospital mortality in the internal and two external validation cohorts. The personalized predictive nomogram integrating the radiomic and clinical features demonstrated significant calibration and discrimination with AUCs of 0.843, 0.811, and 0.834 in the internal and two external validation cohorts. Based on decision curve analysis (DCA), both the radiomic features and nomogram were found to be clinically significant and useful. CONCLUSION: This predictive nomogram incorporating the CT-based radiomic signature and clinical features had maximum accuracy and played an optimized role in the early prediction of in-hospital mortality. The results of this study provide vital insights for the early warning of death in TBI patients.

The Supportive Role of International Government Funds on the Progress of Sepsis Research During the Past Decade (2010-2019): A Narrative Review.

This narrative review aimed to clarify the characteristics of international government support for sepsis research, trends in published literature on sepsis, and potential contributions of government-source grants to progress in sepsis research between fiscal years 2010 and 2019. The data in this study were collected from the National Institutes of Health (NIH, https://projectreporter.nih.gov/reporter.cfm/) of the United States of America (USA), National Natural Science Foundation of China (NSFC, https://isisn.nsfc.gov.cn/egrantweb/), and Japan Society for the Promotion of Science (JSPS, https://kaken.nii.ac.jp/). All sepsis-related projects approved by the NIH, NSFC, and JSPS were retrieved by searching the project titles, abstracts, and key words for "sepsis," "septic shock," or "sepsis inflammatory response syndrome" between 2010 and 2019. Representative sepsis-related studies published between Jan 2010 and Aug 2020 by the first/corresponding authors from these countries were obtained by searching the PubMed database using Medical Subject Heading terms for "sepsis" in representative journals, including Nature, Cell, Science, The Lancet, New England Journal of medicine (New Engl J Med), The Journal of American Medical Association (JAMA), Critical Care Medicine (CCM), Intensive Care Medicine (ICM), Chest, Annals of Emergency Medicine (Ann Emerg Med), and American Thoracic Society journals (ATS). The total/annual institutional budgets, major funding mechanisms and schemes, superior institutions and individual principal investigators, and published original research articles in the field of sepsis in the USA, China, and Japan during the past decade were investigated. The national supporting schemes of the NIH, NSFC, and JSPS were similar. Support from these institutions is quite important for the development of the field of "sepsis" which was acknowledged in 57-64% of original research articles published in CCM. For the future development of precision medicine in sepsis, more government funding support is necessary.