Role of gut-derived bacterial lipopolysaccharide and peripheral TLR4 in immobilization stress-induced itch aggravation in a mouse model of atopic dermatitis.

Psychological stress and intestinal leakage are key factors in atopic dermatitis (AD) recurrence and exacerbation. Here, we demonstrate the mechanism underlying bacterial translocation across intestinal epithelial barrier damaged due to stress and further aggravation of trimellitic anhydride (TMA)-induced itch, which remain unclear, in AD mice. Immobilization (IMO) stress exacerbated scratching bouts and colon histological damage, and increased serum corticosterone and lipopolysaccharide (LPS). Orally administered fluorescein isothiocyanate (FITC)-dextran and surgically injected (into the colon) Cy5.5-conjugated LPS were detected in the serum and skin after IMO stress, respectively. The relative abundance of aerobic or facultative anaerobic bacteria was increased in the colon mucus layer, and Lactobacillus murinus, E. coli, Staphylococcus nepalensis, and several strains of Bacillus sp. were isolated from the spleens and mesenteric lymph nodes. Oral antibiotics or intestinal permeability blockers, such as lubiprostone (Lu), 2,4,6-triaminopyrimidine (TAP) and ML-7, inhibited IMO stress-associated itch; however, it was reinduced through intradermal or i.p. injection of LPS without IMO stress. I.p. injection of TAK-242 (resatorvid), a TLR4 inhibitor, abrogated IMO stress-associated itch, which was also confirmed in TLR4-KO mice. IMO stress alone did not cause itch in naïve mice. IMO stress-induced itch aggravation in TMA-treated AD mice might be attributed to the translocation of gut-derived bacterial cells and LPS, which activates peripheral TLR4 signaling.

Chronic Gut Inflammation and Dysbiosis in IBS: Unraveling Their Contribution to Atopic Dermatitis Progression.

Emerging evidence suggests a link between atopic dermatitis (AD) and gastrointestinal disorders, particularly in relation to gut microbial dysbiosis. This study explored the potential exacerbation of AD by gut inflammation and microbial imbalances using an irritable bowel syndrome (IBS) mouse model. Chronic gut inflammation was induced in the model by intrarectal injection of 2,4,6-trinitrobenzene sulfonic acid (TNBS), followed by a 4-week development period. We noted significant upregulation of proinflammatory cytokines in the colon and evident gut microbial dysbiosis in the IBS mice. Additionally, these mice exhibited impaired gut barrier function, increased permeability, and elevated systemic inflammation markers such as IL-6 and LPS. A subsequent MC903 challenge on the right cheek lasting for 7 days revealed more severe AD symptoms in IBS mice compared to controls. Further, fecal microbial transplantation (FMT) from IBS mice resulted in aggravated AD symptoms, a result similarly observed with FMT from an IBS patient. Notably, an increased abundance of Alistipes in the feces of IBS mice correlated with heightened systemic and localized inflammation in both the gut and skin. These findings collectively indicate that chronic gut inflammation and microbial dysbiosis in IBS are critical factors exacerbating AD, highlighting the integral relationship between gut and skin health.

Performance and usefulness evaluation of a software-based scatter correction technique for mammographic images.

Although physical grids improve contrast in radiographic images by reducing scattered radiation, various artifacts such as grid shadow, moire, and cutoff result in increased patient doses. To overcome these problems, this study evaluates the applicability and usefulness of a material thickness-based scatter-correction technique for mammography. Specifically, this study aims to compare and evaluate the performance of mammography using the proposed software-based scatter correction framework and a physical grid. The proposed technique enables scatter correction based on pre-calculated parameters of a thickness-based scatter kernel at a water slab phantom and an empirical quantity of scatter components in a mammographic system. In the Monte Carlo simulation and experiment, the proposed framework displayed an intensity profile and full width at half maximum that closely approximated those seen in the physical grid. In addition, by applying the proposed framework to the ACR phantom, it was verified that all structures, including specks, were distinctly distinguished. The results demonstrate that the X-ray scatter-correction method with a software-based framework for mammography is applicable to the field of diagnostic imaging, as this approach yields image quality equivalent to that achieved with physical grids while also enabling a reduction in radiation doses for patients.

Sex differences in in-hospital management in patients with sepsis and septic shock: a prospective multicenter observational study.

Sex differences in the in-hospital management of sepsis exist. Previous studies either included patients with sepsis that was defined using previous definitions of sepsis or evaluated the 3-h bundle therapy. Therefore, this study sought to assess sex differences in 1-h bundle therapy and in-hospital management among patients with sepsis and septic shock, defined according to the Sepsis-3 definitions. This observational study used data from Korean Shock Society (KoSS) registry, a prospective multicenter sepsis registry. Adult patients with sepsis between June 2018 and December 2021 were included in this study. The primary outcome was adherence to 1-h bundle therapy. Propensity score matching (PSM) and multivariable logistic regression analyses were performed. Among 3264 patients with sepsis, 3129 were analyzed. PSM yielded 2380 matched patients (1190 men and 1190 women). After PSM, 1-h bundle therapy was performed less frequently in women than in men (13.0% vs. 19.2%; p < 0.001). Among the bundle therapy components, broad-spectrum antibiotics were administered less frequently in women than in men (25.4% vs. 31.6%, p < 0.001), whereas adequate fluid resuscitation was performed more frequently in women than in men (96.8% vs. 95.0%, p = 0.029). In multivariable logistic regression analysis, 1-h bundle therapy was performed less frequently in women than in men [adjusted odds ratio (aOR) 1.559; 95% confidence interval (CI) 1.245-1.951; p < 0.001] after adjustment. Among the bundle therapy components, broad-spectrum antibiotics were administered less frequently to women than men (aOR 1.339, 95% CI 1.118-1.605; p = 0.002), whereas adequate fluid resuscitation was performed more frequently for women than for men (aOR 0.629, 95% CI 0.413-0.959; p = 0.031). Invasive arterial blood pressure monitoring was performed less frequently in women than in men. Resuscitation fluid, vasopressor, steroid, central-line insertion, ICU admission, length of stay in the emergency department, mechanical ventilator use, and renal replacement therapy use were comparable for both the sexes. Among patients with sepsis and septic shock, 1-h bundle therapy was performed less frequently in women than in men. Continuous efforts are required to increase adherence to the 1-h bundle therapy and to decrease sex differences in the in-hospital management of patients with sepsis and septic shock.

Framework for dual-energy-like chest radiography image synthesis from single-energy computed tomography based on cycle-consistent generative adversarial network.

BACKGROUND: Dual-energy (DE) chest radiography (CXR) enables the selective imaging of two relevant materials, namely, soft tissue and bone structures, to better characterize various chest pathologies (i.e., lung nodule, bony lesions, etc.) and potentially improve CXR-based diagnosis. Recently, deep-learning-based image synthesis techniques have attracted considerable attention as alternatives to existing DE methods (i.e., dual-exposure-based and sandwich-detector-based methods) because software-based bone-only and bone-suppression images in CXR could be useful. PURPOSE: The objective of this study was to develop a new framework for DE-like CXR image synthesis from single-energy computed tomography (CT) based on a cycle-consistent generative adversarial network. METHODS: The core techniques of the proposed framework are divided into three categories: (1) data configuration from the generation of pseudo CXR from single energy CT, (2) learning of the developed network architecture using pseudo CXR and pseudo-DE imaging using a single-energy CT, and (3) inference of the trained network on real single-energy CXR. We performed a visual inspection and comparative evaluation using various metrics and introduced a figure of image quality (FIQ) to consider the effects of our framework on the spatial resolution and noise in terms of a single index through various test cases. RESULTS: Our results indicate that the proposed framework is effective and exhibits potential synthetic imaging ability for two relevant materials: soft tissue and bone structures. Its effectiveness was validated, and its ability to overcome the limitations associated with DE imaging techniques (e.g., increase in exposure dose owing to the requirement of two acquisitions, and emphasis on noise characteristics) via an artificial intelligence technique was presented. CONCLUSIONS: The developed framework addresses X-ray dose issues in the field of radiation imaging and enables pseudo-DE imaging with single exposure.

Optimization Method to Predict Optimal Noise Reduction Parameters for the Non-Local Means Algorithm Based on the Scintillator Thickness in Radiography.

The resulting image obtained from an X-ray imaging system depends significantly on the characteristics of the detector. In particular, when an X-ray image is acquired by thinning the detector, a relatively large amount of noise inevitably occurs. In addition, when a thick detector is used to reduce noise in X-ray images, blurring increases and the ability to distinguish target areas deteriorates. In this study, we aimed to derive the optimal X-ray image quality by deriving the optimal noise reduction parameters based on the non-local means (NLM) algorithm. The detectors used were of two thicknesses (96 and 140 µm), and images were acquired based on the IEC 62220-1-1:2015 RQA-5 protocol. The optimal parameters were derived by calculating the edge preservation index and signal-to-noise ratio according to the sigma value of the NLM algorithm. As a result, a sigma value of the optimized NLM algorithm (0.01) was derived, and this algorithm was applied to a relatively thin X-ray detector system to obtain appropriate noise level and spatial resolution data. The no-reference-based blind/referenceless image spatial quality evaluator value, which analyzes the overall image quality, was best when using the proposed method. In conclusion, we propose an optimized NLM algorithm based on a new method that can overcome the noise amplification problem in thin X-ray detector systems and is expected to be applied in various photon imaging fields in the future.

Correction: Prediction of disease severity using serum biomarkers in patients with mild-moderate Atopic Dermatitis: A pilot study.

[This corrects the article DOI: 10.1371/journal.pone.0293332.].

Noise Reduction for a Virtual Grid Using a Generative Adversarial Network in Breast X-ray Images.

In this study, we aimed to address the issue of noise amplification after scatter correction when using a virtual grid in breast X-ray images. To achieve this, we suggested an algorithm for estimating noise level and developed a noise reduction algorithm based on generative adversarial networks (GANs). Synthetic scatter in breast X-ray images were collected using Sizgraphy equipment and scatter correction was performed using dedicated software. After scatter correction, we determined the level of noise using noise-level function plots and trained a GAN using 42 noise combinations. Subsequently, we obtained the resulting images and quantitatively evaluated their quality by measuring the contrast-to-noise ratio (CNR), coefficient of variance (COV), and normalized noise-power spectrum (NNPS). The evaluation revealed an improvement in the CNR by approximately 2.80%, an enhancement in the COV by 12.50%, and an overall improvement in the NNPS across all frequency ranges. In conclusion, the application of our GAN-based noise reduction algorithm effectively reduced noise and demonstrated the acquisition of improved-quality breast X-ray images.

Modified Cardiovascular Sequential Organ Failure Assessment Score in Sepsis: External Validation in Intensive Care Unit Patients.

BACKGROUND: There is a need to update the cardiovascular (CV) Sequential Organ Failure Assessment (SOFA) score to reflect the current practice in sepsis. We previously proposed the modified CV SOFA score from data on blood pressure, norepinephrine equivalent dose, and lactate as gathered from emergency departments. In this study, we externally validated the modified CV SOFA score in multicenter intensive care unit (ICU) patients. METHODS: A multicenter retrospective observational study was conducted on ICU patients at six hospitals in Korea. We included adult patients with sepsis who were admitted to ICUs. We compared the prognostic performance of the modified CV/total SOFA score and the original CV/total SOFA score in predicting 28-day mortality. Discrimination and calibration were evaluated using the area under the receiver operating characteristic curve (AUROC) and the calibration curve, respectively. RESULTS: We analyzed 1,015 ICU patients with sepsis. In overall patients, the 28-day mortality rate was 31.2%. The predictive validity of the modified CV SOFA (AUROC, 0.712; 95% confidence interval [CI], 0.677-0.746; P < 0.001) was significantly higher than that of the original CV SOFA (AUROC, 0.644; 95% CI, 0.611-0.677). The predictive validity of modified total SOFA score for 28-day mortality was significantly higher than that of the original total SOFA (AUROC, 0.747 vs. 0.730; 95% CI, 0.715-0.779; P = 0.002). The calibration curve of the original CV SOFA for 28-day mortality showed poor calibration. In contrast, the calibration curve of the modified CV SOFA for 28-day mortality showed good calibration. CONCLUSION: In patients with sepsis in the ICU, the modified SOFA score performed better than the original SOFA score in predicting 28-day mortality.

ROMIAE (Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram Analysis) trial study protocol: a prospective multicenter observational study for validation of a deep learning-based 12-lead electrocardiogram analysis model for detecting acute myocardial infarction in patients visiting the emergency department.

OBJECTIVE: Based on the development of artificial intelligence (AI), an emerging number of methods have achieved outstanding performances in the diagnosis of acute myocardial infarction (AMI) using an electrocardiogram (ECG). However, AI-ECG analysis using a multicenter prospective design for detecting AMI has yet to be conducted. This prospective multicenter observational study aims to validate an AI-ECG model for detecting AMI in patients visiting the emergency department. METHODS: Approximately 9,000 adult patients with chest pain and/or equivalent symptoms of AMI will be enrolled in 18 emergency medical centers in Korea. The AI-ECG analysis algorithm we developed and validated will be used in this study. The primary endpoint is the diagnosis of AMI on the day of visiting the emergency center, and the secondary endpoint is a 30-day major adverse cardiac event. From March 2022, patient registration has begun at centers approved by the institutional review board. DISCUSSION: This is the first prospective study designed to identify the efficacy of an AI-based 12-lead ECG analysis algorithm for diagnosing AMI in emergency departments across multiple centers. This study may provide insights into the utility of deep learning in detecting AMI on electrocardiograms in emergency departments. Trial registration ClinicalTrials.gov identifier: NCT05435391. Registered on June 28, 2022.

Prediction of disease severity using serum biomarkers in patients with mild-moderate Atopic Dermatitis: A pilot study.

Atopic dermatitis (AD) is an inflammatory skin condition that relies largely on subjective evaluation of clinical signs and symptoms for diagnosis and severity assessment. Using multivariate data, we attempted to construct prediction models that can diagnose the disease and assess its severity. We combined data from 28 mild-moderate AD patients and 20 healthy controls (HC) to create random forest models for classification (AD vs. HC) and regression analysis to predict symptom severities. The classification model outperformed the random permutation model significantly (area under the curve: 0.85 ± 0.10 vs. 0.50 ± 0.15; balanced accuracy: 0.81 ± 0.15 vs. 0.50 ± 0.15). Correlation analysis revealed a significant positive correlation between measured and predicted total SCORing Atopic Dermatitis score (SCORAD; r = 0.43), objective SCORAD (r = 0.53), eczema area and severity index scores (r = 0.58, each p < 0.001), but not between measured and predicted itch ratings (r = 0.21, p = 0.18). We developed and tested multivariate prediction models and identified important features using a variety of serum biomarkers, implying that discovering the deep-branching relationships between clinical measurements and serum measurements in mild-moderate AD patients may be possible using a multivariate machine learning method. We also suggest future methods for utilizing machine learning algorithms to enhance drug target selection, diagnosis, prognosis, and customized treatment in AD.

Effects of Mitochondrial Transplantation on Transcriptomics in a Polymicrobial Sepsis Model.

Previously, we demonstrated that mitochondrial transplantation has beneficial effects in a polymicrobial sepsis model. However, the mechanism has not been fully investigated. Mitochondria have their own genes, and genomic changes in sepsis are an important issue in terms of pathophysiology, biomarkers, and therapeutic targets. To investigate the changes in transcriptomic features after mitochondrial transplantation in a polymicrobial sepsis model, we used a rat model of fecal slurry polymicrobial sepsis. Total RNA from splenocytes of sham-operated (SHAM, n = 10), sepsis-induced (SEPSIS, n = 7), and sepsis receiving mitochondrial transplantation (SEPSIS + MT, n = 8) samples was extracted and we conducted a comparative transcriptome-wide analysis between three groups. We also confirmed these results with qPCR. In terms of percentage of mitochondrial mapped reads, the SEPSIS + MT group had a significantly higher mapping ratio than the others. RT1-M2 and Cbln2 were identified as highly expressed in SEPSIS + MT compared with SEPSIS. Using SHAM expression levels as another control variable, we further identified six genes (Fxyd4, Apex2l1, Kctd4, 7SK, SNORD94, and SNORA53) that were highly expressed after sepsis induction and observed that their expression levels were attenuated by mitochondrial transplantation. Changes in transcriptomic features were identified after mitochondrial transplantation in sepsis. This might provide a hint for exploring the mechanism of mitochondrial transplantation in sepsis.

Graded brain fMRI response to somatic and visual acupuncture stimulation.

Increased stimulation can enhance acupuncture clinical response; however, the impact of acupuncture stimulation as "dosage" has rarely been studied. Furthermore, acupuncture can include both somatic and visual components. We assessed both somatic and visual acupuncture dosage effects on sensory ratings and brain response. Twenty-four healthy participants received somatic (needle inserted, manually stimulated) and visual (needle video, no manual stimulation) acupuncture over the leg at three different dosage levels (control, low-dose, and high-dose) during functional magnetic resonance imaging (fMRI). Participants reported the perceived deqi sensation for each acupuncture dose level. Blood-oxygen-level dependent imaging data were analyzed by general linear model and multivariate pattern analysis. For both somatic and visual acupuncture, reported deqi sensation increased with increased dosage of acupuncture stimulation. Brain fMRI analysis demonstrated that higher dosage of somatic acupuncture produced greater brain responses in sensorimotor processing areas, including anterior and posterior insula and secondary somatosensory cortex. For visual acupuncture, higher dosage of stimulation produced greater brain responses in visual-processing areas, including the middle temporal visual areas (V5/MT+) and occipital cortex. Psychophysical and psychophysiological responses to both somatic and visual acupuncture were graded in response to higher doses. Our findings suggest that acupuncture response may be enhanced by the dosage of needling-specific and nonspecific components, represented by different neural mechanisms.

Prognostic Performance of Sequential Organ Failure Assessment, Acute Physiology and Chronic Health Evaluation III, and Simplified Acute Physiology Score II Scores in Patients with Suspected Infection According to Intensive Care Unit Type.

We investigated the prognostic performance of scoring systems by the intensive care unit (ICU) type. This was a retrospective observational study using data from the Marketplace for Medical Information in the Intensive Care IV database. The primary outcome was in-hospital mortality. We obtained Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) III, and Simplified Acute Physiology Score (SAPS) II scores in each ICU type. Prognostic performance was evaluated with the area under the receiver operating characteristic curve (AUROC) and was compared among ICU types. A total of 29,618 patients were analyzed, and the in-hospital mortality was 12.4%. The overall prognostic performance of APACHE III was significantly higher than those of SOFA and SAPS II (0.807, [95% confidence interval, 0.799-0.814], 0.785 [0.773-0.797], and 0.795 [0.787-0.811], respectively). The prognostic performance of SOFA, APACHE III, and SAPS II scores was significantly different between ICU types. The AUROC ranges of SOFA, APACHE III, and SAPS II were 0.723-0.826, 0.728-0.860, and 0.759-0.819, respectively. The neurosurgical and surgical ICUs had lower prognostic performance than other ICU types. The prognostic performance of scoring systems in patients with suspected infection is significantly different according to ICU type. APACHE III systems have the highest prediction performance. ICU type may be a significant factor in the prognostication.

Development of Adaptive Point-Spread Function Estimation Method in Various Scintillation Detector Thickness for X-ray Imaging.

An indirect conversion X-ray detector uses a scintillator that utilizes the proportionality of the intensity of incident radiation to the amount of visible light emitted. A thicker scintillator reduces the patient's dose while decreasing the sharpness. A thin scintillator has an advantage in terms of sharpness; however, its noise component increases. Thus, the proposed method converts the spatial resolution of radiographic images acquired from a normal-thickness scintillation detector into a thin-thickness scintillation detector. Note that noise amplification and artifacts were minimized as much as possible after non-blind deconvolution. To accomplish this, the proposed algorithm estimates the optimal point-spread function (PSF) when the structural similarity index (SSIM) and feature similarity index (FSIM) are the most similar between thick and thin scintillator images. Simulation and experimental results demonstrate the viability of the proposed method. Moreover, the deconvolution images obtained using the proposed scheme show an effective image restoration method in terms of the human visible system compared to that of the traditional PSF measurement technique. Consequently, the proposed method is useful for restoring degraded images using the adaptive PSF while preventing noise amplification and artifacts and is effective in improving the image quality in the present X-ray imaging system.

Efficacy of Non-Enhanced Brain Computed Tomography in Patients Presenting to the Emergency Department with Headache after COVID-19 Vaccination.

Headaches are a common side effect of vaccination against the severe acute respiratory syndrome, coronavirus 2; however, it is usually not necessary to seek emergency medical attention or undergo brain imaging such as non-enhanced brain computed tomography (CT) for routine evaluation of vaccine-related headaches. This study aimed to demonstrate that brain CT is of no clinical benefit to patients presenting to the emergency department (ED) with post-coronavirus disease 2019 (COVID-19) vaccination headaches. This retrospective, single-center observational study used electronic medical record (EMR) data of patients who received the COVID-19 vaccination during the first year of the vaccination program. In total, 914 patients were analyzed, of whom 435 underwent CT (CT group, n = 435; no CT group, n = 475). More female patients visited the ED, and there was no significant sex difference between the CT and no-CT groups. The type of vaccine affected the clinical decision to perform brain CT, but the number of doses did not. The CT rate was relatively high for patients who had received the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) and Johnson and Johnson Janssen (Jansen) vaccines (p = 0.004). Focal neurological deficits were present in all cases of abnormalities on non-enhanced brain CT in patients complaining of headaches. Two out of the 435 patients had abnormal brain CT findings (glioblastoma and Rathke's pouch cyst) at 35 and 32 days after vaccination, respectively. Non-enhanced brain CT should be performed cautiously in patients visiting the ED for post-vaccination headaches only.

Development and derivation of bacteremia prediction model in patients with hepatobiliary infection.

INTRODUCTION: Hepatobiliary infections are common in the emergency department (ED), and the mortality rate for this condition is high. A suitable bacteremia prediction model would support prompt identification of bacteremia and appropriate management of hepatobiliary infections in the ED. Therefore, we attempted to produce a bacteremia prediction model with both internal and external validation for hepatobiliary infections in the ED. METHODS: Patients with hepatobiliary infection were extracted from retrospective cohort databases of two tertiary hospitals from January 2018 to December 2019 and from January 2016 to December 2019, respectively. Independent risk factors were determined using multivariable logistic regression in a developmental cohort. We assigned a weighted value to predictive factors and developed a prediction model, which was validated both internally and externally. We assessed discrimination using the area under the receiver operating characteristics curve (AUC). RESULTS: One hospital cohort of 1568 patients was randomly divided into a developmental group of 927 patients (60%) and an internal validation group of 641 patients (40%), and 736 people from the other hospital cohort were used for external validation. Bacteremia rates were 20.5%, 18.1%, and 23.1% in the developmental, internal, and external validation cohorts, respectively. Nine significant factors were used for predicting bacteremia, including age, three vital signs, and five laboratory tests. After applying our bacteremia prediction rule to the validation cohort, 56.5% and 53.8% of the internal and external validation groups were classified as low-risk bacteremia groups (bacteremia rates: 8.6% and 13.9%, respectively). The AUCs were 0.727 (95% confidence interval [CI]: 0.686-0.767), 0.730 (95% CI: 0.679-0.781), and 0.715 (95% CI: 0.672-0.758) for the developmental, internal, and external validation cohorts, respectively. The sensitivity and specificity for internal validation/external validation was 73.2%/67.6% and 63.0%/60.2%, respectively. CONCLUSION: A bacteremia prediction model for hepatobiliary infection might be useful to predict the risk of bacteremia. It might also reduce the need for blood culture in low-risk patients.

Effect of iodine concentration reduction by comparison of virtual monoenergetic image quality with dual-energy computed tomography.

This study aimed to evaluate the image quality of virtual monoenergetic images (VMIs) with tube voltage modulation in pediatric abdominal computed tomography (CT) examination and to determine the effect of decreasing contrast agent concentration. Using a 1-year old pediatric phantom, five contrast agent concentration diluent tubes of 100%, 80%, 60%, 40%, and 20% of the same concentration as the average Hounsfield unit (HU) in the descending aorta were inserted, and the mixed image and VMIs (40, 60, and 80 keV) acquired using dual-energy CT were compared with single-energy CT (SECT) images. For quantitative evaluation, the HU and coefficient of variation (COV) of each image were compared and analyzed. The analysis revealed that the HU of the 40 keV VMIs, acquired with a tube voltage of 70 kV and 100% contrast agent concentration, was 61% higher than that of the SECT image. The results showed that SECT had the lowest COV among all contrast agent concentration and tube voltage combinations, while the 40 keV image acquired at 70 kV had the second-lowest COV value. The HU of the 40 keV image acquired at 70 kV at a contrast agent concentration of 100% was 9% higher than that of SECT at 80% concentration. This study confirms that 40 keV VMIs are more useful than SECT images for vascular diagnosis with contrast in pediatric abdominal CT examinations and that a 20% reduction in contrast agent concentration can reduce the risk of contrast agent concentration-induced nephrotoxicity in pediatric patients by increasing the subjective acceptability of image quality for diagnosis.

Hemodynamic management of septic shock: beyond the Surviving Sepsis Campaign guidelines.

Although the Surviving Sepsis Campaign guidelines provide standardized and generalized guidance, they are less individualized. This review focuses on recent updates in the hemodynamic management of septic shock. Monitoring and intervention for septic shock should be personalized according to the phase of shock. In the salvage phase, fluid resuscitation and vasopressors should be given to provide life-saving tissue perfusion. During the optimization phase, tissue perfusion should be optimized. In the stabilization and de-escalation phases, minimal fluid infusion and safe fluid removal should be performed, respectively, while preserving organ perfusion. There is controversy surrounding the use of restrictive versus liberal fluid strategies after initial resuscitation. Fluid administration after initial resuscitation should depend upon the patient's fluid responsiveness and requires individualized management. A number of dynamic tests have been proposed to monitor fluid responsiveness, which can help clinicians decide whether to give fluid or not. The optimal timing for the initiation of vasopressor agents is unknown. Recent data suggest that early vasopressor initiation should be considered. Inotropes can be considered in patients with decreased cardiac contractility associated with impaired tissue perfusion despite adequate volume status and arterial blood pressure. Venoarterial extracorporeal membrane oxygenation should be considered for refractory septic shock with severe cardiac systolic dysfunction.

The Effects of Mitochondrial Transplantation on Sepsis Depend on the Type of Cell from Which They Are Isolated.

Previously, we have shown that mitochondrial transplantation in the sepsis model has immune modulatory effects. The mitochondrial function could have different characteristics dependent on cell types. Here, we investigated whether the effects of mitochondrial transplantation on the sepsis model could be different depending on the cell type, from which mitochondria were isolated. We isolated mitochondria from L6 muscle cells, clone 9 liver cells and mesenchymal stem cells (MSC). We tested the effects of mitochondrial transplantation using in vitro and in vivo sepsis models. We used the LPS stimulation of THP-1 cell, a monocyte cell line, as an in vitro model. First, we observed changes in mitochondrial function in the mitochondria-transplanted cells. Second, we compared the anti-inflammatory effects of mitochondrial transplantation. Third, we investigated the immune-enhancing effects using the endotoxin tolerance model. In the in vivo polymicrobial fecal slurry sepsis model, we examined the survival and biochemical effects of each type of mitochondrial transplantation. In the in vitro LPS model, mitochondrial transplantation with each cell type improved mitochondrial function, as measured by oxygen consumption. Among the three cell types, L6-mitochondrial transplantation significantly enhanced mitochondrial function. Mitochondrial transplantation with each cell type reduced hyper-inflammation in the acute phase of in vitro LPS model. It also enhanced immune function during the late immune suppression phase, as shown by endotoxin tolerance. These functions were not significantly different between the three cell types of origin for mitochondrial transplantation. However, only L6-mitochondrial transplantation significantly improved survival compared to the control in the polymicrobial intraabdominal sepsis model. The effects of mitochondria transplantation on both in vitro and in vivo sepsis models differed depending on the cell types of origin for mitochondria. L6-mitochondrial transplantation might be more beneficial in the sepsis model.