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Background The SpO2/FiO2 is a useful oxygenation parameter with prognostic capacity in patients with ARDS. We investigated the prognostic capacity of SpO2/FiO2 for mortality in patients with ARDS due to COVID–19. Methods This was a post-hoc analysis of a national multicenter cohort study in invasively ventilated patients with ARDS due to COVID–19. The primary endpoint was 28–day mortality. Results In 869 invasively ventilated patients, 28–day mortality was 30.1%. The SpO2/FiO2 on day 1 had no prognostic value. The SpO2/FiO2 on day 2 and day 3 had prognostic capacity for death, with the best cut-offs being 179 and 199, respectively. Both SpO2/FiO2 on day 2 (OR, 0.66 [95%–CI 0.46–0.96]) and on day 3 (OR, 0.70 [95%–CI 0.51–0.96]) were associated with 28–day mortality in a model corrected for age, pH, lactate levels and kidney dysfunction (AUROC 0.78 [0.76–0.79]). The measured PaO2/FiO2 and the PaO2/FiO2 calculated from SpO2/FiO2 were strongly correlated (Spearman's r = 0.79). Conclusions In this cohort of patients with ARDS due to COVID–19, the SpO2/FiO2 on day 2 and day 3 are independently associated with and have prognostic capacity for 28–day mortality. The SpO2/FiO2 is a useful metric for risk stratification in invasively ventilated COVID–19 patients.

By the end of year 2019, the new virus SARS-CoV-2 appeared, causing the Coronavirus Disease 2019 (COVID-19), and spread very fast globally. A continuing need for diagnostic tools is a must to contain its spread. Till now, the gold standard method, the reverse transcription polymerase chain reaction (RT-PCR), is the precise procedure to detect the virus. However, SARS-CoV-2 may escape RT-PCR detection for several reasons. The development of well-designed, specific and sensitive serological test like enzyme immunoassay (EIA) is needed. This EIA can stand alone or work side by side with RT-PCR. In this study, we developed several EIAs including plates that are coated with either specially designed SARS-CoV-2 nucleocapsid or surface recombinant proteins. Each protein type can separately detect anti-SARS-CoV-2 IgM or IgG antibodies. For each EIAs, the cut-off value, specificity and sensitivity were determined utilizing RT-PCR confirmed Covid-19 and pre-pandemic healthy and other viruses-infected sera. Also, the receiver operator characteristic (ROC) analysis was performed to define the specificities and sensitivities of the optimized assay. The in-house EIAs were validated by comparing against commercial EIA kits. All in-house EIAs showed high specificity (98–99%) and sensitivity (97.8–98.9%) for the detection of IgG/IgM against RBD and N proteins of SARS-CoV-2. From these results, the developed Anti-RBD and anti-N IgG and IgM antibodies EIAs can be used as a specific and sensitive tool to detect SARS-CoV-2 infection, calculate the burden of disease and case fatality rates.

Rapid antigen tests (RATs) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have advantages over viral culture in terms of cost and rapidity of testing, but they have low sensitivity. In addition, RATs tend to be negative from approximately 11 days after symptom onset. To determine whether the antigen-negative state indicates a lack of infectiousness, we assessed the association between viral culture and RAT results. Viral culture, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and rapid antigen testing were performed on stored nasopharyngeal samples with threshold cycle values

Background Prognostic implications of blood cholesterol may differ at different stages of life. This cohort study compares the value of total cholesterol (TC) readings earlier versus later in life for the prediction of coronary atherosclerosis, cardiovascular events, and cardiovascular death. Methods In a cardiovascular observation study (CVOS) we performed coronary angiography and prospectively recorded cardiovascular events in 1090 patients over up to 19 years. These patients had participated in a health survey (HS) 15 years prior to the CVOS baseline. TC was measured twice, first at the earlier HS and then later at CVOS recruiting. Findings Patients in the highest versus the lowest TC-category of the HS had an OR of 4.30 [2.41–7.65] for significant CAD at angiography, a HR of 1.74 [1.10–2.76] for cardiovascular events, and a HR of 7.55 [1.05–54.49] for cardiovascular death after multivariate adjustment. In contrast, TC as measured at the baseline of the CVOS was neither significantly associated with significant CAD (OR= 0.75 [0.49–1.13]) nor with cardiovascular events or death during follow-up (HR= 0.86 [0.62–1.18] and 0.79 [0.41–1.53], respectively). Moreover, the ESC/EAS-SCORE was found to be more powerful in predicting cardiovascular mortality when using earlier instead of later TC, with a continuous net reclassification improvement of 0.301 (p Interpretation Early measurement not only enables early intervention in keeping with the concept of lifelong exposure to atherogenic lipoproteins. These data also suggest that cardiovascular risk prediction is more accurate if using earlier in life TC readings. Funding The present study did not receive any particular funding

Background Treatment decisions for multimodal therapy in soft tissue sarcoma (STS) patients greatly depend on the differentiation between low-grade and high-grade tumors. We developed MRI-based radiomics grading models for the differentiation between low-grade (G1) and high-grade (G2/G3) STS. Methods The study was registered at ClinicalTrials.gov (number NCT03798795 ). Contrast-enhanced T1-weighted fat saturated (T1FSGd), fat-saturated T2-weighted (T2FS) MRI sequences, and tumor grading following the French Federation of Cancer Centers Sarcoma Group obtained from pre-therapeutic biopsies were gathered from two independent retrospective patient cohorts. Volumes of interest were manually segmented. After preprocessing, 1394 radiomics features were extracted from each sequence. Features unstable in 21 independent multiple-segmentations were excluded. Least absolute shrinkage and selection operator models were developed using nested cross-validation on a training patient cohort (122 patients). The influence of ComBatHarmonization was assessed for correction of batch effects. Findings Three radiomic models based on T2FS, T1FSGd and a combined model achieved predictive performances with an area under the receiver operator characteristic curve (AUC) of 0.78, 0.69, and 0.76 on the independent validation set (103 patients), respectively. The T2FS-based model showed the best reproducibility. The radiomics model involving T1FSGd-based features achieved significant patient stratification. Combining the T2FS radiomic model into a nomogram with clinical staging improved prognostic performance and the clinical net benefit above clinical staging alone. Interpretation MRI-based radiomics tumor grading models effectively classify low-grade and high-grade soft tissue sarcomas. Fund The authors received support by the medical faculty of the Technical University of Munich and the German Cancer Consortium.

While circulating tumor cell (CTC)–based detection of AR-V7 has been demonstrated to predict patient response to second-generation androgen receptor therapies, the rarity of AR-V7 expression in metastatic castrate-resistant prostate cancer (mCRPC) suggests that other drivers of resistance exist. We sought to use a multiplex gene expression platform to interrogate CTCs and identify potential markers of resistance to abiraterone and enzalutamide. 37 patients with mCRPC initiating treatment with enzalutamide (n = 16) or abiraterone (n = 21) were prospectively enrolled for CTC collection and gene expression analysis using a panel of 89 prostate cancer–related genes. Gene expression from CTCs was correlated with PSA response and radioclinical progression-free survival (PFS) using Kaplan-Meier and Cox regression analyses. Twenty patients (54%) had detectable CTCs. At a median follow-up of 11.3 months, increased expression of the following genes was significantly associated with shorter PSA PFS and radioclinical PFS: AR, AR-V7, PSA, PSCA, TSPAN8, NKX3.1, and WNT5B. Additionally, high SPINK1 expression was associated with increased PFS. A predictive model including all eight genes gave an area under the curve (AUC) of 0.84 for PSA PFS and 0.86 for radioclinical PFS. In comparison, the AR-V7 only model resulted in AUC values of 0.65 and 0.64.These data demonstrate that clinically relevant information regarding gene expression can be obtained from whole blood using a CTC-based approach. Multigene classifiers in this setting may allow for the development of noninvasive predictive biomarkers to guide clinical management.

Prodrug nanoassemblies, which can refrain from large excipients, achieve higher drug loading and control drug release, have been placed as the priority in drug delivery system. Reasoning that glutathione (GSH) and reactive oxygen species (ROS) are highly upgraded in tumor tissues which makes them attractive targets for drug delivery system, we designed and synthetized a novel prodrug which utilized mono thioether bond as a linker to bridge linoleic acid (LA) and docetaxel (DTX). This mono thioether-linked conjugates (DTX-S-LA) could self-assemble into nanoparticles without the aid of much excipients. The mono thioether endowed the nanoparticles redox sensitivity resulting in specific release at the tumor tissue. Our studies demonstrated that the nanoassemblies had uniform particle size, high stability and fast release behavior. DTX-S-LA nanoassemblies outperformed DTX solution in pharmacokinetic profiles for it had longer circulation time and higher area under curve (AUC). Compared with DTX solution, the redox dual-responsive nanoassemblies had comparable cytotoxic activity. Besides, the antitumor efficacy was evaluated in mice bearing 4T1 xenograft. It turned out this nanoassemblies could enhance anticancer efficacy by increasing the dose because of higher tolerance. Overall, these results indicated that the redox sensitivity nanoassemblies may have a great potential to cancer therapy., Graphical abstract A novel prodrug was designed and synthetized which utilized mono thioether bond as a linker to bridge linoleic acid and docetaxel. This redox sensitive conjugate could self-assemble into nanoparticles which had excellent physical stability, strong cytotoxic activity, prolonged circulation time and enhanced anticancer efficacy.fx1

Background Nitrite is reduced by heme-proteins and molybdenum-containing enzymes to form the important signaling molecule nitric oxide (NO), mediating NO signaling. Substantial evidence suggests that deoxygenated hemoglobin within red blood cells (RBCs) is the main erythrocytic protein responsible for mediating nitrite-dependent NO signaling. In other work, infrared and far red light have been shown to have therapeutic potential that some attribute to production of NO. Here we explore whether a combination of nitrite and far red light treatment has an additive effect in NO-dependent processes, and whether this effect is mediated by RBCs. Methods and results Using photoacoustic imaging in a rat model as a function of varying inspired oxygen, we found that far red light (660 nm, five min. exposure) and nitrite feeding (three weeks in drinking water at 100 mg/L) each separately increased tissue oxygenation and vessel diameter, and the combined treatment was additive. We also employed inhibition of human platelet activation measured by flow cytometry to assess RBC-dependent nitrite bioactivation and found that far red light dramatically potentiates platelet inhibition by nitrite. Blocking RBC-surface thiols abrogated these effects of nitrite and far-red light. RBC-dependent production of NO was also shown to be enhanced by far red light using a chemiluminescence-based nitric oxide analyzer. In addition, RBC-dependent bioactivation of nitrite led to prolonged lag times for clotting in platelet poor plasma that was enhanced by exposure to far red light. Conclusions Our results suggest that nitrite leads to the formation of a photolabile RBC surface thiol-bound species such as an S-nitrosothiol or heme-nitrosyl (NO-bound heme) for which far red light enhances NO signaling. These findings expand our understanding of RBC-mediated NO production from nitrite. This pathway of NO production may have therapeutic potential in several applications including thrombosis, and, thus, warrants further study., Graphical abstract Potential mechanism of RBC-mediated nitrite bioactivation and its potentiation by far red light. Nitrite reacts with deoxygenated Hb to make NO which then binds other vacant hemes or forms a nitrosothiol (RSNO). The nitrosyl-heme or nitrosothiol is exported and binds a surface thiol. Another potential NO species that may form is a DNIC (not shown). The NO congener can then be transported in plasma and interact with platelets and other blood components and this action is potentiated by photolysis using far red light.fx1, Highlights • Nitrite and far red light increase tissue oxygenation under hypoxia. • Far red light enhances nitrite-mediated inhibition of platelet activation by red cells. • Blocking red cell surface thiols abrogates nitrite-mediated effects. • NO production from nitrite and red cells is enhanced by far red light. • Lag time in clotting is prolonged by nitrite plus far red light.

A reliable and fast liquid chromatography-tandem mass spectrometry method has been developed for the simultaneous determination of three oxidized nucleic acid damage products in urine, 8-oxoguanine (8-oxoGua), 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodGuo) and 8-oxo-7,8-dihydroguanosine (8-oxoGuo). We applied this method to assess the effect of various urine workup procedures on the urinary concentrations of the oxidized nucleic acid products. Our results showed that frozen urine samples must be warmed (i.e., to 37 °C) to re-dissolve any precipitates prior to analysis. We showed that common workup procedures, such as thawing at room temperature or dilution with deionized water, are not capable of releasing fully the oxidized nucleic acid products from the precipitates, and result in significant underestimation (up to ~ 100% for 8-oxoGua, ~ 86% for both 8-oxodGuo and 8-oxoGuo).With this method, we further assessed and compared the ability of the three oxidized nucleic acid products, as well as malondialdehyde (MDA, a product of lipid peroxidation), to biomonitor oxidative stress in vivo. We measured a total of 315 urine samples from subjects with burdens of oxidative stress from low to high, including healthy subjects, patients with chronic obstructive pulmonary disease (COPD), and patients on mechanical ventilation (MV). The results showed that both the MV and COPD patients had significantly higher urinary levels of 8-oxoGua, 8-oxodGuo, and 8-oxoGuo (P

Purpose Transcriptomic profiling has enabled the neater genomic characterization of several cancers, among them colorectal cancer (CRC), through the derivation of genes with enhanced causal role and informative gene sets. However, the identification of small-sized gene signatures, which can serve as potential biomarkers in CRC, remains challenging, mainly due to the great genetic heterogeneity of the disease. Methods We developed and exploited an analytical framework for the integrative analysis of CRC datasets, encompassing transcriptomic data and positron emission tomography (PET) measurements. Profiling data comprised two microarray datasets, pertaining biopsy specimen from 30 untreated patients with primary CRC, coupled by their F-18-Fluorodeoxyglucose (FDG) PET values, using tracer kinetic analysis measurements. The computational framework incorporates algorithms for semantic processing, multivariate analysis, data mining and dimensionality reduction. Results Transcriptomic and PET data feature sets, were evaluated for their discrimination performance between primary colorectal adenocarcinomas and adjacent normal mucosa. A composite signature was derived, pertaining 12 features: 7 genes and 5 PET variables. This compact signature manifests superior performance in classification accuracy, through the integration of gene expression and PET data. Conclusions This work represents an effort for the integrative, multilayered, signature-oriented analysis of CRC, in the context of radio-genomics, inferring a composite signature with promising results for patient stratification., Graphical Abstract Unlabelled Image

Introduction: Acute and chronic insomnia can exacerbate type 2 diabetes mellitus (T2DM). We investigated suvorexant (an anti-insomnia drug that targets the orexin system) effects on sleep architecture and glucose metabolism in T2DM patients with insomnia. Materials and methods: This 7 day open-label, single-arm, intervention trial included 18 subjects with T2DM and insomnia. After 1 day acclimatization, daily glucose levels, sleep architecture, and autonomic nervous function were evaluated by continuous glucose monitoring (CGM), single-channel electroencephalography, and accelerometry, respectively. Results: Suvorexant treatment for 3 days significantly increased total sleep time and sleep efficiency, with partial suppression of sympathetic nerve activity. CGM-measured 24 h mean glucose level decreased significantly from 157.7 ± 22.9 to 152.3 ± 17.8 mg/dL, especially in the early glucose surge after the midnight nadir (from 28.3 ± 15.0 to 18.2 ± 9.9 mg/dL), and until supper with a significant improvement in homeostasis model assessment of insulin resistance from 4.0 ± 2.8 to 2.9 ± 1.6, respectively. Conclusions: Suvorexant treatment for insomnia of subjects with T2DM significantly improved CGM-measured daily glycemic control, which was associated with changes in sympathomimetic tone and/or improved insulin sensitivity. The amelioration of insomnia may therefore be a target for improving glycemic control in T2DM patients with insomnia. Keywords: Type 2 diabetes mellitus, Therapy for insomnia, Glycemic control, Insulin resistance, Dawn phenomenon, Autonomic nervous function

Objective Non-alcoholic fatty liver disease (NAFLD) risk begins in utero in offspring of obese mothers. A critical unmet need in this field is to understand the pathways and biomarkers underlying fetal hepatic lipotoxicity and whether maternal dietary intervention during pregnancy is an effective countermeasure. Methods We utilized a well-established non-human primate model of chronic, maternal, Western-style diet induced obesity (OB-WSD) compared with mothers on a healthy control diet (CON) or a subset of OB-WSD mothers switched to the CON diet (diet reversal; OB-DR) prior to and for the duration of the next pregnancy. Fetuses were studied in the early 3rd trimester. Results Fetuses from OB-WSD mothers had higher circulating triglycerides (TGs) and lower arterial oxygenation suggesting hypoxemia, compared with fetuses from CON and OB-DR mothers. Hepatic TG content, oxidative stress (TBARs), and de novo lipogenic genes were increased in fetuses from OB-WSD compared with CON mothers. Fetuses from OB-DR mothers had lower lipogenic gene expression and TBARs yet persistently higher TGs. Metabolomic profiling of fetal liver and serum (umbilical artery) revealed distinct separation of CON and OB-WSD groups, and an intermediate phenotype in fetuses from OB-DR mothers. Pathway analysis identified decreased tricarboxylic acid cycle intermediates, increased amino acid (AA) metabolism and byproducts, and increased gluconeogenesis, suggesting an increased reliance on AA metabolism to meet energy needs in the liver of fetuses from OB-WSD mothers. Components in collagen synthesis, including serum protein 5-hydroxylysine and hepatic lysine and proline, were positively correlated with hepatic TGs and TBARs, suggesting early signs of fibrosis in livers from the OB-WSD group. Importantly, hepatic gluconeogenic and arginine related intermediates and serum levels of lactate, pyruvate, several AAs, and nucleotide intermediates were normalized in the OB-DR group. However, hepatic levels of CDP-choline and total ceramide levels remained high in fetuses from OB-DR mothers. Conclusions Our data provide new metabolic evidence that, in addition to fetal hepatic steatosis, maternal WSD creates fetal hypoxemia and increases utilization of AAs for energy production and early activation of gluconeogenic pathways in the fetal liver. When combined with hyperlipidemia and limited antioxidant activity, the fetus suffers from hepatic oxidative stress and altered intracellular metabolism which can be improved with maternal diet intervention. Our data reinforce the concept that multiple “first hits” occur in the fetus prior to development of obesity and demonstrate new biomarkers with potential clinical implications for monitoring NAFLD risk in offspring., Graphical abstract Image 1, Highlights • Maternal WSD increases fetal hypoxemia and utilization of AAs for gluconeogenesis. • Maternal WSD increases fetal oxidative stress and precursors to liver fibrosis. • Carnosine and l-proline uniquely correlated with fetal TG and oxidative stress. • Fetal TGs were correlated with fetal arterial oxygen saturation. • Diet reversal in obese WSD mothers prevents fetal hypoxemia and oxidative stress.

Background Preoperative prediction of lymph node (LN) status is of crucial importance for appropriate treatment planning in patients with colorectal cancer (CRC). In this study, we sought to develop and validate a non-invasive nomogram model to preoperatively predict LN metastasis in CRC. Methods Development of the nomogram entailed three subsequent stages with specific patient sets. In the discovery set (n = 20), LN-status-related miRNAs were screened from high-throughput sequencing data of human CRC serum samples. In the training set (n = 218), a miRNA panel-clinicopathologic nomogram was developed by logistic regression analysis for preoperative prediction of LN metastasis. In the validation set (n = 198), we validated the above nomogram with respect to its discrimination, calibration and clinical application. Findings Four differently expressed miRNAs (miR-122-5p, miR-146b-5p, miR-186-5p and miR-193a-5p) were identified in the serum samples from CRC patients with and without LN metastasis, which also had regulatory effects on CRC cell migration. The combined miRNA panel could provide higher LN prediction capability compared with computed tomography (CT) scans (P

Liver dysfunction during sepsis is associated with increased bilirubin and decreased fetuin-A, a major hepatokine. We aimed to explore the association of bilirubin to fetuin-A (B/F) ratio early in sepsis with severity and outcome in critically ill patients. Based on a previous prospective study, we analyzed data of 90 critically ill patients (52 males, age: 65 ± 15 years, APACHE II: 24 ± 7 and SOFA: 10 ± 3) with sepsis. Bilirubin and fetuin-A increased during the first week of sepsis, (median (IQR) 0.45 (0.32-1) vs 0.55 (0.29-0.78) mg/dL, p = 0.03 and 302 (248-336) vs 358 (307-399) μg/mL, p < 0.001, respectively) while the B/F ratio did not change significantly. However, the B/F ratio at baseline and one week later was significantly higher in patients with septic shock (N = 38) and nonsurvivors (N = 28) compared to patients with sepsis (N = 52) and survivors (N = 62), respectively. The B/F ratio was positively associated with severity scores and outperformed bilirubin as a predictor of mortality in ROC curve analysis (AUC 0.78 (0.69-0.88), p < 0.001 and 0.69 (0.57-0.8), p = 0.003 respectively). The B/F ratio may be a promising sepsis biomarker with possible predictive value in critically ill patients.

The aim of this study was to evaluate hyperferritinemia could be a predicting factor of mortality in hospitalized patients with coronavirus disease-2019 (COVID-19).A total of 100 hospitalized patients with COVID-19 in intensive care unit (ICU) were enrolled and classified into moderate (The amount of ferritin was significantly higher in critical group compared with moderate and severe groups. The median of ferritin concentration was about three times higher in death group than survival group (1722.25 μg/L vs. 501.90 μg/L,The ferritin measured at admission may serve as an independent factor for predicting in-hospital mortality in patients with COVID-19 in ICU.El objetivo de este estudio fue evaluar si la hiperferritinemia podría ser un factor predictivo de la mortalidad en pacientes hospitalizados con enfermedad por coronavirus de 2019 (COVID-19).Se incluyó un total de 100 pacientes hospitalizados con COVID-19 en la unidad de cuidados intensivos (UCI), clasificándose como grupos moderado (n = 17), grave (n = 40) y crítico (n = 43). Se recopiló la información clínica y de laboratorio, comparándose los niveles de ferritina entre los diferentes grupos. Se evaluó la asociación entre ferritina y mortalidad mediante un análisis de regresión logística. Además, se evaluó la eficacia del valor predictivo utilizando la curva ROCLa cantidad de ferritina fue significativamente superior en el grupo de pacientes críticos en comparación con el grupo de pacientes graves. La media de concentración de ferritina fue cerca de 3 veces superior en el grupo de muerte que en el grupo de supervivientes (1.722,25 μg/L vs. 501,90 μg/L, El valor de ferritina medido durante el ingreso puede servir de factor independiente para prevenir la mortalidad intrahospitalaria en los pacientes de COVID-19 en la UCI.

The translocation of sphingosine kinase 1 (SK1) to the plasma membrane (PM) is crucial in promoting oncogenesis. We have previously proposed that SK1 exists as both a monomer and dimer in equilibrium, although it is unclear whether these species translocate to the PM via the same or different mechanisms. We therefore investigated the structural determinants involved to better understand how translocation might potentially be targeted for therapeutic intervention. We report here that monomeric WT mouse SK1 (GFP-mSK1) translocates to the PM of MCF-7L cells stimulated with carbachol or phorbol 12-myristate 13-acetate, whereas the dimer translocates to the PM in response to sphingosine-1-phosphate; thus, the equilibrium between the monomer and dimer is sensitive to cellular stimulus. In addition, carbachol and phorbol 12-myristate 13-acetate induced translocation of monomeric GFP-mSK1 to lamellipodia, whereas sphingosine-1-phosphate induced translocation of dimeric GFP-mSK1 to filopodia, suggesting that SK1 regulates different cell biological processes dependent on dimerization. GFP-mSK1 mutants designed to modulate dimerization confirmed this difference in localization. Regulation by the C-terminal tail of SK1 was investigated using GFP-mSK1 truncations. Removal of the last five amino acids (PPEEP) prevented translocation of the enzyme to the PM, whereas removal of the last ten amino acids restored translocation. This suggests that the penultimate five amino acids (SRRGP) function as a translocation brake, which can be released by sequestration of the PPEEP sequence. We propose that these determinants alter the arrangement of N-terminal and C-terminal domains in SK1, leading to unique surfaces that promote differential translocation to the PM.

Highlights • BMI was associated with widespread structural differences in cortical thickness, surface area, subcortical gray matter volumes and in white matter estimates of fractional anisotropy and mean diffusivity. • BMI was also associated with altered resting-state functional connectivity and working memory during an EN-back task but, contrary to some extant findings, was not related to reward or inhibitory control (as assessed by the Monetary Incentive Delay task and Stop Signal Task). • Excessive weight gain (i.e., more than 20 pounds in a year) was associated at baseline with thicker cortices, and differences in surface area and white matter in regions associated with attention and appetite control (e.g., insula, parahippocampal gyrus), but no functional associations were observed. • All analyses quantified generalizability to an unseen test set. • These findings suggest that brain structure, resting state and working memory are associated with current weight and that brain structure may have potential as an MRI biomarker to identify children at risk for pathological weight gain., Multimodal neuroimaging assessments were utilized to identify generalizable brain correlates of current body mass index (BMI) and predictors of pathological weight gain (i.e., beyond normative development) one year later. Multimodal data from children enrolled in the Adolescent Brain Cognitive Development Study® at 9-to-10-years-old, consisted of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), resting state (rs), and three task-based functional (f) MRI scans assessing reward processing, inhibitory control, and working memory. Cross-validated elastic-net regression revealed widespread structural associations with BMI (e.g., cortical thickness, surface area, subcortical volume, and DTI), which explained 35% of the variance in the training set and generalized well to the test set (R2 = 0.27). Widespread rsfMRI inter- and intra-network correlations were related to BMI (R2train = 0.21; R2test = 0.14), as were regional activations on the working memory task (R2train = 0.20; (R2test = 0.16). However, reward and inhibitory control tasks were unrelated to BMI. Further, pathological weight gain was predicted by structural features (Area Under the Curve (AUC)train = 0.83; AUCtest = 0.83, p < 0.001), but not by fMRI nor rsfMRI. These results establish generalizable brain correlates of current weight and future pathological weight gain. These results also suggest that sMRI may have particular value for identifying children at risk for pathological weight gain.

Background Chest computed tomography (CT) is a useful tool for the diagnosis of coronavirus disease-2019 (COVID-19), although its exact value for predicting critical illness remains unclear. This study evaluated the efficacy of chest CT to predict disease progression, pulmonary complications, and viral positivity duration. Methods A single-center cohort study was conducted by consecutively including hospitalized patients with confirmed COVID-19. The chest CT patterns were described and a total severity score was calculated. The predictive accuracy of the severity score was evaluated using the receiver operating characteristic analysis, while a Cox proportional hazards regression model was implemented to identify the radiological features that are linked to prolonged duration of viral positivity. Results Overall, 42 patients were included with 10 of them requiring intensive care unit admission. The most common lesions were ground glass opacities (92.9%), consolidation (66.7%), and crazy-paving patterns (61.9%). The total severity score significantly correlated with inflammatory and respiratory distress markers, as well as with admission CURB-65 and PSI/PORT scores. It was estimated to predict critical illness with a sensitivity and specificity of 75% and 70%, respectively. Time-to-event analysis indicated that patients without ground-glass opacities presented significantly shorter median viral positivity (16 vs. 27 days). Conclusions Chest CT severity score positively correlates with markers of COVID-19 severity and presents promising efficacy in predicting critical illness. It is suggested that ground-glass opacities are linked to prolonged viral positivity. Further studies should confirm the efficacy of the severity score and elucidate the long-term pulmonary effects of COVID-19.

Background The serum Krebs von den Lungen-6 (KL-6) level is a predictive factor for acute respiratory distress syndrome (ARDS). The development of ARDS has been reported in patients with coronavirus disease 2019 (COVID-19). This study aimed to determine whether serum KL-6 levels are associated with mortality and severity in patients with COVID-19. Methods Among 361 Japanese patients with COVID-19 who were hospitalized at Kanagawa Cardiovascular and Respiratory Center between February 2020 and December 2020, 356 patients with data on serum KL-6 levels were enrolled and their medical records were retrospectively analyzed. Results A negative correlation was observed between KL-6 levels and the ratio of the arterial partial pressure of oxygen to the fraction of inspired oxygen on admission. The KL-6 levels on admission and the maximal KL-6 levels were higher in patients with severe disease (n = 60) than in those with nonsevere disease (n = 296). Furthermore, the maximal KL-6 levels were higher in nonsurvivors (n = 6) than in survivors (n = 350). In nonsurvivors, the KL-6 levels increased as the disease progressed. The optimal cutoff value of the maximal KL-6 level for discriminating between survivors and nonsurvivors was 684 U/mL, with a sensitivity of 83.3%, a specificity of 90.5%, and an area under the curve of 0.89. Conclusions The serum KL-6 level was associated with disease severity. Patients with KL-6 levels ≥684 U/mL had a significantly poorer outcome than those with KL-6 levels

Purpose As of August 30th, there were in total 25.1 million confirmed cases and 845 thousand deaths caused by coronavirus disease of 2019 (COVID-19) worldwide. With overwhelming demands on medical resources, patient stratification based on their risks is essential. In this multi-center study, we built prognosis models to predict severity outcomes, combining patients’ electronic health records (EHR), which included vital signs and laboratory data, with deep learning- and CT-based severity prediction. Method We first developed a CT segmentation network using datasets from multiple institutions worldwide. Two biomarkers were extracted from the CT images: total opacity ratio (TOR) and consolidation ratio (CR). After obtaining TOR and CR, further prognosis analysis was conducted on datasets from INSTITUTE-1, INSTITUTE-2 and INSTITUTE-3. For each data cohort, generalized linear model (GLM) was applied for prognosis prediction. Results For the deep learning model, the correlation coefficient of the network prediction and manual segmentation was 0.755, 0.919, and 0.824 for the three cohorts, respectively. The AUC (95 % CI) of the final prognosis models was 0.85(0.77,0.92), 0.93(0.87,0.98), and 0.86(0.75,0.94) for INSTITUTE-1, INSTITUTE-2 and INSTITUTE-3 cohorts, respectively. Either TOR or CR exist in all three final prognosis models. Age, white blood cell (WBC), and platelet (PLT) were chosen predictors in two cohorts. Oxygen saturation (SpO2) was a chosen predictor in one cohort. Conclusion The developed deep learning method can segment lung infection regions. Prognosis results indicated that age, SpO2, CT biomarkers, PLT, and WBC were the most important prognostic predictors of COVID-19 in our prognosis model.

Graphical abstract, Due to the unforeseen turn of events, our world has undergone another global pandemic from a highly contagious novel coronavirus named COVID-19. The novel virus inflames the lungs similarly to Pneumonia, making it challenging to diagnose. Currently, the common standard to diagnose the virus's presence from an individual is using a molecular real-time Reverse-Transcription Polymerase Chain Reaction (rRT-PCR) test from fluids acquired through nasal swabs. Such a test is difficult to acquire in most underdeveloped countries with a few experts that can perform the test. As a substitute, the widely available Chest X-Ray (CXR) became an alternative to rule out the virus. However, such a method does not come easy as the virus still possesses unknown characteristics that even experienced radiologists and other medical experts find difficult to diagnose through CXRs. Several studies have recently used computer-aided methods to automate and improve such diagnosis of CXRs through Artificial Intelligence (AI) based on computer vision and Deep Convolutional Neural Networks (DCNN), which some require heavy processing costs and other tedious methods to produce. Therefore, this work proposed the Fused-DenseNet-Tiny, a lightweight DCNN model based on a densely connected neural network (DenseNet) truncated and concatenated. The model trained to learn CXR features based on transfer learning, partial layer freezing, and feature fusion. Upon evaluation, the proposed model achieved a remarkable 97.99 % accuracy, with only 1.2 million parameters and a shorter end-to-end structure. It has also shown better performance than some existing studies and other massive state-of-the-art models that diagnosed COVID-19 from CXRs.

Background: Early diagnosis is crucial for patients with pancreatic ductal adenocarcinoma (PDAC). The AXL receptor tyrosine kinase is proteolytically processed releasing a soluble form (sAXL) into the blood stream. Here we explore the use of sAXL as a biomarker for PDAC. Methods: AXL was analysed by immunohistochemistry in human pancreatic tissue samples. RNA expression analysis was performed using TCGA/GTEx databases. The plasma concentrations of sAXL, its ligand GAS6, and CA19-9 were studied in two independent cohorts, the HMar cohort (n = 59) and the HClinic cohort (n = 142), including healthy controls, chronic pancreatitis (CP) or PDAC patients, and in a familial PDAC cohort (n = 68). AXL expression and sAXL release were studied in PDAC cell lines and murine models. Findings: AXL is increased in PDAC and precursor lesions as compared to CP or controls. sAXL determined in plasma from two independent cohorts was significantly increased in the PDAC group as compared to healthy controls or CP patients. Patients with high levels of AXL have a lower overall survival. ROC analysis of the plasma levels of sAXL, GAS6, or CA19-9 in our cohorts revealed that sAXL outperformed CA19-9 for discriminating between CP and PDAC. Using both sAXL and CA19-9 increased the diagnostic value. These results were validated in murine models, showing increased sAXL specifically in animals developing PDAC but not those with precursor lesions or acinar tumours., This work was supported by grants from the Spanish Ministry of Science and Innovation (MICINN)/ Instituto de Salud Carlos III (ISCIII)-European Regional Development Fund (ERDF) (PI20/00625) and the “Generalitat de Catalunya” (2017/SGR/225) to PN; grants from the MICINN (Project# RTI2018-095672-BI00) to AM and PGdF; grant from the MICINN/ ISCIII-FEDER (PI20/01696) to MG and grant from the MICINN/ ISCIII-FEDER (PI18/01034) to AC. We also acknowledge grants from the Instituto de Salud Carlos III (ISCIII)/ERDF(PT20/00023) and the "Xarxa de Bancs de tumours” sponsored by Pla Director d'Oncologia de Catalunya (XBTC). PN’s lab is part of Redes de investigacion (Enfermedades Metabolicas y Cancer RED2018-102799-T), a project run by MINECO. CIBEREHD is funded by Instituto de Salud Carlos III.

Highlights • Focal cervical stenosis causes dynamic alterations across the entire cervical cord. • Spinal cord tissue becomes object of stretching and compressive effects. • Studying spinal cord motion provides information beyond anatomical imaging. • Standardized data processing is the key to valid analysis of spinal cord motion., Background Focally increased spinal cord motion at the level of cervical spinal stenosis has been revealed by phase-contrast MRI (PC-MRI). Objective To investigate spinal cord motion among patients suffering of degenerative cervical myelopathy (DCM) across the entire cervical spine applying automated segmentation and standardized PC-MRI post-processing protocols. Methods Prospective, matched-pair controlled trial on 29 patients with stenosis at C5/C6. MRI-protocol covering all cervical segments: 3D T2-SPACE, prospectively ECG-triggered sagittal PC-MRI. Segmentation by trained 3D hierarchical deep convolutional neural network and data processing were conducted via in-house software pipeline. Parameters per segment: maximum velocity, peak-to-peak (PTP)-amplitude, total displacement, PTP-amplitudeHB (PTP-amplitude per duration of heartbeat), and, for characterization of intraindividual alterations, the PTP-amplitude index between the cervical segments C3/C4–C7/T1 and C2/C3. Results Spinal cord motion was increased at C4/C5, C5/C6 and C6/C7 among patients (all parameters, p

Objective - To validate a novel artificial-intelligence electrocardiogram algorithm (AI-ECG) to detect left ventricular systolic dysfunction (LVSD) in an external population. Background - LVSD, even when asymptomatic, confers increased morbidity and mortality. We recently derived AI-ECG to detect LVSD using ECGs based on a large sample of patients treated at the Mayo Clinic. Methods - We performed an external validation study with subjects from the Know Your Heart Study, a cross-sectional study of adults aged 35–69 years residing in two cities in Russia, who had undergone both ECG and transthoracic echocardiography. LVSD was defined as left ventricular ejection fraction ≤ 35%. We assessed the performance of the AI-ECG to identify LVSD in this distinct patient population. Results - Among 4277 subjects in this external population-based validation study, 0.6% had LVSD (compared to 7.8% of the original clinical derivation study). The overall performance of the AI-ECG to detect LVSD was robust with an area under the receiver operating curve of 0.82. When using the LVSD probability cut-off of 0.256 from the original derivation study, the sensitivity, specificity, and accuracy in this population were 26.9%, 97.4%, 97.0%, respectively. Other probability cut-offs were analysed for different sensitivity values. Conclusions - The AI-ECG detected LVSD with robust test performance in a population that was very different from that used to develop the algorithm. Population-specific cut-offs may be necessary for clinical implementation. Differences in population characteristics, ECG and echocardiographic data quality may affect test performance.

Objectives To find plasma biomarkers prognostic of type 2 diabetes, which could also inform on pancreatic β-cell deregulations or defects in the function of insulin target tissues. Methods We conducted a systems biology approach to characterize the plasma lipidomes of C57Bl/6J, DBA/2J, and BALB/cJ mice under different nutritional conditions, as well as their pancreatic islet and liver transcriptomes. We searched for correlations between plasma lipids and tissue gene expression modules. Results We identified strong correlation between plasma triacylglycerols (TAGs) and islet gene modules that comprise key regulators of glucose- and lipid-regulated insulin secretion and of the insulin signaling pathway, the two top hits were Gck and Abhd6 for negative and positive correlations, respectively. Correlations were also found between sphingomyelins and islet gene modules that overlapped in part with the gene modules correlated with TAGs. In the liver, the gene module most strongly correlated with plasma TAGs was enriched in mRNAs encoding fatty acid and carnitine transporters as well as multiple enzymes of the β-oxidation pathway. In humans, plasma TAGs also correlated with the expression of several of the same key regulators of insulin secretion and the insulin signaling pathway identified in mice. This cross-species comparative analysis further led to the identification of PITPNC1 as a candidate regulator of glucose-stimulated insulin secretion. Conclusion TAGs emerge as biomarkers of a liver-to-β-cell axis that links hepatic β-oxidation to β-cell functional mass and insulin secretion., Highlights • Plasma triacylglycerols correlated with genes controlling β-cell mass and function. • Plasma triacylglycerols correlated with genes controlling liver β-oxidation. • In humans, triacylglycerols also correlated with key regulators of insulin secretion. • Mouse and human data identified PITPNC1 as a candidate regulator of insulin secretion. • Triacylglycerols are biomarkers of the liver-to-β-cell axis and β-cell function.

Highlights • A high platelet-to-lymphocyte ratio (PLR; >124) before curative surgical resection was found to be associated with reduced disease-free survival (DFS) in non-metastatic colon cancer patients. • A high PLR was predominant among patients with circulating tumor microemboli (CTM). • This prospective study revealed a mechanism of interaction between circulating tumor cells (CTCs) and other blood components, and implicated platelets in CTC survival. • The present findings support the use of blood biomarkers to better identify and follow high-risk colon cancer patients., Colorectal cancer is a common and often deadly cancer. Circulating tumor cells (CTCs) have been implicated as a potentially valuable prognosis factor. The detection of circulating tumor microemboli (CTM) and of simple blood component parameters that reflect inflammatory status, such as the platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR), may provide information about tumor progression. The aim of this study was to explore the importance of CTCs, CTM, PLR, and NLR prospectively in non-metastatic colon cancer progression. CTCs were enriched using ISETⓇ (Isolation by SizE of Tumor cells) and identified by immunocytochemical exclusion of leukocytes. We evaluated CTCs and blood cell parameters in a cohort of 69 stage I–III colon cancer patients (52.2% men; median age, 61 years; age range, 19–87 years) at a baseline timepoint prior to resection surgery. The median of CTC levels at baseline was 20 cells/8 mL (0–94) and higher levels were associated with CTM presence (p = 0.02). CTM were found in 18 (26.1%) patients. Of 18 stage I patients, 33.3% had CTM and of 51 stages II or III patients, 13.7% had CTM (p = 0.08). Patients with a high PLR (>124) were mostly (75.6%) diagnosed with high-risk stages II/III cancer (stages I/low-risk II, 24.4%; p = 0.014). All 8 patients that had disease recurrence during follow-up had a high PLR (p = 0.02 vs. low PLR). NLR was not significantly associated with disease stage or recurrence. The present results indicate that CTCs and PLR analyses may be clinically useful for colon cancer management and risk stratification.