Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma: Machine learning model based on contrast-enhanced computed tomography.

BACKGROUND: Recently, vessels encapsulating tumor clusters (VETC) was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner, and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma (HCC). AIM: To develop and validate a preoperative nomogram using contrast-enhanced computed tomography (CECT) to predict the presence of VETC+ in HCC. METHODS: We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers. Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase. Radiomics features, essential for identifying VETC+ HCC, were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set. The model's performance was validated on two separate test sets. Receiver operating characteristic (ROC) analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets. The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features. ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features, the radiomics features and the radiomics nomogram. RESULTS: The study included 190 individuals from two independent centers, with the majority being male (81%) and a median age of 57 years (interquartile range: 51-66). The area under the curve (AUC) for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825, 0.788, and 0.680 in the training set and the two test sets. A total of 13 features were selected to construct the Rad-score. The nomogram, combining clinical-radiological and combined radiomics features could accurately predict VETC+ in all three sets, with AUC values of 0.859, 0.848 and 0.757. Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models. CONCLUSION: This study demonstrates the potential utility of a CECT-based radiomics nomogram, incorporating clinical-radiological features and combined radiomics features, in the identification of VETC+ HCC.

Mycobacterium vaccae alleviates allergic airway inflammation and airway hyper-responsiveness in asthmatic mice by altering intestinal microbiota.

Host immunity can influence the composition of the gut microbiota and consequently affect disease progression. Previously, we reported that a Mycobacterium vaccae vaccine could ameliorate allergic inflammation in asthmatic mice by regulating inflammatory immune processes. Here, we investigated the anti-inflammatory effects of M. vaccae on allergic asthma via gut microbiota modulation. An ovalbumin (OVA)-induced asthmatic murine model was established and treated with M. vaccae. Gut microbiota profiles were determined in 18 BALB/c mice using 16S rDNA gene sequencing and metabolomic profiling was performed using liquid chromatography quadrupole time-of-flight mass spectrometry. Mycobacterium vaccae alleviated airway hyper-reactivity and inflammatory infiltration in mice with OVA-induced allergic asthma. The microbiota of asthmatic mice is disrupted and that this can be reversed with M. vaccae. Additionally, a total of 24 differential metabolites were screened, and the abundance of PI(14:1(9Z)/18:0), a glycerophospholipid, was found to be correlated with macrophage numbers (r = 0.52, p = 0.039). These metabolites may affect chemokine (such as macrophage chemoattractant protein-1) concentrations in the serum, and ultimately affect pulmonary macrophage recruitment. Our data demonstrated that M. vaccae might alleviate airway inflammation and hyper-responsiveness in asthmatic mice by reversing imbalances in gut microbiota. These novel mechanistic insights are expected to pave the way for novel asthma therapeutic strategies.

Perfusion parameters of triphasic computed tomography hold preoperative prediction value for microvascular invasion in hepatocellular carcinoma.

The purpose of this study was to evaluate perfusion parameters of triphasic computed tomography (CT) scans in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). All patients were pathologically diagnosed as HCC and underwent triple-phase enhanced CT imaging, which was used to calculate the blood perfusion parameters of hepatic arterial supply perfusion (HAP), portal vein blood supply perfusion (PVP), hepatic artery perfusion Index (HPI), and arterial enhancement fraction (AEF). Receiver operating characteristic (ROC) curve was used to evaluate the performance. The mean values of PVP(Min), AEF(Min), the difference in PVP, HPI and AEF related parameters, the relative PVP(Min) and AEF(Min) in MVI negative group were significantly higher than those in MVI positive group, while for the difference in HPI(Max), the relative HPI(Max) and AEF(Max), the value of MVI positive group significantly higher than that of negative group. The combination of PVP, HPI and AEF had the highest diagnostic efficacy. The two parameters related to HPI had the highest sensitivity, while the combination of PVP related parameters had higher specificity. A combination of perfusion parameters in patients with HCC derived from traditional triphasic CT scans can be used as a preoperative biomarker for predicting MVI.

Functional Law of Large Numbers and PDEs for Epidemic Models with Infection-Age Dependent Infectivity.

We study epidemic models where the infectivity of each individual is a random function of the infection age (the elapsed time since infection). To describe the epidemic evolution dynamics, we use a stochastic process that tracks the number of individuals at each time that have been infected for less than or equal to a certain amount of time, together with the aggregate infectivity process. We establish the functional law of large numbers (FLLN) for the stochastic processes that describe the epidemic dynamics. The limits are described by a set of deterministic Volterra-type integral equations, which has a further characterization using PDEs under some regularity conditions. The solutions are characterized with boundary conditions that are given by a system of Volterra equations. We also characterize the equilibrium points for the PDEs in the SIS model with infection-age dependent infectivity. To establish the FLLNs, we employ a useful criterion for weak convergence for the two-parameter processes together with useful representations for the relevant processes via Poisson random measures.

Value of perfusion parameters histogram analysis of triphasic CT in differentiating intrahepatic mass forming cholangiocarcinoma from hepatocellular carcinoma.

We aim to gain further insight into identifying differential perfusion parameters and corresponding histogram parameters of intrahepatic mass-forming cholangiocarcinoma (IMCC) from hepatocellular carcinomas (HCCs) on triphasic computed tomography (CT) scans. 90 patients with pathologically confirmed HCCs (n = 54) and IMCCs (n = 36) who underwent triple-phase enhanced CT imaging were included. Quantitative analysis of CT images derived from triphasic CT scans were evaluated to generate liver perfusion and histogram parameters. The differential performances, including the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity were assessed. The mean value, and all thepercentiles of the arterial enhancement fraction (AEF) were significantly higher in HCCs than in IMCCs. The difference in hepatic arterial blood supply perfusion (HAP) and AEF (ΔHAP = HAPtumor - HAPliver, ΔAEF = AEFtumor - AEFliver) for the mean perfusion parameters and all percentile parameters between tumor and peripheral normal liver were significantly higher in HCCs than in IMCCs. The relative AEF (rAEF = ΔAEF/AEFliver), including the mean value and all corresponding percentile parameters were statistically significant between HCCs and IMCCs. The 10th percentiles of the ΔAEF and rAEF had the highest AUC of 0.788 for differentiating IMCC from HCC, with sensitivities and specificities of 87.0%, 83.3%, and 61.8%, 64.7%, respectively. Among all parameters, the mean value of ∆AEF, the 75th percentiles of ∆AEF and rAEF, and the 25th percentile of HFtumor exhibited the highest sensitivities of 94.4%, while the 50th percentile of rAEF had the highest specificity of 82.4%. AEF (including ΔAEF and rAEF) and the corresponding histogram parameters derived from triphasic CT scans provided useful value and facilitated the accurate discrimination between IMCCs and HCCs.

Impact of novel deep learning image reconstruction algorithm on diagnosis of contrast-enhanced liver computed tomography imaging: Comparing to adaptive statistical iterative reconstruction algorithm.

OBJECTIVE: To assess clinical application of applying deep learning image reconstruction (DLIR) algorithm to contrast-enhanced portal venous phase liver computed tomography (CT) for improving image quality and lesions detection rate compared with using adaptive statistical iterative reconstruction (ASIR-V) algorithm under routine dose. METHODS: The raw data from 42 consecutive patients who underwent contrast-enhanced portal venous phase liver CT were reconstructed using three strength levels of DLIRs (low [DL-L]; medium [DL-M]; high [DL-H]) and two levels of ASIR-V (30%[AV-30]; 70%[AV-70]). Objective image parameters, including noise, signal-to-noise (SNR), and the contrast-to-noise ratio (CNR) relative to muscle, as well as subjective parameters, including noise, artifact, hepatic vein-clarity, index lesion-clarity, and overall scores were compared pairwise. For the lesions detection rate, the five reconstructions in patients who underwent subsequent contrast-enhanced magnetic resonance imaging (MRI) examinations were compared. RESULTS: For objective parameters, DL-H exhibited superior image quality of lower noise and higher SNR than AV-30 and AV-70 (all P < 0.05). CNR was not statistically different between AV-70, DL-M, and DL-H (all P > 0.05). In both objective and subjective parameters, only image noise was statistically reduced as the strength of DLIR increased compared with ASIR-V (all P < 0.05). Regarding the lesions detection rate, a total of 45 lesions were detected by MRI examination and all five reconstructions exhibited similar lesion-detection rate (25/45, 55.6%). CONCLUSION: Compared with AV-30 and AV 70, DLIR leads to better image quality with equal lesion detection rate for liver CT imaging under routine dose.

Estimating the state of the COVID-19 epidemic in France using a model with memory.

In this paper, we use a deterministic epidemic model with memory to estimate the state of the COVID-19 epidemic in France, from early March until mid-December 2020. Our model is in the SEIR class, which means that when a susceptible individual (S) becomes infected, he/she is first exposed (E), i.e. not yet contagious. Then he/she becomes infectious (I) for a certain length of time, during which he/she may infect susceptible individuals around him/her, and finally becomes removed (R), that is, either immune or dead. The specificity of our model is that it assumes a very general probability distribution for the pair of exposed and infectious periods. The law of large numbers limit of such a model is a model with memory (the future evolution of the model depends not only upon its present state, but also upon its past). We present theoretical results linking the (unobserved) parameters of the model to various quantities which are more easily measured during the early stages of an epidemic. We then apply these results to estimate the state of the COVID-19 epidemic in France, using available information on the infection fatality ratio and on the distribution of the exposed and infectious periods. Using the hospital data published daily by Santé Publique France, we gather some information on the delay between infection and hospital admission, intensive care unit (ICU) admission and hospital deaths, and on the proportion of people who have been infected up to the end of 2020.

Value of perfusion parameters and histogram analysis of triphasic computed tomography in pre-operative prediction of histological grade of hepatocellular carcinoma.

BACKGROUND: Pre-operative non-invasive histological evaluation of hepatocellular carcinoma (HCC) remains a challenge. Tumor perfusion is significantly associated with the development and aggressiveness of HCC. The purpose of the study was to evaluate the clinical value of quantitative liver perfusion parameters and corresponding histogram parameters derived from traditional triphasic enhanced computed tomography (CT) scans in predicting histological grade of HCC. METHODS: Totally, 52 patients with HCC were enrolled in this retrospective study and underwent triple-phase enhanced CT imaging. The blood perfusion parameters were derived from triple-phase CT scans. The relationship of liver perfusion parameters and corresponding histogram parameters with the histological grade of HCC was analyzed. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal ability of the parameters to predict the tumor histological grade. RESULTS: The variance of arterial enhancement fraction (AEF) was significantly higher in HCCs without poorly differentiated components (NP-HCCs) than in HCCs with poorly differentiated components (P-HCCs). The difference in hepatic blood flow (HF) between total tumor and total liver flow (ΔHF = HFtumor - HFliver) and relative flow (rHF = ΔHF/HFliver) were significantly higher in NP-HCCs than in P-HCCs. The difference in portal vein blood supply perfusion (PVP) between tumor and liver tissue (ΔPVP) and the ΔPVP/liver PVP ratio (rPVP) were significantly higher in patients with NP-HCCs than in patients with P-HCCs. The area under ROC (AUC) of ΔPVP and rPVP were both 0.697 with a high sensitivity of 84.2% and specificity of only 56.2%. The ΔHF and rHF had a higher specificity of 87.5% with an AUC of 0.681 and 0.673, respectively. The combination of rHF and rPVP showed the highest AUC of 0.732 with a sensitivity of 57.9% and specificity of 93.8%. The combined parameter of ΔHF and rPVP, rHF and rPVP had the highest positive predictive value of 0.903, and that of rPVP and ΔPVP had the highest negative predictive value of 0.781. CONCLUSION: Liver perfusion parameters and corresponding histogram parameters (including ΔHF, rHF, ΔPVP, rPVP, and AEFvariance) in patients with HCC derived from traditional triphasic CT scans may be helpful to non-invasively and pre-operatively predict the degree of the differentiation of HCC.

Tumor attenuation and quantitative analysis of perfusion parameters derived from tri-phasic CT scans in hepatocellular carcinoma: Relationship with histological grade.

ABSTRACT: The aim of the current study was to explore the value of tumor attenuation and quantitative analysis of perfusion parameters obtained from traditional tri-phasic CT scans in grading hepatocellular carcinoma (HCC).Totally 39 patients (42 lesion samples) with pathologically confirmed HCC who underwent tri-phasic CT scans were enrolled. HCC lesions were divided into non-poorly differentiated HCC (NP-HCC; n = 31) and poorly differentiated HCC (pHCC; n = 11). All lesions were divided into 5 groups according to the attenuation on different CT enhancement phase. The values of tumor attenuation on different scanning phases were measured. The following parameters were calculated: arterial enhancement fraction (AEF), portal venous supply coefficient (PVC), and hepatic arterial supply coefficient (HAC). The relationship of perfusion parameters with the histological grade of HCC was analyzed. Receiver operating characteristic curves were generated.No significant correlation was observed between the perfusion parameters and tumor grading. Only HAC showed a non-significant trend in different grades of HCC (pHCC < NP-HCC; P = .07). The pHCC cases had significantly decreased values of tumor attenuation on the unenhanced phase (TAu), tumor attenuation on the portal phase portal phase (TAp), and equilibrium phase (TAe) (P < .01). The difference of tumor attenuation between the portal phase and the unenhanced phase (TAp-TAu) of the pHCC cases was decreased than that of the NP-HCC cases (P < .01), whereas the difference of attenuation between the equilibrium phase and portal phase (TAe-TAp) was significantly higher in the pHCC cases than that in the NP-HCC cases (P < .01). TAe-TAp had the highest area under the curve. The number of tumor enhancement pattern in Group 5 of HCCs with a diameter of 3 cm or more was significantly more than that of HCCs with a diameter of less than 3 cm or with other different enhancement patterns (P < .01).Histological HCC grading cannot be predicted by the perfusion parameters derived from traditional tri-phasic CT scans, whereas the tumor attenuation on different phases and the tumor attenuation differences among different phases, especially the mean value of TAe-TAp, might be useful for non-invasive prediction on the degree of HCC differentiation.

Heterogeneity analysis of triphasic CT scan perfusion parameters in differential diagnosis of hepatocellular carcinoma and hemangioma.

This study is to investigate quantitative measures and heterogeneity of perfusion parameters in the differential diagnosis of hepatocellular carcinoma (HCC) and hemangioma.In total, 32 HCC and 44 hemangioma (types 1, 2, and 3) cases were included in this retrospective study. Hepatic artery coefficient (HAC), portal vein coefficient (PVC), and arterial enhancement fraction (AEF) were calculated. Tumor heterogeneity was analyzed. Perfusion parameters and corresponding percentiles were compared between the HCC and hemangioma (especially atypical hemangioma) cases, as well as between the substantial lesion part and surrounding normal tissue.The mean value, and the 10th, 50th, 75th, and 90th percentiles of PVC were significantly lower in the HCC cases than the types 1 and 2 hemangioma cases (P < .01). Moreover, the 90th percentile PVC in the HCC cases was also significantly lower than the type 3 hemangioma case (P < .01), while the mean value, and all the percentiles of AEF in the HCC cases were higher than the types 2 and 3 hemangioma cases (P < .01). The 10th percentile HAC in the HCC cases was higher than the type 2 hemangioma cases (P < .05). The mean value, and the 10th and 50th percentile HAC in the HCC cases were higher than the type 3 hemangioma case (P < .05). However, there was no statistically significant difference in HAC between the HCC and type 1 hemangioma cases (P > .05).Quantitative measurement of perfusion parameters and heterogeneity analysis show significance differences in the early detection and differential diagnosis of HCC and hemangioma cases, which might contribute to increasing the diagnostic accuracy.

CT virtual endoscopy for analyzing variations in the hepatic portal vein.

PURPOSE: To evaluate the value of CT virtual endoscopy (CTVE) for accurately distinguishing varying types of portal veins (PVs). MATERIALS AND METHODS: From 526 consecutive patients whose hepatic portal vein was well visualized, patients who were considered to have trifurcation of the main portal vein (MPV) or right portal vein (RPV) on volume rendering (VR) and maximum intensity projection (MIP) imaging were chosen for the analysis. Two radiologists evaluated the PV anatomy of these patients and re-classified the types of PV variation using the CTVE technique. The Wilcoxon rank sum test was used to calculate differences in age between males and females. RESULTS: Thirty-two patients (20 males, 12 females; age range 21-68 years; mean age 43 years) were considered to have trifurcation of the MPV (15) or RPV (17) on VR and MIP imaging. Fifteen patients in total had a trifurcation confirmed by CTVE (6 patients were proven to have an MPV trifurcation by CTVE, and 9 were confirmed to have a RPV trifurcation). CONCLUSIONS: CTVE can differentiate PV variations that cannot be identified accurately on MIP and VR.

Ubiquitin-activating enzyme E1 inhibitor PYR41 attenuates angiotensin II-induced activation of dendritic cells via the IκBa/NF-κB and MKP1/ERK/STAT1 pathways.

The activation of dendritic cells (DCs) is necessary to initiate immune responses. Angiotensin II (Ang II) can enhance the maturation and activation of DCs, but the mechanisms are still unclear. Ubiquitin-activating enzyme (E1/Uba1) is the common first step in ubiquitylation, which decides whether or not the modified protein is ultimately degraded by the proteasome. This study aimed to investigate the role of E1 in Ang II-induced activation of DCs and the underlying mechanisms. First, we showed that Ang II stimulation significantly up-regulated E1 expression in DCs. Moreover, Ang II treatment markedly induced phenotypic maturation, the secretion of cytokines and the immunostimulatory capacity of DCs. In contrast, inhibition of E1 by a small molecule inhibitor, 4 [4-(5-nitro-furan-2-ylmethylene)-3, 5-dioxo-pyrazolidin-1-yl]-benzoic acid ethyl ester (PYR41), markedly attenuated these effects. Mechanistically, PYR41 treatment markedly decreased K63-linked ubiquitination of tumour necrosis factor receptor-associated factor 6 and nuclear factor-κB essential modulator, inhibited proteasomal degradation of nuclear factor-κB inhibitor α and mitogen-activated protein kinase phosphatase 1 thereby resulting in activation of nuclear factor-κB, extracellular signal-regulated kinase 1/2 and signal transducer and activator of transcription 1 signalling pathways in DCs induced by Ang II. Taken together, our results demonstrate a novel role of E1 in Ang II-induced activation of DCs, and inhibition of E1 activity might be a potential therapeutic target for DC-mediated autoimmune diseases.

Meta-analysis of the association of HLA-DRB1 with rheumatoid arthritis in Chinese populations.

BACKGROUND: Individual studies have reported different results regarding the association of HLA alleles with RA in Chinese populations. This study was performed to systematically summarize results on the association of HLA-DRB1 with rheumatoid arthritis (RA) in China. METHODS: We examined the case-control studies concerned about the relationship between HLA-DRB1 and RA and differences of clinical and laboratory parameters between the HLA-DR4 (DR4)+ and DR4- in RA patients in Chinese populations. Odds ratios (ORs) and weighted mean difference (WMD) with corresponding 95% confidence intervals (CI) was used to describe the relationship. RESULTS: 22 studies with 1690 cases and 1793 controls were included. Chinese populations with RA had significantly higher frequencies of HLA-DRB1*04, *0401, *0404, *0405 and *0410 than controls (ORDRB1*04 =4.19, 95% CI =3.44-5.11, p<0.00001; ORDRB1*0401 =2.53, 95% CI =1.54-4.16, p=0.0003; ORDRB1*0404 =2.28, 95% CI =1.28-4.06, p=0.005; ORDRB1*0405=3.71, 95% CI =2.52-5.45, p<0.00001; ORDRB1*0410 =2.99, 95% CI =1.25-7.14, p=0.01 respectively). As to laboratory parameters, Erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), Rheumatoid factor (RF), Anti-cyclic citrullinated peptide antibodies (Anti-CCP ) in patients with DR4+ were higher than patients with DR4- (WMD=0.26, 95% CI =0.15-0.37, p<0.00001; WMD = 0.26, 95% CI =0.12-0.41, p=0.0005; WMD = 0.44, 95% CI =0.23-0.65, p<0.00001; WMD = 0.58, 95% CI =0.24-0.91, p=0.0007 respectively). As to clinical features, there was no difference in duration of morning stiffness, number of swollen joints, number of joint tenderness, X-ray phases and joint function between the DR4+ and DR4- in RA patients. CONCLUSIONS: It was found that HLA-DRB1*04, *0401, *0404, *0405 and *0410 are risk factors for RA in Chinese populations. ESR, CRP, RF, Anti-CCP are different between the DR4+ and DR4- in RA patients in Chinese populations, while there's no difference for indexes of clinical features.

[Expression and clinical significance of COX-2 and BCL-2 in distal transitional mucosa adjacent to rectal carcinoma].

OBJECTIVE: To investigate the expression of COX-2 and BCL-2 in transitional mucosa adjacent to rectal carcinoma, and to determine whether precursor event exists in the transitional mucosa. METHODS: Mucin histochemical method (HID/AB) was used to determine the distal mucosa 2 cm away from rectal carcinoma in 54 patients with rectal cancer. Immunohistochemical method was employed to detect the expression of BCL-2 and COX-2 in the rectal cancer specimen, transitional mucosa (TM), non-transitional mucosa (NTM), and 20 cases of normal rectal mucosa. Student's t-test and Chi-square test were preformed. RESULTS: Nineteen patients with positive TM were found. COX-2 expression was identified in 81.5% of cancer tissue, 21.1% of TM, 17.1% of NTM, and 10.0% in normal mucosa. BCL-2 protein was found in 77.8% of cancer tissue, 21.1% of TM, 22.9% of NTM, and 5.0% of normal mucosa. The expressions of COX-2 and BCL-2 in TM were significantly different from tumor tissue[(0.737±0.895) versus (3.519±1.998), and (0.632±0.955) versus (2.833±1.756), all P<0.01]. However, there were no significant differences between TM and NTM or normal mucosa. CONCLUSIONS: Expressions of COX-2 and BCL-2 are non-specific in the transitional mucosa at the distal rectum. Evidence is not available in TM being precursor lesion.