Preoperatively predicting human epidermal growth factor receptor 2-low expression in breast cancer using neural network model based on multiparameter magnetic resonance imaging.

Background: Preoperative prediction of human epidermal growth factor receptor 2 (HER2)-low expression using magnetic resonance imaging (MRI) can enhance the selection of clinical treatment strategies and enhance patient outcomes. Herein, we investigated the value of a neural network model constructed with multiparametric MRI in diagnosing HER2-low breast cancer.

Methods: This retrospective study involved two different centers.

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.

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.

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.

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.

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.

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.

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.

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.

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

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).

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.

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.

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.

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.

[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.