Dynamic 3D radiomics analysis using artificial intelligence to assess the stage of COVID-19 on CT images.

OBJECTIVE: To develop a dynamic 3D radiomics analysis method using artificial intelligence technique for automatically assessing four disease stages (i.e., early, progressive, peak, and absorption stages) of COVID-19 patients on CT images. METHODS: The dynamic 3D radiomics analysis method was composed of three AI algorithms (the lung segmentation, lesion segmentation, and stage-assessing AI algorithms) that were trained and tested on 313,767 CT images from 520 COVID-19 patients. This proposed method used 3D lung lesion that was segmented by the lung and lesion segmentation algorithms to extract radiomics features, and then combined with clinical metadata to assess the possible stage of COVID-19 patients using stage-assessing algorithm. Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were used to evaluate diagnostic performance. RESULTS: Of 520 patients, 66 patients (mean age, 57 years ± 15 [standard deviation]; 35 women), including 203 CT scans, were tested. The dynamic 3D radiomics analysis method used 30 features, including 27 radiomics features and 3 clinical features to assess the possible disease stage of COVID-19 with an accuracy of 90%. For the prediction of each stage, the AUC of stage 1 was 0.965 (95% CI: 0.934, 0.997), AUC of stage 2 was 0.958 (95% CI: 0.931, 0.984), AUC of stage 3 was 0.998 (95% CI: 0.994, 1.000), and AUC of stage 4 was 0.975 (95% CI: 0.956, 0.994). CONCLUSION: With high diagnostic performance, the dynamic 3D radiomics analysis using artificial intelligence could represent a potential tool for helping hospitals make appropriate resource allocations and follow-up of treatment response. KEY POINTS: • The AI segmentation algorithms were able to accurately segment the lung and lesion of COVID-19 patients of different stages. • The dynamic 3D radiomics analysis method successfully extracted the radiomics features from the 3D lung lesion. • The stage-assessing AI algorithm combining with clinical metadata was able to assess the four stages with an accuracy of 90%, a macro-average AUC of 0.975.

Pearson's patterns correlational of clinical risks at admissions with hospitalization outcomes during initial COVID-19 outbreak.

COVID-19 outbreaks have crushed our healthcare systems, which requires clinical guidance for the healthcare following the outbreaks. We conducted retrospective cohort studies with Pearson's pattern-based analysis of clinical parameters of 248 hospitalized patients with COVID-19. We found that dysregulated neutrophil densities were correlated with hospitalization duration before death (p = 0.000066, r = -0.45 for % neutrophil; p = 0.0001, r = -0.47 for neutrophil count). As such, high neutrophil densities were associated with mortality (p = 4.23 × 10-31 for % neutrophil; p = 4.14 × 10-27 for neutrophil count). These findings were further illustrated by a representative "second week crash" pattern and validated by an independent cohort (p = 5.98 × 10-11 for % neutrophil; p = 1.65 × 10-7 for neutrophil count). By contrast, low aspartate aminotransferase (AST) or lactate dehydrogenase (LDH) levels were correlated with quick recovery (p ≤ 0.00005). Collectively, these correlational at-admission findings may provide healthcare guidance for patients with COVID-19 in the absence of targeted therapy.

Container CT scanner: a solution for modular emergency radiology department during the COVID-19 pandemic.

During the coronavirus disease 2019 (COVID-19) pandemic period, container computed tomography (CT) scanners were developed and used for the first time in China to perform CT examinations for patients with clinically mild to moderate COVID-19 who did not need to be hospitalized for comprehensive treatment, but needed to be isolated in Fangcang shelter hospitals (also known as makeshift hospitals) to receive some supportive treatment. The container CT is a multidetector CT scanner installed within a radiation-protected stand-alone container (a detachable lead shielding room) that is deployed outside the makeshift hospital buildings. The container CT approach provided various medical institutions with the solution not only for rapid CT installation and high adaptability to site environments, but also for significantly minimizing the risk of cross-infection between radiological personnel and patients during CT examination in the pandemic. In this article, we described the typical setup of a container CT and how it worked for chest CT examinations in Wuhan city, the epicenter of COVID-19 outbreak.

Radiology indispensable for tracking COVID-19.

With the rapid spread of COVID-19 worldwide, early detection and efficient isolation of suspected patients are especially important to prevent the transmission. Although nucleic acid testing of SARS-CoV-2 is still the gold standard for diagnosis, there are well-recognized early-detection problems including time-consuming in the diagnosis process, noticeable false-negative rate in the early stage and lacking nucleic acid testing kits in some areas. Therefore, effective and rational applications of imaging technologies are critical in aiding the screen and helping the diagnosis of suspected patients. Currently, chest computed tomography is recommended as the first-line imaging test for detecting COVID-19 pneumonia, which could allow not only early detection of the typical chest manifestations, but also timely estimation of the disease severity and therapeutic effects. In addition, other radiological methods including chest X-ray, magnetic resonance imaging, and positron emission computed tomography also show significant advantages in the detection of COVID-19 pneumonia. This review summarizes the applications of radiology and nuclear medicine in detecting and diagnosing COVID-19. It highlights the importance for these technologies to curb the rapid transmission during the pandemic, considering findings from special groups such as children and pregnant women.

Differential Diagnosis of COVID-19 Pneumonia From Influenza A (H1N1) Pneumonia Using a Model Based on Clinicoradiologic Features.

Objectives: Both coronavirus disease 2019 (COVID-19) pneumonia and influenza A (H1N1) pneumonia are highly contagious diseases. We aimed to characterize initial computed tomography (CT) and clinical features and to develop a model for differentiating COVID-19 pneumonia from H1N1 pneumonia. Methods: In total, we enrolled 291 patients with COVID-19 pneumonia from January 20 to February 13, 2020, and 97 patients with H1N1 pneumonia from May 24, 2009, to January 29, 2010 from two hospitals. Patients were randomly grouped into a primary cohort and a validation cohort using a seven-to-three ratio, and their clinicoradiologic data on admission were compared. The clinicoradiologic features were optimized by the least absolute shrinkage and selection operator (LASSO) logistic regression analysis to generate a model for differential diagnosis. Receiver operating characteristic (ROC) curves were plotted for assessing the performance of the model in the primary and validation cohorts. Results: The COVID-19 pneumonia mainly presented a peripheral distribution pattern (262/291, 90.0%); in contrast, H1N1 pneumonia most commonly presented a peribronchovascular distribution pattern (52/97, 53.6%). In LASSO logistic regression, peripheral distribution patterns, older age, low-grade fever, and slightly elevated aspartate aminotransferase (AST) were associated with COVID-19 pneumonia, whereas, a peribronchovascular distribution pattern, centrilobular nodule or tree-in-bud sign, consolidation, bronchial wall thickening or bronchiectasis, younger age, hyperpyrexia, and a higher level of AST were associated with H1N1 pneumonia. For the primary and validation cohorts, the LASSO model containing above eight clinicoradiologic features yielded an area under curve (AUC) of 0.963 and 0.943, with sensitivity of 89.7 and 86.2%, specificity of 89.7 and 89.7%, and accuracy of 89.7 and 87.1%, respectively. Conclusions: Combination of distribution pattern and category of pulmonary opacity on chest CT with clinical features facilitates the differentiation of COVID-19 pneumonia from H1N1 pneumonia.

Emerging Evidence for Neuropsycho-Consequences of COVID-19.

The pandemic novel coronavirus disease (COVID-19) has become a global concern in which the respiratory system is not the only one involved. Previous researches have presented the common clinical manifestations including respiratory symptoms (i.e., fever and cough), fatigue and myalgia. However, there is limited evidence for neurological and psychological influences of SARS-CoV-2. In this review, we discuss the common neurological manifestations of COVID-19 including acute cerebrovascular disease (i.e., cerebral hemorrhage) and muscle ache. Possible viral transmission to the nervous system may occur via circulation, an upper nasal transcribrial route and/or conjunctival route. Moreover, we cannot ignore the psychological influence on the public, medical staff and confirmed patients. Dealing with public psychological barriers and performing psychological crisis intervention are an important part of public health interventions.

Nonlinear Method to Predict the Distribution of Structurally Diverse Compounds between Blood and Tissue.

In this work, methods for predicting the distribution of compounds between blood and tissue were investigated using nonlinear regression analysis. For the tissue/blood partition coefficient, 282 compounds and 810 activity data for seven tissues were selected. Twenty-four parameters were studied for each state of the compound. A study set with the most compounds and activity data in similar studies was established, and a model with good prediction ability was obtained. A total of 773 data points were randomly divided into two data sets: the training set contained 623 data points (n = 623, r = 0.822, s = 0.438, F = 142.2, and Q = 0.814) and the test set contained 150 data points (n = 150, r = 0.814, and s = 0.334). Furthermore, individual tissue/blood distribution coefficients were also studied in depth to obtain separate models for predicting the distribution coefficient of a drug between blood and a tissue. By applying these models, not only can the tissue/blood distribution coefficient or single tissue/blood distribution coefficient of the seven tissues and organs of the human body be predicted, but the distribution of the drug molecules in different states (neutral, cation, and anion) in the three tissue components can also be predicted.

Resilience of Alzheimer's Disease to COVID-19.

BACKGROUND: Facing the novel coronavirus disease 2019 (COVID-19), most vulnerable individuals are seniors, especially those with comorbidities. More attention needs to been paid to the COVID-19 patients with Alzheimer's disease (AD), which is the top age-related neurodegenerative disease. OBJECTIVE: Since it is unclear whether AD patients are prone to COVID-19 infection and progression to severe stages, we report for the first time a retrospective analysis of the clinical characteristics of AD patients with COVID-19 pneumonia. METHODS: We conducted a retrospective cohort study of the clinical data of 19 AD patients with COVID-19 pneumonia, compared with 23 non-AD COVID-19 patients admitted at the same time to our hospital. Demographic, clinical, laboratory, radiological, and treatment data were collected and analyzed. RESULTS: Between AD patients and non-AD patients with COVID-19 pneumonia, the pneumonia severity was not significantly different. AD patients had a higher clustering onset than non-AD patients. The median duration from symptom onset to hospitalization were shorter in AD patients than non-AD patients, indicating the former were sent to the hospital by their family or from nursing home earlier than the later. The median duration from hospitalization to discharge seemed shorter in AD patients than non-AD patients. Dementia patients seemed less likely to report fatigue. It is noticed that more AD patients might have pericardial effusion than the non-AD patients. CONCLUSION: AD patients with COVID-19 were in milder conditions with a better prognosis than non-AD patients. AD patients who had adequate access to healthcare showed resilience to COVID-19 with shorter hospital stays.

Management of a Parkinson's disease patient with severe COVID-19 pneumonia.

Elderly populations with underlying chronic diseases are more vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and have higher mortality. Parkinson's disease (PD) is a neurodegenerative disease that occurs more often in elderly people. Currently, little is known about whether patients with PD are more susceptible to novel coronavirus disease 2019 (COVID-19) and whether the treatment of PD would affect the management of COVID-19 or vice versa. Here, we report a case of a PD patient with severe COVID-19 pneumonia in Wuhan, China. After diagnosis of COVID-19, this PD patient had worsening of motor symptoms, complicated with acute hypoxemic respiratory failure, urinary tract infection, and acute encephalopathy. In addition to treatment for COVID-19 and urinary tract infection, we adjusted anti-PD medicine by stepwise increasing of dose, resulting in better control of her mobility symptoms and non-motor symptoms.

Proteomic characterization of copper stress response in Elsholtzia splendens roots and leaves.

Elsholtzia splendens is generally considered as a Cu-tolerant and -accumulating plant species, and a candidate for phytoremediation of Cu-contaminated soils. To better understand the Cu tolerance/accumulation mechanisms in E. splendens, proteomic analysis was performed on E. splendens roots and leaves exposed to 100 muM CuSO(4) for 3 and 6 days. After 6 days of treatment, Cu accumulation in roots increased much more than that in leaves. SDS-PAGE analysis showed that the proteins changed more intensively in roots than did in leaves upon Cu stress. Two-dimensional gel electrophoresis (2-DE) and image analyses found that 45 protein spots were significantly changed in roots, but only six protein spots in leaves. The abundance of protein spots mostly showed temporal changes. MALDI-TOF MS and LTQ-ESI-MS/MS were used to identify the differently expressed protein spots. The identified root proteins were involved in various cellular processes such as signal transduction, regulation of transcription and translation, energy metabolism, regulation of redox homeostasis and cell defense. The leaf proteins were mainly degraded fragments of RuBisCo and antioxidative protein. The roles of these proteins in Cu tolerance/accumulation were discussed. The resulting differences in protein expression pattern suggested that redirection of root cellular metabolism and redox homeostasis might be important survival mechanisms of E. splendens upon Cu stress.

TNF-α and IFN-γ synergistically inhibit the repairing ability of mesenchymal stem cells on mice colitis and colon cancer.

BACKGROUND: Mesenchymal stem cells (MSCs) can be efficiently recruited to wound, inflammatory and tumor sites to repair and regenerate tissue. However, its role in colitis and colitis associated colon cancer is still controversial. This study was designed to evaluate the role and mechanisms of inflammatory cytokines-activated-MSCs in mice colitis and colon cancer. METHODS: We selected two well-characterized pro-inflammatory cytokines, tumor necrosis factor-alpha (TNF-α) and interferon-gamma (IFN-γ), to expand the inflammatory microenvironment of MSCs. The severity of colitis and colon cancer was evaluated by measuring colon length, Myeloperoxidase (MPO) activity, Hematoxylin-eosin staining, Western Blot, Immunohistochemistry and Immunofluorescence. These techniques were also performed to analyze the mechanisms of inflammatory cytokines-activated-MSCs in mice colitis and colon cancer. Real-time PCR and Enzyme-linked Immunosorbent Assay (ELISA) were used to measure the secretion of pro-inflammatory factors. RESULTS: We found that the incubation of MSCs with TNF-α and IFN-γ aggravates colitis, where high levels of pro-inflammatory factors, such as interleukin (IL)-17, IL-8, IL-12, IL-1ß, transforming growth factor (TGF)-ß, TNF-α and IFN-γ, were secreted. Furthermore, this phenomenon was associated with the activation of the nuclear factor-kappa-B (NF-κB)/Signal transducer and activator of transcription three (STAT3) pathway. In addition, our study demonstrated that TNF-α and IFN-γ pretreated MSCs synergistically exacerbated mice colon cancer, which was closely associated with angiogenesis. CONCLUSIONS: Taken together, these results indicate that TNF-α and IFN-γ pretreatment effectively inhibited the repair ability of MSCs and accelerated inflammation and tumor progression involving NF-κB/STAT3 pathway and angiogenesis-related factors.

Prediction of distribution of neutral, acidic and basic structurally diverse compounds between blood and brain by the nonlinear methodology.

The methodology for predicting the distribution of compounds between Blood and Brain, i.e. their brain/blood partition coefficients (logBB values), was studied using a nonlinear regression analysis in this work. The equations were established on the basis of the different states (neutral, cationic and anionic) of the compounds distributing into the three dominating composition (lipid, protein and water) of the brain. The equations bear strong fitting and predictive power for the distribution of compounds (total set: n=160, r=0.906, s=0.326; training set: n=139, r=0.908, s=0.320; testing set: n=21, r=0.903, s=0.297), and can describe the distribution of the different states of the compounds in three compositions of brain. The compounds in the dataset contained many different types, such as drug molecules, small structure-simple molecules, carboxylic acids and also alkaloids. Therefore the equations were very useful and instructional for the prediction of the compound distribution into the brain and blood. Finally, the percentages of the amount of a compound in lipid, protein and water in brain were calculated using the model, such subdivision will be very useful in drug research and discovery. By an analysis of the percentages a conclusion can be obtained that a well distributed drug is mainly affected by distribution of lipid and protein.

Mesenchymal stem cells in inflammatory microenvironment potently promote metastatic growth of cholangiocarcinoma via activating Akt/NF-κB signaling by paracrine CCL5.

Our previous work has demonstrated that mesenchymal stem cells (MSCs) could induce metastatic growth of the inflammation-related cholangiocarcinoma (CCA). However, the functional mechanism of MSCs on CCA progression in the early inflammatory microenvironment remained undetermined. Here, we showed that TNF-α and IFN-γ-induced inflammatory microenvironment stimulated the expression of TNF-α, CCL5, IL-6, IDO, and activated the NF-κB signaling with p65 nuclear translocation in MSCs cells. CCA cell lines QBC939 and Mz-chA-1 exposed to the conditioned medium of MSCs after being stimulated by TNF-α and IFN-γ (TI-CM) exhibited enhanced mobility. Moreover, MSCs pre-stimulated by both inflammatory cytokines (TI-MSCs) increased tumor metastasis in vivo. The conditioned medium of TI-MSCs stimulated the transcription of snail, slug, ZEB1 and ZEB2. Next, the expression of CCL5 of TI-MSCs was verified by ELISA, which indicated that MSCs contributed to CCA migration and metastasis in a paracrine fashion. CCA cells treated with TI-CM up-regulated CCA chemokine receptors, especially CCR5; CCL5 neutralizing antibody or CCR5 inhibitor Maraviroc inhibited the effects of MSCs on CCA cells migration. We also found that Akt/NF-κB signaling was activated by CCL5/CCR5 axis, which increased the expression of MMP2, MMP9. Together, these findings suggest that MSCs in tumor inflammatory microenvironment are elicited of CCL5, which activate AKT/NF-κB signaling and lead to metastatic growth of CCA cells.

Involvement of Wnt/ß-catenin signaling in the mesenchymal stem cells promote metastatic growth and chemoresistance of cholangiocarcinoma.

Mesenchymal stem cells (MSCs) are multi-potent progenitor cells with ability to differentiate into multiple lineages, including bone, cartilage, fat, and muscles. Recent research indicates that MSCs can be efficiently recruited to tumor sites, modulating tumor growth and metastasis. However, the underlying molecular mechanisms are not fully understood. Here, we first demonstrated that human umbilical cord-derived mesenchymal stem cells (hUC-MSCs), when mixed with human cholangiocarcinoma cell lines QBC939 in a xenograft tumor model, significantly increased the cancer cells proliferation and metastatic potency. MSCs and their conditioned media (MSC-CM) could improve the drug resistance of tumor when the compound K (CK) as an anti-cancer drug, a major intestinal bacterial metabolite of panaxoside, was administered to xenograft tumor mice. Furthermore, MSCs greatly increased the colony formation and invasion of cholangiocarcinoma cells QBC939 and Mz-ChA-1. Immunochemistry studies of cholangiocarcinoma tissue chips and transplantation tumor from nude mice showed that the expression of ß-catenin was important for cholangiocarcinoma development. We further demonstrated that MSCs and MSCs-CM could promote proliferation and migration of cholangiocarcinoma cells through targeting the Wnt/ß-catenin signaling pathway. hUC-MSCs or MSCs-CM stimulated Wnt activity by promoting the nuclear translocation of ß-catenin, and up-regulated Wnt target genes MMPs family, cyclin D1 and c-Myc. Together, our studies highlight a critical role for MSCs on cancer metastasis and indicate MSCs promote metastatic growth and chemoresistance of cholangiocarcinoma cells via activation of Wnt/ß-catenin signaling.

Humulus scandens exhibits immunosuppressive effects in vitro and in vivo by suppressing CD4(+) T cell activation.

Humulus scandens, rich in flavonoids, is a traditional Chinese medicine. It is widely used in China to treat tuberculosis, dysentery and chronic colitis. In this study, the major active faction of Humulus scandens (H.S) was prepared. Then, its immunosuppressive effects and underlying mechanisms on T cell activation were investigated in vitro and in vivo. Results showed that H.S significantly inhibited the proliferation of splenocytes induced by concanavalin A, lipopolysaccharides, and mixed-lymphocyte reaction in vitro. Additionally, H.S could dramatically suppress the proliferation and interferon-γ (IFN-γ) production from T cells stimulated by anti-CD3 and anti-CD28. Flow cytometric results confirmed that H.S could suppress the differentiation of IFN-γ-producing type 1 helper T cells (Th1). Furthermore, using ovalbumin immunization-induced T cell reaction and CD4(+) T-cell-mediated delayed type hypersensitivity reaction, H.S the immunosuppressive effects of H.S was also demonstrated in vivo. Western blot results showed that H.S could impede the activation of both Erk1/2 and P38 in primary T cells triggered by anti-CD3/28. Collectively, the active fraction of H.S showed promising immunosuppressive activities both in vitro and in vivo.

Ginsenoside metabolite compound K promotes recovery of dextran sulfate sodium-induced colitis and inhibits inflammatory responses by suppressing NF-κB activation.

Phytogenic compounds with anti-oxidant and anti-inflammatory properties, such as ginsenoside metabolite compound K (CK) or berberine (BBR), are currently discussed as promising complementary agents in the prevention and treatment of cancer and inflammation. The latest study showed that ginsenoside Rb1 and its metabolites could inhibit TNBS-induced colitis injury. However, the functional mechanisms of anti-inflammation effects of ginsenoside, particularly its metabolite CK are still not clear. Here, using dextran sulfate sodium (DSS)-induced colitis in mice, clinical parameters, intestinal integrity, pro-inflammatory cytokines production, and signaling pathways in colonic tissues were determined. In mild and sever colitis mice, CK and BBR (as a positive agent) alleviated colitis histopathology injury, ameliorated myeloperoxidase (MPO) activity, reduced pro-inflammatory cytokines production, such as, IL-6, IL-1ß, TNF-α, and increased anti-inflammatory cytokine IL-10 production in both mice colon tissues and blood. Nevertheless, the results revealed that CK and BBR inhibited NF-κB p65 nuclear translocation, downregulated p-IκBα and upregulated IκBα, indicating that CK, as well as BBR, suppressed the activation of the NF-κB pathway in the progression of colitis with immunofluorescence, immunohistochemical and western blotting analysis. Furthermore, CK inhibited pro-inflammatory cytokines production in LPS-activated macrophages via down-regulation of NF-κB signaling pathway. Taken together, our results not only reveal that CK promotes the recovery of the progression of colitis and inhibits the inflammatory responses by suppressing NF-κB activation, but also suggest that CK downregulates intestinal inflammation through regulating the activation of macrophages and pro-inflammatory cytokines production.

[Feasibility of washing as a remediation technology for the heavy metals-polluted soils left by chemical plant].

Laboratory simulation tests were conducted to examine the effects of different washing reagents (distilled water, HCl, H3PO4, oxalic acid, and CaCl2) in extracting the heavy metals from contaminated soils left by a chemical plant. The effects of reagent concentration, reaction time, and washing time on the washing efficiency were investigated, and the form variation of test heavy metals was determined before and after HCl washing. Distilled water, H3PO4, and CaCl2 could remove less than 1% of most heavy metals, and the highest removal rate was only 3.58%; while 2 mol HCl x L(-1) could obtain the highest washing efficiency under the optimal conditions, i. e., soil:liquid ratio was 1:3, reaction time was 1 hour, and the soils were washed twice by HCl solution. The removal rates of Cr, Pb, Zn, Cu, and Cd from test soils were 80.75%, 88.69%, 98.00%, 79.33%, and 95.52%, respectively. Among the washing reagents, HCl could effectively remove all forms of heavy metals.

[Persisters and their effects on microbial biofilm tolerance: a review].

Persisters are a group of special subpopulation of bacteria, only occupying < 0.1% of the whole population but having the characteristics different from the ordinary bacteria and resistant mutants. They have complex formation mechanism, and are difficult to isolate and culture. The persisters can adapt to the adverse environment via "dormancy-growth-proliferation" to maintain their survival and cell structure stability, and play a vital role in the multi-drug and multi-metal tolerance of microbial biofilm, being of great significance in maintaining the stability of microbial community structure. This paper reviewed the research progress on the characteristics of persisters, their gene regulation mechanisms, and their effects on the multi-drug and multi-metal tolerance of microbial biofilm. The related research directions in the future were also prospected.