Assessing the impacts of pandemic and the increase in minimum down payment rate on Shanghai housing prices.

In 2016, the city of Shanghai increased the minimum down payment rate requirement for purchasing various types of properties. We study the treatment effect of this major policy change on Shanghai's housing market by employing panel data from March 2009 to December 2021. Since the observed data are either in the form of no treatment or under the treatment but before and after the outbreak of COVID-19, we use the panel data approach suggested by Hsiao et al. (J Appl Econ, 27(5):705-740, 2012) to estimate the treatment effects and a time-series approach to disentangle the treatment effects and the effects of the pandemic. The results suggest that the average treatment effect on the housing price index of Shanghai over 36 months after the treatment is -8.17%. For time periods after the outbreak of the pandemic, we find no significant impact of the pandemic on the real estate price indices between 2020 and 2021.

Adipocytes Encapsulating Telratolimod Recruit and Polarize Tumor-Associated Macrophages for Cancer Immunotherapy.

Tumor-associated adipocytes (TAAs) recruit monocytes and promote their differentiation into tumor-associated macrophages (TAMs) that support tumor development. Here, TAAs are engineered to promote the polarization of TAMs to the tumor suppressive M1 phenotype. Telratolimod, a toll-like receptor 7/8 agonist, is loaded into the lipid droplets of adipocytes to be released at the tumor site upon tumor cell-triggered lipolysis. Locally administered drug-loaded adipocytes increased tumor suppressive M1 macrophages in both primary and distant tumors and suppressed tumor growth in a melanoma model. Furthermore, drug-loaded adipocytes improved CD8+ T cell-mediated immune responses within the tumor microenvironment and favored dendritic cell maturation in the tumor draining lymph nodes.

Impaired Humoral Immunity Identified in Inactivated SARS-CoV-2 Vaccine Recipients without Anti-Spike RBD Antibodies.

Inactivated SARS-CoV-2 vaccines have been deployed in a significant portion of the world population, who have widely varied responses to vaccination. Understanding this differential response would help the development of new vaccines for non-responders. Here, we conducted surveillance of anti-Spike receptor-binding domain (RBD) antibody levels in a large cohort of 534 healthy Chinese subjects vaccinated with two doses of inactivated SARS-CoV-2 vaccines. We show that the positive rate of antibodies among vaccinated subjects rapidly wanes as the interval between antibody testing and vaccination increases (14 to 119 days: 81.03%, 363 of 448 subjects; 120 to 149 days: 46.43%, 13 of 28 subjects; more than 150 days: 20%, 1 of 5 subjects). However, the antibodies were maintained at high levels in 16 convalescent COVID-19 patients at more than 150 days after recovery. We also found that increased age and body mass index are associated with decreased antibody levels. Vaccinated subjects who fail to produce antibodies display impaired B-cell activating humoral immunity, which was confirmed in COVID-19 patients without antibodies detected at 4 to 18 days after diagnosis. IMPORTANCE Our study illustrates the immune responses engaged by encountering antigen, highlighting the critical roles of B-cell activating humoral immunity in the body's antibody production.

Differences in Clinical and Imaging Features between Asymptomatic and Symptomatic COVID-19 Patients.

Objectives: The clinical and imaging features of asymptomatic carriers of severe acute respiratory syndrome coronavirus 2 and symptomatic COVID-19 patients. Methods: The clinical and chest computed tomography imaging data of 47 asymptomatic carriers and 36 symptomatic COVID-19 patients were derived. All patients underwent 4-6 CT scans over a period of 2-5 days. Results: The bulk of asymptomatic carriers who developed symptoms and most of the COVID-19 patients were older than 18 years of age with a decreased lymphocyte count, abnormal hepatic and renal function, and increased D-dimer and C-reactive protein. In the early stage, the pulmonary lesion involved mostly 1-2 lobes at the peripheral area in asymptomatic carriers but more than three lobes at both the central and peripheral areas in COVID-19 patients. In the progression stage, the lesion of asymptomatic carriers extended from the peripheral to the central area, and no significant difference was found in the lesion range compared with the symptomatic control group. In early improvement stage, the lesion was rapidly absorbed, and lesions were located primarily at the peripheral area in asymptomatic carriers; contrastingly, lesions were primarily located at both the central and peripheral areas in symptomatic patients. Asymptomatic carriers reflected a significantly shorter duration from disease onset to peak progression stage compared with the symptomatic. Conclusions: Asymptomatic carriers are a potential source of transmission and may become symptomatic COVID-19 patients despite indicating less severe pulmonary damage, earlier improvement, and better prognosis. Early isolation and intervention can eliminate such carriers as potential sources of transmission and improve their prognosis.

Effectiveness of inactivated COVID-19 vaccines against mild disease, pneumonia, and severe disease among persons infected with SARS-CoV-2 Omicron variant: Real-world study in Jilin Province, China.

BACKGROUND: : It is critical to determine the real-world performance of vaccines against coronavirus disease 2019 (COVID-19) so that appropriate treatments and policies can be implemented. There was a rapid wave of infections by the Omicron variant in Jilin Province (China) during spring 2022. We examined the effectiveness of inactivated vaccines against Omicron using real-world data from this epidemic. METHODS: . This retrospective case-case study of vaccine effectiveness (VE) examined infected patients who were quarantined and treated from April 16 to June 8, 2022 and responded to an electronic questionnaire. Data were analyzed by univariable and multivariable analyses. RESULTS: . A total of 2968 cases with SARS-CoV-2 infections (asymptomatic: 1029, mild disease: 1858, pneumonia: 108, severe disease: 21) were enrolled in the study. Multivariable regression indicated that the risk for pneumonia or severe disease was greater in those who were older or had underlying diseases, but was less in those who received COVID-19 vaccines. Relative to no vaccination, VE against the composite of pneumonia and severe disease was significant for those who received 2 doses (60.1%, 95%CI: 40.0%, 73.5%) or 3 doses (68.1%, 95%CI: 44.6%, 81.7%), and VE was similar in the subgroups of males and females. However, VE against the composite of all three classes of symptomatic diseases was not significant overall, nor after stratification by sex. There was no statistical difference in the VE of vaccines from different manufacturers. CONCLUSION: . The inactivated COVID-19 vaccines protected patients against pneumonia and severe disease from Omicron infection, and booster vaccination enhanced this effect.

Computed tomography findings and clinical evidence of improvement in coronavirus disease 2019 infection after convalescent plasma therapy in a critically ill patient

The spread of severe acute respiratory syndrome coronavirus 2 worldwide has created a major threat to human life and safety. Antiviral drugs and antibiotics have poor therapeutic effects, and there is no specific treatment for this virus. Chest computed tomography (CT) plays an important role in the diagnosis and management of coronavirus disease 2019 (COVID-19). We report a patient who was critically ill with COVID-19 and recovered after receiving transfusions of convalescent plasma. To evaluate the efficacy of convalescent plasma in the treatment of COVID-19, we compared chest CT findings, clinical manifestations, and laboratory findings before and after treatment with convalescent plasma. After the transfusion of convalescent plasma, clinical manifestations and indicators of inflammation improved, accompanied by an increase in the partial pressure of oxygen and oxygen saturation. Chest CT showed some resolution of the lung lesions, and multiple viral nucleic acid tests were negative. Therefore, the patient's condition was improved after the transfusion of convalescent plasma, suggesting that it may be an effective treatment for patients who are critically ill with COVID-19.

Mechanism and computed tomography features of liver injury caused by coronavirus disease 2019: Current status

Liver injury is found in some patients with coronavirus disease-2019 (COVID-19). Both the clinical treatment efficacy and the patient's prognosis are affected by the severity of liver injury. In addition, in some cases, liver injury may occur in the absence of respiratory symptoms. To date, liver injury diagnosed based on laboratory findings and abdominal computed tomography (CT) has been reported in COVID-19 patients. The aim of this review was to summarize the mechanism of liver injury caused by COVID-19 and describe the CT features of COVID-19-induced liver damage.

Two-stage hybrid network for segmentation of COVID-19 pneumonia lesions in CT images: a multicenter study.

COVID-19 has been spreading continuously since its outbreak, and the detection of its manifestations in the lung via chest computed tomography (CT) imaging is essential to investigate the diagnosis and prognosis of COVID-19 as an indispensable step. Automatic and accurate segmentation of infected lesions is highly required for fast and accurate diagnosis and further assessment of COVID-19 pneumonia. However, the two-dimensional methods generally neglect the intraslice context, while the three-dimensional methods usually have high GPU memory consumption and calculation cost. To address these limitations, we propose a two-stage hybrid UNet to automatically segment infected regions, which is evaluated on the multicenter data obtained from seven hospitals. Moreover, we train a 3D-ResNet for COVID-19 pneumonia screening. In segmentation tasks, the Dice coefficient reaches 97.23% for lung segmentation and 84.58% for lesion segmentation. In classification tasks, our model can identify COVID-19 pneumonia with an area under the receiver-operating characteristic curve value of 0.92, an accuracy of 92.44%, a sensitivity of 93.94%, and a specificity of 92.45%. In comparison with other state-of-the-art methods, the proposed approach could be implemented as an efficient assisting tool for radiologists in COVID-19 diagnosis from CT images.

Dynamics of influenza-like illness under urbanization procedure and COVID-19 pandemic in the subcenter of Beijing during 2013-2021.

Influenza-like illness (ILI) varies in intensity year by year, generally keeping a stable pattern except for great changes of its epidemic pattern. Of the most impacting factors, urbanization has been suggested as shaping the intensity of influenza epidemics. Besides, growing evidence indicates the nonpharmaceutical interventions (NPIs) to severe acute respiratory syndrome coronavirus 2 offer great advantages in controlling infectious diseases. The present study aimed to evaluate the impact of urbanization and NPIs on the dynamic of ILI in Tongzhou, Beijing, during January 2013 to March 2021. ILI epidemiological surveillance data in Tongzhou district were obtained from Beijing Influenza Surveillance Network and separated into three periods of urbanization and four intervals of coronavirus disease 2019 pandemic. Standardized average incidence rates of ILI in each separate stages were calculated and compared by using Wilson method and time series model of seasonal ARIMA. Influenza seasonal outbreaks showed similar epidemic size and intensity before urbanization during 2013-2016. Increased ILI activity was found during the process of Tongzhou's urbanization during 2017-2019, with the rate difference of 2.48 (95% confidence interva [CI]: 2.44, 2.52) and the rate ratio of 1.75 (95% CI: 1.74, 1.76) of ILI incidence between preurbanization and urbanization periods. ILI activity abruptly decreased from the beginning of 2020 and kept at the bottom level almost in every epidemic interval. The top decrease in ILI activity by NPIs was shown in 5-14 years group in 2020-2021 influenza season, as 92.2% (95% CI: 78.3%, 95.2%). The results indicated that both urbanization and NPIs interrupted the epidemic pattern of ILI. We should pay more attention to public health when facing increasing population density, human contact, population mobility, and migration in the process of urbanization. NPIs and influenza vaccination should be implemented as necessary measures to protect people from common infectious diseases like ILI.

Epidemiological characteristics of associated epidemics in Tongzhou district, Beijing, 2015-2020

Objective: To analyze the characteristics of the associated epidemics in Tongzhou district of Beijing from 2015 to 2020, identify the risk factors and provide scientific basis for the early warning, prevention and control of infectious disease epidemics.

Angiotensin-Converting Enzyme Genotype-Specific Immune Response Contributes to the Susceptibility of COVID-19: A Nested Case-Control Study.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease 2019 (COVID-19), which has resulted in a global pandemic. Methodology: We used a two-step polymerase chain reaction to detect the ACE genotype and ELISA kits to detect the cytokine factor. We also used proteomics to identify the immune pathway related to the ACE protein expression. Result: In this study, we found that the angiotensin-converting enzyme (ACE) deletion polymorphism was associated with the susceptibility to COVID-19 in a risk-dependent manner among the Chinese population. D/D genotype distributions were higher in the COVID-19 disease group than in the control group (D/D odds ratio is 3.87 for mild (p value < 0.0001), 2.59 for moderate (p value = 0.0002), and 4.05 for severe symptoms (p value < 0.0001), logic regression analysis. Moreover, genotype-specific cytokine storms and immune responses were found enriched in patients with the ACE deletion polymorphism, suggesting the contribution to the susceptibility to COVID-19. Finally, we identified the immune pathway such as the complement system related to the ACE protein expression of patients by lung and plasma proteomics. Conclusion: Our results demonstrated that it is very important to consider gene polymorphisms in the population to discover a host-based COVID-19 vaccine and drug design for preventive and precision medicine.

The Role of Imaging in the Detection and Management of COVID-19: A Review.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnosis and treatment assessment of the disease. Herein, we review the imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography - CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.

Diagnostic value of chest computed tomography imaging for COVID-19 based on reverse transcription-polymerase chain reaction: a meta-analysis.

BACKGROUND: The computed tomography (CT) diagnostic value of COVID-19 is controversial. We summarized the value of chest CT in the diagnosis of COVID-19 through a meta-analysis based on the reference standard. METHODS: All Chinese and English studies related to the diagnostic value of CT for COVID-19 across multiple publication platforms, was searched for and collected. Studies quality evaluation and plotting the risk of bias were estimated. A heterogeneity test and meta-analysis, including plotting sensitivity (Sen), specificity (Spe) forest plots, pooled positive likelihood ratio (+LR), negative likelihood ratio (-LR), dignostic odds ratio (DOR) values and 95% confidence interval (CI), were estimated. If there was a threshold effect, summary receiver operating characteristic curves (SROC) was further plotted. Pooled area under the receiver operating characteristic curve (AUROC) and 95% CI were also calculated. RESULTS: Twenty diagnostic studies that represented a total of 9004 patients were included from 20 pieces of literatures after assessing all the aggregated studies. The reason for heterogeneity was caused by the threshold effect, so the AUROC = 0.91 (95% CI: 0.89-0.94) for chest CT of COVID-19. Pooled sensitivity, specificity, +LR, -LR from 20 studies were 0.91 (95% CI: 0.88-0.94), 0.71 (95% CI: 0.59-0.80), 3.1(95% CI: 2.2-4.4), 0.12 (95% CI: 0.09-0.17), separately. The I2 was 85.6% (P = 0.001) by Q-test. CONCLUSIONS: The results of this study showed that CT diagnosis of COVID-19 was close to the reference standard. The diagnostic value of chest CT may be further enhanced if there is a unified COVID-19 diagnostic standard. However, please pay attention to rational use of CT.

Mix Contrast for COVID-19 Mild-to-Critical Prediction.

OBJECTIVE: In a few patients with mild COVID-19, there is a possibility of the infection becoming severe or critical in the future. This work aims to identify high-risk patients who have a high probability of changing from mild to critical COVID-19 (only account for 5% of cases). METHODS: Using traditional convolutional neural networks for classification may not be suitable to identify this 5% of high risk patients from an entire dataset due to the highly imbalanced label distribution. To address this problem, we propose a Mix Contrast model, which matches original features with mixed features for contrastive learning. Three modules are proposed for training the model: 1) a cumulative learning strategy for synthesizing the mixed feature; 2) a commutative feature combination module for learning the commutative law of feature concatenation; 3) a united pairwise loss assigning adaptive weights for sample pairs with different class anchors based on their current optimization status. RESULTS: We collect a multi-center computed tomography dataset including 918 confirmed COVID-19 patients from four hospitals and evaluate the proposed method on both the COVID-19 mild-to-critical prediction and COVID-19 diagnosis tasks. For mild-to-critical prediction, the experimental results show a recall of 0.80 and a specificity of 0.815. For diagnosis, the model shows comparable results with deep neural networks using a large dataset. Our method demonstrates improvements when the amount of training data is small or imbalanced. SIGNIFICANCE: Identifying mild-to-critical COVID-19 patients is important for early prevention and personalized treatment planning.

Anti-infection mechanism of phosphodiesterase-5 inhibitors and their roles in coronavirus disease 2019 (Review)

Coronavirus disease 2019 (COVID-19) has a variety of impacts on the human body. Severe acute respiratory syndrome coronavirus 2 is the pathogen that causes COVID-19. It invades human tissues through the receptor angiotensin-converting enzyme 2, resulting in an imbalance in the angiotensin II (AngII) level and upregulation of renin-angiotensin system/AngII pathway activity. Furthermore, the binding of AngII to its receptor leads to vasoconstriction, endothelial injury and intravascular thrombosis. In addition, COVID-19 may have adverse effects on male reproductive organs and a marked impact on male reproductive health. Phosphodiesterase-5 inhibitors (PDE5Is) may improve vascular endothelial function, promote testicular and systemic blood circulation and testosterone secretion and enhance epididymal function, as well as sperm maturation and capacitation. PDE5Is may also be of use in the treatment of infectious diseases by enhancing immunity and anti-inflammatory responses and improving vascular endothelial function. Based on the pharmacological mechanism of PDE5Is, they are of unique value in the fight against infectious diseases and may be effective in combination with direct antiviral drugs. The anti-infection mechanisms of PDE5Is and their roles in COVID-19 were reviewed in the present study. [ABSTRACT FROM AUTHOR] Copyright of Experimental & Therapeutic Medicine is the property of Spandidos Publications UK Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Transplantation of ACE2- Mesenchymal Stem Cells Improves the Outcome of Patients with COVID-19 Pneumonia.

A coronavirus (HCoV-19) has caused the novel coronavirus disease (COVID-19) outbreak in Wuhan, China. Preventing and reversing the cytokine storm may be the key to save the patients with severe COVID-19 pneumonia. Mesenchymal stem cells (MSCs) have been shown to possess a comprehensive powerful immunomodulatory function. This study aims to investigate whether MSC transplantation improves the outcome of 7 enrolled patients with COVID-19 pneumonia in Beijing YouAn Hospital, China, from Jan 23, 2020 to Feb 16, 2020. The clinical outcomes, as well as changes of inflammatory and immune function levels and adverse effects of 7 enrolled patients were assessed for 14 days after MSC injection. MSCs could cure or significantly improve the functional outcomes of seven patients without observed adverse effects. The pulmonary function and symptoms of these seven patients were significantly improved in 2 days after MSC transplantation. Among them, two common and one severe patient were recovered and discharged in 10 days after treatment. After treatment, the peripheral lymphocytes were increased, the C-reactive protein decreased, and the overactivated cytokine-secreting immune cells CXCR3+CD4+ T cells, CXCR3+CD8+ T cells, and CXCR3+ NK cells disappeared in 3-6 days. In addition, a group of CD14+CD11c+CD11bmid regulatory DC cell population dramatically increased. Meanwhile, the level of TNF-α was significantly decreased, while IL-10 increased in MSC treatment group compared to the placebo control group. Furthermore, the gene expression profile showed MSCs were ACE2- and TMPRSS2- which indicated MSCs are free from COVID-19 infection. Thus, the intravenous transplantation of MSCs was safe and effective for treatment in patients with COVID-19 pneumonia, especially for the patients in critically severe condition.

Cardiac involvement in COVID-19 patients: mid-term follow up by cardiovascular magnetic resonance.

BACKGROUND: Coronavirus disease 2019 (COVID-19) induces myocardial injury, either direct myocarditis or indirect injury due to systemic inflammatory response. Myocardial involvement has been proved to be one of the primary manifestations of COVID-19 infection, according to laboratory test, autopsy, and cardiovascular magnetic resonance (CMR). However, the middle-term outcome of cardiac involvement after the patients were discharged from the hospital is yet unknown. The present study aimed to evaluate mid-term cardiac sequelae in recovered COVID-19 patients by CMR METHODS: A total of 47 recovered COVID-19 patients were prospectively recruited and underwent CMR examination. The CMR protocol consisted of black blood fat-suppressed T2 weighted imaging, T2 star mapping, left ventricle (LV) cine imaging, pre- and post-contrast T1 mapping, and late gadolinium enhancement (LGE). LGE were assessed in mixed both recovered COVID-19 patients and healthy controls. The LV and right ventricle (RV) function and LV mass were assessed and compared with healthy controls. RESULTS: A total of 44 recovered COVID-19 patients and 31 healthy controls were studied. LGE was found in 13 (30%) of COVID-19 patients. All LGE lesions were located in the mid myocardium and/or sub-epicardium with a scattered distribution. Further analysis showed that LGE-positive patients had significantly decreased LV peak global circumferential strain (GCS), RV peak GCS, RV peak global longitudinal strain (GLS) as compared to non-LGE patients (p < 0.05), while no difference was found between the non-LGE patients and healthy controls. CONCLUSION: Myocardium injury existed in 30% of COVID-19 patients. These patients have depressed LV GCS and peak RV strains at the 3-month follow-up. CMR can monitor the COVID-19-induced myocarditis progression, and CMR strain analysis is a sensitive tool to evaluate the recovery of LV and RV dysfunction.

Texture feature-based machine learning classifier could assist in the diagnosis of COVID-19.

PURPOSE: Differentiating COVID-19 from other acute infectious pneumonias rapidly is challenging at present. This study aims to improve the diagnosis of COVID-19 using computed tomography (CT). METHOD: COVID-19 was confirmed mainly by virus nucleic acid testing and epidemiological history according to WHO interim guidance, while other infectious pneumonias were diagnosed by antigen testing. The texture features were extracted from CT images by two radiologists with 5 years of work experience using modified wavelet transform and matrix computation analyses. The random forest (RF) classifier was applied to identify COVID-19 patients and images. RESULTS: We retrospectively analysed the data of 95 individuals (291 images) with COVID-19 and 96 individuals (279 images) with other acute infectious pneumonias, including 50 individuals (160 images) with influenza A/B. In total, 6 texture features showed a positive association with COVID-19, while 4 features were negatively associated. The mean AUROC, accuracy, sensitivity, and specificity values of the 5-fold test sets were 0.800, 0.722, 0.770, and 0.680 for image classification and 0.858, 0.826, 0.809, and 0.842 for individual classification, respectively. The feature 'Correlation' contributed most both at the image level and individual level, even compared with the clinical factors. In addition, the texture features could discriminate COVID-19 from influenza A/B, with an AUROC of 0.883 for images and 0.957 for individuals. CONCLUSIONS: The developed texture feature-based RF classifier could assist in the diagnosis of COVID-19, which could be a rapid screening tool in the era of pandemic.