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1.
Placenta ; 124: 62-66, 2022 06 24.
Article in English | MEDLINE | ID: covidwho-1914906

ABSTRACT

INTRODUCTION: COVID-19 has been associated with several adverse pregnancy outcomes, including perinatal loss. Differential effects of COVID-19 in a twin pregnancy may provide unique insights into virus-placental interactions. We present a case of perinatal loss of a female fetus with survival of the male co-twin in a pregnancy complicated by COVID-19 and premature delivery. METHODS: Viral detection methods recommended by the NICHD task force were used to identify SARS-CoV-2 and its viral receptors in the placentas and fetal tissue (Antoun et al., 2020) [1] RESULTS: Compared with the surviving twin, we found a more severe intervillous necrosis and a relatively low detection of ACE2 membranous expression in the syncytiotrophoblasts of the female twin that succumbed. DISCUSSION: The interactions of SARS-CoV-2 and ACE2 at the maternal fetal interface within the placenta may play a significant role in perinatal loss, and the effects of fetal sex and gestational age at time of infection need to be explored further.


Subject(s)
COVID-19 , Pregnancy Complications, Infectious , Angiotensin-Converting Enzyme 2 , Female , Humans , Infectious Disease Transmission, Vertical , Male , Placenta/metabolism , Pregnancy , Pregnancy Complications, Infectious/pathology , SARS-CoV-2
2.
Front Psychol ; 13: 891778, 2022.
Article in English | MEDLINE | ID: covidwho-1903158

ABSTRACT

Background: Psychological dynamics of college students have changed during the COVID-19 outbreak but little research has been done in this area. The purpose of this study is to investigate the dynamic changes in the mental health status of college students since the outbreak of the COVID-19 pandemic 1 year and the influencing factors. Methods: The research period was from February 2020 to August 2021. 384 college students were analyzed three times during this period on the recognition and psychological state of the pandemic. Results: During the period from February 2020 to August 2021, in general, the positive scores rose from 20.79 to 23.46, while the negative scores dropped from 17.41 to 14.00. The regression analysis results on the influencing factors showed the degree of recognition of the pandemic is all significant in the three phases (p < 0.05). Conclusion: With the effective control of the pandemic, the mental state of the students showed a slight improvement in the environment of sporadic cases. Behavior has a partial mediating effect between the source of fear and psychological changes. Correct behavior guidance can effectively reduce the psychological changes caused by college students' fear.

3.
Expert Rev Mol Diagn ; 22(5): 559-574, 2022 May.
Article in English | MEDLINE | ID: covidwho-1878677

ABSTRACT

INTRODUCTION: The emergence of SARS-CoV-2, the causative agent the COVID-19 pandemic, has led to a rapidly expanding arsenal of molecular diagnostic assays for the detection of viral material in tissue specimens. AREAS COVERED: We review the value and shortcomings of available tissue-based assays for SARS-CoV-2 detection in formalin-fixed paraffin-embedded (FFPE) tissue, including immunohistochemistry, in situ hybridization, and quantitative reverse transcription PCR (RT-qPCR). The validation, accuracy, and comparative utility of each method is discussed. Subsequently, we identify commercially available antibodies which render the greatest specificity and reproducibility of staining in FFPE specimens. EXPERT OPINION: We offer expert opinion on the efficacy of such techniques and guidance for future implementation, both clinical and experimental.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , Humans , Immunohistochemistry , In Situ Hybridization , Pandemics , RNA , RNA, Viral/genetics , Reproducibility of Results , SARS-CoV-2/genetics , Sensitivity and Specificity
4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-336822

ABSTRACT

Background While considerable attention was placed on SARS-CoV-2 testing and surveillance programs in the K-12 setting, younger age groups in childcare centers were largely overlooked. Childcare facilities are vital to communities, allowing parents/guardians to remain at work and providing safe environments for both children and staff. Therefore, early in the COVID-19 pandemic, we established a PCR-based COVID-19 surveillance program in childcare facilities, testing children and staff with the goal of collecting actionable public health data and aiding communities in the progressive resumption of standard operations and ways of life. In this study we describe the development of a weekly saliva testing program and provide early results from our experience implementing this in childcare centers. Methods We enrolled children (aged 6 months to 7 years) and staff at 8 childcare facilities and trained participants in saliva collection using video chat technology. Weekly surveys were sent out to assess exposures, symptoms, and vaccination status changes. Participants submitted weekly saliva samples at school. Samples were transported to a partnering clinical laboratory for RT-PCR testing using SalivaDirect and results were uploaded to each participant’s online patient portal within 24 hours. Results This study fostered a cooperative partnership with participating childcare centers, parents/guardians, and staff with the goal of mitigating COVID-19 transmission in childcare centers. Age-related challenges in saliva collection were overcome by working with parents/guardians to conceptualize new collection strategies and by offering parents/guardians continued virtual guidance and support. Conclusion SARS-CoV-2 screening and routine testing programs have focused less on the childcare population, resulting in knowledge gaps in this critical age group, especially as many are still ineligible for vaccination. SalivaDirect testing for SARS-CoV-2 provides a feasible method of asymptomatic screening and symptomatic testing for children and childcare center staff. Given the relative aversion to nasal swabs in the childcare age group, especially as a routine surveillance tool, an at-home saliva collection method provides an attractive alternative. Results can be shared rapidly electronically through participants’ private medical chart portals, and video chat technology allows for discussion and instruction between investigators and participants.

5.
Commun Biol ; 5(1): 439, 2022 05 11.
Article in English | MEDLINE | ID: covidwho-1839575

ABSTRACT

SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Genomics , Humans , Pandemics , SARS-CoV-2/genetics , United States/epidemiology
6.
Sci Rep ; 12(1): 5729, 2022 04 06.
Article in English | MEDLINE | ID: covidwho-1778632

ABSTRACT

The Coronavirus disease 2019 (COVID-19) pandemic-caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)- has posed a global threat and presented with it a multitude of economic and public-health challenges. Establishing a reliable means of readily available, rapid diagnostic testing is of paramount importance in halting the spread of COVID-19, as governments continue to ease lockdown restrictions. The current standard for laboratory testing utilizes reverse transcription quantitative polymerase chain reaction (RT-qPCR); however, this method presents clear limitations in requiring a longer run-time as well as reduced on-site testing capability. Therefore, we investigated the feasibility of a reverse transcription looped-mediated isothermal amplification (RT-LAMP)-based model of rapid COVID-19 diagnostic testing which allows for less invasive sample collection, named SaliVISION. This novel, two-step, RT-LAMP assay utilizes a customized multiplex primer set specifically targeting SARS-CoV-2 and a visual report system that is ready to interpret within 40 min from the start of sample processing and does not require a BSL-2 level testing environment or special laboratory equipment. When compared to the SalivaDirect and Thermo Fisher Scientific TaqPath RT-qPCR testing platforms, the respective sensitivities of the SaliVISION assay are 94.29% and 98.28% while assay specificity was 100% when compared to either testing platform. Our data illustrate a robust, rapid diagnostic assay in our novel RT-LAMP test design, with potential for greater testing throughput than is currently available through laboratory testing and increased on-site testing capability.


Subject(s)
COVID-19 , COVID-19/diagnosis , COVID-19 Testing , Communicable Disease Control , Diagnostic Tests, Routine , Humans , Molecular Diagnostic Techniques/methods , Nucleic Acid Amplification Techniques/methods , RNA, Viral/analysis , RNA, Viral/genetics , SARS-CoV-2/genetics , Saliva/chemistry , Sensitivity and Specificity
7.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-331876

ABSTRACT

Middle East Respiratory Syndrome coronavirus (MERS-CoV) and several bat coronaviruses employ Dipeptidyl peptidase-4 (DPP4) as their functional receptors. However, the receptor for NeoCoV, the closest MERS-CoV relative yet discovered in bats, remains enigmatic. In this study, we unexpectedly found that NeoCoV and its close relative, PDF-2180-CoV, can efficiently use some types of bat Angiotensin-converting enzyme 2 (ACE2) and, less favorably, human ACE2 for entry. The two viruses use their spikes' S1 subunit carboxyl-terminal domains (S1-CTD) for high-affinity and species-specific ACE2 binding. Cryo-electron microscopy analysis revealed a novel coronavirus-ACE2 binding interface and a protein-glycan interaction, distinct from other known ACE2-using viruses. We identified a molecular determinant close to the viral binding interface that restricts human ACE2 from supporting NeoCoV infection, especially around residue Asp338. Conversely, NeoCoV efficiently infects human ACE2 expressing cells after a T510F mutation on the receptor-binding motif (RBM). Notably, the infection could not be cross-neutralized by antibodies targeting SARS-CoV-2 or MERS-CoV. Our study demonstrates the first case of ACE2 usage in MERS-related viruses, shedding light on a potential bio-safety threat of the human emergence of an ACE2 using "MERS-CoV-2" with both high fatality and transmission rate.

8.
J Thorac Dis ; 14(2): 355-370, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1737501

ABSTRACT

Background: The current COVID-19 pandemic is posing a major challenge to public health on a global scale. While it is generally believed that severe COVID-19 results from over-expression of inflammatory mediators (i.e., a "cytokine storm"), it is still unclear whether and how co-infecting pathogens contribute to disease pathogenesis. To address this, we followed the entire course of the disease in cases with severe or critical COVID-19 to determine the presence and abundance of all potential pathogens present-the total "infectome"-and how they interact with the host immune system in the context of severe COVID-19. Methods: We examined one severe and three critical cases of COVID-19, as well as a set of healthy controls, with longitudinal samples (throat swab, whole blood, and serum) collected from each case. Total RNA sequencing (meta-transcriptomics) was performed to simultaneously investigate pathogen diversity and abundance, as well as host immune responses, in each sample. A Bio-Plex method was used to measure serum cytokine and chemokine levels. Results: Eight pathogens, SARS-CoV-2, Aspergillus fumigatus (A. fumigatus), Mycoplasma orale (M. orale), Myroides odoratus (M. odoratus), Acinetobacter baumannii (A. baumannii), Candida tropicalis, herpes simplex virus (HSV) and human cytomegalovirus (CMV), identified in patients with COVID-19 appeared at different stages of the disease. The dynamics of inflammatory mediators in serum and the respiratory tract were more strongly associated with the dynamics of the infectome compared with SARS-CoV-2 alone. Correlation analysis revealed that pulmonary injury was directly associated with cytokine levels, which in turn were associated with the proliferation of SARS-CoV-2 and co-infecting pathogens. Conclusions: For each patient, the cytokine storm that resulted in acute lung injury and death involved a dynamic and highly complex infectome, of which SARS-CoV-2 was a component. These results indicate the need for a precision medicine approach to investigate both the infection and host response as a standard means of infectious disease characterization.

9.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-324296

ABSTRACT

Early and accurate severity assessment of Coronavirus disease 2019 (COVID-19) based on computed tomography (CT) images offers a great help to the estimation of intensive care unit event and the clinical decision of treatment planning. To augment the labeled data and improve the generalization ability of the classification model, it is necessary to aggregate data from multiple sites. This task faces several challenges including class imbalance between mild and severe infections, domain distribution discrepancy between sites, and presence of heterogeneous features. In this paper, we propose a novel domain adaptation (DA) method with two components to address these problems. The first component is a stochastic class-balanced boosting sampling strategy that overcomes the imbalanced learning problem and improves the classification performance on poorly-predicted classes. The second component is a representation learning that guarantees three properties: 1) domain-transferability by prototype triplet loss, 2) discriminant by conditional maximum mean discrepancy loss, and 3) completeness by multi-view reconstruction loss. Particularly, we propose a domain translator and align the heterogeneous data to the estimated class prototypes (i.e., class centers) in a hyper-sphere manifold. Experiments on cross-site severity assessment of COVID-19 from CT images show that the proposed method can effectively tackle the imbalanced learning problem and outperform recent DA approaches.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-322231

ABSTRACT

The clinical features, molecular characteristics, and immune responses of COVID-19 patients with persistent SARS-CoV-2 infection are not yet well described. In this study, we investigated the differences in clinical parameters, laboratory indexes, plasma cytokines, and peripheral blood mononuclear cell responses, which were assessed using single-cell RNA-sequencing in patients with non-critical COVID-19 with long durations (LDs) and short durations (SDs) of viral shedding. Our results revealed that clinical parameters and laboratory indexes, such as c-reactive protein (CRP) and D-dimer, were comparable between SDs and LDs. Most inflammatory cytokines/chemokines, such as IL-2, IL2R, TNFα/β, IL1β, and CCL5 were present at low levels in LDs. Our single-cell RNA-sequencing revealed a reconfiguration of the peripheral immune cell phenotype in LDs, including decreases in natural killer (NK) cells and CD14 + monocytes and an increase in regulatory T cells (Tregs). Furthermore, most cell subsets in LDs consistently exhibited reduced expression of ribosomal protein (RP) genes, indicating dysfunctions in cytokine/chemokine synthesis, folding, modification, and assembly. Accordingly, the negative correlation between the RP levels and viral shedding duration was validated in an independent cohort of bulk-RNA-sequencing data from 103 non-critical patients, which may help guide clinical management and resource allocation. Moreover, peripheral T and NK cells and memory B cells in LDs likely failed to activate, which contributed to the persistence of viral shedding.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315388

ABSTRACT

Background: Some mild patients can deteriorate to moderate or severe within a week with the natural progression of COVID-19.it has been crucial to early identify those mild cases and give timely treatment . The chest computed tomography (CT) has shown to be useful to assist clinical diagnosis of COVID-19.In this study, machine learning was used to develop an early-warning CT feature model for predicting mild patients with potential malignant progression. Methods: : The total of 140 COVID-19 mild patients were collected. All patients at admission were divided into groups (alleviation group and exacerbation group) with or without malignant progression.The clinical and laboratory data at admission, the first CT, and the follow-up CT at critical stage of the two groups were compared with Chi-square test,.The CT features data (distribution, morphology,etc) were used to establish the prediction model by Fisher's linear discriminant method and Unconditional logistic regression algorithm. And the model was validated with 40 exception data.and the Area Under ROC curve (AUC) was used to evaluate the models. Results: : The model filtered out three variables of CT features including distal air bronchogram, fibrosis,and reversed halo sign. Notably, the distal air bronchograms was less common in alleviation group, while the fibrosis and reversed halo sign were more common.The sensitivity, specificity and Youden index of unconditional logistic regression were 86.1%, 92.6% and 78.7%, For the analysis of Fisher's linear discriminant, the sensitivity, specificity and Youden index were 83.3%, 94.1% and 77.4%. The generalization ability of both models were consistent with sensitivity of 95.89%, specificity of 100%, and Youden index of 83.33%. Conclusions: : The CT imaging features-based machine learning model has a high sensitivity for finding out the mild patients who are easy to deteriorate into severe/critical cases efficiently so that timely treatments came true for those patients,while largely help to relieve the medical pressure.

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315333

ABSTRACT

Background: Since the first case of a coronavirus disease 2019 (COVID-19) infection pneumonia was detected in Wuhan, China, a series of confirmed cases of the COVID-19 were found in Southwest China. The aim of this study was to describe the imaging manifestations of hospitalized patients with confirmed COVID-19 infection in southwest China. Methods: In this retrospective study, data were collected from 131 patients with confirmed coronavirus disease 2019 (COVID-19) from 3 Chinese hospitals. Their common clinical manifestations, as well as characteristics and evolvement features of chest CT images, were analyzed. Results: A total of 100 (76%) patients had a history of close contact with people living in Wuhan , Hubei. The clinical manifestations of COVID-19 included cough, fever. Most of the lesions identified in chest CT images were multiple lesions of bilateral lungs, lesions were more localized in the peripheral lung, 109 (83%) patients had more than two lobes involved, 20 (15%) patients presented with patchy ground glass opacities, patchy ground glass opacities and consolidation of lesions co-existing in 61 (47%) cases. Complications such as pleural thickening, hydrothorax, pericardial effusion, and enlarged mediastinal lymph nodes were detected but only in rare cases. For the follow-up chest CT examinations (91 cases), We found 66 (73%) cases changed very quickly, with an average of 3.5 days, 25 cases (27%) presented absorbed lesions, progression was observed in 41 cases (46%), 25 (27%) cases showed no significant changes. Conclusion: Chest CT plays an important role in diagnosing COVID-19. The imaging pattern of multifocal peripheral ground glass or mixed consolidation is highly suspicious of COVID-19, that can quickly change over a short period of time.

13.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315192

ABSTRACT

Background: Air pollution and idiopathic pulmonary fibrosis (IPF) cause a poor prognosis after COVID-19 infection, but the underlying mechanisms are not well exploited. Angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) are the keys to the entry of SARS-CoV-2. We measured their expression levels in lung tissues of control non-IPF and IPF patients, and used murine animal models to study the deterioration of IPF caused by particulate matter (PM) and the molecular pathways involved in the expression of ACE2 and TMPRSS2. Results: : In non-IPF patients, cells expressing ACE2 and TMPRSS2 were limited to human alveolar cells. ACE2 and TMPRSS2 were largely upregulated in IPF patients, and were co-expressed by fibroblast specific protein 1 (FSP-1)+ lung fibroblasts in human pulmonary fibrotic tissue. In animal models, PM exposure increased the severity of bleomycin-induced pulmonary fibrosis. ACE2 and TMPRSS2 were also expressed in FSP-1+ lung fibroblasts in bleomycin-inuced pulmonary fibrosis, and when combined with PM exposure, they were further upregulated. The severity of pulmonary fibrosis and the expression of ACE2 and TMPRSS2 caused by PM exposure were blocked by deletion of KC, a murine homologue of IL‐8, or treatment with reparixin, an inhibitor of IL‐8 receptors CXCR1/2. Conclusions: : These data suggest that poor prognosis after COVID-19 infection caused by air pollution and IPF is mediated through upregulation of ACE2 and TMPRSS2 in pulmonary fibroblasts, which can be prevented by blocking the IL-8/CXCR1/2 pathway.

14.
Emerg Microbes Infect ; 11(1): 567-572, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1642256

ABSTRACT

Global concern has been raised by the emergence and rapid transmission of the heavily mutated SARS-CoV-2 Omicron variant (B.1.1.529). So far, the infection features and immune escape ability of the Omicron variant have not been extensively studied. Here, we produced the Omicron pseudovirus and compared its entry, membrane fusion, and immune escape efficiency with the original strain and the dominating Delta variant. We found the Omicron variant showed slightly higher infectivity than the Delta variant and a similar ability to compete with the Delta variant in using Angiotensin-converting enzyme 2 (ACE2) in a BHK21-ACE2 cell line. However, the Omicron showed a significantly reduced fusogenicity than the original strain and the Delta variant in both BHK21-ACE2 and Vero-E6 cells. The neutralization assay testing the Wuhan convalescents' sera one-year post-infection showed a more dramatic reduction (10.15 fold) of neutralization against the Omicron variant than the Delta variant (1.79 fold) compared with the original strain with D614G. Notably, immune-boosting through three vaccine shots significantly improved the convalescents' immunity against the Omicron variants. Our results reveal a reduced fusogenicity and a striking immune escape ability of the Omicron variant, highlighting the importance of booster shots against the challenge of the SARS-CoV-2 antigenic drift.


Subject(s)
COVID-19 , SARS-CoV-2/immunology , Animals , COVID-19/immunology , Chlorocebus aethiops , Humans , Immune Evasion , Immunization, Secondary , Vero Cells
15.
Aging (Albany NY) ; 13(23): 24943-24962, 2021 12 04.
Article in English | MEDLINE | ID: covidwho-1622953

ABSTRACT

Ongoing pandemic and potential resurgence of Coronavirus disease 2019 (COVID-19) has prompted urgent efforts to investigate the immunological memory of convalescent patients, especially in patients with active cancers. Here we performed single-cell RNA sequencing in peripheral blood samples of 3 healthy donors (HDs), 4 COVID-19 patients (Covs) and 4 COVID-19 patients with active gynecological tumor (TCs) pre- and post- anti-tumor treatment. All Covs patients had recovered from their acute infection. Interestingly, the molecular features of PBMCs in TCs are similar to that in Covs, suggesting that convalescent COVID-19 with gynecologic tumors do not have major immunological changes and may be protected against reinfection similar to COVID-19 patients without tumors. Moreover, the chemotherapy given to these patients mainly caused neutropenia, while having little effect on the proportion and functional phenotype of T and B cells, and T cell clonal expansion. Notably, anti-PD-L1 treatment massively increased cytotoxic scores of NK cells, and T cells, and facilitated clonal expansion of T cells in these patients. It is likely that T cells could protect patients from SARS-CoV-2 virus reinfection and anti-PD-L1 treatment can enhance the anti-viral activity of the T cells.


Subject(s)
COVID-19/complications , Genital Neoplasms, Female/complications , Genital Neoplasms, Female/therapy , Immune Checkpoint Inhibitors/therapeutic use , Immunotherapy , Antibodies, Viral/immunology , B-Lymphocytes/drug effects , B-Lymphocytes/immunology , COVID-19/immunology , COVID-19/prevention & control , Female , Genital Neoplasms, Female/immunology , Humans , Immune Checkpoint Inhibitors/pharmacology , SARS-CoV-2/drug effects , SARS-CoV-2/immunology , Single-Cell Analysis , T-Lymphocytes/drug effects , T-Lymphocytes/immunology
16.
Spine (Phila Pa 1976) ; 47(4): 352-360, 2022 Feb 15.
Article in English | MEDLINE | ID: covidwho-1599588

ABSTRACT

STUDY DESIGN: A prospective and nonrandomized concurrent controlled trial. OBJECTIVE: To address the early effects of concurrent treatment with vitamin K2 and vitamin D3 on fusion rates in patients who have undergone spinal surgery. SUMMARY OF BACKGROUND DATA: Intervertebral pseudarthrosis has been reported after transforaminal lumbar interbody fusion (TLIF) or posterior lumbar interbody fusion (PLIF), especially in patients with osteopenia or osteoporosis. No study has assessed the early effects of concurrent treatment with vitamin K2 and vitamin D3 on fusion rates. METHODS: Patients with osteopenia or osteoporosis who underwent TLIF or PLIF in our department were included. Patients in the VK2+VD3 group received vitamin K2, vitamin D3, and calcium treatment, whereas subjects in the control group only received calcium and vitamin D3. Spine fusion was evaluated by computed tomography. The Japanese Orthopedic Association Back Pain Evaluation Questionnaire (JOA-BPEQ) and visual analog scale (VAS) were used to assess the clinical and neurological symptoms. Bone mineral density (BMD) and bone metabolism markers were measured for osteoporotic evaluation. RESULTS: Seventy-eight patients were included, and nine patients subsequently discontinued because of 2019-nCoV. At six months postoperatively, complete fusion rates were significantly higher in the VK2+VD3 group than that in the control group (91.18% vs 71.43%, P = 0.036). At six months postoperatively, BMD was increased in the VK2+VD3 group and was higher than that in the control group, although there was no significant difference. At three months postoperatively, a significant increase in procollagen type I amino terminal propeptide (91.81%) and a slight decrease in C-terminal end peptide (8.06%) were observed in the VK2+VD3 group. In both groups, the JOA-BPEQ and VAS scores were significantly improved after spine surgery. CONCLUSION: Administration of vitamin K2 and vitamin D3 can increase lumbar interbody fusion rates, improve clinical symptoms, promote bone information, and avoid further decline in BMD within six months after TLIF or PLIF.Level of Evidence: 3.


Subject(s)
COVID-19 , Intervertebral Disc Degeneration , Osteoporosis , Spinal Fusion , Collagen Type I , Humans , Intervertebral Disc Degeneration/complications , Intervertebral Disc Degeneration/diagnostic imaging , Intervertebral Disc Degeneration/drug therapy , Lumbar Vertebrae/diagnostic imaging , Lumbar Vertebrae/surgery , Osteoporosis/complications , Osteoporosis/drug therapy , Prospective Studies , Retrospective Studies , SARS-CoV-2 , Spinal Fusion/adverse effects , Treatment Outcome , Vitamin K 2
17.
IEEE Trans Med Imaging ; 41(1): 88-102, 2022 01.
Article in English | MEDLINE | ID: covidwho-1593541

ABSTRACT

Early and accurate severity assessment of Coronavirus disease 2019 (COVID-19) based on computed tomography (CT) images offers a great help to the estimation of intensive care unit event and the clinical decision of treatment planning. To augment the labeled data and improve the generalization ability of the classification model, it is necessary to aggregate data from multiple sites. This task faces several challenges including class imbalance between mild and severe infections, domain distribution discrepancy between sites, and presence of heterogeneous features. In this paper, we propose a novel domain adaptation (DA) method with two components to address these problems. The first component is a stochastic class-balanced boosting sampling strategy that overcomes the imbalanced learning problem and improves the classification performance on poorly-predicted classes. The second component is a representation learning that guarantees three properties: 1) domain-transferability by prototype triplet loss, 2) discriminant by conditional maximum mean discrepancy loss, and 3) completeness by multi-view reconstruction loss. Particularly, we propose a domain translator and align the heterogeneous data to the estimated class prototypes (i.e., class centers) in a hyper-sphere manifold. Experiments on cross-site severity assessment of COVID-19 from CT images show that the proposed method can effectively tackle the imbalanced learning problem and outperform recent DA approaches.


Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Tomography, X-Ray Computed
18.
Annu Int Conf IEEE Eng Med Biol Soc ; 2021: 2592-2596, 2021 11.
Article in English | MEDLINE | ID: covidwho-1566189

ABSTRACT

For COVID-19 prevention and treatment, it is essential to screen the pneumonia lesions in the lung region and analyze them in a qualitative and quantitative manner. Three-dimensional (3D) computed tomography (CT) volumes can provide sufficient information; however, extra boundaries of the lesions are also needed. The major challenge of automatic 3D segmentation of COVID-19 from CT volumes lies in the inadequacy of datasets and the wide variations of pneumonia lesions in their appearance, shape, and location. In this paper, we introduce a novel network called Comprehensive 3D UNet (C3D-UNet). Compared to 3D-UNet, an intact encoding (IE) strategy designed as residual dilated convolutional blocks with increased dilation rates is proposed to extract features from wider receptive fields. Moreover, a local attention (LA) mechanism is applied in skip connections for more robust and effective information fusion. We conduct five-fold cross-validation on a private dataset and independent offline evaluation on a public dataset. Experimental results demonstrate that our method outperforms other compared methods.


Subject(s)
COVID-19 , Attention , Humans , Research Design , SARS-CoV-2 , Tomography, X-Ray Computed
19.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296427

ABSTRACT

Background: COVID-19 disease severity is associated with endocrine system. We hypothesis radiomics features from the adrenal gland and periadrenal fat CT images can assess possibilities of disease exacerbation.Methods: A total of 1,245 patients (685 moderate and 560 severe patients) were enrolled in a retrospective study. We proposed 3D V-Net to segment adrenal glands in onset CT images automatically, and periadrenal fat was obtained using inflation operation around the adrenal gland. Next, we built a clinical model (CM), three radiomics models (adrenal gland model [AM], periadrenal fat model [PM], and fusion of adrenal gland and periadrenal fat model [FM]), and radiomics nomogram (RN) after radiomics features extracted.Findings: The auto-segmentation framework yielded a dice value of 0.79 in the training set. CM, AM, PM, FM, and RN obtained AUCs of 0.717, 0.716, 0.736, 0.760, and 0.833, respectively in the validation set. FM and RN had better predictive efficacy than CM (P < 0.0001) in the training set. RN showed that there was no significant difference in the validation set (mean absolute error [MAE] = 0.04) and test set (MAE = 0.075) between predictive and actual results. Decision curve analysis showed that if the threshold probability was more than 0.3 in the validation set or between 0.4 and 0.8 in the test set, it could gain more net benefits using RN than FM and CM.Interpretation: Radiomics features extracted from adrenal gland and periadrenal fat CT images are related to disease exacerbation in patients with COVID-19.Funding Information: The study was supported by the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT320003);The Science and Technology Foundation of Guizhou Province (QKHPTRC[2019]5803);The Guiyang Science and Technology Project (ZKXM[2020]4);Beijing Medical and Health Foundation (YWJKJJHKYJJ-B20261CS) and Chongqing Science and Health Joint Medical Research Project (2021MSXM052).Declaration of Interests: The authors have declared that no conflict of interest exists.Ethics Approval Statement: This multicenter study was approved by the ethics committees of all participating hospitals (2020,NO.01). Because of its retrospective nature, the need to obtain informed consent in advance was waived. The study was performed according to the principles of the declaration of Helsinki.

20.
Med Phys ; 48(12): 7913-7929, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1516790

ABSTRACT

PURPOSE: Feature maps created from deep convolutional neural networks (DCNNs) have been widely used for visual explanation of DCNN-based classification tasks. However, many clinical applications such as benign-malignant classification of lung nodules normally require quantitative and objective interpretability, rather than just visualization. In this paper, we propose a novel interpretable multi-task attention learning network named IMAL-Net for early invasive adenocarcinoma screening in chest computed tomography images, which takes advantage of segmentation prior to assist interpretable classification. METHODS: Two sub-ResNets are firstly integrated together via a prior-attention mechanism for simultaneous nodule segmentation and invasiveness classification. Then, numerous radiomic features from the segmentation results are concatenated with high-level semantic features from the classification subnetwork by FC layers to achieve superior performance. Meanwhile, an end-to-end feature selection mechanism (named FSM) is designed to quantify crucial radiomic features greatly affecting the prediction of each sample, and thus it can provide clinically applicable interpretability to the prediction result. RESULTS: Nodule samples from a total of 1626 patients were collected from two grade-A hospitals for large-scale verification. Five-fold cross validation demonstrated that the proposed IMAL-Net can achieve an AUC score of 93.8% ± 1.1% and a recall score of 93.8% ± 2.8% for identification of invasive lung adenocarcinoma. CONCLUSIONS: It can be concluded that fusing semantic features and radiomic features can achieve obvious improvements in the invasiveness classification task. Moreover, by learning more fine-grained semantic features and highlighting the most important radiomics features, the proposed attention and FSM mechanisms not only can further improve the performance but also can be used for both visual explanations and objective analysis of the classification results.


Subject(s)
Adenocarcinoma of Lung , Adenocarcinoma , Lung Neoplasms , Adenocarcinoma/diagnostic imaging , Adenocarcinoma of Lung/diagnostic imaging , Humans , Lung Neoplasms/diagnostic imaging , Neural Networks, Computer , Tomography, X-Ray Computed
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