A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics.

During the diagnostic process, clinicians leverage multimodal information, such as the chief complaint, medical images and laboratory test results. Deep-learning models for aiding diagnosis have yet to meet this requirement of leveraging multimodal information. Here we report a transformer-based representation-learning model as a clinical diagnostic aid that processes multimodal input in a unified manner. Rather than learning modality-specific features, the model leverages embedding layers to convert images and unstructured and structured text into visual tokens and text tokens, and uses bidirectional blocks with intramodal and intermodal attention to learn holistic representations of radiographs, the unstructured chief complaint and clinical history, and structured clinical information such as laboratory test results and patient demographic information. The unified model outperformed an image-only model and non-unified multimodal diagnosis models in the identification of pulmonary disease (by 12% and 9%, respectively) and in the prediction of adverse clinical outcomes in patients with COVID-19 (by 29% and 7%, respectively). Unified multimodal transformer-based models may help streamline the triaging of patients and facilitate the clinical decision-making process.

Canadian SARS-CoV-2 serological survey using antenatal serum samples: a retrospective seroprevalence study.

BACKGROUND: Insufficient data on the rate and distribution of SARS-CoV-2 infection in Canada has presented a substantial challenge to the public health response to the COVID-19 pandemic. Our objective was to assess SARS-CoV-2 seroprevalence in a representative sample of pregnant people throughout Canada, across multiple time points over 2 years of the pandemic, to describe the seroprevalence and show the ability of this process to provide prevalence estimates. METHODS: This Canadian retrospective serological surveillance study used existing serological prenatal samples across 10 provinces over multiple time periods: Feb. 3-21, 2020; Aug. 24-Sept. 11, 2020; Nov. 16-Dec. 4, 2020; Nov. 15-Dec. 3, 2021; and results from the province of British Columbia during a period in which the SARS-CoV-2 B.1.1.529 (Omicron) variant was predominant, from Nov. 15, 2021, to June 11, 2022. Age and postal code administrative data allowed for comparison with concurrent polymerase chain reactivity (PCR)-positive results collected by Statistics Canada and the Canadian Surveillance of COVID-19 in Pregnancy (CANCOVID-Preg) project. RESULTS: Seropositivity in antenatal serum as early as February 2020 indicates SARS-CoV-2 transmission before the World Health Organization's declaration of the pandemic. Seroprevalence in our sample of pregnant people was 1.84 to 8.90 times higher than the recorded concurrent PCR-positive prevalence recorded among females aged 20-49 years in November-December 2020. Overall seropositivity in our sample of pregnant people was low at the end of 2020, increasing to 15% in 1 province by the end of 2021. Seroprevalence among pregnant people in BC during the Omicron period increased from 5.8% to 43% from November 2021 to June 2022. INTERPRETATION: These results indicate widespread vulnerability to SARS-CoV-2 infection before vaccine availability in Canada. During the time periods sampled, public health tracking systems were under-reporting infections, and seroprevalence results during the Omicron period indicate extensive community spread of SARS-CoV-2 infection.

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics† † Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d2na00608a

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening. This review summarizes the integration of machine learning with surface-enhanced Raman scattering and infrared absorption in terms of concepts, processes, and applications, and provides an outlook on the future development of this technology.

Influencing factors of medical device-related pressure ulcers in medical personnel during the COVID-19 pandemic: A systematic review and meta-analysis.

OBJECTIVE: To determine the influencing factors of medical device related pressure injury (MDRPU) in medical staff by meta-analysis. METHODS: A comprehensive literature search was conducted by PubMed, Embase, Cochrane Library, Web of Science, CNKI, VIP, CBM, and WanFang Data (from inception to July 27, 2022). Two researchers independently performed literature screening, quality evaluation and data extraction, and meta-analysis was conducted with RevMan 5.4 and Stata12.0 software. RESULTS: Total of 11215 medical staff were included in 9 articles. Meta analysis showed that gender, occupation, sweating, wearing time, single working time, department of COVID-19, preventive measures, and level 3 PPE were the risk factors for MDRPU in medical staff (P < 0.05). CONCLUSION: The outbreak of COVID-19 led to the occurrence of MDRPU among medical staff, and the influencing factors should be focused on. The medical administrator can further improve and standardize the preventive measures of MDRPU according to the influencing factors. Medical staff should accurately identify high-risk factors in the clinical work process, implement intervention measures, and reduce the incidence of MDRPU.

The SARS-CoV-2 nucleocapsid protein: its role in the viral life cycle, structure and functions, and use as a potential target in the development of vaccines and diagnostics.

Coronavirus disease 2019 (COVID-19) continues to take a heavy toll on personal health, healthcare systems, and economies around the globe. Scientists are expending tremendous effort to develop diagnostic technologies for detecting positive infections within the shortest possible time, and vaccines and drugs specifically for the prevention and treatment of COVID-19 disease. At the same time, emerging novel variants have raised serious concerns about vaccine efficacy. The SARS-CoV-2 nucleocapsid (N) protein plays an important role in the coronavirus life cycle, and participates in various vital activities after virus invasion. It has attracted a large amount of attention for vaccine and drug development. Here, we summarize the latest research of the N protein, including its role in the SARS-CoV-2 life cycle, structure and function, and post-translational modifications in addition to its involvement in liquid-liquid phase separation (LLPS) and use as a basis for the development of vaccines and diagnostic techniques.

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics.

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.

Identification and assessment of TCR-T cells targeting an epitope conserved in SARS-CoV-2 variants for the treatment of COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) continues to be a major global public health challenge, with the emergence of variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Current vaccines or monoclonal antibodies may not well be protect against infection with new SARS-CoV-2 variants. Unlike antibody-based treatment, T cell-based therapies such as TCR-T cells can target epitopes that are highly conserved across different SARS-CoV-2 variants. Reportedly, T cell-based immunity alone can restrict SARS-CoV-2 replication. METHODS: In this study, we identified two TCRs targeting the RNA-dependent RNA polymerase (RdRp) protein in CD8 + T cells. Functional evaluation by transducing these TCRs into CD8 + or CD4 + T cells confirmed their specificity. RESULTS: Combinations of inflammatory and anti-inflammatory cytokines secreted by CD8 + and CD4 + T cells can help control COVID-19 in patients. Moreover, the targeted epitope is highly conserved in all emerged SARS-CoV-2 variants, including the Omicron. It is also conserved in the seven coronaviruses that infect humans and more broadly in the subfamily Coronavirinae. CONCLUSIONS: The pan-genera coverage of mutant epitopes from the Coronavirinae subfamily by the two TCRs highlights the unique strengths of TCR-T cell therapies in controlling the ongoing pandemic and in preparing for the next coronavirus outbreak.

Human-to-human transmission of Chlamydia psittaci in China, 2020: an epidemiological and aetiological investigation.

BACKGROUND: Chlamydia psittaci can infect a wide range of avian species, occasionally causing psittacosis (also known as parrot fever) in humans. Most human psittacosis cases are associated with close contact with pet birds or poultry. In December, 2020, an outbreak of severe community-acquired pneumonia of unknown aetiology was reported in a hospital in Shandong province, China, and some of the patients' close contacts had respiratory symptoms. Our aims were to determine the causative agent of this epidemic and whether there had been human-to-human transmission. METHODS: For this epidemiological and aetiological investigation study, we enrolled patients who had community-acquired pneumonia confirmed by chest CT at two local hospitals in Shandong Province in China. We collected sputum, bronchoalveolar lavage fluid, and nasopharyngeal swab samples from participants and detected pathogens by surveying for 22 target respiratory microbes using a commercial assay, followed by metagenomic next-generation sequencing, specific nested PCR, and qPCR tests. We excluded individuals who were C psittaci-negative on both tests. We recruited close contacts of the C psittaci-positive patients, and tested nasopharyngeal swabs from the close contacts and samples from ducks from the processing plant where these patients worked. We then integrated the epidemiological, clinical, and laboratory data to reveal the potential chain of transmission of C psittaci that characterised this outbreak. FINDINGS: Between Dec 4 and 29, 2020, we used metagenomic next-generation sequencing and different PCR-based approaches to test 12 inpatients with community-acquired pneumonia, of whom six (50%) were workers at a duck-meat processing plant and two (17%) were unemployed people, who were positive for C psittaci and enrolled in this study. We contacted 61 close contacts of the six patients who worked at the duck-meat processing plant, of whom 61 (100%) were enrolled and tested, and we determined that the community-acquired pneumonia outbreak was caused by C psittaci. Within the outbreak cluster, 17 (77%) of 22 participants had confirmed C psittaci infections and five (23%) of 22 participants were asymptomatic C psittaci carriers. The outbreak had begun with avian-to-human transmission, and was followed by secondary and tertiary human-to-human transmission, which included transmission by several asymptomatic carriers and by health-care workers. In addition, some of the participants with confirmed C psittaci infection had no identified source of infection, which suggested cryptic bacterial transmission. INTERPRETATION: Our study data might represent the first documented report of human-to-human transmission of C psittaci in China. Therefore, C psittaci has the potential to evolve human-to-human transmission via various routes, should be considered an elevated biosecurity and emergent risk, and be included as part of the routine diagnosis globally, especially for high-risk populations. FUNDING: Academic Promotion Programme of Shandong First Medical University, National Science and Technology Major Project, ARC Australian Laureate Fellowship.

Identification and assessment of TCR-T cells targeting an epitope conserved in SARS-CoV-2 variants for the treatment of COVID-19

Background Coronavirus disease 2019 (COVID-19) continues to be a major global public health challenge, with the emergence of variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Current vaccines or monoclonal antibodies may not well be protect against infection with new SARS-CoV-2 variants. Unlike antibody-based treatment, T cell-based therapies such as TCR-T cells can target epitopes that are highly conserved across different SARS-CoV-2 variants. Reportedly, T cell-based immunity alone can restrict SARS-CoV-2 replication. Methods In this study, we identified two TCRs targeting the RNA-dependent RNA polymerase (RdRp) protein in CD8+ T cells. Functional evaluation by transducing these TCRs into CD8+ or CD4+ T cells confirmed their specificity. Results Combinations of inflammatory and anti-inflammatory cytokines secreted by CD8+ and CD4+ T cells can help control COVID-19 in patients. Moreover, the targeted epitope is highly conserved in all emerged SARS-CoV-2 variants, including the Omicron. It is also conserved in the seven coronaviruses that infect humans and more broadly in the subfamily Coronavirinae. Conclusions The pan-genera coverage of mutant epitopes from the Coronavirinae subfamily by the two TCRs highlights the unique strengths of TCR-T cell therapies in controlling the ongoing pandemic and in preparing for the next coronavirus outbreak.

Effect on implant drills and postoperative reactions for pre-extraction interradicular implant bed preparation during the COVID-19 pandemic and beyond.

The aim of the present study was to observe the abrasion of implant drills and postoperative reactions for the preparation of the interradicular immediate implant bed during the COVID-19 pandemic and beyond. Thirty-two implant drills were included in four groups: blank, improved surgery, traditional surgery, and control. In the improved surgery group, a dental handpiece with a surgical bur was used to decoronate the first molar and create a hole in the middle of the retained root complex, followed by the pilot drilling protocol through the hole. The remaining root complex was separated using a surgical bur and then extracted. Subsequently, the implant bed was prepared. Implant drills were used in the traditional surgery group to complete the decoronation, hole creation, and implant-drilling processes. The tooth remained intact until the implant bed was prepared. The surface roughness of the pilot drill was observed and measured. Surgery time, postoperative reactions (swelling, pain, and trismus), and fear of coronavirus disease 2019 scale (FCV-19S) were measured and recorded, respectively. Statistical analysis revealed significant difference with surface roughness among blank group (0.41 ± 0.05 µm), improved surgery group (0.37 ± 0.06 µm), traditional surgery group (0.16 ± 0.06 µm), and control group (0.26 ± 0.04 µm) (P < .001). Significant differences were revealed with surgery time between improved surgery group (5.63 ± 1.77 min) and traditional surgery group (33.63 ± 2.13 min) (P < .001). Swelling, pain, and trismus (improved group: r ≥ 0.864, P ≤ .006; traditional group: r ≥ 0.741, P ≤ .035) were positively correlated with the FCV-19S. This study proved that a new pilot drill could only be used once in traditional surgery but could be used regularly in improved surgery. Improved surgery was more effective, efficient, and economical than the traditional surgery. The higher FCV-19S, the more severe swelling, pain, and trismus.

Incentives to Enhance Production Reliability against Disruption: Cost-Sharing vs. Penalty

Two kinds of incentive strategies, cost-sharing and penalty, are examined in dealing with production disruption, with consideration of production process reliability as an endogenous factor for a two-echelon supply chain. Based on the Stackelberg game framework, we derive the optimal decisions of supply chain partners and compare their expected profits with different strategies. Considering the uncertain demand and the retailer’s preference against the risk, we further analyze how the partners’ decisions and the retailer’s expected profit are influenced by the feature of loss aversion. From theoretical analysis and numerical experiments, we find that: (1) overall, a penalty strategy dominates that of cost-sharing for the retailer, whereas the reverse applies with respect to the manufacturer;(2) a penalty strategy may outperform a cost-sharing strategy for the whole supply chain, depending on demand;and (3) a reasonable aversion against risk can help the retailer to achieve a more robust result when a penalty strategy is adopted under volatile and unpredictable demand.

Application of serum antibody detection in the identification of transmission chain of COVID-19

Objective: To explore the transmission chain of COVID-19 by serum antibody detection, and to provide scientific evidence for the prevention and control of the epidemic.

Virtual Reality in Treatment for Psychological Problems in First-Line Health Care Professionals Fighting COVID-19 Pandemic: A Case Series.

ABSTRACT: Virtual reality therapy (VRT) is a new psychotherapeutic approach integrating virtual reality technology and psychotherapy. This case series aimed to study effectiveness of VRT in treating psychological problems. We described four cases of first-line health care professionals with emerging clinically significant early psychological problems during the COVID-19 outbreak, and specifically received the VRT treatment. We compared the Patient Health Questionnaire 9 items (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), PHQ-15, and Athens Insomnia Scale to evaluate psychological symptoms and sleep quality before and after sessions. All four cases showed a reduction in scale comparison. General scores of the PHQ-9 reduced 65%, GAD-7 reduced 52.17%, PHQ-15 decreased 38.17%, and scores of the Athens Insomnia Scale reduced 67.44%. Meanwhile, a reduction in depression, anxiety, psychosomatic, and sleeping symptoms was also found, which decreased 76.92% in general. These results are highly significant statistically. This case series demonstrated the effectiveness of VRT on psychological problems as a promising approach to apply on various psychological distress and disorders.

Hypertension Exacerbates Severity and Outcomes of COVID-19 in Elderly Patients: A Retrospective Observational Study.

OBJECTIVE: To evaluate the impact of hypertension on the clinical outcome of COVID-19 patients aged 60 years old and older. METHODS: This single-center retrospective cohort study enrolled consecutive COVID-19 patients aged 60 years old and older, who were admitted to Liyuan Hospital from January 1, 2020 to April 25, 2020. All included patients were divided into two groups: hypertension and nonhypertension group. The baseline demographic characteristics, laboratory test results, chest computed tomography (CT) images and clinical outcomes were collected and analyzed. The prognostic value of hypertension was determined using binary logistic regression. RESULTS: Among the 232 patients included in the analysis, 105 (45.3%) patients had comorbid hypertension. Compared to the nonhypertension group, patients in the hypertension group had higher neutrophil-to-lymphocyte ratios, red cell distribution widths, lactate dehydrogenase, high-sensitivity C-reactive protein, D-dimer and severity of lung lesion, and lower lymphocyte counts (all P<0.05). Furthermore, the hypertension group had a higher proportion of intensive care unit admissions [24 (22.9%) vs. 14 (11.0%), P=0.02) and deaths [16 (15.2%) vs. 3 (2.4%), P<0.001] and a significantly lower probability of survival (P<0.001) than the nonhypertension group. Hypertension (OR: 4.540, 95% CI: 1.203-17.129, P=0.026) was independently correlated with all-cause in-hospital death in elderly patients with COVID-19. CONCLUSION: The elderly COVID-19 patients with hypertension tend to have worse conditions at baseline than those without hypertension. Hypertension may be an independent prognostic factor of poor clinical outcome in elderly COVID-19 patients.

Analysis of epidemic characteristics of COVID-19 clusters in Chenzhou, Hunan Province

Objective: To analyze the epidemiological characteristics of 8 clusters of coronavirus disease 2019 (COVID-19) in Chenzhou City, and provide scientific basis for epidemic prevention and control.

Advances in Pathogenesis, Progression, Potential Targets and Targeted Therapeutic Strategies in SARS-CoV-2-Induced COVID-19.

As the new year of 2020 approaches, an acute respiratory disease quietly caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as coronavirus disease 2019 (COVID-19) was reported in Wuhan, China. Subsequently, COVID-19 broke out on a global scale and formed a global public health emergency. To date, the destruction that has lasted for more than two years has not stopped and has caused the virus to continuously evolve new mutant strains. SARS-CoV-2 infection has been shown to cause multiple complications and lead to severe disability and death, which has dealt a heavy blow to global development, not only in the medical field but also in social security, economic development, global cooperation and communication. To date, studies on the epidemiology, pathogenic mechanism and pathological characteristics of SARS-CoV-2-induced COVID-19, as well as target confirmation, drug screening, and clinical intervention have achieved remarkable effects. With the continuous efforts of the WHO, governments of various countries, and scientific research and medical personnel, the public's awareness of COVID-19 is gradually deepening, a variety of prevention methods and detection methods have been implemented, and multiple vaccines and drugs have been developed and urgently marketed. However, these do not appear to have completely stopped the pandemic and ravages of this virus. Meanwhile, research on SARS-CoV-2-induced COVID-19 has also seen some twists and controversies, such as potential drugs and the role of vaccines. In view of the fact that research on SARS-CoV-2 and COVID-19 has been extensive and in depth, this review will systematically update the current understanding of the epidemiology, transmission mechanism, pathological features, potential targets, promising drugs and ongoing clinical trials, which will provide important references and new directions for SARS-CoV-2 and COVID-19 research.

The Role of the Vascular Niche in Organ Fibrosis and COVID-19-Related Organ Damage and the Countermeasures adopted by Chinese and Western Medicine

The vascular niche is a microenvironment located around capillaries and is mainly composed of endothelial cells, pericytes, macrophages, lymphocytes, mesenchymal stem cells, and hematopoietic stem cells. Studies have found that the vascular niche not only functions to regulate cell growth and differentiation in normal tissues, but also has an important role in regulating fibrosis in various organs and tissues in disease states. Coronavirus disease 2019 (COVID-19) is a systemic disease that broke out in 2019, caused by SARS-CoV-2 infection, which results in pulmonary inflammation, systemic multi-organ damage, and an inflammatory cytokine storm. Recently, the vascular niche has been found to play a role in COVID-19-related multi-organ damage. In this review, we introduce the important role of the vascular niche in organ fibrosis and COVID-19-related organ damage, summarize some of the cellular signaling pathways in the vascular niche that promote fibrosis, and discuss the treatment of organ fibrosis in Traditional Chinese medicine and Western medicine.

SARS-CoV-2, SARS-CoV, and MERS-CoV encode circular RNAs of spliceosome-independent origin.

Circular RNAs (circRNAs) are a newly recognized component of the transcriptome with critical roles in autoimmune diseases and viral pathogenesis. To address the importance of circRNA in RNA viral transcriptome, we systematically identified and characterized circRNAs encoded by the RNA genomes of betacoronaviruses using both bioinformatical and experimental approaches. We predicted 351, 224, and 2764 circRNAs derived from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), SARS-CoV, and Middle East respiratory syndrome coronavirus, respectively. We experimentally identified 75 potential SARS-CoV-2 circRNAs from RNA samples extracted from SARS-CoV-2-infected Vero E6 cells. A systematic comparison of viral and host circRNA features, including abundance, strand preference, length distribution, circular exon numbers, and breakpoint sequences, demonstrated that coronavirus-derived circRNAs had a spliceosome-independent origin. We further showed that back-splice junctions (BSJs) captured by inverse reverse-transcription polymerase chain reaction have different level of resistance to RNase R. Through northern blotting with a BSJ-spanning probe targeting N gene, we identified three RNase R-resistant bands that represent SARS-CoV-2 circRNAs that are detected cytoplasmic by single-molecule and amplified fluorescence in situ hybridization assays. Lastly, analyses of 169 sequenced BSJs showed that both back-splice and forward-splice junctions were flanked by homologous and reverse complementary sequences, including but not limited to the canonical transcriptional regulatory sequences. Our findings highlight circRNAs as an important component of the coronavirus transcriptome, offer important evaluation of bioinformatic tools in the analysis of circRNAs from an RNA genome, and shed light on the mechanism of discontinuous RNA synthesis.