Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge (preprint)

Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway trees remains prohibitively time-consuming. While significant efforts have been made towards enhancing airway modelling, current public-available datasets concentrate on lung diseases with moderate morphological variations. The intricate honeycombing patterns present in the lung tissues of fibrotic lung disease patients exacerbate the challenges, often leading to various prediction errors. To address this issue, the 'Airway-Informed Quantitative CT Imaging Biomarker for Fibrotic Lung Disease 2023' (AIIB23) competition was organized in conjunction with the official 2023 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). The airway structures were meticulously annotated by three experienced radiologists. Competitors were encouraged to develop automatic airway segmentation models with high robustness and generalization abilities, followed by exploring the most correlated QIB of mortality prediction. A training set of 120 high-resolution computerised tomography (HRCT) scans were publicly released with expert annotations and mortality status. The online validation set incorporated 52 HRCT scans from patients with fibrotic lung disease and the offline test set included 140 cases from fibrosis and COVID-19 patients. The results have shown that the capacity of extracting airway trees from patients with fibrotic lung disease could be enhanced by introducing voxel-wise weighted general union loss and continuity loss. In addition to the competitive image biomarkers for prognosis, a strong airway-derived biomarker (Hazard ratio>1.5, p<0.0001) was revealed for survival prognostication compared with existing clinical measurements, clinician assessment and AI-based biomarkers.

Preclinical safety assessment of the suction-assisted intradermal injection of the SARS-CoV-2 DNA vaccine candidate pGO-1002 in white rabbit.

pGO-1002, a non-viral DNA vaccine that expresses both spike and ORF3a antigens of SARS-CoV-2, is undergoing phase 1 and phase 2a clinical trials in Korea and the US. A preclinical repeated-dose toxicity study in New Zealand white rabbits in compliance with Good Laboratory Practice (GLP) was conducted to assess the potential toxicity, local tolerance, and immunogenicity of the vaccine and GeneDerm suction device. The dose rate was 1.2 mg/head pGO-1002, and this was administered intradermally to a group of animals (eight animals/sex/group) three times at 2-week intervals, followed by a 4-week recovery period. After each administration, suction was applied to the injection site using the GeneDerm device. Mortality, clinical signs, body weight, food consumption, skin irritation, ophthalmology, body temperature, urinalysis, and clinical pathology were also monitored. Gross observations and histopathological evaluation were performed. Overall, pGO-1002 administration-related changes were confined to minor damage or changes at the injection site, increased spleen weight and minimal increased cellularity in white pulp. All changes of injection site were considered local inflammatory changes or pharmacological actions due to the vaccine with the changes in spleen considered consistent with vaccine-induced immune activation. All findings showed reversibility during the 4-week recovery period. Animals vaccinated with pGO-1002, administered by intradermal injection and followed by application of suction with GeneDerm, developed humoral and cellular responses against the SARS-CoV-2 antigens consistent with prior studies in rats. Collectively, it was concluded that the pGO-1002 vaccine was safe and effective under these experimental conditions and these data supported future human study of the vaccine, now known as GLS-5310, for clinical trial use.

Lymphocyte–C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission

In this study, we aimed to explore whether lymphocyte–C-reactive protein ratio (LCR) can differentiate disease severity of coronavirus disease 2019 (COVID-19) patients and its value as an assistant screening tool for admission to hospital and intensive care unit (ICU). A total of 184 adult COVID-19 patients from the COVID-19 Treatment Center in Heilongjiang Province at the First Affiliated Hospital of Harbin Medical University between January 2020 and March 2021 were included in this study. Patients were divided into asymptomatic infection group, mild group, moderate group, severe group, and critical group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (ninth edition). Demographic and clinical data including gender, age, comorbidities, severity of COVID-19, white blood cell count (WBC), neutrophil proportion (NEUT%), lymphocyte count (LYMPH), lymphocyte percentage (LYM%), red blood cell distribution width (RDW), platelet (PLT), C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (SCr), albumin (ALB), total bilirubin (TB), direct bilirubin (DBIL), indirect bilirubin (IBIL), and D-dimer were obtained and collated from medical records at admission, from which sequential organ failure assessment (SOFA) score and LCR were calculated, and all the above indicators were compared among the groups. Multiple clinical parameters, including LYMPH, CRP, and LCR, showed significant differences among the groups. The related factors to classify COVID-19 patients into moderate, severe, and critical groups included age, number of comorbidities, WBC, LCR, and AST. Among these factors, the number of comorbidities showed the greatest effect, and only WBC and LCR were protective factors. The area under the receiver operating characteristic (ROC) curve of LCR to classify COVID-19 patients into moderate, severe, and critical groups was 0.176. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 1,780.7050 and 84.6% and 66.2%, respectively. The related factors to classify COVID-19 patients into severe and critical groups included the number of comorbidities, PLT, LCR, and SOFA score. Among these factors, SOFA score showed the greatest effect, and LCR was the only protective factor. The area under the ROC curve of LCR to classify COVID-19 patients into severe and critical groups was 0.106. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 571.2200 and 81.3% and 90.0%, respectively. In summary, LCR can differentiate disease severity of COVID-19 patients and serve as a simple and objective assistant screening tool for hospital and ICU admission.

Accounting Transparency, Fear Sentiment and the COVID-19 Epidemic: For Public Health Security and the Construction of an Early Warning System

A central issue of public health security and the construction of an early warning system is to establish a set of responsibility-oriented incentives and restraint mechanisms. This is closely related to the accounting transparency of the institutional environment and the fear sentiment of the individual's predicament. This study analyses the relationship between accounting transparency, fear sentiment, and COVID-19 through a VAR model analysis. The results show a significant and negative relationship between accounting transparency and daily new COVID-19 patients. In particular, accounting transparency has a negative impact on the increase in the number of people infected with a two-period lag, while the three-period lag in the number of new epidemics has a negative impact on accounting information. Second, accounting transparency has a positive impact on the increase in the search volume on COVID-19 within a three-period lag. After the three-period lag, the number of new epidemics has a positive impact on accounting information. Third, an increase in fear sentiment can be driven by the fear of COVID-19. Fourth, in the public health early warning system, according to the abovementioned time characteristics, the system arranges the emotional counseling, early warning incentives, and institutional constraints to be dealt with in the first 4 days. In addition, in the early warning target-oriented system setting, the parallel system helps to improve the early warning efficiency.

The effect of the COVID-19 pandemic on gendered research productivity and its correlates (preprint)

Female researchers may have experienced more difficulties than their male counterparts since the COVID-19 outbreak because of gendered housework and childcare. Using Microsoft Academic Graph data from 2016 to 2020, this study examined how the proportion of female authors in academic journals on a global scale changed in 2020 (net of recent yearly trends). We observed a decrease in research productivity for female researchers in 2020, mostly as first authors, followed by last author position. Female researchers were not necessarily excluded from but were marginalised in research. We also identified various factors that amplified the gender gap by dividing the authors' backgrounds into individual, organisational and national characteristics. Female researchers were more vulnerable when they were in their mid-career, affiliated to the least influential organisations, and more importantly from less gender-equal countries with higher mortality and restricted mobility as a result of COVID-19.