Serum banks for serological survey of SARS-CoV-2 and emerging infectious diseases (preprint)

In June 2021, Udom et al. published their article in  Transboundary and Emerging Diseases performing a serological survey revealed evidence of anti-N-IgG antibodies suggesting SARS-CoV-2 exposure in both dogs and cats during the first and second coronavirus disease 2019 (COVID-19) outbreaks in Thailand. Seroprevalence studies have proven an important tool to monitor the progression of the COVID-19 pandemic. The duration of immunity of SARS-CoV-2 is crucial for the course of the pandemic and for this reason the monitoring of antibodies against SARS-CoV-2 is important. The serum samples from different periods and regions were valuable in terms of scientific significance for serological survey of SARS-CoV-2 and emerging infectious diseases. In order to preserve the remaining serum samples and ensure the stability of anti-virus antibodies in storage serum samples, we strongly suggest that standard serum banks should be established worldwide.

Robust Evidence C-Means Clustering Combining Spatial Information for Image Segmentation (preprint)

Although evidence c-means clustering (ECM) based on evidence theory overcomes the limitations of fuzzy theory to some extent and improves the capability of fuzzy c-means clustering (FCM) to express and process the uncertainty of information, the ECM does not consider the spatial information of pixels, which makes it to be unable to effectively deal with noise pixels. Applying ECM directly to image segmentation cannot obtain satisfactory results. This paper proposes a robust evidence c-means clustering combining spatial information for image segmentation algorithm. Firstly, an adaptive noise distance is constructed by using the local information of pixels to improve the ability to detect noise points. Secondly, the pixel’s original, local and non-local information are introduced into the objective function through adaptive weights to enhance the robustness to noise. Then, the entropy of pixel membership degree is used to design an adaptive parameter to solve the problem of distance parameter selection in credal c-means clustering (CCM). Finally, the Dempster’s rule of combination was improved by introducing spatial neighborhood information, which is used to assign the pixels belonging to the meta-cluster and the noise cluster into the singleton cluster. Experiments on synthetic images, real images and remote sensing SAR images demonstrate that the proposed algorithm not only suppress noise effectively, but also retain the details of the image. Both the segmentation visual effect and evaluation indexes indicate its effectiveness in image segmentation.

The Alleviation of LPS-Induced Murine Acute Lung Injury by GSH-Mediated PEGylated Artesunate Prodrugs

Acute lung injury (ALI) or its aggravated stage acute respiratory distress syndrome (ARDS) is a common severe clinical syndrome in intensive care unit, may lead to a life-threatening form of respiratory failure, resulting in high mortality up to 30–40% in most studies. Nanotechnology-mediated anti-inflammatory therapy is an emerging novel strategy for the treatment of ALI, has been demonstrated with unique advantages in solving the dilemma of ALI drug therapy. Artesunate (ART), a derivative of artemisinin, has been reported to have anti-inflammatory effects. Therefore, in the present study, we designed and synthesized PEGylated ART prodrugs and assessed whether ART prodrugs could attenuate lipopolysaccharide (LPS) induced ALI in vitro and in vivo. All treatment groups were conditioned with ART prodrugs 1 h before challenge with LPS. Significant increased inflammatory cytokines production and decreased GSH levels were observed in the LPS stimulated mouse macrophage cell line RAW264.7. Lung histopathological changes, lung W/D ratio, MPO activity and total neutrophil counts were increased in the LPS-induced murine model of ALI via nasal administration. However, these results can be reversed to some extent by treatment of ART prodrugs. The effectiveness of mPEG2k-SS-ART in inhibition of ALI induced by LPS was confirmed. In conclusion, our results demonstrated that the ART prodrugs could attenuate LPS-induced ALI effectively, and mPEG2k-SS-ART may serve as a novel strategy for treatment of inflammation induced lung injury.

Guideline for diagnosis and treatment of spine trauma in the epidemic of COVID-19.

Outbreak of COVID-19 is ongoing all over the world. Spine trauma is one of the most common types of trauma and will probably be encountered during the fight against COVID-19 and resumption of work and production. Patients with unstable spine fractures or continuous deterioration of neurological function require emergency surgery. The COVID-19 epidemic has brought tremendous challenges to the diagnosis and treatment of such patients. To coordinate the diagnosis and treatment of infectious disease prevention and spine trauma so as to formulate a rigorous diagnosis and treatment plan and to reduce the disability and mortality of the disease, multidisciplinary collaboration is needed. This expert consensus is formulated in order to (1) prevent and control the epidemic, (2) diagnose and treat patients with spine trauma reasonably, and (3) reduce the risk of cross-infection between patients and medical personnel during the treatment.

The Prevalence of Mental Health Problems and Associated Risk Factors among Military Health Workers of COVID-19 Specialized Hospitals in Wuhan, China: A Cross-Sectional Survey (preprint)

Background China has been severely affected by COVID-19 (Coronavirus Disease 2019) since December 2019.In the combat against COVID-19, military health workers in China suffered from many pressures. This study aimed to investigate the current psychological status and risk factors of the military health workers.Methods Using a web-based cross-sectional survey, we collected data from 194 military health workers from three inpatient wards in two COVID-19 specialized hospitals. The survey questions consisted of demographic information, Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-15 (PHQ-15). Hierarchical regression analysis was used to explore potential risk factors for mental health problem.Results The overall prevalence of depressive symptoms, generalized anxiety and somatic symptoms were37.6%, 32.5% and 50%, respectively. Severe depression, generalized anxiety and somatic symptoms was 5.2%, 3.6% and 15.5%. In 22.7% of cases, comorbidities existed between depression, generalized anxiety and somatization. Junior-grade professional title was associated with depression, older age was associated with generalized anxiety and somatization, and less sleep duration and poor sleep quality were associated with all three symptoms.Conclusion The prevalence of depression, generalized anxiety and somatic symptoms were high in military health workers of COVID-19 specialized hospitals during the COVID-19 outbreak. Junior-grade professional title, older age, less sleep duration, and poor sleep quality have significant effects on the mental health of military health workers. Continuous surveillance and monitoring of the psychological consequences of the COVID-19outbreak should become routine to promote the mental health of military health workers.