Newly Characterized Porcine Epidemic Diarrhea Virus GII Subtype Strain

Diarrhea outbreaks in piglets on pig farms are commonly attributed to porcine epidemic diarrhea virus (PEDV) infection. This research analyzed the S gene prevalence variation and recombination patterns in PEDV GII strains. Throughout the previous two years, 172 clinical samples of piglet diarrhea have been collected, from which 24 PEDV isolates have been isolated. Analysis of the evolutionary relationships among all 24 S genes revealed that 21 were most closely related to strains within the GII-a subgroup. The 2 isolates grouped into one clade with the GII-b subgroup. According to the mutation analysis of the amino acids (aa) that encode the S protein, 43 of the common aa in strains of the GII subtype were found to have undergone a change in polarity or charge, and 36 of these aa had a mutation frequency of more than 90%. Three different aa mutation sites were identified as exclusive to GII-a subtype strains. The genomes of three PEDV isolates were sequenced, and the resulting range in genome length was 28,035−28,041 nt. The results of recombination analysis showed that the SD1 isolate is a novel strain recombinant from the foreign S-INDEL strain and a domestic GII subtype strain. Based on the findings, the PEDV GII-a strain has been the most circulating strain in several parts of China during the previous two years. Our study reveals for the first time the unique change of aa mutations in the S protein of the GII-a subtype strain and the new characteristics of the recombination of foreign strains and domestic GII subtype strains, indicating that it is crucial to monitor the epidemic dynamics of PEDV promptly to prevent and control the occurrence of PED effectively.

Location Scheme of Routine Nucleic Acid Testing Sites Based on Location-Allocation Models: A Case Study of Shenzhen City

Since late 2019, the explosive outbreak of Coronavirus Disease 19 (COVID-19) has emerged as a global threat, necessitating a worldwide overhaul of public health systems. One critical strategy to prevent virus transmission and safeguard public health, involves deploying Nucleic Acid Testing (NAT) sites. Nevertheless, determining the optimal locations for public NAT sites presents a significant challenge, due to the varying number of sites required in different regions, and the substantial influences of population, the population heterogeneity, and daily dynamics, on the effectiveness of fixed location schemes. To address this issue, this study proposes a data-driven framework based on classical location-allocation models and bi-objective optimization models. The framework optimizes the number and location of NAT sites, while balancing various cost constraints and adapting to population dynamics during different periods of the day. The bi-objective optimization process utilizes the Knee point identification (KPI) algorithm, which is computationally efficient and does not require prior knowledge. A case study conducted in Shenzhen, China, demonstrates that the proposed framework provides a broader service coverage area and better accommodates residents' demands during different periods, compared to the actual layout of NAT sites in the city. The study's findings can facilitate the rapid planning of primary healthcare facilities, and promote the development of sustainable healthy cities.

The Development of a Counseling Service Questionnaire: Study of Validation and Reliability

The study developed items of a counseling service questionnaire to aid counselors and universities in supporting students ' mental health. The participants of this study were 1,022 Chinese college students from three universities in Thailand. The questionnaire included development items and content validity and reliability testing. The questionnaire contained 17 items covering four aspects: (1) developmental counseling;(2) adaptive counseling;(3) disorder counseling;and (4) intervention in psychological crises. The results showed that the counseling services questionnaire is a valid and reliable instrument that can be used to determine students' mental health.

Insufficient epitope-specific T cell clones are responsible for impaired cellular immunity to inactivated SARS-CoV-2 vaccine in older adults.

Aging is a critical risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine efficacy. The immune responses to inactivated vaccine for older adults, and the underlying mechanisms of potential differences to young adults, are still unclear. Here we show that neutralizing antibody production by older adults took a longer time to reach similar levels in young adults after inactivated SARS-CoV-2 vaccination. We screened SARS-CoV-2 variant strains for epitopes that stimulate specific CD8 T cell response, and older adults exhibited weaker CD8 T-cell-mediated responses to these epitopes. Comparison of lymphocyte transcriptomes from pre-vaccinated and post-vaccinated donors suggested that the older adults had impaired antigen processing and presentation capability. Single-cell sequencing revealed that older adults had less T cell clone expansion specific to SARS-CoV-2, likely due to inadequate immune receptor repertoire size and diversity. Our study provides mechanistic insights for weaker response to inactivated vaccine by older adults and suggests the need for further vaccination optimization for the old population.

A safer and more practical tracheotomy in invasive mechanical ventilated patients with COVID-19: A quality improvement study.

Importance: The number of infections and deaths caused by the global epidemic of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) invasion is steadily increasing daily. In the early stages of outbreak, approximately 15%-20% of patients with coronavirus disease 2019 (COVID-19) inevitably developed severe and critically ill forms of the disease, especially elderly patients and those with several or serious comorbidities. These more severe forms of disease mainly manifest as dyspnea, reduced blood oxygen saturation, severe pneumonia, acute respiratory distress syndrome (ARDS), thus requiring prolonged advanced respiratory support, including high-flow nasal cannula (HFNC), non-invasive mechanical ventilation (NIMV), and invasive mechanical ventilation (IMV). Objective: This study aimed to propose a safer and more practical tracheotomy in invasive mechanical ventilated patients with COVID-19. Design: This is a single center quality improvement study. Participants: Tracheotomy is a necessary and important step in airway management for COVID-19 patients with prolonged endotracheal intubation, IMV, failed extubation, and ventilator dependence. Standardized third-level protection measures and bulky personal protective equipment (PPE) may hugely impede the implementation of tracheotomy, especially when determining the optimal pre-surgical positioning for COVID-19 patients with ambiguous surface position, obesity, short neck or limited neck extension, due to vision impairment, reduced tactile sensation and motility associated with PPE. Consequently, the aim of this study was to propose a safer and more practical tracheotomy, namely percutaneous dilated tracheotomy (PDT) with delayed endotracheal intubation withdrawal under the guidance of bedside ultrasonography without the conventional use of flexible fiberoptic bronchoscopy (FFB), which can accurately determine the optimal pre-surgical positioning, as well as avoid intraoperative damage of the posterior tracheal wall and prevent the occurrence of tracheoesophageal fistula (TEF).

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.

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.

Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been far more devastating than expected, showing no signs of slowing down at present. Heilongjiang Province is the most northeastern province of China, and has cold weather for nearly half a year and an annual temperature difference of more than 60ºC, which increases the underlying morbidity associated with pulmonary diseases, and thus leads to lung dysfunction. The demographic features and laboratory parameters of COVID-19 deceased patients in Heilongjiang Province, China with such climatic characteristics are still not clearly illustrated. AIM: To illustrate the demographic features and laboratory parameters of COVID-19 deceased patients in Heilongjiang Province by comparing with those of surviving severe and critically ill cases. METHODS: COVID-19 deceased patients from different hospitals in Heilongjiang Province were included in this retrospective study and compared their characteristics with those of surviving severe and critically ill cases in the COVID-19 treatment center of the First Affiliated Hospital of Harbin Medical University. The surviving patients were divided into severe group and critically ill group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (the seventh edition). Demographic data were collected and recorded upon admission. Laboratory parameters were obtained from the medical records, and then compared among the groups. RESULTS: Twelve COVID-19 deceased patients, 27 severe cases and 26 critically ill cases were enrolled in this retrospective study. No differences in age, gender, and number of comorbidities between groups were found. Neutrophil percentage (NEUT%), platelet (PLT), C-reactive protein (CRP), creatine kinase isoenzyme (CK-MB), serum troponin I (TNI) and brain natriuretic peptides (BNP) showed significant differences among the groups (P = 0.020, P = 0.001, P < 0.001, P = 0.001, P < 0.001, P < 0.001, respectively). The increase of CRP, D-dimer and NEUT% levels, as well as the decrease of lymphocyte count (LYMPH) and PLT counts, showed significant correlation with death of COVID-19 patients (P = 0.023, P = 0.008, P = 0.045, P = 0.020, P = 0.015, respectively). CONCLUSION: Compared with surviving severe and critically ill cases, no special demographic features of COVID-19 deceased patients were observed, while some laboratory parameters including NEUT%, PLT, CRP, CK-MB, TNI and BNP showed significant differences. COVID-19 deceased patients had higher CRP, D-dimer and NEUT% levels and lower LYMPH and PLT counts.

Porcine epidemic diarrhea virus strain FJzz1 infection induces type I/III IFNs production through RLRs and TLRs-mediated signaling.

Interferons (IFNs) including type I/III IFNs are the major components of the host innate immune response against porcine epidemic diarrhea virus (PEDV) infection, and several viral proteins have been identified to antagonize type I/III IFNs productions through diverse strategies. However, the modulation of PEDV infection upon the activation of the host's innate immune response has not been fully characterized. In this study, we observed that various IFN-stimulated genes (ISGs) were upregulated significantly in a time- and dose-dependent manner in LLC-PK1 cells infected with the PEDV G2 strain FJzz1. The transcriptions of IRF9 and STAT1 were increased markedly in the late stage of FJzz1 infection and the promotion of the phosphorylation and nuclear translocation of STAT1, implicating the activation of the JAK-STAT signaling pathway during FJzz1 infection. In addition, abundant type I/III IFNs were produced after FJzz1 infection. However, type I/III IFNs and ISGs decreased greatly in FJzz1-infected LLC-PK1 cells following the silencing of the RIG-I-like receptors (RLRs), including RIG-I and MDA5, and the Toll-like receptors (TLRs) adaptors, MyD88 and TRIF. Altogether, FJzz1 infection induces the production of type-I/III IFNs in LLC-PK1 cells, in which RLRs and TLRs signaling pathways are involved, followed by the activation of the JAK-STAT signaling cascade, triggering the production of numerous ISGs to exert antiviral effects of innate immunity.

Assessing personal exposure to COVID-19 transmission in public indoor spaces based on fine-grained trajectory data: A simulation study.

The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to worldwide health systems in quick response to epidemics. The assessment of personal exposure to COVID-19 in enclosed spaces is critical to identifying potential infectees and preventing outbreaks. However, traditional contact tracing methods rely heavily on a manual interview, which is costly and time consuming given the large population involved. With advanced indoor localisation techniques, it is possible to collect people's footprints accurately by locating their smartphones. This study presents a new framework for the assessment of personal exposure to COVID-19 carriers using their fine-grained trajectory data. An integral model was established to quantify the exposure risk, in which the spatial and temporal decay effects are simultaneously considered when modelling the airborne transmission of COVID-19. Regarding the obstacle effect of the indoor layout on airborne transmission, a weight graph based on the space syntax technique was further introduced to constrain the transmission strength between subspaces that are less inter-visible. The proposed framework was demonstrated by a simulation study, in which external comparison and internal analysis were conducted to justify its validity and robustness in different scenarios. Our method is expected to promote the efficient identification of potential infectees and provide an extensible spatial-temporal model to simulate different control measures and examine their effectiveness in a built environment.