Loneliness during the last phase of the COVID-19 pandemic in China: Trajectories, predictors, and impact on adolescent mental health (preprint)

Background Little is known about the long-term courses of loneliness, associated risk factors and effect on mental health in adolescents during the COVID-19 pandemic. This study aimed to explore the trajectories of loneliness among Chinese adolescents during the last phase of the pandemic. We also aimed to identify risk factors in each loneliness course and the impact of loneliness on emotional problems, peer problems, hyperactivity and conduct problems. Methods  We conducted longitudinal analyses using four waves of data from 2347 Chinese adolescents covering a period of 20 months (October 2021 – May 2023). Loneliness was assessed using the UCLA 3-Item Loneliness Scale. The self-reported version of the Strengths and Difficulties Questionnaire was utilized to evaluate participants’ mental health outcomes. Growth mixture modelling was employed to identify latent classes of loneliness trajectories. Associated risk factors were investigated using multinomial logistic regression model. Mixed-effects logistic regression models were constructed to examine the long-term impact of loneliness classes on mental health outcomes. Results Three courses of loneliness were identified: Decreasing Low Loneliness (58.71%), Increasing Medium Loneliness (36.52%), and Increasing High Loneliness (4.77%). Risk factors for poorer loneliness trajectories included lack of physical exercise habits, poorer mental health literacy, medium or low perceived social support, having study difficulties, being female, higher grades, and lower economic status. Loneliness courses were associated with the severity and variability of emotional problems, peer problems, hyperactivity and conduct problems. Individuals in the higher loneliness classes experienced a significant increase in these mental health problems over time. Conclusions  During the last phase of the pandemic, a large proportion of adolescents in our study endured medium to high levels of loneliness with no signs of improvement. Both unfavorable loneliness trajectories adversely affected internalizing and externalizing problems and displayed an upward trend in these difficulties. Results highlight the importance of considering how to tackle loneliness both within the context of COVID-19 and more generally.

Leukopenia of Asymptomatic COVID-19 Infections under 18 Years Old in Recovery Stage (Running head: Leukopenia of Asymptomatic COVID-19 Infections) (preprint)

Objectives In December, 2019, a type of novel coronavirus which was designated novel coronavirus 2019 (2019-nCoV) by the World Health Organization (WHO) occurred in Wuhan, Hubei, China. There is limited information available on the epidemiological and clinical characteristics of patients under 18 years old in the recovery stage. To compare the difference of epidemiological and clinical characteristics of COVID-19 involving 25 patients under 18 years old in the recovery stage between confirmed and asymptomatic infections.Methods The retrospective, single-center cohort study of COVID-19 involving 25 patients under 18 years old in the recovery stage at Guizhou Provincial Staff Hospital in Guiyang, China, from January 29 to March 31, 2020; last date of follow-up was April 22. We collected and analyzed epidemiological, demographic, clinical, laboratory, radiological, and treatment data. The researchers compared the epidemiological and clinical characteristics of confirmed COVID-19 infections and asymptomatic infections.Results Among the 25 COVID infections under 18 years old, 16 (64%) were mild or moderate confirmed cases, and 9 (36%) were asymptomatic. The shortest treatment period was 6 days, the longest 26 days, and the average treatment period was 14 days. Four cases (44.4%) had visited Wuhan or had a living story in the city. There were 9 (100%) asymptomatic cases were familial cluster outbreak, with an average infection number was 6 cases among all families. The number of asymptomatic COVID-19 infections with leukopenia was significantly more than confirmed cases (p = 0.04).Conclusions Leukopenia mostly occurred in asymptomatic COVID-19 infections under 18 years old compared with the confirmed patients.Trial registration: The Chinese Clinical Trial Register (CCTR number: ChiCTR2000032458) registered this study retrospectively on 28 April 2020.

Analysis of Medication Utilization in Isolated Areas of Fever Clinics During the COVID-19 Epidemic Outbreak: A Multicenter Study in General Hospitals in China (preprint)

Objective: To analyze the demographic characteristics and patterns of medication use among patients in fever clinics (FCs) during the COVID-19 outbreak in China and provide information for COVID-19 treatment. Method: Various-grade general hospitals in China were selected, and patient information was extracted during the initial wave of the COVID-19 epidemic. Demographic characteristics were analyzed, including visit time, age, sampling morbidity rate, and disease distribution. Prescription information from the FC database was extracted to analyze drug use and the rationality of the medication. Result: Between September 1 and December 31, 2022, 41,445 patients received treatment at FCs in 11 included hospitals. After the relaxation of COVID-19 control measures, there was a rapid increase in the number of daily patient visits (peaking >1,000 people/day, with a growth rate of 158.8%). The highest sampling morbidity rate was observed among individuals over 85 years old (>100 person-times/million population), followed by children (60-94 person-times/million population). Respiratory system diseases (39,295 cases) were the most diagnosed, with respiratory system infections (21,201 cases) and fever (15,132 cases) the most common. The proportion and frequency of use of essential national drugs were 34.3% and 73.1%, respectively, while those for the drugs recommended in the national COVID-19 treatment guidelines were 6.1% and 43.2%, respectively. Ibuprofen, acetaminophen, and Lianhua Qingwen had the highest frequency of drug use. The most prescribed drugs by cost were immunoglobulin, azivudine, and cefoperazone sulbactam. The water-electrolyte balance regulator drugs, respiratory system drugs, anti-infective drugs, and traditional Chinese patent drugs were the most frequently used. In contrast, immunomodulators, anti-infectives, and Chinese patent drugs had the largest monetary amounts. There was a significant difference in medication rationality between different hospital grades (P<0.001), with tertiary teaching hospitals having the highest rate. Conclusion: Strict epidemic control measures and the role of FCs played a crucial role in controlling the spread of the COVID-19 epidemic. Patients treated in FCs predominantly suffered from respiratory diseases, with older patients and children identified as high-risk populations. Physicians often choose national guidelines, essential drugs, and traditional Chinese for COVID-19 treatment. Tertiary teaching hospitals played a crucial role during the epidemic outbreak.

No evidence for the association between COVID-19 and neuroinflammation: A diffusion basis spectrum imaging study. (preprint)

COVID continues to be a major international public health concern, the underlying mechanisms of which are not fully understood. Recent studies suggest that COVID may cause prolonged inflammation within the central nervous system. However, the evidence so far has been limited to few small-scale case studies. To address this, this study leveraged a longitudinal dataset from the UK Biobank that included neuroimaging data prior to and following COVID testing (analytic N=416 including n=224 COVID-positive cases) and applied a novel and non-invasive Diffusion Basis Spectrum Imaging (DBSI) technique to derive putative indices of neuroinflammation (i.e., restricted fraction; DBSI-RF) for gray matter structures and white matter tracts in the brain. We hypothesized that SARS-CoV-2 infection would be associated with elevated DBSI markers of putative neuroinflammation and conducted linear regression analyses with adjustment for age, sex, race, body mass index, smoking frequency, and data acquisition interval. After multiple testing correction using false discovery rate, we found no evidence that COVID is associated with variability in neuroinflammation. Several brain regions showed nominally significant differences in DBSI-RF between COVID cases and controls including psychopathology-related regions linked that are either part of (i.e., orbitofrontal cortex) or functionally connected to the olfactory network (e.g., amygdala, caudate). It remains possible that there are acute and transitory neuroinflammatory effects associated with COVID that were not observed in our study due to potential resolution of COVID prior to the scan. Future research is warranted to examine whether neuroinflammation is associated with SARS-CoV-2 infection in a time- and/or symptom-dependent manner.

Bayesian Poisson Regression and Tensor Train Decomposition Model for Learning Mortality Pattern Changes during COVID-19 Pandemic (preprint)

COVID-19 has led to excess deaths around the world, however it remains unclear how the mortality of other causes of death has changed during the pandemic. Aiming at understanding the wider impact of COVID-19 on other death causes, we study Italian data set that consists of monthly mortality counts of different causes from January 2015 to December 2020. Due to the high dimensional nature of the data, we develop a model which combines conventional Poisson regression with tensor train decomposition to explore the lower dimensional residual structure of the data. We take a Bayesian approach, impose priors on model parameters. Posterior inference is performed using an efficient Metropolis-Hastings within Gibbs algorithm. The validity of our approach is tested in simulation studies. Our method not only identifies differential effects of interventions on cause specific mortality rates through the Poisson regression component, but also offers informative interpretations of the relationship between COVID-19 and other causes of death as well as latent classes that underline demographic characteristics, temporal patterns and causes of death respectively.

The number of similar epitopes determines the longevity of immunological memory (preprint)

The half-life of specific antibodies against various antigens varies tremendously from a few months to over 10,000 years. The reasons are largely unknown. Through epitope analysis of representative viruses, we found that the longevity of immunological memory may be correlated with the number of epitopes with similar sequences (EWSS) within each virus. Accordingly, a vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with 4.5-times higher antibody titers and over 100 months of half-life was developed in a rabbit model. The decay pattern of antibodies against each epitope or the entire SARS-CoV-2 spike protein was roughly correlated with the number of EWSS in immunizationtreatments, –that is, for every additional EWSS, the half-life of the antibody would be doubled. After immunization, proportions of antigen-specific memory B cells (MBC) first increased and then decreased. In the descending phase, the antibody titers were positively correlated with the numbers of MBC. This study also discusses improvement measures for vaccines against other viruses.

Effectiveness of Traditional Chinese Medicine on coronavirus disease 2019 in 92 patients: a retrospective study.

OBJECTIVE: To investigate the antipyretic effect of early treatment with Traditional Chinese Medicine (TCM) on coronavirus disease 2019 (COVID-19) patients. METHODS: We retrospectively analyzed 369 patients from January 26th, 2020 to April 15th, 2020, who had been diagnosed with COVID-19. Among 92 eligible cases, 45 cases were identified as treatment group Ⅰ ( 45) and 47 cases were identified as treatment group Ⅱ. Patients in the treatment group Ⅰ were treated with TCM herbal decoction within 5 d after admission. Patients in the treatment group Ⅱ were treated with TCM herbal decoction after the 6th admission day. The onset time of antipyretic effect, the antipyretic time, the time of negative oropharyngeal swab nucleic acid conversion, and the changes of cell count in blood routine test were compared. RESULTS: The treatment group I showed shorter average antipyretic duration (4 7 d; <0.05), and shorter average time for polymerase chain reaction (PCR) nucleic acid test results to turn negative (7 11 d; <0.05) than the treatment group II. For patients ( 54) with body temperature>38 ℃, patients in the treatment group I had shorter median onset time of antipyretic effect than those in the treatment group II (3 4 d; <0.05). The absolute lymphocyte (LYMPH) count and absolute eosinophil (EOS) count on the 3rd day after admission and the neutrophil/lymphocyte ratio on the 6th day after admission of patients in the treatment group I were notably different from those in the treatment group II at the same time point (0.05). Based on Spearman's rank correlation analysis, the change of body temperature on the 3rd day after admission was positively correlated with the increase of EOS count and the increase of EOS count and LYMPH counts on the 6th day after admission (0.01). CONCLUSIONS: Early TCM intervention within 5 d after hospital admission shortened the onset time of antipyretic effect and fever duration of COVID-19 patients, reduced the time required for PCR test results to turn negative. Moreover, early TCM intervention also improved the results of inflammatory markers for COVID-19 patients. LYMPH and EOS counts can be used as indicators of TCM antipyretic effect.

Study on prescription medication mode and mechanism of traditional Chinese medicine in the treatment of noncritical COVID-19 based on data mining

Background: As of 2023, coronavirus disease 2019 (COVID-19) is still spreading globally. Therefore, we aim to integrate non-critical COVID-19 high-frequency and high-targeting Chinese medicines to provide a reference for clinical prescriptions to improve COVID-19-related symptoms. Materials and methods: The information on non-critical COVID-19 high-frequency Chinese medicines in the diagnosis and treatment of COVID-19 was obtained by the TCM inheritance support platform. Using network pharmacology and molecular docking technology, high-targeting Chinese medicines with good docking activity with COVID-19 receptors angiotensin-converting enzyme-II (ACE2), 3CLpro and tyrosine-protein kinase receptor UFO (AXL) were obtained. A new prescription for non-critical COVID-19 was established by integrating high-frequency and high-targeting Chinese medicines. Rats with acute lung injury induced by lipopolysaccharide were used as the experimental model. The histopathological changes in the lungs of rats in each group were observed by hematoxylin-eosin staining. The lung coefficient of rats was measured. The levels of IL-6, TNF-a, and IL-1ß in serum were detected by enzyme-linked immunosorbent assay. The mRNA and protein levels of ACE2 and AXL in lung tissue were detected by real-time quantitative polymerase chain reaction and western blot. Results: Through data mining, it was found that there were 39 high-frequency traditional Chinese medicines for non-critical COVID-19 in the diagnosis and treatment guidelines. According to network pharmacology and molecular docking, 30 highly targeted traditional Chinese drugs for COVID-19 were found. The new prescriptions for non-critical COVID-19 were comprehensively obtained, including Glycyrrhizae Radix, Ephedra Herba, Amygdalus Communis Vas, Gypsum Fibrosum, Descurainiae Semen, Atractylodes Lancea, Scutellariae Radix, Amomum Tsao-Ko Crevostet, Forsythiae Fructus, Pogostemon cablin, Magnolia Officinalis. Compared with the LPS-induced lung injury model group, the medium dose of the new prescription group had significantly alleviated pathological changes in lung tissue, decreased lung coefficient, decreased contents of IL-6, TNF-a and IL-1ß, and increased mRNA and protein expression of ACE2 and AXL (P < 0.05). Conclusion: Based on data mining, network pharmacology and molecular docking technology, the new prescription for non-critical COVID-19 established by this method has an anti-inflammatory effect on rats with acute lung injury induced by lipopolysaccharide and can provide a reference for clinicians to alleviate the symptoms related to non-critical COVID-19. [ FROM AUTHOR] Copyright of Traditional Medicine Research is the property of TMR Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

AT2 Cell-Derived IgA Trapped by the Extracellular Matrix and Promoted Pulmonary Fibrosis (preprint)

Pulmonary fibrosis is an interstitial lung disease caused by various factors such as exposure to workplace environmental contaminants, drugs, or X-rays. Epithelial cells are among the driving factors of pulmonary fibrosis. Immunoglobulin A (IgA), traditionally thought to be secreted by B cells, is an important immune factor involved in COVID-19 infection and vaccination. In current study, we found lung epithelial cells were involved in IgA secretion which, in turn, promoted pulmonary fibrosis. The spatial transcriptomics and single-cell sequencing suggests that Igha transcripts were highly expressed in the fibrotic lesion areas of lungs from silica-treated mice. Reconstruction of B-cell receptor (BCR) sequences revealed a new cluster of AT2-like epithelial cells with a shared BCR and high expression of genes related to IgA production. Furthermore, the secretion of IgA by AT2-like cells were trapped by extracellular matrix and aggravated pulmonary fibrosis by activating fibroblasts. Targeted blockade of IgA secretion by pulmonary epithelial cells may be a potential strategy for treating pulmonary fibrosis.

Systematic Mendelian randomization study of the effect of gut microbiome and plasma metabolome on severe COVID-19 (preprint)

Background COVID-19 could develop severe respiratory symptoms in certain infected patients, especially in the patients with immune disorders. Gut microbiome and plasma metabolome act important immunological modulators in the human body and could contribute to the immune responses impacting the progression of COVID-19.Methods Based on two-sample Mendelian randomization framework, the causal effects of 131 microbiota in genus or species level and 452 plasma metabolites on severe COVID-19 are estimated. Single nucleotide polymorphisms (SNPs) strongly associated with the abundance of intestinal bacteria in gut and the concentration of metabolites in plasma have been utilized as the instrument variables to infer whether they are causal factors of severe COVID-19. In addition, mediation analysis is conducted to find the potential link between the microbiota and metabolite which identified by polygenic Mendelian randomization analysis, while colocalization analysis has been performed to validate the causal relationships which identified by cis-Mendelian randomization analysis.Results Mendelian randomization support 13 microbiota and 53 metabolites, which are significantly causal association with severe COVID-19. Mediation analysis find 11 mediated relations, such as myo-inositol, 2-stearoylglycerophosphocholine and alpha-glutamyltyrosine, which appeared to mediate the association of Howardella and Ruminiclostridium 6 with severe COVID-19 respectively, while Butyrivibrio and Ruminococcus gnavus appeared to mediate the association of myo-inositol and N-acetylalanine respectively. Ruminococcus torques abundance was colocalized with severe COVID-19 (PP.H4 = 0.77) and the colon expression of permeability related protein RASIP1 (PP.H4 = 0.95).Conclusions Our study results highlight the causal relationships of gut microbiome and plasma metabolome for severe COVID-19, which have the promise to be served as clinical biomarkers for risk stratification and prognostication, and novel basis to unravel the pathophysiological mechanisms of severe COVID-19.

The impact of the first peak of the COVID-19 pandemic on childhood myopia control practice patterns among ophthalmologists-an international pediatric ophthalmology and strabismus council global perspective.

BACKGROUND: The prevalence of myopia keeps increasing during the COVID-19 pandemic. We aimed to map the worldwide treatment preferences of ophthalmologists managing myopia control during the first wave of the pandemic. METHODS: An online questionnaire inquiring about pharmacological and optical treatment patterns during the first half of 2020 was sent to pediatric ophthalmology as well as general ophthalmology memberships worldwide. The results among pediatric ophthalmologists were compared to a previous study we performed before the pandemic. RESULTS: A total of 2269 respondents from 94 countries were included. Most respondents were pediatric ophthalmologists (64.6%), followed by ophthalmologists from other subspecialties (32.3%). The preferred modality for all geographical regions was a combination therapy of pharmacological and optical treatments. When evaluated independently, the pharmacological treatment was more popular than the optical treatment in most regions other than East Asia (P < 0.001). Compared to a pre-pandemic questionnaire, the participation of pediatric ophthalmologists affiliated with non-university hospitals increased. Additionally, the prevalence of respondents utilizing either any type of pharmacological treatment and those that using only evidence-based treatments increased globally. Although a decline in the use of optical treatment was evident worldwide, the use of evidence-based optical treatments increased. CONCLUSION: Ophthalmologists around the world preferred a combination therapy of pharmacological and optical treatments. More pediatric ophthalmologists treated myopia progression and preferred a better evidence-based approach to control myopia. These trends reflect a positive response and more awareness of the rising prevalence of myopia due to the increased burden of myopia imposed by the COVID-19 pandemic.

The improvement of levofloxacin and tetracycline removal from simulated water by thermosensitive flocculant: Mechanisms and simulation

Antibiotics were detected in worldwide natural water especially in COVID-19 period. The common flocculants rarely removed the dissolved antibiotics from natural water and wastewater. The flocculation improvement of organic polymer flocculants might solve the issue of antibiotic pollution or promote the removal efficiencies of antibiotics in water/wastewater treatment plants. Herein, a thermosensitive flocculant, P(DAC-NIPAM), was prepared via one-step method. It was investigated that the relationship between the various functional groups of P(DAC-NIPAM) and its flocculation performances in the treatment of simulated water containing levofloxacin, tetracycline, colloidal particles and natural organic matters. The removal mechanisms were discussed. The results indicated that the rich cationic, hydrophilic and hydrophobic groups of P(DAC-NIPAM) enhanced the interaction between flocculants and pollutants. The bridging of P(DAC-NIPAM) among micelles, charge neutralization, hydrogen bond between P(DAC-NIPAM) and two antibiotics, the shrinkage of P(DAC-NIPAM) molecule and enhancement of hydrophobicity when water temperature was above low critical solution temperature (LCST), co-flocculation and co-settlement of multiple pollutants all contributed to the efficient removal of levofloxacin and tetracycline from water. Flocculation simulation further confirmed that thermosensitive flocculant combined with heating plates was a potential candidate for antibiotic treatment in actual water treatment plants.

Redistribution and activation of CD16brightCD56dim NK cell subset to fight against Omicron subvariant BA.2 after COVID-19 vaccination (preprint)

With the alarming surge in COVID-19 cases globally, vaccination must be prioritised to achieve herd immunity. Immune dysfunction is detected in the majority of patients with COVID-19; however, it remains unclear whether the immune responses elicited by COVID-19 vaccination function against the Omicron subvariant BA.2. Of the 508 Omicron BA.2-infected patients enrolled, 102 were unvaccinated controls and 406 were vaccinated. Despite the presence of clinical symptoms in both groups, vaccination led to a significant decline in nausea or vomiting, abdominal pain, headache, pulmonary infection, overall clinical symptoms, and a moderate rise in body temperature. Omicron BA.2-infected individuals were also characterised by a mild increase in both serum pro- and anti-inflammatory cytokine levels after vaccination. There were no significant differences or trend changes between T and B lymphocyte subsets; however, a significant expansion of NK lymphocytes in COVID-19-vaccinated patients was observed. Moreover, the most effective CD16brightCD56dim subsets of NK cells showed increased functional capacities, as evidenced by a significantly greater IFN-{gamma} secretion and stronger cytotoxic potential in Omicron BA.2-infected patients after vaccination. Collectively, these results suggest that COVID-19 vaccination interventions promote the redistribution and activation of CD16brightCD56dim NK cell subsets against viral infections, and could facilitate the clinical management of Omicron BA.2-infected patients.

Latent profile analysis of security among patients with COVID-19 infection in mobile cabin hospitals and its relationship with psychological capital

Aim COVID-19 patients' security is related to their mental health. However, the classification of this group's sense of security is still unclear. The aim of our research is to clarify the subtypes of security of patients infected with COVID-19, explore the factors affecting profile membership, and examine the relationship between security and psychological capital for the purpose of providing a reference for improving patients' sense of security and mental health. Methods A total of 650 COVID-19 patients in a mobile cabin hospital were selected for a cross-sectional survey from April to May 2022. They completed online self-report questionnaires that included a demographic questionnaire, security scale, and psychological capital scale. Data analysis included latent profile analysis, variance analysis, the Chi-square test, multiple comparisons, multivariate logistical regression, and hierarchical regression analysis. Results Three latent profiles were identified—low security (Class 1), moderate security (Class 2), and high security (Class 3)—accounting for 12.00, 49.51, and 38.49% of the total surveyed patients, respectively. In terms of the score of security and its two dimensions, Class 3 was higher than Class 2, and Class 2 was higher than Class 1 (all P < 0.001). Patients with difficulty falling asleep, sleep quality as usual, and lower tenacity were more likely to be grouped into Class 1 rather than Class 3;Patients from families with a per capita monthly household income <3,000 and lower self-efficacy and hope were more likely to be grouped into Classes 1 and 2 than into Class 3. Psychological capital was an important predictor of security, which could independently explain 18.70% of the variation in the patients' security. Conclusions Security has different classification features among patients with COVID-19 infection in mobile cabin hospitals. The security of over half of the patients surveyed is at the lower or middle level, and psychological capital is an important predictor of the patients' security. Medical staff should actively pay attention to patients with low security and help them to improve their security level and psychological capital.

Impact and Recovery of Coastal Tourism Amid COVID-19: Tourism Flow Networks in Indonesia

This study aims to explore tourism changes in coastal tourism destinations before and during the COVID-19 pandemic from the perspective of regional resilience. A mixed method of a social network and spatial analysis was used to evaluate inbound tourists' geotagged photos of Indonesia on Flickr from 2018–2022 as metadata. The DBSCAN algorithm and Markov chains were used to comprehensively analyze the hotspot areas and the patterns of tourism movement trajectories amid a complicated recovery. The results demonstrate that: (1) The distribution of geotagged photos before and during the pandemic generally exhibited stage and regional unevenness. The main clusters were Java and the Nusa Tenggara Islands, with the rest displaying a scattered distribution. (2) The tourism flow network was unevenly distributed, and the nodes had obvious core and edge areas. Owing to the crisis, the tourism flow network realized a change in form from network to line and point. (3) Its impact on Indonesian inbound tourism may persist in the short term, and the volatility of national anti-pandemic policies influences the resilience of tourism flow during COVID-19. The dominance of the core nodes highlights the network's resistance to disruptions due to the prominence of the location of network connections during the pandemic, and marginal nodes reflect the vulnerability to pandemic shocks owing to the hypocentricity of the nodes and the thinness of the connections within and outside the islands. These results provide marketing and promotion policies for the sustainable development of coastal areas.