A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea.

To investigate different contents of pu-erh tea polyphenol affected by abiotic stress, this research determined the contents of tea polyphenol in teas produced by Yuecheng, a Xishuangbanna-based tea producer in Yunnan Province. The study drew a preliminary conclusion that eight factors, namely, altitude, nickel, available cadmium, organic matter, N, P, K, and alkaline hydrolysis nitrogen, had a considerable influence on tea polyphenol content with a combined analysis of specific altitudes and soil composition. The nomogram model constructed with three variables, altitude, organic matter, and P, screened by LASSO regression showed that the AUC of the training group and the validation group were respectively 0.839 and 0.750, and calibration curves were consistent. A visualized prediction system for the content of pu-erh tea polyphenol based on the nomogram model was developed and its accuracy rate, supported by measured data, reached 80.95%. This research explored the change of tea polyphenol content under abiotic stress, laying a solid foundation for further predictions for and studies on the quality of pu-erh tea and providing some theoretical scientific basis.

Perceived differences in peer-to-peer accommodation before and after COVID-19: evidence from China. (Special Issue: The sharing economy in a post-pandemic world.)

Purpose: Based on text content analysis using big data, this study aims to explore differences in guest perceptions of peer-to-peer accommodations before and after COVID-19 to provide suggestions for the development of these properties in China postpandemic. Design/methodology/approach: A guest perception dictionary was established by collecting Ctrip customer reviews of peer-to-peer accommodations. After data cleaning, thematic word analysis and semantic association network analysis were used to explore perceptions and thematic differences before and after COVID-19. Findings: This research constructed a multidimensional framework of guest-perceived values for peer-to-peer accommodation in the context of COVID-19. The findings showed that the emphasis on functionality in peer-to-peer accommodation changed;perceived emotional values associated with peer-to-peer stays were more complex;perceived social values decreased, host-guest interactions were reduced and online communication became a stronger trend;tourist preferences for types of experiences changed, and people changed their destination selections;perceived conditional value was reflected in perceived risks, and the perceptions of environmental health, service and physical risks increased. Research limitations/implications: This research has constructed a multidimensional framework of tourist perceived value on the basis of peer-to-peer accommodation context and epidemic background and has thus shown the changes in tourist perceived value of peer-to-peer accommodation before and after COVID-19. Originality/value: To the best of authors' knowledge, this research constitutes the first attempt to explore the perceptual differences for peer-to-peer accommodations before and after COVID-19 based on an extensive data set of online reviews from multiple provinces of China.

The characteristics and predictive role of lymphocyte subsets in COVID-19 patients.

OBJECTIVE: To investigate the characteristics and predictive roles of lymphocyte subsets in COVID-19 patients. METHOD: We evaluated lymphocyte subsets and other clinical features of COVID-19 patients, and analyzed their potential impacts on COVID-19 outcomes. RESULTS: 1. Lymphocyte subset counts in the peripheral blood of patients with COVID-19 were significantly reduced, especially in patients with severe disease. 2. In patients with non-severe disease, the time from symptom onset to hospital admission was positively correlated with total T cell counts. 3. Among COVID-19 patients who did not reach the composite endpoint, lymphocyte subset counts were higher than in patients who had reached the composite endpoint. 4. The Kaplan-Meier survival curves showed significant differences in COVID-19 patients, classified by the levels of total, CD8+, and CD4+ T cells at admission. CONCLUSION: Our study showed that total, CD8+, and CD4+ T cell counts in patients with COVID-19 were significantly reduced, especially in patients with severe disease. Lower T lymphocyte subsets were significantly associated with a higher occurrence of composite endpoint events. These subsets may help identify patients with a high risk of composite endpoint events.

Perceived differences in peer-to-peer accommodation before and after COVID-19: evidence from China

PurposeBased on text content analysis using big data, this study aims to explore differences in guest perceptions of peer-to-peer accommodations before and after COVID-19 to provide suggestions for the development of these properties in China postpandemic.Design/methodology/approachA guest perception dictionary was established by collecting Ctrip customer reviews of peer-to-peer accommodations. After data cleaning, thematic word analysis and semantic association network analysis were used to explore perceptions and thematic differences before and after COVID-19.FindingsThis research constructed a multidimensional framework of guest-perceived values for peer-to-peer accommodation in the context of COVID-19. The findings showed that the emphasis on functionality in peer-to-peer accommodation changed;perceived emotional values associated with peer-to-peer stays were more complex;perceived social values decreased, host–guest interactions were reduced and online communication became a stronger trend;tourist preferences for types of experiences changed, and people changed their destination selections;perceived conditional value was reflected in perceived risks, and the perceptions of environmental health, service and physical risks increased.Research limitations/implicationsThis research has constructed a multidimensional framework of tourist perceived value on the basis of peer-to-peer accommodation context and epidemic background and has thus shown the changes in tourist perceived value of peer-to-peer accommodation before and after COVID-19.Originality/valueTo the best of authors' knowledge, this research constitutes the first attempt to explore the perceptual differences for peer-to-peer accommodations before and after COVID-19 based on an extensive data set of online reviews from multiple provinces of China.

A Hybrid Approach for the Assessment of Risk Spillover to ESG Investment in Financial Networks

In this paper, we present a framework for evaluating risk contagion by merging financial networks with machine learning techniques. The framework begins with building a financial network model based on the inter-institutional correlation network, followed by analyzing the structure and overall value changes of the financial network under the stress of a liquidation shock. We then examine the network's evolution over time. We also use three machine learning techniques to assess the abnormal volatility of important financial institutions in the financial network. Finally, we evaluate the spillover effects of risk volatility in financial networks on ESG investments. The findings suggest that the financial network becomes more robust as the connections among financial institutions become more intricate. This leads to an improvement in the ability of the financial network to withstand systemic risk events. Overall, our study provides evidence of the negative impact of risk spillovers in financial networks on ESG investments, highlighting the need for a more sustainable and resilient financial system. This innovative framework combining financial network modeling and machine learning prediction provides a deeper understanding of the evolution of financial networks and a more accurate evaluation of abnormal volatility in financial networks.

A machine learning-based study on the impact of COVID-19 on three kinds of pollution in Beijing-Tianjin-Hebei region.

Large-scale restrictions on anthropogenic activities in China in 2020 due to the Corona Virus Disease 2019 (COVID-19) indirectly led to improvements in air quality. Previous studies have paid little attention to the changes in nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3) concentrations at different levels of anthropogenic activity limitation and their interactions. In this study, machine learning models were used to simulate the concentrations of three pollutants during periods of different levels of lockdown, and compare them with observations during the same period. The results show that the difference between the simulated and observed values of NO2 concentrations varies at different stages of the lockdown. Variation between simulated and observed O3 and PM2.5 concentrations were less distinct at different stages of lockdowns. During the most severe period of the lockdowns, NO2 concentrations decreased significantly with a maximum decrease of 65.28 %, and O3 concentrations increased with a maximum increase of 75.69 %. During the first two weeks of the lockdown, the titration reaction in the atmosphere was disrupted due to the rapid decrease in NO2 concentrations, leading to the redistribution of Ox (NO2 + O3) in the atmosphere and eventually to the production of O3 and secondary PM2.5. The effect of traffic restrictions on the reduction of NO2 concentrations is significant. However, it is also important to consider the increase in O3 due to the constant volatile organic compounds (VOCs) and the decrease in NOx (NO+NO2). Traffic restrictions had a limited effect on improving PM2.5 pollution, so other beneficial measures were needed to sustainably reduce particulate matter pollution. Research on COVID-19 could provide new insights into future clean air action.

Development of a model by LASSO to predict hospital length of stay (LOS) in patients with the SARS-Cov-2 omicron variant.

The length of stay (LOS) in hospital varied considerably in different patients with COVID-19 caused by SARS-CoV-2 Omicron variant. The study aimed to explore the clinical characteristics of Omicron patients, identify prognostic factors, and develop a prognostic model to predict the LOS of Omicron patients. This was a single center retrospective study in a secondary medical institution in China. A total of 384 Omicron patients in China were enrolled. According to the analyzed data, we employed LASSO to select the primitive predictors. The predictive model was constructed by fitting a linear regression model using the predictors selected by LASSO. Bootstrap validation was used to test performance and eventually we obtained the actual model. Among these patients, 222 (57.8%) were female, the median age of patients was 18 years and 349 (90.9%) completed two doses of vaccination. Patients on admission diagnosed as mild were 363 (94.5%). Five variables were selected by LASSO and a linear model, and those with P < 0.05 were integrated into the analysis. It shows that if Omicron patients receive immunotherapy or heparin, the LOS increases by 36% or 16.1%. If Omicron patients developed rhinorrhea or occur familial cluster, the LOS increased by 10.4% or 12.3%, respectively. Moreover, if Omicron patients' APTT increased by one unit, the LOS increased by 0.38%. Five variables were identified, including immunotherapy, heparin, familial cluster, rhinorrhea, and APTT. A simple model was developed and evaluated to predict the LOS of Omicron patients. The formula is as follows: Predictive LOS = exp(1*2.66263 + 0.30778*Immunotherapy + 0.1158*Familiar cluster + 0.1496*Heparin + 0.0989*Rhinorrhea + 0.0036*APTT).

Direct Multi-Material Reconstruction via Iterative Proximal Adaptive Descent for Spectral CT Imaging.

Spectral computed tomography (spectral CT) is a promising medical imaging technology because of its ability to provide information on material characterization and quantification. However, with an increasing number of basis materials, the nonlinearity of measurements causes difficulty in decomposition. In addition, noise amplification and beam hardening further reduce image quality. Thus, improving the accuracy of material decomposition while suppressing noise is pivotal for spectral CT imaging. This paper proposes a one-step multi-material reconstruction model as well as an iterative proximal adaptive decent method. In this approach, a proximal step and a descent step with adaptive step size are designed under the forward-backward splitting framework. The convergence analysis of the algorithm is further discussed according to the convexity of the optimization objective function. For simulation experiments with different noise levels, the peak signal-to-noise ratio (PSNR) obtained by the proposed method increases approximately 23 dB, 14 dB, and 4 dB compared to those of other algorithms. Magnified areas of thorax data further demonstrated that the proposed method has a better ability to preserve details in tissues, bones, and lungs. Numerical experiments verify that the proposed method efficiently reconstructed the material maps, and reduced noise and beam hardening artifacts compared with the state-of-the-art methods.

Therapeutic strategies for critically ill patients with COVID-19.

Since the 2019 novel coronavirus disease (COVID-19) outbreak originated from Wuhan, Hubei Province, China, at the end of 2019, it has become a clinical threat to the general population worldwide. Among people infected with the novel coronavirus (2019-nCoV), the intensive management of the critically ill patients in intensive care unit (ICU) needs substantial medical resource. In the present article, we have summarized the promising drugs, adjunctive agents, respiratory supportive strategies, as well as circulation management, multiple organ function monitoring and appropriate nutritional strategies for the treatment of COVID-19 in the ICU based on the previous experience of treating other viral infections and influenza. These treatments are referable before the vaccine and specific drugs are available for COVID-19.

The dynamic changes of psychosomatic symptoms in three waves of COVID-19 outbreak and fatigue caused by enduring pandemic in China.

BACKGROUND: Two years have passed since the 2019 novel coronavirus disease (COVID-19) was first reported. The persistent pandemic might lead to severe psychosomatic problems and fatigue. In addition, the recent rapid rising COVID-19 cases in China have become a trending issue. Therefore, this study aimed to investigate the dynamic changes in psychosomatic problems at the initial and current stages of the pandemic. METHODS: Three waves of cross-sectional online survey were conducted during the initial COVID outbreak in China. The psychosomatic symptom scale (PSSS), perceived stress scale (PSS), and pandemic fatigue scale (PFS) were used to assess the psychosomatic problems, stress, and fatigue. RESULTS: 4317, 1096, and 2172 participants completed the first, second, and third surveys. The prevalence of psychosomatic disorder was 22 %, 28 %, and 39 %, respectively. The network structure of PSSS symptoms has not significantly changed as the pandemic progresses. However, the global strength of the PSSS networks, indicating the overall connectivity, in the third wave was significantly higher than in the first wave (s = 0.54, P = 0.007). The most central symptoms in the first and third wave networks were depressed mood and tiredness. The PFS score was higher in the people concerned with indirect impact than those concerned with health (P < 0.001). PFS has positive relationships with PSSS and PSS score (R = 0.41, P < 0.001 and R = 0.35, P < 0.001, respectively). CONCLUSIONS: The persistence of the pandemic caused critical psychosomatic issues, stress, and indirect burden over time, leading to inevitable fatigue. People endured needing immediate attention to prevent or reduce psychosomatic disorders.

Depression and the risk factors for isolated infectious disease fever patients in the hospital during the COVID-19.

Objectives: To compare and analyze the incidence of anxiety and depression of infectious disease fever patients in hospitalized isolation and home isolation during the COVID-19 pandemic, as well as the risk factors for the negative emotions of hospitalized isolation patients. Methods: Forty isolated infectious disease fever patients in Baoding No.1 Hospital were randomly selected as the study group, and the other 40 isolated infectious disease fever patients at home were randomly selected as the control group from March 2020 to August 2020. The scores and prevalence of depression and anxiety between the two groups were compared and analyzed. The logistic regression analysis was used to judge and analyze the negative psychological factors of hospitalized isolation patients such as depression and anxiety. Result: The HAMA and HAMD-17 scores of study group are significantly higher than those of control group (HAMA, p=0.00; HAMD-17, p=0.01). The prevalence of anxiety and depression in the study group was significantly higher than that in the control group (p=0.03, p=0.04). The gender (p=0.002), economic status (p=0.004) and isolation attitude (p=0.023) are the related factors of anxiety, among which economic status is the protective factor, while women and resistant attitude are the risk factors. Economic status (p=0.003) and isolation attitude (p=0.001) are the related factors of depression, among which economic status is the protective factor, and resistant attitude is the risk factor. Conclusion: The prevalence and severity of anxiety and depression in hospitalized isolation patients due to infectious disease fever are significantly higher than those of home isolation patients. The focus groups are women, with bad economic status and poor isolation attitude. Necessary psychological counseling and social support should be provided to these groups to reduce negative emotions and increase the experience of isolated patients.

Site of vulnerability on SARS-CoV-2 spike induces broadly protective antibody against antigenically distinct Omicron subvariants.

The rapid evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants has emphasized the need to identify antibodies with broad neutralizing capabilities to inform future monoclonal therapies and vaccination strategies. Herein, we identified S728-1157, a broadly neutralizing antibody (bnAb) targeting the receptor-binding site (RBS) that was derived from an individual previously infected with WT SARS-CoV-2 prior to the spread of variants of concern (VOCs). S728-1157 demonstrated broad cross-neutralization of all dominant variants, including D614G, Beta, Delta, Kappa, Mu, and Omicron (BA.1/BA.2/BA.2.75/BA.4/BA.5/BL.1/XBB). Furthermore, S728-1157 protected hamsters against in vivo challenges with WT, Delta, and BA.1 viruses. Structural analysis showed that this antibody targets a class 1/RBS-A epitope in the receptor binding domain via multiple hydrophobic and polar interactions with its heavy chain complementarity determining region 3 (CDR-H3), in addition to common motifs in CDR-H1/CDR-H2 of class 1/RBS-A antibodies. Importantly, this epitope was more readily accessible in the open and prefusion state, or in the hexaproline (6P)-stabilized spike constructs, as compared with diproline (2P) constructs. Overall, S728-1157 demonstrates broad therapeutic potential and may inform target-driven vaccine designs against future SARS-CoV-2 variants.

Resilience and high-quality development of tourism destinations under the epidemic crisis

Because of its wide spread, long duration, and large number of infected people, the COVID-19 epidemic has had an unprecedented huge and permanent impact on the global tourism industry. As of now, the trend of the epidemic is still unclear, and the future of the tourism industry is still full of uncertainties. Strengthening the resilience of tourist destinations, accelerating the sustainable transformation of tourist destinations, and promoting the high-quality development of regional tourism have become an important direction for the recovery and reconstruction of the current tourism industry.

Immune response and homeostasis mechanism following administration of BBIBP-CorV SARS-CoV-2 inactivated vaccine.

The BBIBP-CorV severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inactivated vaccine has been authorized for emergency use and widely distributed. We used single-cell transcriptome sequencing to characterize the dynamics of immune responses to the BBIBP-CorV inactivated vaccine. In addition to the expected induction of humoral immunity, we found that the inactivated vaccine induced multiple, comprehensive immune responses, including significantly increased proportions of CD16+ monocytes and activation of monocyte antigen presentation pathways; T cell activation pathway upregulation in CD8+ T cells, along with increased activation of CD4+ T cells; significant enhancement of cell-cell communications between innate and adaptive immunity; and the induction of regulatory CD4+ T cells and co-inhibitory interactions to maintain immune homeostasis after vaccination. Additionally, comparative analysis revealed higher neutralizing antibody levels, distinct expansion of naive T cells, a shared increased proportion of regulatory CD4+ T cells, and upregulated expression of functional genes in booster dose recipients with a longer interval after the second vaccination. Our research will support a comprehensive understanding of the systemic immune responses elicited by the BBIBP-CorV inactivated vaccine, which will facilitate the formulation of better vaccination strategies and the design of new vaccines.

AMPK directly phosphorylates TBK1 to integrate glucose sensing into innate immunity.

Nutrient sensing and damage sensing are two fundamental processes in living organisms. While hyperglycemia is frequently linked to diabetes-related vulnerability to microbial infection, how body glucose levels affect innate immune responses to microbial invasion is not fully understood. Here, we surprisingly found that viral infection led to a rapid and dramatic decrease in blood glucose levels in rodents, leading to robust AMPK activation. AMPK, once activated, directly phosphorylates TBK1 at S511, which triggers IRF3 recruitment and the assembly of MAVS or STING signalosomes. Consistently, ablation or inhibition of AMPK, knockin of TBK1-S511A, or increased glucose levels compromised nucleic acid sensing, while boosting AMPK-TBK1 cascade by AICAR or TBK1-S511E knockin improves antiviral immunity substantially in various animal models. Thus, we identify TBK1 as an AMPK substrate, reveal the molecular mechanism coupling a dual sensing of glucose and nuclei acids, and report its physiological necessity in antiviral defense.

Comparison of clinical characteristics between SARS-CoV-2 Omicron variant and Delta variant infections in China.

Background: The continued 'evolution' of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of the Omicron variant after the Delta variant, resulting in a significant increase in the number of people with COVID-19. This increase in the number of cases continues to have a significant impact on lives. Therefore, a more detailed understanding of the clinical characteristics of Omicron infection is essential. Methods: Using medical charts, we extracted clinical information for 384 patients infected with the Omicron variant in Anyang City, Henan Province, China. Epidemiology and clinical characteristics were compared with a cohort of people infected with the Delta variant in Zhengzhou in 2021. Findings: Common initial symptoms at onset of illness were cough [240 (63%)], expectoration [112 (29%)], fever [96 (25%)], nasal congestion [96 (25%)] and myalgia or fatigue [30 (6%)]. In patients with the Omicron variant, levels of total cholesterol, low-density lipoprotein and creatinine increased in 52 (14%), 36 (9%) and 58 (15%) patients, respectively, compared with patients with the Delta variant [one (1%), one (1%) and two (2%)]. Levels of triglyceride and high-density lipoprotein also increased. In patients with the Omicron variant, the levels of specific gravity and the erythrocyte sedimentation rate were increased in 115 (30%) and 81 (21%) patients, and serum levels of complement 3 decreased in 93 (41%). Results: Compared with patients infected with Delta, no major differences in initial clinical symptoms were identified in patients infected with Omicron. However, dyslipidemia and kidney injury were much more severe in patients with the Omicron variant, and the erythrocyte sedimentation rate was increased. Due to decreased levels of complement 3, the immunity of patients with the Omicron variant was weak.

Comparison of clinical characteristics between SARS-CoV-2 Omicron variant and Delta variant infections in China

Background The continued ‘evolution’ of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of the Omicron variant after the Delta variant, resulting in a significant increase in the number of people with COVID-19. This increase in the number of cases continues to have a significant impact on lives. Therefore, a more detailed understanding of the clinical characteristics of Omicron infection is essential. Methods Using medical charts, we extracted clinical information for 384 patients infected with the Omicron variant in Anyang City, Henan Province, China. Epidemiology and clinical characteristics were compared with a cohort of people infected with the Delta variant in Zhengzhou in 2021. Findings Common initial symptoms at onset of illness were cough [240 (63%)], expectoration [112 (29%)], fever [96 (25%)], nasal congestion [96 (25%)] and myalgia or fatigue [30 (6%)]. In patients with the Omicron variant, levels of total cholesterol, low-density lipoprotein and creatinine increased in 52 (14%), 36 (9%) and 58 (15%) patients, respectively, compared with patients with the Delta variant [one (1%), one (1%) and two (2%)]. Levels of triglyceride and high-density lipoprotein also increased. In patients with the Omicron variant, the levels of specific gravity and the erythrocyte sedimentation rate were increased in 115 (30%) and 81 (21%) patients, and serum levels of complement 3 decreased in 93 (41%). Results Compared with patients infected with Delta, no major differences in initial clinical symptoms were identified in patients infected with Omicron. However, dyslipidemia and kidney injury were much more severe in patients with the Omicron variant, and the erythrocyte sedimentation rate was increased. Due to decreased levels of complement 3, the immunity of patients with the Omicron variant was weak.

Changes in aerosol loading before, during and after the COVID-19 pandemic outbreak in China: Effects of anthropogenic and natural aerosol.

Anthropogenic emissions reduced sharply in the short-term during the coronavirus disease pandemic (COVID-19). As COVID-19 is still ongoing, changes in atmospheric aerosol loading over China and the factors of their variations remain unclear. In this study, we used multi-source satellite observations and reanalysis datasets to synergistically analyze the spring (February-May) evolution of aerosol optical depth (AOD) for multiple aerosol types over Eastern China (EC) before, during and after the COVID-19 lockdown period. Regional meteorological effects and the radiative response were also quantitatively assessed. Compared to the same period before COVID-19 (i.e., in 2019), a total decrease of -14.6 % in tropospheric TROPOMI nitrogen dioxide (NO2) and a decrease of -6.8 % in MODIS AOD were observed over EC during the lockdown period (i.e., in 2020). After the lockdown period (i.e., in 2021), anthropogenic emissions returned to previous levels and there was a slight increase (+2.3 %) in AOD over EC. Moreover, changes in aerosol loading have spatial differences. AOD decreased significantly in the North China Plain (-14.0 %, NCP) and Yangtze River Delta (-9.4 %) regions, where anthropogenic aerosol dominated the aerosol loading. Impacted by strong wildfires in Southeast Asia during the lockdown period, carbonaceous AOD increased by +9.1 % in South China, which partially offset the emission reductions. Extreme dust storms swept through the northern region in the period after COVID-19, with an increase of +23.5 % in NCP and + 42.9 % in Northeast China (NEC) for dust AOD. However, unfavorable meteorological conditions overwhelmed the benefits of emission reductions, resulting in a +20.1 % increase in AOD in NEC during the lockdown period. Furthermore, the downward shortwave radiative flux showed a positive anomaly due to the reduced aerosol loading in the atmosphere during the lockdown period. This study highlights that we can benefit from short-term controls for the improvement of air pollution, but we also need to seriously considered the cross-regional transport of natural aerosol and meteorological drivers.

Effects of the COVID-19 pandemic on elderly patients with head and neck squamous cell carcinoma.

Background: The 2019 novel coronavirus disease (COVID-19) strongly affects health care activities in countries around the world. The diagnosis and treatment of cancer have also been involved, and elderly head and neck squamous carcinoma is one of them. This study aimed to assess the impact of COVID-19 on elderly patients with head and neck squamous cell carcinoma (HNSCC) in our center. Methods: This retrospective study analyzed the clinical characteristics of 400 HNSCC patients over 65 years of age, calculated their treatment interruption rates, and compared the time of delayed diagnosis. Results: The rate of elderly patients with HNSCC with a delayed diagnosis was higher in the "during COVID-19 pandemic" group (DCOV19 group) than in the "during COVID-19 pandemic" group (BCOV19 group), and the difference was statistically significant (p=0.0017). There was a substantial difference in the rate of treatment interruption between the two groups (p=0.002). Conclusions: This is the first study to explore the effect of the COVID-19 pandemic on visits and treatment interruptions in elderly patients with HNSCC. The current impact of the COVID-19 pandemic on HNSCC treatment has resulted in reductions and delays in diagnosing cancer and providing treatment.

Effect of inactivated COVID-19 vaccination on intrauterine insemination cycle success: A retrospective cohort study.

Background: Vaccine hesitancy was found in couples seeking artificial reproductive technology (ART) services. As the main vaccine used in China, investigations into the influence of inactivated coronavirus disease 2019 (COVID-19) vaccines on human fertility is needed. Methods: This retrospective cohort study included data on COVID-19 vaccination, clinical characteristics, and reproductive outcome of 1,000 intrauterine insemination (IUI) cycles in 653 couples from March 2021 to March 2022 in a single university hospital-based center for reproductive medicine. The IUI cycles were divided into two categories based on sperm source, including 725 cycles in 492 women undergoing artificial insemination with their husband's sperm (AIH) and 275 cycles in 161 women undergoing artificial insemination with donor sperm (AID). Women were then divided into two groups. The vaccine exposed group included women vaccinated prior to insemination and the unexposed group included women who were not vaccinated or vaccinated after insemination. Reproductive outcomes including ongoing pregnancy rate, clinical pregnancy rate, and miscarriage rate were assessed. Results: Inactivated COVID-19 vaccinated women prior to intrauterine insemination in AIH cycles have comparable ongoing pregnancy rate (11.1 vs. 10.3%, P = 0.73), clinical pregnancy rate (12.5 vs. 11.3%, P = 0.60) as compared with unvaccinated counterparts. Similarly, there were no significant differences in ongoing pregnancy rate (20.9 vs. 28.1%, P = 0.17), clinical pregnancy rate (21.7 vs. 28.8%, P = 0.19) between vaccine exposed and unexposed groups in AID cycles. Multivariable logistic regression analyses showed that inactivated COVID-19 vaccination status cannot independently influence the reproductive outcomes of AIH and AID cycles. Subgroup analysis of vaccine exposed cycles showed that doses of vaccination and Interval between the last dose of vaccination and insemination have no influence on the reproductive outcomes of AIH cycles. Conclusions: No negative effects were found on female fertility in IUI cycles following exposure to the inactivated COVID-19 vaccine. These findings indirectly reflect the safety of inactivated COVID-19 vaccine toward reproductive health and help to mitigate vaccine hesitancy among people planning to conceive.