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With the upgrading and innovation of the logistics industry, the requirements for the level of transportation smart technologies continue to increase. The outbreak of the COVID-19 has further promoted the development of unmanned transportation machines. Aimed at the requirements of intelligent following and automatic obstacle avoidance of mobile robots in dynamic and complex environments, this paper uses machine vision to realize the visual perception function, and studies the real-time path planning of robots in complicated environment. And this paper proposes the Dijkstra-ant colony optimization (ACO) fusion algorithm, the environment model is established by the link viewable method, the Dijkstra algorithm plans the initial path. The introduction of immune operators improves the ant colony algorithm to optimize the initial path. Finally, the simulation experiment proves that the fusion algorithm has good reliability in a dynamic environment. © 2022 IEEE.
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In December 2019, a virus named SARS-CoV-2 broke out in Wuhan in China. The spread of the virus has brought great challenges to the global medical system. At present, over 6 million people died of the diseases caused by the virus. Under these situations, various corresponding vaccines such as Oxford, Pfizer, and Moderna vaccines have been developed and applied to the population. Nevertheless, due to the development of variants of the virus such as Delta and Omicron, there has been a decline in the effectiveness of current vaccines to some extent. Moreover, the proportion of people who have been inoculated with the COVID-19 vaccine in low-income countries is less than 20%. In this case, we designed a new vaccine to deal with these problems. Specifically, we utilized the antigens (RBD, HR1, and HR2) of the virus to cope with its potential variants of it, increasing the effectiveness of the vaccine. Moreover, we designed a new cell expression system to increase the efficiency of vaccine production by using CHO cells as host cells, Neo gene as a selective marker, CMV as a promoter, MBP as affinity tag, and β-globin as a terminator. Eventually, it was worth stating that our designed vaccine was hypothesized to be practicable and functional, it just started one step on the way to tackling the variants of this virus and increasing the productivity of the vaccine. The detailed experiments still needed to be implemented to verify the feasibility of our design. © 2023 SPIE.
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Traffic flowprediction has always been the focus of research in the field of Intelligent Transportation Systems, which is conducive to the more reasonable allocation of basic transportation resources and formulation of transportation policies. The spread of COVID-19 has seriously affected the normal order in the transportation sector. With the increase in the number of infected people and the government's anti-epidemic policy, human outgoing activities have gradually decreased, resulting in increasingly obvious discreteness and irregularities in traffic flow data. This article proposes a deep-space time traffic flow prediction model based on discrete wavelet transform (DSTM-DWT) to overcome the highly discrete and irregular nature of the new crown epidemic. First, DSTM-DWT decomposes traffic flow into discrete attributes, such as flow trend, discrete amplitude, and discrete baseline. Second, we design the spatial relationship of the transportation network as a graph and integrate the new crown pneumonia epidemic data into the characteristics of each transportation node. Then, we use the graph convolutional network to calculate the spatial correlation of each node, and the temporal convolutional network to calculate the temporal correlation of the data. In order to solve the problem of high discreteness of traffic flow data during the epidemic, this article proposes a graph memory network (GMN), which is used to convert discrete magnitudes separated by discrete wavelet transform into highdimensional discrete features. Finally, use DWT to segment the predicted traffic data, and then perform the inverse discrete wavelet transform between the newly segmented traffic trend and discrete baseline and the discrete model predicted by GMN to obtain the final traffic flow prediction result. In simulation experiments, this work was compared with the existing advanced baselines to verify the superiority of DSTM-DWT.
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Background and Objectives: The WHO has identified HCV infection as a public health threat and set a global target for HCV elimination by 2030, yet currently only 11 countries are on track to achieve HCV elimination targets. Up to 60% of HCV + patients are lost to follow-up and remain untreated and this has likely been further exacerbated by the COVID-19 pandemic, which may have reduced HCV treatment urgency, causing many patients to delay care. To achieve the WHO goal, still many patients need to be screened and linked to care. Gilead has been running Local Elimination Programs Leading to Global Action in HCV (LEGA-C) to support implementation science projects toward HCV elimination. Here, we explore the outcomes of LEGA-C programs for patients with HCV especially in Asia. Method(s): The outcomes and impact were measured through the number of studies and patients to be reached;steps in the care cascade as well as efficacy of each model were assessed along with the presentations and publications from each study. Result(s): In total,[120 studies were supported. Of these, 18 have completed or are ongoing in Asia. Through July 2022, 175,192 persons were screened, 6,287 were HCV + and enrolled in a study, and 3,768 received treatment. A simplified screening and linkage to care/ minimal monitoring model was investigated in 8 studies and demonstrated that linkage to care with minimal monitoring could achieve antiviral response comparable to standard practice.[i] Four test-and-treat studies showed that aggressive screening and on-site treatment promotes HCV microelimination.[ii] Three outreach-andcallback studies showed demonstrated the feasibility of recruiting persons to HCV screening programs in community settings.[iii] Seven studies focused on special populations, and 4 of them described the characteristics of special populations with higher rates of HCV infection. Publications from these studies in Asia include 14 full articles, and these papers were cited a total of 56 times. Conclusion(s): The ongoing LEGA-C initiative is demonstrably contributing to the understanding, treatment, and ultimate elimination of HCV. Innovative ideas, active promotion of HCV testing, disease education, patient navigation, and care coordination in these programs led to increased screening and rates of linkage to care. Adopting and adapting effective strategies from these programs may be a feasible way to increase treatment numbers and improve patient outcomes, thus contributing to meeting the WHO goal of HCV elimination in Asia.
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Wearing masks is an easy way to operate and popular measure for preventing epidemics. Although masks can slow down the spread of viruses, their efficacy in gathering environments involving heterogeneous person-to-person contacts remains unknown. Therefore, we aim to investigate the epidemic prevention effect of masks in different real-life gathering environments. This study uses four real interpersonal contact datasets to construct four empirical networks to represent four gathering environments. The transmission of COVID-19 is simulated using the Monte Carlo simulation method. The heterogeneity of individuals can cause mask efficacy in a specific gathering environment to be different from the baseline efficacy in general society. Furthermore, the heterogeneity of gathering environments causes the epidemic prevention effect of masks to differ. Wearing masks can greatly reduce the probability of clustered epidemics and the infection scale in primary schools, high schools, and hospitals. However, the use of masks alone in primary schools and hospitals cannot control outbreaks. In high schools with social distancing between classes and in workplaces where the interpersonal contact is relatively sparse, masks can meet the need for prevention. Given the heterogeneity of individual behavior, if individuals who are more active in terms of interpersonal contact are prioritized for mask-wearing, the epidemic prevention effect of masks can be improved. Finally, asymptomatic infection has varying effects on the prevention effect of masks in different environments. The effect can be weakened or eliminated by increasing the usage rate of masks in high schools and workplaces. However, the effect on primary schools and hospitals cannot be weakened. This study contributes to the accurate evaluation of mask efficacy in various gathering environments to provide scientific guidance for epidemic prevention. © 2022, Higher Education Press.
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There is evidence suggesting that infection with SARS-CoV-2 can lead to several long-term sequelae including diabetes. This mini-review examines the rapidly evolving and conflicting literature on new-onset diabetes after COVID-19, which we term NODAC. We searched PubMed, MEDLINE, and medRxiv from inception until December 1, 2022 using both MeSH terms and free text words including "COVID-19," "SARS-CoV-2," "diabetes," "hyperglycemia," "insulin resistance," and "pancreatic ß-cell." We also supplemented searches by examining reference lists from retrieved articles. Current evidence suggests that COVID-19 increases the risk of developing diabetes, but the attributable risk is uncertain due to limitations of study designs and the evolving nature of the pandemic, including new variants, widespread population exposure to the virus, diagnostic options for COVID-19 and vaccination status. The etiology of diabetes after COVID-19 is likely multifactorial and includes factors associated with host characteristics (e.g., age), social determinants of health (e.g., deprivation index), and pandemic-related effects both at the personal (e.g., psychosocial stress) and the societal-community level (e.g., containment measures). COVID-19 may have direct and indirect effects on pancreatic ß-cell function and insulin sensitivity related to: the acute infection and its treatment (e.g., glucocorticoids); autoimmunity; persistent viral residency in multiple organs including adipose tissue; endothelial dysfunction; and hyperinflammatory state. While our understanding of NODAC continues to evolve, consideration should be given for diabetes to be classified as a post-COVID syndrome, in addition to traditional classifications of diabetes (e.g., type 1 or type 2), so that the pathophysiology, natural history and optimal management can be studied.
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Background: Previous studies have demonstrated promising serologic responses in PLWH receiving a third dose of vaccine against SARS-CoV-2. However, real-world clinical effectiveness, especially during the pandemic caused by B.1.1.529 variant, remains less investigated. Method(s): PLWH seeking HIV care at our hospital from 2021/6 to 2022/6 were included and advised to receive the third dose of COVID-19 vaccine. Individuals were excluded from this study if they had been previously diagnosed with COVID-19. Different types of COVID-19 vaccines were available in the vaccination program, including BNT162b2, mRNA-1273 (either 50 or 100 mug), MVC-COV1901 and NVX-CoV2373 vaccines. PLWH were screening for the occurrence of COVID-19 through the reporting system of notifiable diseases of Taiwan CDC, and were tested for anti-nucleocapsid (anti-N) IgG every 1 to 3 months. Participants were followed for 180 days until the fourth dose of COVID-19 vaccination, occurrence of SARS-CoV-2 infection, seroconversion of anti-N IgG, death, or loss to follow-up, whichever occurred first. Result(s): 1,496 PLWH were included: 631 (42.2%) receiving 100 mug mRNA-1273 vaccine, 468 (31.3%) 50 mug mRNA-1273 vaccine, and 328 (21.9%) BNT162b2 vaccine, 65 (4.3%) MVC-COV1901 vaccine, and 4 (0.3%) NVX-CoV2373 vaccine for the third dose of SARS-CoV-2 vaccination. 297 (19.9%) PLWH were diagnosed with COVID-19 during the follow-up period, including 92 (14.6%) who received 100 mug mRNA-1273, 111 (23.7%) 50 mug mRNA-1273, 79 (24.1%) BNT162b2 and 15 (21.7%) either MVC-COV1901 or NVX-CoV2373;in addition, 98 PLWH had seroconversion of anti-N IgG during follow-up, including 23, 50, 19 and 6 PLWH who received 100 mug mRNA-1273, 50 mug mRNA-1273, BNT162b2, and either MVC-COV1901 or NVX-CoV2373, respectively. Similar rates of new infection with SARS-CoV-2 or seroconversion of anti-N IgG were demonstrated regardless the vaccine type of the third dose (log-rank test, p=0.46). Factors associated with a diagnosis of SARS-CoV-2 infection and seroconversion of anti-N IgG included an age >50 years (aOR, 0.67;95% CI, 0.49-0.91) and newly infected with hepatitis C virus (HCV) (aOR, 1.41;95% CI, 1.09-1.83). Conclusion(s): Our study demonstrated that clinical effectiveness of the third dose of different vaccines available to PLWH was similar in preventing SARSCoV- 2 infection or seroconversion of anti-N IgG Taiwan. PLWH aged less than 50 years and those with newly diagnosed HCV infection were at higher risk of acquiring COVID-19. Kaplan-Meier survival curve for acquiring COVID-19 or seroconversion of anti-N IgG in PLWH receiving different COVID-19 vaccination of the third dose (log-rank test, 4 groups, p = 0.46).
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Background: Previous studies had demonstrated that patients with hematologic malignancies had suboptimal antibody response after receiving COVID-19 vaccines, especially among those having previously treated with anti- CD20 monoclonal antibodies. Method(s): Adult patients with non-Hodgkin's lymphoma or chronic lymphocytic leukemia (CLL) were enrolled before receiving the second dose of SARS-CoV-2 vaccine. Determinations of anti-SARS-CoV-2 spike and nucleocapsid IgG titers were performed every 1-3 months, after they received the second and the third dose of SARS-CoV-2 vaccine, respectively. Patients were excluded from analysis if they were diagnosed with COVID-19. All serum samples were tested for anti-nucleocapsid antibody and those tested positive were excluded from subsequent analyses. Result(s): A total of 85 participants were enrolled, including 42 (49.4%) with diffused large B-cell lymphoma, and 13 (15.3) with follicular lymphoma and 9 with CLL. 72 (84.7%) participants had received anti-CD20 monoclonal antibodies, with a median interval of 24 months between last anti-CD20 treatment and the second dose of vaccine, and 21 (24.7%) had HIV infection. Factors associated with failure to achieve an anti-spike IgG titer >141 BAU/ mL within 12 weeks after the second dose of vaccine included HIV infection (adjusted odds ratio [aOR], 0.14;95% CI, 0.04-0.51), active hematologic disease (aOR, 5.50;95% CI 1.42-21.32), receipt of anti-CD20 monoclonal antibodies (aOR, 6.65;95% CI 1.52-29.07), and receipt of two doses of homologous mRNA vaccination (aOR, 0.17;95% CI 0.05-0.56). In the participants having previously treated with anti-CD20 regimen, only 8.6% achieved an antibody response ( >141 BAU/mL) in the first year, while 78.3% achieved anti-spike IgG titer > 141 BAU/mL after two years post B-cell depleting treatment. After the third dose of SARS-CoV-2 vaccine, 53.6% achieved an antispike IgG titer > 141 BAU/mL in the first year post anti-CD20 treatment. Conclusion(s): Our study demonstrated that previous treatment with anti-CD20 monoclonal antibodies was associated a lower antibody response among patients with lymphoproliferative disorders receiving two doses of SARS-CoV-2 vaccine. While two doses of SARS-CoV-2 vaccines might not be sufficient even one year apart from the last dose of rituximab, a third dose of vaccine may boost anti-spike IgG particularly in the subset of recent exposure to rituximab. Anti-spike IgG determined 1-3 months after the second (A) / third (B) dose of COVID-19 vaccine, stratified by the interval between last anti-CD20 regimen and the second / third dose of COVID-19 vaccine. (Figure Presented).
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Vaccines are crucial for controlling deadly diseases, and how to persuade people to get vaccinated has become a hot topic in enhancing public health benefits. One way to increase the vaccination rate is to raise public awareness of the importance of vaccines through advertising. As an effective and cost-friendly approach, goal framing has been widely used in vaccine advertising. However, the literature has mixed findings about whether positive or negative goal framing is more effective in persuading people to get vaccinated. The present study aims to investigate how temporal distance (present vs. future) interacts with different types of goal framing (positive vs. negative) in persuading people to get the COVID-19 vaccine. We hypothesized that negative goal framing is more persuasive when the advertising focuses on present outcomes, while positive goal framing is more effective when combined with future- focused outcomes. We further hypothesized that the inner mechanism is the intertemporal asymmetry of approach and avoidance motivation. More specifically, the avoidance motivation induced by a negative frame is stronger in the present, while the approach motivation induced by a positive frame is stronger in the future. The perceived risk of COVID-19 moderated this effect. Four studies were conducted to examine our hypotheses. Study 1 was conducted to preliminarily investigate how goal framing and temporal distance jointly influence willingness to get the COVID-19 vaccine. The aim of Study 2 was to verify the mediating effect of approach and avoidance motivation in a different advertising setting, as well as to rule out the potential mediators of the construal level and positive/ negative emotions. In Study 3, we further tested the mediators by manipulating participants' approach and avoidance motivation. Study 4 was a quasi-experiment in which we recruited participants from areas with different levels of COVID-19 risk to test how perceived risk moderated the interaction effect of goal framing and temporal distance. The results showed that a negative goal frame was more persuasive when combined with present-focused advertising, while a positive goal frame was more effective when combined with future- focused advertising (Study 1, N = 363). Avoidance motivation mediated the relationship between the goal frame and vaccine uptake in the present context, while approach motivation mediated the relationship between the goal frame and vaccine uptake in the future context (Study 2, N = 292). The results in Study 3 ( N = 347) revealed that approach motivation priming increases the persuasiveness of the present-positive frame, while avoidance motivation priming increases the persuasiveness of the future- negative frame. COVID-19 risk also had an impact on the relationship between goal framing and temporal distance on vaccine uptake. When the COVID-19 risk was high, the difference in vaccine uptake between present-positive and present-negative conditions disappeared, while the future-positive frame was still more persuasive than the future- negative frame (Study 4, N = 423). In conclusion, the present study found an interactive effect of goal framing and temporal distance in persuading people to get the COVID-19 vaccine. Avoidance/approach motivation mediates the relationship between goal framing and vaccine uptake in the present/future temporal context. The perceived COVID risk further moderated the interaction effect. The present study contributes to both the framing and approachavoidance motivation literature and sheds light on future practices in persuading people to get the COVID vaccine and promoting the uptake of other vaccines.
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Objective: To study the clinical characteristics of diabetes mellitus with Coronavirus disease 2019 (COVID-19) and explore the possible mechanism of diabetes predisposition. Method(s): A single center, retrospective and observational study was used to collect 48 inpatients diagnosed with COVID-19 who were admitted to the first ward of the third department of infection, Raytheon hospital, Wuhan from February 23, 2020 to March 30, 2020. Demographic data, symptoms, laboratory tests, comorbidities, treatments and clinical outcomes have been collected. The patients were divided into non-diabetic group and diabetic group according to the combination of diabetes. The clinical data and laboratory test results of the two groups were observed, and the t test, non-parametric test and Chi square test were used for comparison. Result(s): All the 5 patients with COVID-19 diabetes mellitus had fever and respiratory symptoms, chest CT was consistent with typical COVID-19 imaging features, and novel coronavirus nucleic acid test results were positive. There were no statistically significant differences in age, gender composition, co-existing diseases, clinical symptoms, clinical typing, disease course and treatment plan between the diabetic group and the non-diabetic group (P>0.05).There was a statistically significant difference in fasting blood glucose between the non-diabetic group and the diabetic group (P<0.05).The difference of fasting blood glucose at discharge from the diabetes group compared with that at admission was also statistically significant (P<0.05).There was no statistically significant difference between the two groups in other laboratory examination indexes (P>0.05). Conclusion(s): COVID-19 patients with diabetes are mainly manifested by fever and respiratory symptoms.Chest CT shows typical COVID-19 imaging features.Copyright © 2020 by the Chinese Medical Association.
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We explore how technology use helped to cope with the stresses of social distancing during the pandemic contributing insights about the impact of work adaptation enabled by technology on economic vulnerability and resilience. Using a three-wave survey conducted across 10 states in the United States, we found evidence that a high level of technology use was linked to a greater chance of maintaining employment during the pandemic. We evaluate job retention as a function of an index based on the prevalence of information technology (IT) usage in the workplace and psychological and somatic well-being, controlling for technology use outside of the workplace, and socioeconomic and demographic characteristics. © 2023 The Southern Economic Association.
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BACKGROUND: Consensus has not been reached on what constitutes an optimal diet in individuals with prediabetes and type 2 diabetes mellitus (T2DM), especially between low-carbohydrate options. OBJECTIVES: We compared 2 low-carbohydrate diets with 3 key similarities (incorporating nonstarchy vegetables and avoiding added sugars and refined grains) and 3 key differences (incorporating compared with avoiding legumes, fruits, and whole, intact grains) for their effects on glucose control and cardiometabolic risk factors in individuals with prediabetes and T2DM. METHODS: Keto-Med was a randomized, crossover, interventional trial. Forty participants aged ≥18 years with prediabetes or T2DM followed the well-formulated ketogenic diet (WFKD) and the Mediterranean-plus diet (Med-Plus) for 12 weeks each, in random order. The diets shared the 3 key similarities noted above. The Med-Plus incorporated legumes, fruits, and whole, intact grains, while the WFKD avoided them. The primary outcome was the percentage change in glycated hemoglobin (HbA1c) after 12 weeks on each diet. Secondary and exploratory outcomes included percentage changes in body weight, fasting insulin, glucose, and blood lipids; average glucose from continuous glucose monitor (CGM), and nutrient intake. RESULTS: The primary analysis was of 33 participants with complete data. The HbA1c values did not differ between diets at 12 weeks. Triglycerides decreased more for the WFKD [percentage changes, -16% (SEM, 4%) compared with -5% (SEM, 6%) for the Med-Plus; P = 0.02] and LDL cholesterol was higher for the WFKD [percentage changes, +10% (SEM, 4%) compared with -5% (SEM, 5%) for the Med-Plus; P = 0.01]. Weight decreased 8% (SEM, 1%) compared with 7% (SEM, 1%) and HDL cholesterol increased 11% (SEM, 2%) compared with 7% (SEM, 3%) for the WFKD compared with the Med-Plus, respectively; however, there was a significant interaction of diet × order for both. Participants had lower intakes of fiber and 3 nutrients on the WFKD compared with the Med-Plus. Twelve-week follow-up data suggest the Med-Plus is more sustainable. CONCLUSIONS: HbA1c values were not different between diet phases after 12 weeks, but improved from baseline on both diets, likely due to several shared dietary aspects. The WFKD led to a greater decrease in triglycerides, but also had potential untoward risks from elevated LDL cholesterol and lower nutrient intakes from avoiding legumes, fruits, and whole, intact grains, as well as being less sustainable. This trial was registered at clinicaltrials.gov as NCT03810378.
Subject(s)
Diabetes Mellitus, Type 2 , Diet, Ketogenic , Diet, Mediterranean , Prediabetic State , Adolescent , Adult , Blood Glucose , Cholesterol, LDL , Cross-Over Studies , Glycated Hemoglobin/analysis , Humans , Triglycerides , VegetablesABSTRACT
Online communities play a vital role in coping with mental health problems and have become a popular place for depressed individuals to communicate with others. Yet, little is known about online depression self-help communities, the topics that are commonly being discussed among members of these groups, and if and how topics have evolved during the COVID-19 pandemic. Topics may shift not only because of socio-psychological factors but also due to other contextual factors, such as global pandemics and strict health measures that come with them. At times of crisis, such as the COVID-19 lockdown, topics may attract a higher volume of participation and/or change in scope and range. We address this gap by analyzing 2, 999 posts and 25, 173 comments submitted over a period of three months to two online depression self-help groups in China. We traced the evolution of topics over time—before, during, and after the COVID-19 lockdown—and uncovered topic similarities and variations between the groups during the three stages. Then, we investigated the language features of common concerns and each group's main topics in each stage. We discuss and explain our findings in light of the COVID-19 lockdown in China. We conclude with the implications of the study for research and practice and suggest future research directions. © 2023 selection and editorial matter, Shengnan Yang, Xiaohua Zhu and Pnina Fichman;individual chapters, the contributors.
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Social distance monitoring is of great significance for public health in the era of COVID-19 pandemic. However, existing monitoring methods cannot effectively detect social distance in terms of efficiency, accuracy, and robustness. In this paper, we proposed a social distance monitoring method based on an improved YOLOv4 algorithm. Specifically, our method constructs and pre-processes a dataset. Afterwards, our method screens the valid samples and improves the K-means clustering algorithm based on the IoU distance. Then, our method detects the target pedestrians using a trained improved YOLOv4 algorithm and gets the pedestrian target detection frame location information. Finally, our method defines the observation depth parameters, generates the 3D feature space, and clusters the offending aggregation groups based on the L2 parametric distance to finally realize the pedestrian social distance monitoring of 2D video. Experiments show that the proposed social distance monitoring method based on improved YOLOv4 can accurately detect pedestrian target locations in video images, where the pre-processing operation and improved K-means algorithm can improve the pedestrian target detection accuracy. Our method can cluster the offending groups without going through calibration mapping transformation to realize the pedestrian social distance monitoring of 2D videos. © 2023 World Scientific Publishing Company.
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The Corona Virus Disease 2019 (COVID-19) that occurred December of 2019 has a wide range of impacts, and its epidemic situation is grim. China has a large population of liver cancer, accounting for 50% of new cases of liver cancer worldwide. How to ensure the diagnosis, treatment and rehabilitation of liver cancer patients while preventing and controlling the epidemic situation is an issue that urgently need specialists pay attention to. The authors propose an overall management model for patients with liver cancer, combined with their own experience, in order to guide specialists to safely and effectively carry out clinical diagnosis and treatment of liver cancer during the prevention and control of epidemics, and to help liver cancer patients receive treatment.Copyright © 2020 by the Chinese Medical Association.
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Pandemics such as COVID-19 have exposed global inequalities in essential health care. Here, we proposed a novel analytics of nucleic acid amplification tests (NAATs) by combining paper microfluidics with deep learning and cloud computing. Real-time amplifications of synthesized SARS-CoV-2 RNA templates were performed in paper devices. Information pertained to on-chip reactions in time-series format were transmitted to cloud server on which deep learning (DL) models were preloaded for data analysis. DL models enable prediction of NAAT results using partly gathered real-time fluorescence data. Using information provided by the G-channel, accurate prediction can be made as early as 9 min, a 78% reduction from the conventional 40 min mark. Reaction dynamics hidden in amplification curves were effectively leveraged. Positive and negative samples can be unbiasedly and automatically distinguished. Practical utility of the approach was validated by cross-platform study using clinical datasets. Predicted clinical accuracy, sensitivity and specificity were 98.6%, 97.6% and 99.1%. Not only the approach reduced the need for the use of bulky apparatus, but also provided intelligent, distributable and robotic insights for NAAT analysis. It set a novel paradigm for analyzing NAATs, and can be combined with the most cutting-edge technologies in fields of biosensor, artificial intelligence and cloud computing to facilitate fundamental and clinical research.Copyright © 2023 Elsevier Ltd
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Objective: To study the clinical characteristics of diabetes mellitus with Coronavirus disease 2019 (COVID-19) and explore the possible mechanism of diabetes predisposition. Method(s): A single center, retrospective and observational study was used to collect 48 inpatients diagnosed with COVID-19 who were admitted to the first ward of the third department of infection, Raytheon hospital, Wuhan from February 23, 2020 to March 30, 2020. Demographic data, symptoms, laboratory tests, comorbidities, treatments and clinical outcomes have been collected. The patients were divided into non-diabetic group and diabetic group according to the combination of diabetes. The clinical data and laboratory test results of the two groups were observed, and the t test, non-parametric test and Chi square test were used for comparison. Result(s): All the 5 patients with COVID-19 diabetes mellitus had fever and respiratory symptoms, chest CT was consistent with typical COVID-19 imaging features, and novel coronavirus nucleic acid test results were positive. There were no statistically significant differences in age, gender composition, co-existing diseases, clinical symptoms, clinical typing, disease course and treatment plan between the diabetic group and the non-diabetic group (P>0.05).There was a statistically significant difference in fasting blood glucose between the non-diabetic group and the diabetic group (P<0.05).The difference of fasting blood glucose at discharge from the diabetes group compared with that at admission was also statistically significant (P<0.05).There was no statistically significant difference between the two groups in other laboratory examination indexes (P>0.05). Conclusion(s): COVID-19 patients with diabetes are mainly manifested by fever and respiratory symptoms.Chest CT shows typical COVID-19 imaging features.Copyright © 2020 by the Chinese Medical Association.
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Although the epidemic situation of Corona Virus Disease 2019 (COVID-19) has been controlled, the epidemic situation remains grim. The COVID-19 is highly infectious, with various clinical manifestations including liver injury. The authors make a preliminary investigation on the mechanisms of liver injury related to COVID-19, and put forward corresponding control measures for reference.Copyright © 2020 by the Chinese Medical Association.
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Bacterial drug resistance has become a global public health threat, among which the infection of carbapenem-resistant Enterobacterales (CRE) is one of the top noticeable issues in the global anti-infection area due to limited therapy options. In recent years, the prevalence of CRE transmission around the world has increased, and the transmission of COVID-19 has intensified the situation to a certain extent. CRE resistance can be induced by carbapenemase, porin, efflux pump, penicillin-binding protein alteration, and biofilm production. Deletion, mutation, insertion, and post-transcriptional modification of corresponding coding genes may affect the sensitivity of Enterobacterales bacteria to carbapenems. Clinical and laboratory methods to detect CRE and explore its resistance mechanisms are being developed. Due to the limited options of antibiotics, the clinical treatment of CRE infection also faces severe challenges. The clinical therapies of CRE include single or combined use of antibiotics, and some new antibiotics and treatment methods are also being developed. Hence, this review summarizes the epidemiology, resistance mechanisms, screening and clinical treatments of CRE infection, to provide references for clinical prevention, control and treatment of CRE infection. © 2022 Elsevier GmbH