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Aim: To analyze the role of the logistics support services in nosocomial infection control during emergency periods, with a focus on job responsibilities including the organization of vehicle parking, supply of hospital meals, washing of medical bedding and clothing, disposal and management of medical sewage and waste, elevator services, disinfection of air conditioning systems, disinfection and cleaning of ambulances, management of hospital buildings, storage of sterilization supplies, reception and delivery of oxygen cylinders and protection of staff health as examples. Methods: The adjustment and optimization of the emergency support system and working mode as part of hospitals' response to major public emergencies were summarized, and the vital supporting role of the logistics support services in nosocomial infection control was analyzed. Results: The logistics support services played a crucial role in ensuring the high-performance operations of the hospitals and control of nosocomial infections, resulting in the excellent outcome of "zero infection” among hospital staff. Conclusion: Establishing a safe, flexible and efficient system for the logistics support services is important in ensuring an effective response by hospitals to health emergencies.
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Aim: To analyze the role of the logistics support services in nosocomial infection control during emergency periods, with a focus on job responsibilities including the organization of vehicle parking, supply of hospital meals, washing of medical bedding and clothing, disposal and management of medical sewage and waste, elevator services, disinfection of air conditioning systems, disinfection and cleaning of ambulances, management of hospital buildings, storage of sterilization supplies, reception and delivery of oxygen cylinders and protection of staff health as examples. Methods: The adjustment and optimization of the emergency support system and working mode as part of hospitals' response to major public emergencies were summarized, and the vital supporting role of the logistics support services in nosocomial infection control was analyzed. Results: The logistics support services played a crucial role in ensuring the high-performance operations of the hospitals and control of nosocomial infections, resulting in the excellent outcome of "zero infection" among hospital staff. Conclusion: Establishing a safe, flexible and efficient system for the logistics support services is important in ensuring an effective response by hospitals to health emergencies.
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Multinational firms can outsource to contract manufacturers in low-labor-cost regions. However, in recent years, several developed countries and regions have subsidized their local manufacturers (LM[s], she) to encourage reshoring for external benefit (e.g., creating more domestic jobs or improving industrial structure), especially after the COVID-19 pandemic started. This paper investigates the sourcing problem of an LM with brand premium in the presence of government subsidy and differences in labor costs. An LM faces three options: producing in-house, outsourcing to an original brand manufacturer (OBM, he), which sells competitive substitutes without brand premium, or outsourcing to a non-competing contract manufacturer (NCM). We find that, first, the LM chooses reshoring if the external benefit or brand premium is sufficiently high. Second, if the LM decides to outsource, she chooses the OBM (NCM) if her brand premium is high (low). Third, the government prefers to subsidize LM reshoring or outsourcing to an NCM. If the government intends to induce LM to reshore, the subsidy should be at a moderate level. Interestingly, when the LM has a low brand premium but chooses outsourcing, the government still subsidizes her to improve her competitiveness.
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Background: Ammonia acyl tRNA synthase complex interaction of multifunctional protein 1 (AIMP1) is a specific type of cytokine, which controls angiogenesis, inflammation, and the healing of wounds. Previous studies have reported that AIMP1 exhibits anti-tumor activity. However, these studies have not determined the molecular functions of AIMP1. Moreover, scientists have not yet clearly elucidated the relationship between AIMP1 and tumor-infiltrating immune cells (TIICs) of lung adenocarcinoma (LUAD) tissues. In this study, our main aim to understand how AIMP1 is related to the occurrence and development of LUAD. Moreover, we also elucidated the relationship between the expression of AIMP1 and the immune microenvironment. This new idea is the basis for providing targeted treatment to LUAD patients. Methods: To determine the expression of AIMP1 in LUAD tissues, we used the Tumor Immune Evaluation Resource (TIMER) database. To understand the relationship between the expression of AIMP1 and the survival time of LUAD patients, we constructed the Kaplan-Meier plotter with the help of R software. The LUAD data was downloaded and analyzed from the GEO database. Thus, we established a correlation between AIMP1 and various clinicopathological parameters of LUAD patients. The Western Blot technique and immunohistochemistry (IHC) tests were conducted to ascertain the expression of AIMP1 in 165 LUAD patients, which were recruited from the Affiliated Hospital of Nantong University (Nantong, Jiangsu Province, China). Thereafter, KEGG enrichment analysis and protein-protein interaction (PPI) network analysis were performed to determine the potential biological functions of AIMP1. Furthermore, the relationship between AIMP1 and tumor immune infiltration was revealed by the deconvolution algorithm of the analytical tool named CIBERSORT and the TIMER2.0 database. Results: The distribution of AIMP1 was estimated in the tumor tissues of all TCGA cancers. We found that the expression of AIMP1 was significantly enhanced in LUAD patients. However, the prognosis of LUAD patients was better when the mRNA expression of AIMP1 was upregulated. Furthermore, the protein level of AIMP1 was significantly greater in LUAD tissues (p < 0.05). By performing multivariate cox analysis, we found that AIMP1 acts as an independent prognostic factor of LUAD. Moreover, the expression of AIMP1 was found to have a correlation with tumor size and lymph node metastasis. The KEGG enrichment analysis and gene ontology (GO) database proved that AIMP1 enriched the immune-related activities of genes co-expressed with AIMP1. Cell cycle, COVID-19, and other signaling pathways were involved in this process. In addition, the expression of AIMP1 was positively correlated to the infiltration of following cell types: CD4 + T cells, activated dendritic cells, and macrophages. At the same time, they were negatively correlated to the infiltration of following cell types: B cells, regulatory T cells, and myeloid dendritic cells. Conclusions: Our findings indicate that the expression of AIMP1 was an independent prognostic factor of LUAD. Moreover, its overexpression was conducive in creating an anti-tumor immune microenvironment. However, further studies must be conducted to evaluate the potential role of AIMP1, which acts as a biomarker in eliciting an immunotherapeutic effect on LUAD patients.
Subject(s)
Neoplasms , COVID-19 , InflammationABSTRACT
Recently emerged SARS-CoV-2 Omicron subvariant, BA.2.75, displayed a growth advantage over circulating BA.2.38, BA.2.76 and BA.5 in India. However, the underlying mechanisms for enhanced infectivity, especially compared to BA.5, remain unclear. Here we show BA.2.75 exhibits substantially higher affinity for host receptor ACE2 than BA.5 and other variants. Structural analyses of BA.2.75 Spike shows its decreased thermostability and increased frequency of the receptor binding domain (RBD) in the “up” conformation under acidic conditions, suggesting enhanced low-pH-endosomal cell entry. Relative to BA.4/BA.5, BA.2.75 exhibits reduced evasion of humoral immunity from BA.1/BA.2 breakthrough-infection convalescent plasma, but greater evasion of Delta breakthrough-infection convalescent plasma. BA.5 breakthrough infection plasma also exhibits weaker neutralization against BA.2.75 than BA.5, mainly due to BA.2.75’s distinct neutralizing antibody escape pattern. Antibody therapeutics Evusheld and Bebtelovimab remain effective against BA.2.75. These results suggest BA.2.75 may prevail after BA.4/BA.5, and its increased receptor-binding capability could support further immune-evasive mutations. Graphical SARS-CoV-2 BA.2.75 is growing rapidly and globally. Cao et al. solved the structure of BA.2.75 spike and show it has stronger binding to human ACE2 than previous variants. BA.2.75 also exhibited distinct antigenicity compared to BA.5, escaping neutralizing antibodies targeting various epitopes and evading convalescent plasma from BA.5 breakthrough infections.
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Background: Many issues, such as severity assessment and antibody responses, remain to be answered eagerly for evaluation and understanding of COVID-19. Immune lesion is one of key pathogenesis of the disease. It would be helpful to understand the disease if an investigation on antigenemia and association was conducted in the patients with SARS-CoV-2 infection. Methods: A total of 156 patients admitted to the First People's Hospital of Hefei or Anhui Provincial Hospital on January to February 2020 were involved in this study. SARS-CoV-2 nucleocapsid (NP) antigen, specific IgM/IgG antibodies, and RNA were detected in sequential sera from three COVID-19 patients, and additional 153 COVID-19 patients by means of NP-antigen capture enzyme-linked immunosorbent assay, colloidal gold quick diagnosis, and real-time RT-PCR, respectively. The clinical types of COVID-19 patients were classified into asymptomatic, mild, moderate, severe, and critical, following on the Chinese guideline of COVID-19 diagnosis and treatment. The demographic and clinical data of patients were obtained for comparable analysis. Results: NP antigen was detected in 5 of 20 sequential sera collected from three COVID-19 patients with typically clinical symptoms, and 60.13% (92/153) expanded samples collected within 17 days after illness onset. No SARS-CoV-2 RNA segment was detected in these sera. The NP positive proportion reached a peak (84.85%, 28/33) on 6 to 8 days after illness onset. Both NP concentration and positive proportion were increased with the increase of clinical severity of COVID-19. Compared to NP negative patients, NP positive patients had older age [years, medians (interquartile ranges (IQR)), 49 (6) vs. 31 (11)], lower positive proportion of NP specific IgM [27.17% (25/92) vs. 59.02% (36/61)], and IgG [21.74% (20/92) vs. 59.02% (36/61)] antibodies, and longer duration [days, medians (IQR), 24 (10) vs. 21 (13)] from illness to recovery. Conclusions: SARS-CoV-2 NP antigenemia occurred in COVID-19, and presented highly prevalent at early stage of the disease. The antigenemia was related to clinical severity of the disease, and may be responsible for the delay of detectable SARS-Cov-2 IgM.
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As the outbreak of the Covid-19 pandemic, isopropyl alcohol (IPA) molecules played significant role as a biomarker for anti-virus diagnosis. However, conventional gas molecules detection exhibited dramatic drawbacks, like the strict working conditions of ion mobility methodology and weak light-matter interaction of mid-infrared spectroscopy, yielding a limited response of targeted molecules. We propose a synergistic methodology of artificial intelligence (AI)-augmented ion mobility and mid-infrared spectroscopy(IMMS), leveraging the complementary features from the sensing signal in different dimensions to reach superior accuracy for IPA identification. We pull in “cold” plasma discharge from triboelectric generator which improves the mid-infrared spectroscopic response of IPA with good linear prediction. Moreover, even with interferences of more than three different carbon-based gases, this synergistic methodology achieved ～99.08% accuracy for a precise gas concentration prediction. The synergistic methodology of AI-augmented IMMS creates a mechanism of gas sensing for accurate gas mixture and regression prediction in healthcare.
Subject(s)
COVID-19ABSTRACT
Background As COVID-19 continues to spread rapidly in 2019, the risks to human health cannot be underestimated. There is still lack of antiviral drugs for COVID-19, and the development of effective treatments is urgent. Traditional Chinese Medicine (TCM) has been widely used in the treatment of epidemic infectious diseases, The purpose of this randomized controlled clinical trial will to evaluate the clinical efficacy and safety of Hanshiyi Formula (HSYF) in patients with COVID-19.Methods We will conduct this randomized, controlled, open, non-inferiority test clinical study in 240 COVID-19 subjects. Eligible patients will be divided into a control group ( LH granule ) or a treatment group ( HSYF ) in a 1:1 ratio. The intervention duration will be 14 days, and the medication could be stopped in advance if the discharge standard was reached. Clinical efficacy measures will be analyzed at baseline and on day 1–14 of enrollment, The occurrence of adverse events will be monitored throughout the trial. The statistical analysis plan included the treatment of missing data, the analysis of outcome measures, and the method of safety endpoints.Discussion To investigate the efficacy and safety of HSYF in the treatment of COVID-19, provide more sufficient high-quality evidence-based medical basis for TCM intervention in the diagnosis and treatment of COVID-19. To avoid selective reporting bias and data-driven analysis, the statistical analysis plan will standardize the statistical analysis of clinical trials.Trial registration: Chinese Clinical Trial Registry, ChiCTR2200058384. Version V1.2, created on April 11, 2022.https://www.chictr.org.cn/com/25/hvshowproject.aspx?id=159938.
Subject(s)
COVID-19ABSTRACT
Background: Recent applications of wastewater-based epidemiology (WBE) have demonstrated its ability to track the spread and dynamics of COVID-19 at the community level. Despite the growing body of research, quantitative synthesis of SARS-CoV-2 titers in wastewater generated from studies across space and time using diverse methods has not been performed. Objective: The objective of this study is to examine the correlations between SARS-CoV-2 viral titers in wastewater across studies, stratified by key covariates in study methodologies. In addition, we examined the associations of proportions of positive detections (PPD) in wastewater samples and methodological covariates. Methods: We systematically searched the Web of Science for studies published by February 16th, 2021, performed a reproducible screen, and employed mixed-effects models to estimate the levels of SARS-CoV-2 viral titers in wastewater samples and their correlations to case prevalence, sampling mode (grab or composite sampling), and the fraction of analysis (FOA, i.e., solids, solid-supernatant mixtures, or supernatants/filtrates) Results: A hundred and one studies were found; twenty studies (1,877 observations) were retained following a reproducible screen. The mean of PPD across all studies was 0.67 (95%-CI, [0.56, 0.79]). The mean titer was 5,244.37 copies/mL (95%-CI, [0; 16,432.65]). The Pearson Correlation coefficients (PCC) between viral titers and case prevalences were 0.28 (95%-CI, [0.01; 0.51) for daily new cases or 0.29 (95%-CI, [-0.15; 0.73]) for cumulative cases. FOA accounted for 12.4% of the variability in PPD, followed by case prevalence (9.3% by daily new cases and 5.9% by cumulative cases) and sampling mode (0.6%). Among observations with positive detections, FOA accounted for 56.0% of the variability in titers, followed by sampling mode (6.9%) and case prevalence (0.9% by daily new cases and 0.8% by cumulative cases). While sampling mode and FOA both significantly correlated with SARS-CoV-2 titers, the magnitudes of increase in PPD associated with FOA were larger. Mixed-effects model treating studies as random effects and case prevalence as fixed effects accounted for over 90% of the variability in SARS-CoV-2 PPD and titers. Interpretations: Positive pooled means and confidence intervals in PCC between SARS-CoV-2 titers and case prevalence indicators provide quantitative evidence reinforcing the value of wastewater-based monitoring of COVID-19. Large heterogeneities among studies in proportions of positive detections, titers, and PCC suggest a strong demand in methods to generate data accounting for cross-study heterogeneities and more detailed metadata reporting. Large variance explained by FOA suggesting FOA as a direction that needs to be prioritized in method standardization. Mixed-effects models accounting for study level variations provide a new perspective to synthesize data from multiple studies.
Subject(s)
COVID-19 , Severe Acute Respiratory SyndromeABSTRACT
Nonoverlapping sequential pattern mining, as a kind of repetitive sequential pattern mining with gap constraints, can find more valuable patterns. Traditional algorithms focused on finding all frequent patterns and found lots of redundant short patterns. However, it not only reduces the mining efficiency, but also increases the difficulty in obtaining the demand information. To reduce the frequent patterns and retain its expression ability, this paper focuses on the Nonoverlapping Maximal Sequential Pattern (NMSP) mining which refers to finding frequent patterns whose super-patterns are infrequent. In this paper, we propose an effective mining algorithm, Nettree for NMSP mining (NetNMSP), which has three key steps: calculating the support, generating the candidate patterns, and determining NMSPs. To efficiently calculate the support, NetNMSP employs the backtracking strategy to obtain a nonoverlapping occurrence from the leftmost leaf to its root with the leftmost parent node method in a Nettree. To reduce the candidate patterns, NetNMSP generates candidate patterns by the pattern join strategy. Furthermore, to determine NMSPs, NetNMSP adopts the screening method. Experiments on biological sequence datasets verify that not only does NetNMSP outperform the state-of-the-arts algorithms, but also NMSP mining has better compression performance than closed pattern mining. On sales datasets, we validate that our algorithm guarantees the best scalability on large scale datasets. Moreover, we mine NMSPs and frequent patterns in SARS-CoV-1, SARS-CoV-2 and MERS-CoV. The results show that the three viruses are similar in the short patterns but different in the long patterns. More importantly, NMSP mining is easier to find the differences between the virus sequences.
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Objective: To explore the characteristics and relationship between physical activity and self-efficacy of college students during the COVID-19 epidemic, so as to provide evidence for the orderly development of physical education and curriculum reform of college students after their return to school.
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In the Chinese medical insurance industry, the assessor's role is essential and requires significant efforts to converse with the claimant. This is a highly professional job that involves many parts, such as identifying personal information, collecting related evidence, and making a final insurance report. Due to the coronavirus (COVID-19) pandemic, the previous offline insurance assessment has to be conducted online. However, for the junior assessor often lacking practical experience, it is not easy to quickly handle such a complex online procedure, yet this is important as the insurance company needs to decide how much compensation the claimant should receive based on the assessor's feedback. In order to promote assessors' work efficiency and speed up the overall procedure, in this paper, we propose a dialogue-based information extraction system that integrates advanced NLP technologies for medical insurance assessment. With the assistance of our system, the average time cost of the procedure is reduced from 55 minutes to 35 minutes, and the total human resources cost is saved 30% compared with the previous offline procedure. Until now, the system has already served thousands of online claim cases.
Subject(s)
COVID-19ABSTRACT
Knowledge bases (KBs) and text often contain complementary knowledge: KBs store structured knowledge that can support long range reasoning, while text stores more comprehensive and timely knowledge in an unstructured way. Separately embedding the individual knowledge sources into vector spaces has demonstrated tremendous successes in encoding the respective knowledge, but how to jointly embed and reason with both knowledge sources to fully leverage the complementary information is still largely an open problem. We conduct a large-scale, systematic investigation of aligning KB and text embeddings for joint reasoning. We set up a novel evaluation framework with two evaluation tasks, few-shot link prediction and analogical reasoning, and evaluate an array of KB-text embedding alignment methods. We also demonstrate how such alignment can infuse textual information into KB embeddings for more accurate link prediction on emerging entities and events, using COVID-19 as a case study.
Subject(s)
COVID-19ABSTRACT
To explore the correlation between T lymphocytes and clinical severity in patients of COVID-19. A total of 183 COVID-19 patients were recruited in Shenzhen Third People's Hospital from January 11 to February 16, 2020. According to the clinical classification criteria, they were divided into severe group (46 cases) and non-severe (137cases). T lymphocyte counts, lymphocyte subpopulation, IL-6 levels, and clinical outcomes were compared between the two groups. Compared with the non-severe group, the lymphocyte count, T lymphocyte count, T lymphocyte percentage, CD4+ T lymphocyte count, CD4+ T lymphocyte percentage, CD8+ T lymphocyte count, and CD8+ T lymphocyte percentage were lower in the severe group (p < 0.05). Compared with the non-severe group, IL-6 were higher in the severe group (p < 0.05). Compared with admission, the T lymphocyte count, CD4+ T lymphocyte count, and CD8+ T lymphocyte count were significantly increased upon discharge in severe patients, non-severe patients and all patients. Multivariate Logsitic regression analysis showed CD4+ T lymphocyte count (OR −0.011;95% CI −0.041 to −0.001;p = 0.011), CD8+ T lymphocyte count (OR −0.14;95% CI −0.048 to −0.003;p = 0.013) were closely correlated with the clinical severity in patients of COVID-19. Multivariate Logsitic regression analysis also showed CD4+ T lymphocyte count (OR −0.012;95% CI −3.177 to 0.261;p = 0.021), CD8+ T lymphocyte count (OR −0.019;95% CI −5.852 to 0.115;p = 0.004) were independent predictors of disease progressing to the composite endpoint. Subgroup analysis for critically ill patients: The T lymphocyte count, CD4+ T lymphocyte count, and CD8+ T lymphocyte count remained low in the death patients. The T lymphocyte count, CD4+ T lymphocyte count, and CD8+ T lymphocyte count recovered soon in the discharged patients. In the event of COVID-19 infection, the T-lymphoid system is the primary activated immune system. The T lymphocytes, CD4+ T lymphocytes, CD8+ T lymphocytes continued to be low may be significantly related to the deterioration of the disease, and may indicate a poor prognosis. [ABSTRACT FROM AUTHOR] Copyright of European Journal of Inflammation (Sage Publications, Ltd.) is the property of Sage Publications, Ltd. 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 abstract 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 abstract. (Copyright applies to all Abstracts.)
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Background: The optimal timing of corticosteroid treatment for coronavirus disease 2019(COVID-19) pneumonia is uncertain. We evaluated the clinical outcomes of methylprednisolone therapy (MPT) for patients with a high-risk common type(HRCT) COVID-19 pneumonia. Methods: We conducted a multi-centre retrospective cohort study in northeast China. A comparison was performed between the standard treatment (SDT) group and the SDT+MPT group to determine the efficacy of methylprednisolone in treating HRCT COVID-19 pneumonia. Results: We collected the medical records of 403 patients with HRCT COVID-19 pneumonia (127 in the SDT+MPT group and 276 in the SDT group). None of the patients had received mechanical ventilation or died. Further, there had been no side-effects associated with of MPT. Patients in the SDT+MPT group treated with methylprednisolone received an intravenous injection for a median interval of five days (interquartile range of three to seven days). The trends in lymphocyte count, C-reactive protein, interleukin 6, lactic acid dehydrogenase, respiratory rate, SpO2, PaO2, D-dimer and body temperature were similar between the SDT+MPT and SDT groups. The results for the SDT+MPT group seems to be faster improved than the SDT group; however, the results were not statistically significant. Clinical outcomes revealed that the average hospitalisation days and the rate of progression to severe type COVID-19 pneumonia in both the SDT+MPT group and the SDT group were present in 14.56±0.57days vs 16.55±0.3days(p=0.0009) and 21.26%(27/127) vs 32.4%(89/276)(p=0.0254), respectively. The 16-day nucleic acid negative rate was higher in the SDT+MPT group than the SDT group, 81.73% (104/127) vs 65.27% (180/276) (p = 0.0014). Conclusions: MPT effectively prevents patients with HRCT COVID-19 pneumonia from progressing to the severe stage. Therefore, patients with HRCT may be the optimal timing for MPT.Funding Statement: 1.The National Key Laboratory of Sponsored by Open Project of State Key Laboratory of Respiratory Disease (Project Funding Number：SKLRD-OP-201902)” 2.The National Key Laboratory of Urban Water Resources and Water Environment Full Funds. (Project Funding Number：ESK201602.)Declaration of Interests: We have not any conflict of interests to declare.Ethics Approval Statement: Ethical approval by the institutional ethics board of the Qun'li branch of the First Affiliated Hospital of Harbin Medical University and Kang'an Hospital of Mudanjiang was obtained for the analysis and summary of clinical data from COVID-19-infected inpatients.
Subject(s)
Coronavirus Infections , Laboratory Infection , COVID-19ABSTRACT
Background: AKI is related to severe adverse outcomes and mortality with Coronavirus Infection Disease 2019 (COVID-19) patients, that early diagnosed and intervened is imperative. Neutrophil gelatinase-associated lipocalin (NGAL) is one of the most promising biomarkers for detection of acute kidney injury (AKI), but current detection methods are inadequacy, so more rapid, convenient and accuracy methods are needed to detect NGAL for early diagnosis of AKI. Herein, we established a rapid, reliable and accuracy lateral flow immunoassay based on europium nanoparticles (Eu-NPS-LFIA) for the detection of NGAL in human urine specimens. Methods: : A double-antibody sandwich immunofluorescent assay using europium doped nanoparticles was employed and the NGAL monoclonal antibodies conjugate as labels were generated by optimizing electric fusion parameters. Eighty-three urine samples were used to evaluate the clinical application efficiency of this method. Results: : The quantitative detection range of NGAL in AKI was 1-3000 ng/mL, and the detection sensitization was 0.36 ng/mL. The CV of intra-assay and inter-assay were 2.57%-4.98% and 4.11%-7.83%, respectively. Meanwhile, the correlation coefficient between Eu-NPS-LFIA and ARCHITECT analyzer was significant (R 2 =0.9829, n=83, p <0.01). Conclusions: : Thus, a faster and easier operation quantitative assay of NGAL for AKI has been established, which is very important and meaningful to diagnose the early AKI, suggesting that the assay can provide an early warning of final outcome of disease.