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The role of CD39 pathway in Th1 cell function in tuberculosis (TB) is rarely elucidated. The present study aims to investigate the modulating mechanism of CD39 pathway during Mycobacterium tuberculosis (MTB) infection. CD39 expression was examined on host immune cells among patients with TB. The relationship between CD39 expression and Th1 cell function was analysed. Patients with TB displayed dramatically higher CD39 expression on Th1 cells than healthy controls, and a significantly increased expression of surface markers, including activation, exhaustion and apoptosis markers, were noted in CD39

The COVID-19 pandemic remains a significant problem involving health systems worldwide. Several diagnostic methods are reported for detecting the coronavirus in clinical, research, and public health laboratories. rRT-PCR is considered the gold standard; however, as it required skilled personnel and special equipment, rapid antigen tests have been developed and used as first-line screening. The serologic testing of antibodies can also be used to enhance the detection sensitivity and accuracy, which are used to assess the overall infection rate. This review summarizes the molecular techniques and serologic assays widely used in China and discusses the advantages and disadvantages of these techniques.

Discriminating active tuberculosis (ATB) from latent tuberculosis infection (LTBI) remains challenging. The present study aims to evaluate the performance of diagnostic models established using machine learning based on routine laboratory indicators in differentiating ATB from LTBI.Participants were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Diagnostic models were established based on routine laboratory indicators using machine learning.A total of 2619 participants (1025 ATB and 1594 LTBI) were enrolled in discovery cohort and another 942 subjects (388 ATB and 554 LTBI) were recruited in validation cohort. ATB patients had significantly higher levels of tuberculosis-specific antigen/phytohemagglutinin ratio and coefficient variation of red blood cell volume distribution width, and lower levels of albumin and lymphocyte count than those of LTBI individuals. Six models were built and the optimal performance was obtained from GBM model. GBM model derived from training set (n = 1965) differentiated ATB from LTBI in the test set (n = 654) with a sensitivity of 84.38% (95% CI, 79.42%-88.31%) and a specificity of 92.71% (95% CI, 89.73%-94.88%). Further validation by an independent cohort confirmed its encouraging value with a sensitivity of 87.63% (95% CI, 83.98%-90.54%) and specificity of 91.34% (95% CI, 88.70%-93.40%), respectively.We successfully developed a model with promising diagnostic value based on machine learning for the first time. Our study proposed that GBM model may be of great benefit served as a tool for the accurate identification of ATB.

Age has been found to be one of the main risk factors for the severity and outcome of COVID-19. However, differences in SARS-CoV-2 specific antibody responses among COVID-19 patients of different age groups remain largely unknown. In this study, we analyzed the IgG/IgM responses to 21 SARS-CoV-2 proteins and 197 peptides that fully cover the spike protein against 731 sera collected from 731 COVID-19 patients aged from 1 to We show that there is no overall difference in SARS-CoV-2 antibody responses in COVID-19 patients in the 4 age groups. By antibody response landscape maps, we find that the IgG response profiles of SARS-CoV-2 proteins are positively correlated with age. The S protein linear epitope map shows that the immunogenicity of the S-protein peptides is related to peptide sequence, disease severity and age of the COVID-19 patients. Furthermore, the enrichment analysis indicates that low S1 IgG responses are enriched in patients aged50 and high S1 IgG responses are enriched in mild COVID-19 patients aged60. In addition, high responses of non-structural/accessory proteins are enriched in severe COVID-19 patients aged70. These results suggest the distinct immune response of IgG/IgM to each SARS-CoV-2 protein in patients of different age, which may facilitate a deeper understanding of the immune responses in COVID-19 patients.

Graphical abstract, Introduction The COVID-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for early predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies evolved with disease progression and severity in COIVD-19 patients. Objectives We assumed that antibodies may serve as biomarkers for predicting the clinical outcome of hospitalized COVID-19 patients on admission. Methods By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgG responses against 20 proteins of SARS-CoV-2 in 1,034 hospitalized COVID-19 patients on admission and followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality. Results Nonsurvivors (n=955) induced higher levels of IgG responses against most of non-structural proteins than survivors (n=79) on admission. In particular, the magnitude of IgG antibodies against 8 non-structural proteins (NSP1, NSP4, NSP7, NSP8, NSP9, NSP10, RdRp, and NSP14) and 2 accessory proteins (ORF3b and ORF9b) possessed significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory biomarkers for disease severity (all with p trend < 0.05). Additionally, IgG responses to all of these 10 non-structural/accessory proteins were also associated with the severity of disease, and differential kinetics and serum positive rate of these IgG responses were confirmed in COVID-19 patients of varying severities within 20 days after symptoms onset. The area under curves (AUCs) for these IgG responses, determined by computational cross-validations, were between 0.62 and 0.71. Conclusions Our findings might have important implications for improving clinical management of COVID-19 patients.

Background The discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging. The present study aims to investigate the value of diagnostic models established by machine learning based on multiple laboratory data for distinguishing Mycobacterium tuberculosis (Mtb) infection status. Methods T-SPOT, lymphocyte characteristic detection, and routine laboratory tests were performed on participants. Diagnostic models were built according to various algorithms. Results A total of 892 participants (468 ATB and 424 LTBI) and another 263 participants (125 ATB and 138 LTBI), were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Receiver operating characteristic (ROC) curve analysis showed that the value of individual indicator for differentiating ATB from LTBI was limited (area under the ROC curve (AUC) Conclusions Cforest model developed upon machine learning could serve as a valuable and prospective tool for identifying Mtb infection status. The present study provided a novel and viable idea for realizing the clinical diagnostic application of the combination of machine learning and laboratory findings.

BackgroundBloodstream infections (BSIs), especially hospital-acquired BSIs, are a major cause of morbidity and mortality. However, the details about the pathogens and antimicrobial resistance profile of BSIs across China are still lacking.MethodsAn investigation was conducted in 10 large teaching hospitals from seven geographic regions across China in 2016 based on China Antimicrobial Surveillance Network (CHINET) to profile the clinical and etiological features of BSIs.ResultsA total of 2,773 cases of BSIs were identified, a majority (97.3%) of which were monomicrobial. Overall, 38.4% (1,065/2,773) were community-acquired BSIs (CABSIs), and 61.6% (1,708/2,773) were hospital-acquired BSIs (HABSIs). Of the 2,861 pathogenic BSI isolates, 67.5% were Gram-negative bacteria, 29.6% were Gram-positive bacteria, and 2.9% were fungi. The top BSI pathogens were Escherichia coli, Klebsiella pneumoniae, coagulase-negative Staphylococci (CNS), Staphylococcus aureus, Enterococci, and Acinetobacter baumannii. Escherichia coli and K. pneumoniae isolates showed low susceptibility to penicillins, cephalosporins (except ceftazidime and cefepime), and ampicillin-sulbactam (13.1%–43.4% susceptible); moderate susceptibility (about 60% susceptible) to ceftazidime, cefepime, and aztreonam; and high susceptibility (>90%) to β-lactam/β-lactamase inhibitor combinations other than ampicillin-sulbactam, except K. pneumoniae strains to piperacillin-tazobactam (59.2% susceptible). HABSIs were associated with significantly higher prevalence of carbapenem-resistant and extended-spectrum β-lactamases-producing K. pneumoniae, methicillin-resistant S. aureus, methicillin-resistant CNS, and ampicillin-resistant Enterococci than CABSIs. Overall, 42.0% of the BSI due to S. aureus strains were resistant to methicillin.ConclusionsThe findings about BSIs in teaching hospitals across China add more scientific evidence to inform the appropriate management of the disease.

To explore the predictive efficacy of prothrombin time (PT) with regarding for the severity and prognosis of septic patients, along with comparing with other routine coagulation parameters.A retrospective analysis was conducted. The clinical data of 302 septic patients who were admitted to the intensive care unit (ICU) of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology from January 1 to December 31 in 2019 were enrolled. Demographic and basic clinical data were collected. Laboratory data, including PT, activated partial thromboplastin time (APTT), thrombin time (TT), fibrinogen (FIB), D-dimer, fibrin (fibrinogen) degradation product (FDP), antithrombin (AT), platelet count (PLT) at ICU admission were recorded, and sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation II (APACHE II) score within 24 hours of admission to ICU were also collected. What's more, some major clinical events, such as septic shock, disseminated intravascular coagulation (DIC), etc. during ICU stay were also monitored. A follow-up 28 days observation of prognosis was performed. The patients were divided into the septic shock group and the non-septic shock group according to the occurrence of septic shock, and they were divided into the survival group and the non-survival group according to the 28-day prognosis. The differences in terms of above parameters between each two groups were compared. Spearman correlation method was used to analyze the correlation between routine coagulation parameters and SOFA score or APACHE II score. Receiver operator characteristic curve (ROC curve) was plotted to determine the predictive efficacy of each routine coagulation parameter with regarding to predict septic shock and 28-day mortality. Based on the cut-off value of PT, the septic patients were divided into two risk stratifications, and then the major clinical and end point outcome were compared. Kaplan-Meier survival curve analysis was applied to investigate the difference of the 28-day cumulated survival rate based on the different risk stratifications of PT level. Finally, multivariate Logistic regression analysis was used to explore whether prolonged PT level was an independent risk factor for septic shock and 28-day mortality.The 302 patients were all enrolled, including 120 patients with septic shock and 182 patients without. Seventy-five patients died within 28 days, while 227 survived. Comparing with the non-septic shock group or the survival group, the septic shock group or the non-survival group patients both had longer PT, APTT and TT, higher D-dimer, FDP and lower PLT, FIB and AT. Correlation analysis revealed that PT and PLT were better correlated with SOFA score (r values were 0.503 and -0.524, both P0.01), and PT was better correlated with APACHE II score (r = 0.407, P0.01). ROC curve analysis showed that PT had the most powerful predictive efficacy for septic shock and 28-day mortality. The area under the ROC curve (AUC) and 95% confidence interval (95%CI) were 0.831 (0.783-0.879) and 0.739 (0.674-0.805), respectively. The cut-off value were 16.8 s and 16.3 s, respectively, with the sensitivity of 64.2%, 72.0% and the specificity of 89.0%, 70.9%, respectively. Risk stratification based on PT level revealed that the patients with PT16.5 s (n = 103) had higher rate of 28-day mortality, incidence of septic shock and DIC, and score of SOFA and APACHE II comparing to those with PT ≤ 16.5 s (n = 199). Kaplan-Meier survival curve analysis showed that the 28-day cumulative survival rate was significantly lower in the patients with PT16.5 s than those with PT ≤ 16.5 s (52.43% vs. 86.93%; Log-Rank test: χCompared with other routine coagulation parameters, PT has the potential best predictive value for evaluating the severity of sepsis and the prognosis. When a patient is diagnosed with sepsis and has a result of PT longer than 16.5 s at ICU admission, the patient may have a higher risk of progression to septic shock and short-term death.

The outbreak of coronavirus disease 2019 (COVID-19) is a global health emergency. Various omics results have been reported for COVID-19, but the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here we collect blood samples from 231 COVID-19 patients, prefiltered to exclude those with selected comorbidities, yet with symptoms ranging from asymptomatic to critically ill. Using integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles, we report a trans-omics landscape for COVID-19. Our analyses find neutrophils heterogeneity between asymptomatic and critically ill patients. Meanwhile, neutrophils over-activation, arginine depletion and tryptophan metabolites accumulation correlate with T cell dysfunction in critical patients. Our multi-omics data and characterization of peripheral blood from COVID-19 patients may thus help provide clues regarding pathophysiology of and potential therapeutic strategies for COVID-19., COVID-19 is a critical public health threat, but molecular characterizations of patients’ immunity is still lacking. Here the authors collected blood from patients with various disease severity, and prefiltered to exclude selected comorbidity, to obtain genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles to report a trans-omics landscape.

Background Non-sputum methods are urgently needed to improve tuberculosis diagnosis and treatment monitoring in children. This study evaluated the ability of a serum assay quantifying a species-specific peptide of the Mycobacterium tuberculosis CFP-10 virulence factor via nanotechnology and matrix-assisted laser desorption ionization time-of-flight mass spectrometry to diagnose tuberculosis in HIV-infected and HIV-uninfected infants. Methods Serum CFP-10 peptide signal was blinded evaluated in cryopreserved sera of 519 BCG-immunized, HIV-exposed infants (284 HIV-infected, 235 HIV-uninfected) from a multi-center randomized placebo-controlled isoniazid prophylaxis trial conducted in southern Africa between 2004 and 2008, who were followed up to 192 weeks for Mtb infection and TB. Children were classified as confirmed, unconfirmed, or unlikely tuberculosis cases using 2015 NIH diagnostic criteria for pediatric TB. Results In HIV-infected infants, CFP-10 signal had 100% sensitivity for confirmed TB (5/5, 95% CI, 47.8–100) and 83.7% sensitivity for unconfirmed TB (36/43, 95% CI 69.3–93.2), with 93.1% specificity (203/218, 95% CI 88.9–96.1). In HIV-uninfected infants, CFP-10 signal detected the single confirmed TB case and 75.0% of unconfirmed TB cases (15/20; 95% CI 50.9–91.3), with 96.2% specificity (177/184, 95% CI, 92.3–98.5). Serum CFP-10 achieved 77% diagnostic sensitivity for confirmed and unconfirmed TB (13/17, 95% CI, 50–93%) at ≤ 24 weeks pre-diagnosis, and both CFP-10-positivity and concentration declined following anti-TB therapy initiation. Conclusions Serum CFP-10 signal exhibited high diagnostic sensitivity and specificity for tuberculosis in HIV-infected and HIV-uninfected infants and potential utility for early TB detection and monitoring of anti-TB treatment responses.

Background/purpose As the incidence of fungal infections in China increases, the demand for rapid and accurate diagnosis of mycoses is growing. Yet, information on current diagnostic capacity is scarce. Methods An online survey was conducted in February 2018 to collect information on mycology testing from tertiary care hospitals across China. Responses from 348 hospitals were analyzed, and a scoring system was designed and employed to assess the overall diagnostic capacity. Results Most of the surveyed hospitals did not have separate laboratory space, manpower, or equipment dedicated for fungal testing. Conventional staining methods were widely available (>70%), whereas GMS and fluorescent staining were less common. Fungal identification services were offered mostly with chromogenic medium, morphological characterization or automated identification systems, other than more advanced methods such as MALDI-TOF MS and DNA sequencing. Fungal serology testing was available in 81.1%, with G test being the most often used. Though 91.8% of the respondents had the ability to perform antifungal susceptibility testing for yeasts, less than 13% conducted such testing for molds. The percentage of laboratories participating in External Quality Assessment programs and research was 57.5% and 32.5%, respectively. The average score for the 348 surveyed hospitals was 37.2 (out of a maximum of 89 points), with only 15 hospitals scoring >60, suggesting a general lack of high-quality mycology laboratories. Conclusions The overall clinical testing capacity for fungal infection in China is insufficient. More investment and training efforts are warranted to establish centers of excellence and promote access to high-quality diagnostic services.

BACKGROUND: The impacts of chronic airway diseases on coronavirus disease 2019 (COVID-19) are far from understood. OBJECTIVE: To explore the influence of asthma and chronic obstructive pulmonary disease (COPD) comorbidity on disease expression and outcomes, and the potential underlying mechanisms in COVID-19 patients. METHODS: A total of 961 hospitalized COVID-19 patients with a definite clinical outcome (death or discharge) were retrospectively enrolled. Demographic and clinical information were extracted from the medical records. Lung tissue sections from patients suffering from lung cancer were used for immunohistochemistry study of angiotensin-converting enzyme II (ACE2) expression. BEAS-2B cell line was stimulated with various cytokines. RESULTS: In this cohort, 21 subjects (2.2%) had COPD and 22 (2.3%) had asthma. After adjusting for confounding factors, COPD patients had higher risk of developing severe illness (OR: 23.433; 95% CI 1.525-360.135; P

Background Discriminating active tuberculosis (ATB) from latent tuberculosis infection (LTBI) remains challenging. This study aimed to investigate a diagnostic model based on a combination of iron metabolism and the TB-specific antigen/phytohemagglutinin ratio (TBAg/PHA ratio) in T-SPOT.TB assay for differentiation between ATB and LTBI. Methods A total of 345 participants with ATB (n = 191) and LTBI (n = 154) were recruited based on positive T-SPOT.TB results at Tongji hospital between January 2017 and January 2020. Iron metabolism analysis was performed simultaneously. A diagnostic model for distinguishing ATB from LTBI was established according to multivariate logistic regression. Results The TBAg/PHA ratio showed 64.00% sensitivity and 90.10% specificity in distinguishing ATB from LTBI when a threshold of 0.22 was used. All iron metabolism biomarkers in the ATB group were significantly different from those in the LTBI group. Specifically, serum ferritin and soluble transferrin receptor in ATB were significantly higher than LTBI. On the contrary, serum iron, transferrin, total iron binding capacity, and unsaturated iron binding capacity in ATB were significantly lower than LTBI. The combination of iron metabolism indicators accurately predicted 60.00% of ATB cases and 91.09% of LTBI subjects, respectively. Moreover, the combination of iron metabolism indexes and TBAg/PHA ratio resulted in a sensitivity of 88.80% and specificity of 90.10%. Furthermore, the performance of models established in the Qiaokou cohort was confirmed in the Caidian cohort. Conclusions The data suggest that the combination of iron metabolism indexes and TBAg/PHA ratio could serve as a biomarker to distinguish ATB from LTBI in T-SPOT-positive individuals.

Background: Chest CT is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to reverse-transcription polymerase chain reaction (RT-PCR) tests.Purpose: To investigate the diagnostic value and consistency of chest CT as compared with RT-PCR assay in COVID-19.Materials and Methods: This study included 1014 patients in Wuhan, China, who underwent both chest CT and RT-PCR tests between January 6 and February 6, 2020. With use of RT-PCR as the reference standard, the performance of chest CT in the diagnosis of COVID-19 was assessed. In addition, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negativeto positive, positive to negative) was analyzed as compared with serial chest CT scans for those with a time interval between RT-PCR tests of 4 days or more.Results: Of the 1014 patients, 601 of 1014 (59%) had positive RT-PCR results and 888 of 1014 (88%) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95% confidence interval: 95%, 98%; 580 of 601 patients) based on positive RT-PCR results. In the 413 patients with negative RT-PCR results, 308 of 413 (75%) had positive chest CT findings. Of those 308 patients, 48% (103 of 308) were considered as highly likely cases and 33% (103 of 308) as probable cases. At analysis of serial RT-PCR assays and CT scans, the mean interval between the initial negative to positive RT-PCR results was 5.1 days +/- 1.5; the mean interval between initial positive to subsequent negative RT-PCR results was 6.9 days +/- 2.3. Of the 1014 patients, 60% (34 of 57) to 93% (14 of 15) had initial positive CT scans consistent with COVID-19 before (or parallel to) the initial positive RT-PCR results. Twenty-four of 57 patients (42%) showed improvement on follow-up chest CT scans before the RT-PCR results turned negative.Conclusion: Chest CT has a high sensitivity for diagnosis of coronavirus disease 2019 (COVID-19). Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. (C) RSNA, 2020

Highlights • The novel coronavirus pneumonia patients were frequently encountered in the sixth and seventh decades of life. • Significantly decreased white blood cells, alkaline phosphatase, and d-dimer were observed in novel coronavirus pneumonia patients compared with influenza patients. • the results of lactate dehydrogenase, erythrocyte sedimentation rate and fibrinogen were significantly increased in novel coronavirus pneumonia patients compared with those in influenza patients. • An optimal diagnostic model with moderate value was established based on the combination of eighteen biomarkers from routine laboratory tests to discriminate novel coronavirus pneumonia patients from influenza patients., Background The differential diagnosis between novel coronavirus pneumonia patients (NCPP) and influenza patients (IP) remains a challenge in clinical practice. Methods Between January 2018 and March 2020, 1027 NCPP and 1140 IP were recruited from Tongji hospital. Blood routine examination, biochemical indicators, and coagulation function analysis were performed in all participants simultaneously. Results There was no sex predominance in NCPP. The NCPP were frequently encountered in the sixth and seventh decades of life. The mean age of NCPP (56 ± 16 years) was higher than IP (47 ± 17 years), but without statistical difference. Although most results of routine laboratory tests between NCPP and IP had no significant difference, some laboratory tests showed an obvious change in NCPP. We observed that NCPP had significantly decreased white blood cells, alkaline phosphatase, and d-dimer, compared with IP. However, the results of lactate dehydrogenase, erythrocyte sedimentation rate and fibrinogen were significantly increased in NCPP compared with those in IP. The diagnostic model based on combination of eighteen routine laboratory indicators showed an area under the curve of 0.796 (95% CI, 0.777 to 0.814), with a sensitivity of 46.93% and a specificity of 90.09% when using a cutoff value of 0.598. Conclusions Some routine laboratory results had statistical difference between NCPP and IP. A diagnostic model based on combination of routine laboratory results provides an adjunct approach in the differential diagnosis between NCPP and IP.

Accurate monitoring of host immunity is hampered by the flaws of conventional tests. The relationship between lymphocyte number and function is unknown. The function of lymphocytes was analyzed based on IFN-γ secretion assay. Lymphocyte number and function was investigated in individuals under various states. The number of CD4+ and CD8+ T cells was gradually decreased, whereas the function of them was gradually increased with increasing age. A significantly negative correlation existed between the number and function of both CD4+ and CD8+ T cells. Differently, both the number and function of NK cells are maintained at a high level after birth. Staying up all night was found to impair the function of CD4+, CD8+ T cells, or NK cells. Lymphocyte number and function were both decreased in patients with immunosuppressive conditions or opportunistic infections, while the opposite phenomenon was observed in patients with some autoimmune diseases (except for NK cells). In kidney transplant recipients, the number and function of CD4+ and CD8+ T cells were increased or decreased when rejection or infection occurred. We demonstrated that evaluation of host immunity based on combination of lymphocyte number and function plays an important role in the diagnosis, treatment, and prognosis of diseases.

Background Solid transplant patients are susceptible to Pneumocystis jirovecii pneumonia (PJP). While the vast majority of PJP cases occur within the first 6 months after transplantation, very few PJP cases are seen beyond 1 year post-transplantation (late-onset PJP). PJP and coronavirus disease 2019 (COVID-19, caused by infection with SARS-CoV-2) share quite a few common clinical manifestations and imaging findings, making the diagnosis of PJP often underappreciated during the current COVID-19 pandemic. To date, only 1 case of kidney transplantation who developed COVID-19 and late-onset PJP has been reported, but this patient also suffered from many other infections and died from respiratory failure and multiple organ dysfunction syndrome. A successful treatment of kidney patients with COVID-19 and late-onset PJP has not been reported. Case presentation We present a case of a 55-year-old male kidney transplant patient with COVID-19 who also developed late-onset PJP. He received a combined treatment strategy, including specific anti-pneumocystis therapy, symptomatic supportive therapy, adjusted immunosuppressive therapy, and use of antiviral drugs/antibiotics, ending with a favorable outcome. Conclusions This case highlights the importance of prompt and differential diagnosis of PJP in kidney transplant patients with SARS-CoV-2 infection. Further studies are required to clarify if kidney transplant patients with COVID-19 could be prone to develop late-onset PJP and how these patients should be treated.

BackgroundThe differential diagnosis between tuberculous meningitis (TBM) and bacterial meningitis (BM) remains challenging in clinical practice. This study aimed to establish a diagnostic model that could accurately distinguish TBM from BM.MethodsPatients with TBM or BM were recruited between January 2017 and January 2021 at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort). The detection for indicators involved in cerebrospinal fluid (CSF) and T-SPOT assay were performed simultaneously. Multivariate logistic regression was used to create a diagnostic model.ResultsA total of 174 patients (76 TBM and 98 BM) and another 105 cases (39 TBM and 66 BM) were enrolled from Qiaokou cohort and Caidian cohort, respectively. Significantly higher level of CSF lymphocyte proportion while significantly lower levels of CSF chlorine, nucleated cell count, and neutrophil proportion were observed in TBM group when comparing with those in BM group. However, receiver operating characteristic (ROC) curve analysis showed that the areas under the ROC curve (AUCs) produced by these indicators were all under 0.8. Meanwhile, tuberculosis-specific antigen/phytohemagglutinin (TBAg/PHA) ratio yielded an AUC of 0.889 (95% CI, 0.840–0.938) in distinguishing TBM from BM, with a sensitivity of 68.42% (95% CI, 57.30%–77.77%) and a specificity of 92.86% (95% CI, 85.98%–96.50%) when a cutoff value of 0.163 was used. Consequently, we successfully established a diagnostic model based on the combination of TBAg/PHA ratio, CSF chlorine, CSF nucleated cell count, and CSF lymphocyte proportion for discrimination between TBM and BM. The established model showed good performance in differentiating TBM from BM (AUC: 0.949; 95% CI, 0.921–0.978), with 81.58% (95% CI, 71.42%–88.70%) sensitivity and 91.84% (95% CI, 84.71%–95.81%) specificity. The performance of the diagnostic model obtained in Qiaokou cohort was further validated in Caidian cohort. The diagnostic model in Caidian cohort produced an AUC of 0.923 (95% CI, 0.867–0.980) with 79.49% (95% CI, 64.47%–89.22%) sensitivity and 90.91% (95% CI, 81.55%–95.77%) specificity.ConclusionsThe diagnostic model established based on the combination of four indicators had excellent utility in the discrimination between TBM and BM.

ObjectivesThe longitudinal and systematic evaluation of immunity in coronavirus disease 2019 (COVID-19) patients is rarely reported.MethodsParameters involved in innate, adaptive, and humoral immunity were continuously monitored in COVID-19 patients from onset of illness until 45 days after symptom onset.ResultsThis study enrolled 27 mild, 47 severe, and 46 deceased COVID-19 patients. Generally, deceased patients demonstrated a gradual increase of neutrophils and IL-6 but a decrease of lymphocytes and platelets after the onset of illness. Specifically, sustained low numbers of CD8+T cells, NK cells, and dendritic cells were noted in deceased patients, while these cells gradually restored in mild and severe patients. Furthermore, deceased patients displayed a rapid increase of HLA-DR expression on CD4+T cells in the early phase, but with a low level of overall CD45RO and HLA-DR expressions on CD4+and CD8+T cells, respectively. Notably, in the early phase, deceased patients showed a lower level of plasma cells and antigen-specific IgG, but higher expansion of CD16+CD14+proinflammatory monocytes and HLA-DR−CD14+monocytic-myeloid-derived suppressor cells (M-MDSCs) than mild or severe patients. Among these immunological parameters, M-MDSCs showed the best performance in predicting COVID-19 mortality, when using a cutoff value of ≥10%. Cluster analysis found a typical immunological pattern in deceased patients on day 9 after onset, which was characterized as the increase of inflammatory markers (M-MDSCs, neutrophils, CD16+CD14+monocytes, and IL-6) but a decrease of host immunity markers.ConclusionsThis study systemically characterizes the kinetics of immunity of COVID-19, highlighting the importance of immunity in patient prognosis.

Heavy metal(loid)s (HMs) have been consistently entering the food chain, imposing great harm on environment and public health. However, previous studies on the spatial dynamics and transport mechanism of HMs have been profoundly limited by the field sampling issues, such as the uneven observations of individual carriers and their spatial mismatch, especially over large-scale catchments with complex environment. In this study, a novel methodological framework for mapping HMs at catchment scale was proposed and applied, combining a species distribution model (SDM) with physical environment and human variables. Based on the field observations, we ecologicalized HMs in different carriers as different species. This enabled the proposed framework to model the 'enrichment area' of individual HMs in the geographic space (termed as the HM 'habitat') and identify their 'hotspots' (peak value points) within the catchment. Results showed the output maps of HM habitats from secondary carriers (soil, sediment, and wet deposition) well agreed with the influence of industry contaminants, hydraulic sorting, and precipitation washout process respectively, indicating the potential of SDM in modeling the spatial distributions of the HM. The derived maps of HMs from secondary carriers, along with the human and environmental variables were then input as explanatory variables in SDM to predict the spatial patterns of the final HM accumulation in river water, which was observed to have largely improved the prediction quality. These results confirmed the value of our framework to leverage SDMs from ecology perspective to study HM contamination transport at catchment scale, offering new insights not only to map the spatial HM habitats but also help locate the HM transport chains among different carriers.

Background Novel approaches for tuberculosis (TB) diagnosis, especially for distinguishing active TB (ATB) from latent TB infection (LTBI), are urgently warranted. The present study aims to determine whether the combination of HLA-DR on Mycobacterium tuberculosis (MTB)-specific cells and TB antigen/phytohemagglutinin (TBAg/PHA) ratio could facilitate MTB infection status discrimination. Methods Between June 2020 and June 2021, participants with ATB and LTBI were recruited from Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort), respectively. The detection of HLA-DR on MTB-specific cells upon TB antigen stimulation and T-SPOT assay were simultaneously performed on all subjects. Results A total of 116 (54 ATB and 62 LTBI) and another 84 (43 ATB and 41 LTBI) cases were respectively enrolled from Qiaokou cohort and Caidian cohort. Both HLA-DR on IFN-γ+TNF-α+ cells and TBAg/PHA ratio showed discriminatory value in distinguishing between ATB and LTBI. Receiver operator characteristic (ROC) curve analysis showed that HLA-DR on IFN-γ+TNF-α+ cells produced an area under the ROC curve (AUC) of 0.886. Besides, TBAg/PHA ratio yield an AUC of 0.736. Furthermore, the combination of these two indicators resulted in the accurate discrimination with an AUC of 0.937. When the threshold was set as 0.36, the diagnostic model could differentiate ATB from LTBI with a sensitivity of 92.00% and a specificity of 81.82%. The performance obtained in Qiaokou cohort was further validated in Caidian cohort. Conclusions The combination of HLA-DR on MTB-specific cells and TBAg/PHA ratio could serve as a robust tool to determine TB disease states.

Background Searching the risk factors for carbapenem-resistant Enterobacteriaceae (CRE) infection is important in clinical practice. In the present study, we aim to investigate bacterial characteristics of colonizing strains and their correlation with subsequent CRE infection. Methods Between May 2018 and January 2019, patients hospitalized in the department of haematology and intensive care unit (ICU) were screened for CRE by rectal swabs and monitored for the outcome of infection. We identified the species and carbapenemase-encoding genes of colonizing strains and performed antimicrobial susceptibility tests and multilocus sequence typing (MLST). Risk factors for subsequent CRE infections were ascertained by univariate and multivariable analysis. Results We collected a total of 219 colonizing strains from 153 patients. Klebsiella pneumoniae was the most abundant species, and MLST analysis showed rich diversity. K. pneumoniae carbapenemase (KPC) was predominant in the infection group (72.4%). In the non-infection group, 35.4% of strains were non-carbapenemase-producing CRE (NCP-CRE), and New Delhi metallo-β-lactamase (NDM) was predominant (42.2%). The rate of high-level carbapenem resistance (minimum inhibitory concentration [MIC] ≥ 64 mg/L for meropenem and ertapenem, ≥ 32 mg/L for imipenem) was remarkably higher in the infection group than in the non-infection group (P K. pneumoniae, high-level carbapenem resistance, CP-CRE and KPC-CRE were infection risk factors after CRE colonization. On multivariable analysis with different carbapenemase dichotomizations, KPC-CRE (adjusted odds ratio [aOR], 4.507; 95% confidence interval [CI], 1.339–15.171; P = 0.015) or imipenem MIC ≥ 32 mg/L (aOR, 9.515; 95% CI, 1.617–55.977; P = 0.013) were respectively identified as independent risk factors for subsequent infection. Conclusions Patients colonized with KPC-CRE or strains with an imipenem MIC ≥ 32 mg/L were at particularly high risk of subsequent CRE infections during their hospital stay.

BackgroundDistinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.MethodsBetween 2013 and 2019, 2,059 (1,097 ATB and 962 LTBI) and another 883 (372 ATB and 511 LTBI) participants were recruited based on positive T-SPOT.TB (T-SPOT) results from Qiaokou (training) and Caidian (validation) cohorts, respectively. Blood routine examination (BRE) was performed simultaneously. Diagnostic model was established according to multivariate logistic regression.ResultsSignificant differences were observed in all indicators of BRE and T-SPOT assay between ATB and LTBI. Diagnostic model built on BRE showed area under the curve (AUC) of 0.846 and 0.850 for discriminating ATB from LTBI in the training and validation cohorts, respectively. Meanwhile, TB-specific antigens spot-forming cells (SFC) (the larger of early secreted antigenic target 6 and culture filtrate protein 10 SFC in T-SPOT assay) produced lower AUC of 0.775 and 0.800 in the training and validation cohorts, respectively. The diagnostic model based on combination of BRE and T-SPOT showed an AUC of 0.909 for differentiating ATB from LTBI, with 78.03% sensitivity and 90.23% specificity when a cutoff value of 0.587 was used in the training cohort. Application of the model to the validation cohort showed similar performance. The AUC, sensitivity, and specificity were 0.910, 78.23%, and 90.02%, respectively. Furthermore, we also assessed the performance of our model in differentiating ATB from LTBI with lung lesions. Receiver operating characteristic analysis showed that the AUC of established model was 0.885, while a threshold of 0.587 yield a sensitivity of 78.03% and a specificity of 85.69%, respectively.ConclusionsThe diagnostic model based on combination of BRE and T-SPOT could provide a reliable differentiation between ATB and LTBI.

Background Rapid and effective discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains a challenge. There is an urgent need for developing practical and affordable approaches targeting this issue. Methods Participants with ATB and LTBI were recruited at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort) based on positive T-SPOT results from June 2020 to January 2021. The expression of activation markers including HLA-DR, CD38, CD69, and CD25 was examined on Mycobacterium tuberculosis (MTB)-specific CD4+ T cells defined by IFN-γ, TNF-α, and IL-2 expression upon MTB antigen stimulation. Results A total of 90 (40 ATB and 50 LTBI) and another 64 (29 ATB and 35 LTBI) subjects were recruited from the Qiaokou cohort and Caidian cohort, respectively. The expression patterns of Th1 cytokines including IFN-γ, TNF-α, and IL-2 upon MTB antigen stimulation could not differentiate ATB patients from LTBI individuals well. However, both HLA-DR and CD38 on MTB-specific cells showed discriminatory value in distinguishing between ATB patients and LTBI individuals. As for developing a single candidate biomarker, HLA-DR had the advantage over CD38. Moreover, HLA-DR on TNF-α+ or IL-2+ cells had superiority over that on IFN-γ+ cells in differentiating ATB patients from LTBI individuals. Besides, HLA-DR on MTB-specific cells defined by multiple cytokine co-expression had a higher ability to discriminate patients with ATB from LTBI individuals than that of MTB-specific cells defined by one kind of cytokine expression. Specially, HLA-DR on TNF-α+IL-2+ cells produced an AUC of 0.901 (95% CI, 0.833–0.969), with a sensitivity of 93.75% (95% CI, 79.85–98.27%) and specificity of 72.97% (95% CI, 57.02–84.60%) as a threshold of 44% was used. Furthermore, the performance of HLA-DR on TNF-α+IL-2+ cells for differential diagnosis was obtained with validation cohort data: 90.91% (95% CI, 72.19–97.47%) sensitivity and 68.97% (95% CI, 50.77–82.73%) specificity. Conclusions We demonstrated that HLA-DR on MTB-specific cells was a potentially useful biomarker for accurate discrimination between ATB and LTBI.

BackgroundEasily accessible tools that reliably stratify Mycobacterium tuberculosis (MTB) infection are needed to facilitate the improvement of clinical management. The current study attempts to reveal lymphocyte-related immune characteristics of active tuberculosis (ATB) patients and establish immunodiagnostic model for discriminating ATB from latent tuberculosis infection (LTBI) and healthy controls (HC).MethodsA total of 171 subjects consisted of 54 ATB, 57 LTBI, and 60 HC were consecutively recruited at Tongji hospital from January 2019 to January 2021. All participants were tested for lymphocyte subsets, phenotype, and function. Other examination including T-SPOT and microbiological detection for MTB were performed simultaneously.ResultsCompared with LTBI and HC, ATB patients exhibited significantly lower number and function of lymphocytes including CD4+ T cells, CD8+ T cells and NK cells, and significantly higher T cell activation represented by HLA-DR and proportion of immunosuppressive cells represented by Treg. An immunodiagnostic model based on the combination of NK cell number, HLA-DR+CD3+ T cells, Treg, CD4+ T cell function, and NK cell function was built using logistic regression. Based on receiver operating characteristic curve analysis, the area under the curve (AUC) of the diagnostic model was 0.920 (95% CI, 0.867-0.973) in distinguishing ATB from LTBI, while the cut-off value of 0.676 produced a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and specificity of 91.23% (95% CI, 81.06%-96.20%). Meanwhile, AUC analysis between ATB and HC according to the diagnostic model was 0.911 (95% CI, 0.855-0.967), with a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and a specificity of 90.00% (95% CI, 79.85%-95.34%).ConclusionsOur study demonstrated that the immunodiagnostic model established by the combination of lymphocyte-related indicators could facilitate the status differentiation of MTB infection.

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (named COVID-ONE-hi). COVID-ONE-hi is based on the data that contain the IgG/IgM responses to 24 full-length/truncated proteins corresponding to 20 of 28 known SARS-CoV-2 proteins and 199 spike protein peptides against 2360 serum samples collected from 783 COVID-19 patients. In addition, 96 clinical parameters for the 2360 serum samples and basic information for the 783 patients are integrated into the database. Furthermore, COVID-ONE-hi provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-hi is freely available at www.COVID-ONE.cn.

BackgroundThe prompt diagnosis of pulmonary tuberculosis (PTB) remains a challenge in clinical practice. The present study aimed to optimize an algorithm for rapid diagnosis of PTB in a real-world setting.Methods28,171 adult inpatients suspected of having PTB in China were retrospectively analyzed. Bronchoalveolar lavage fluid (BALF) and/or sputum were used for acid-fast bacilli (AFB) smear, Xpert MTB/RIF (Xpert), and culture. A positive mycobacterial culture was used as the reference standard. Peripheral blood mononuclear cells (PBMC) were used for T-SPOT.TB. We analyzed specimen types’ effect on these assays’ performance, determined the number of smears for diagnosing PTB, and evaluated the ability of these assays performed alone, or in combination, to diagnose PTB and nontuberculous mycobacteria (NTM) infections.ResultsSputum and BALF showed moderate to substantial consistency when they were used for AFB smear or Xpert, with a higher positive detection rate by BALF. 3-4 smears had a higher sensitivity than 1-2 smears. Moreover, simultaneous combination of AFB and Xpert correctly identified 44/51 of AFB+/Xpert+ and 6/7 of AFB+/Xpert- cases as PTB and NTM, respectively. Lastly, when combined with AFB/Xpert sequentially, T-SPOT showed limited roles in patients that were either AFB+ or Xpert+. However, T-SPOTMDC (manufacturer-defined cut-off) showed a high negative predicative value (99.1%) and suboptimal sensitivity (74.4%), and TBAg/PHA (ratio of Mycobacterium tuberculosis-specific antigens to phytohaemagglutinin spot-forming cells, which is a modified method calculating T-SPOT.TB assay results) ≥0.3 demonstrated a high specificity (95.7%) and a relatively low sensitivity (16.3%) in AFB-/Xpert- patients.ConclusionsConcurrently performing AFB smear (at least 3 smears) and Xpert on sputum and/or BALF could aid in rapid diagnosis of PTB and NTM infections in a real-world high-burden setting. If available, BALF is preferred for both AFB smear and Xpert. Expanding this algorithm, PBMC T-SPOTMDC and TBAg/PHA ratios have a supplementary role for PTB diagnosis in AFB-/Xpert- patients (moderately ruling out PTB and ruling in PTB, respectively). Our findings may also inform policy makers’ decisions regarding prevention and control of TB in a high burden setting.

BackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has become a global public health concern. Many inpatients with COVID-19 have shown clinical symptoms related to sepsis, which will aggravate the deterioration of patients’ condition. We aim to diagnose Viral Sepsis Caused by SARS-CoV-2 by analyzing laboratory test data of patients with COVID-19 and establish an early predictive model for sepsis risk among patients with COVID-19.MethodsThis study retrospectively investigated laboratory test data of 2,453 patients with COVID-19 from electronic health records. Extreme gradient boosting (XGBoost) was employed to build four models with different feature subsets of a total of 69 collected indicators. Meanwhile, the explainable Shapley Additive ePlanation (SHAP) method was adopted to interpret predictive results and to analyze the feature importance of risk factors.FindingsThe model for classifying COVID-19 viral sepsis with seven coagulation function indicators achieved the area under the receiver operating characteristic curve (AUC) 0.9213 (95% CI, 89.94–94.31%), sensitivity 97.17% (95% CI, 94.97–98.46%), and specificity 82.05% (95% CI, 77.24–86.06%). The model for identifying COVID-19 coagulation disorders with eight features provided an average of 3.68 (±) 4.60 days in advance for early warning prediction with 0.9298 AUC (95% CI, 86.91–99.04%), 82.22% sensitivity (95% CI, 67.41–91.49%), and 84.00% specificity (95% CI, 63.08–94.75%).InterpretationWe found that an abnormality of the coagulation function was related to the occurrence of sepsis and the other routine laboratory test represented by inflammatory factors had a moderate predictive value on coagulopathy, which indicated that early warning of sepsis in COVID-19 patients could be achieved by our established model to improve the patient’s prognosis and to reduce mortality.

Introduction. Shigella sonnei, the cause of bacillary dysentery, belongs to Gram-negative enteropathogenic bacteria. S. sonnei contains a 210 kb virulence plasmid that encodes an O-antigen gene cluster of LPSs. However, this virulence plasmid is frequently lost during replication. It is well-documented that after losing the O-antigen and becoming rough strains, the Gram-negative bacteria may express an LPS core on its surface. Previous studies have suggested that by using the LPS core, Gram-negative bacteria can interact with several C-type lectin receptors that are expressed on antigen-presenting cells (APCs). Hypothesis/Gap Statement. S. sonnei by losing the virulence plasmid may hijack APCs via the interactions of LPS-CD209/CD207. Aim. This study aimed to investigate if the S. sonnei rough strain, by losing the virulence plasmid, interacted with APCs that express C-type lectins of human CD207, human CD209a and mouse CD209b. Methodology. SDS-PAGE silver staining was used to examine the O-antigen expression of S. sonnei WT and its rough strain. Invasion assays and inhibition assays were used to examine the ability of S. sonnei WT and its rough strain to invade APCs and investigate whether CD209 and CD207 are receptors for phagocytosis of rough S. sonnei . Animal assays were used to observe the dissemination of S. sonnei . Results. S. sonnei did not express O-antigens after losing the virulence plasmid. The S. sonnei rough strain invades with APCs, including human dendritic cells (DCs) and mouse macrophages. CD209 and CD207 are receptors for phagocytosis of rough S. sonnei . Expression of the O-antigen reduces the ability of the S. sonnei rough strain to be disseminated to mesenteric lymph nodes and spleens. Conclusion. This work demonstrated that S. sonnei rough strains – by losing the virulence plasmid – invaded APCs through interactions with CD209 and CD207 receptors.

Iodine is an essential micronutrient in the human diet and an appropriate human iodine intake level is important for population health. Excessive iodine intake is often associated with high iodine groundwater which serves as an important drinking water source in many regions. This study aims to identify the source and key hydrogeochemical processes for iodine accumulation and mobility in the groundwaters of the Northern Jiangsu Yishusi Plain. Combined hydrogeochemical and statistical analyses, specifically random forest modeling and factor analysis, were used to explore the mechanisms affecting the spatial distribution of iodine. The concentration of iodine in the investigated groundwaters was found to vary widely and to range between 4.8 and 4750 μg/L, with 48.9% of the total samples (674) exceeding the threshold value of 100 μg/L for toxic exposure, as defined by the Chinese high‑iodine standard guideline. High iodine concentrations are shown to mainly occur in the marine plain and the shallow aquifer associated with the floodplains of the Old Yellow River. The marine or lagoons-facies sediments were identified as the most plausible iodine source. In addition, mixing of groundwater with paleo-seawater might also have played a role in the coastal area. In contrast, the flood sediments of the Old Yellow River are shown to be an unlikely source. However, they serve as a cover layer that favored the development of reducing hydrogeochemical conditions that can trigger iodine mobilization via the reductive dissolution of iron oxides and the degradation of organic matter. Slow groundwater flow rates also appear to favor iodine release from sediments.

Background Pneumocystis jiroveci pneumonia (PJP) is the most common opportunistic infection in immunocompromised patients. The accurate prediction of PJP development in patients undergoing immunosuppressive therapy remains challenge. Methods Patients undergoing immunosuppressive treatment and with confirmed pneumocystis jiroveci infection were enrolled. Another group of matched patients with immunosuppressant treatment but without signs of infectious diseases were enrolled to control group. Results A total of 80 (40 PJP, 40 non-PJP) participants were enrolled from Tongji Hospital. None of the patients were HIV positive. The routine laboratory indicators, such as LYM, MON, RBC, TP, and ALB, were significantly lower in PJP patients than in non-PJP patients. Conversely, LDH in PJP patients was significantly higher than in non-PJP controls. For immunological indicators, the numbers of T, B, and NK cells were all remarkably lower in PJP patients than in non-PJP controls, whereas the functional markers such as HLA-DR, CD45RO and CD28 expressed on CD4+ or CD8+ T cells had no statistical difference between these two groups. Cluster analysis showing that decrease of host immunity markers including CD3+, CD4+ and CD8+ T cells, and increase of tissue damage marker LDH were the most typical characteristics of PJP patients. A further established model based on combination of CD8+ T cells and LDH showed prominent value in distinguishing PJP from non-PJP, with AUC of 0.941 (95% CI, 0.892-0.990). Conclusions A model based on combination of routine laboratory and immunological indicators shows prominent value for predicting the development of PJP in HIV-negative patients undergoing immunosuppressive therapy.

Background. Neutralizing antibody (nAb) response is generated following infection or immunization and plays an important role in the protection against a broad of viral infections. The role of nAb during clinical progression of coronavirus disease 2019 (COVID-19) remains little known. Methods. 123 COVID-19 patients during hospitalization in Tongji Hospital were involved in this retrospective study. The patients were grouped based on the severity and outcome. The nAb responses of 194 serum samples were collected from these patients within an investigation period of 60 days after the onset of symptoms and detected by a pseudotyped virus neutralization assay. The detail data about onset time, disease severity and laboratory biomarkers, treatment, and clinical outcome of these participants were obtained from electronic medical records. The relationship of longitudinal nAb changes with each clinical data was further assessed. Results. The nAb response in COVID-19 patients evidently experienced three consecutive stages, namely, rising, stationary, and declining periods. Patients with different severity and outcome showed differential dynamics of the nAb response over the course of disease. During the stationary phase (from 20 to 40 days after symptoms onset), all patients evolved nAb responses. In particular, high levels of nAb were elicited in severe and critical patients and older patients (≥60 years old). More importantly, critical but deceased COVID-19 patients showed high levels of several proinflammation cytokines, such as IL-2R, IL-8, and IL-6, and anti-inflammatory cytokine IL-10 in vivo, which resulted in lymphopenia, multiple organ failure, and the rapidly decreased nAb response. Conclusion. Our results indicate that nAb plays a crucial role in preventing the progression and deterioration of COVID-19, which has important implications for improving clinical management and developing effective interventions.

BackgroundConsidering the increasing incidence of carbapenem-resistant Enterobacteriaceae in China, this study aimed to establish the in vitro effectiveness of imipenem/relebactam (IMI/REL) on clinical Enterobacteriaceae isolates derived from intra-abdominal infections (IAIs), respiratory tract infections (RTIs), and urinary tract infections (UTIs) in China between 2015 and 2018.MethodsIn total, 8781 Enterobacteriaceae isolates from IAI, RTI, and UTI samples were collected from 22 hospitals across 7 geographic regions of China. Susceptibility to antimicrobial drugs was tested using the Clinical and Laboratory Standards Institute broth microdilution and breakpoints, and IMI/REL activity was assessed using United States Food and Drug Administration guidelines.ResultsIn 2015–2018, the most frequently identified Enterobacteriaceae species was Escherichia coli (n = 4676 [53.3%]), followed by Klebsiella pneumoniae (n = 2949 [33.6%]) and Enterobacter cloacae (n = 542 [6.2%]). The Enterobacteriaceae isolates showed 95.2% overall susceptibility to IMI/REL, of which the susceptibility rates in isolates from IAI, RTI, and UTI were 95.8%, 91.4%, and 96.6%, respectively. Overall, the susceptibilities of both intensive care unit (ICU) and non-ICU Enterobacteriaceae isolates to colistin were 92.9%, followed by IMI/REL (90.7% [95.9%]) and amikacin (83.3% [92.3%]). In addition, IMI/REL restored 66.3% susceptibility in imipenem-nonsusceptible Enterobacteriaceae.ConclusionsGiven their high in vitro susceptibility, Enterobacteriaceae infections in China should be considered for IMI/REL treatment, especially with isolates that are not susceptible to carbapenems.

Background The positive rate of pathogenic examination about tuberculosis is low. It is still difficult to achieve early diagnosis for some TB patients. The value of Interferon-gamma release assays (IGRA) in the diagnosis of active tuberculosis remains controversial. The purpose of this multicenter prospective study was to verify and validate the role of TBAg/PHA ratio (TB-specific antigen to phytohaemagglutinin) of T-SPOT.TB assay in diagnosing ATB. Methods We prospectively enrolled 2390 suspected pulmonary tuberculosis patients with positive T-SPOT assay results from three tertiary hospitals. Results A total of 1549 ATB (active tuberculosis) patients (including 1091 confirmed and 458 probable ATB) and 724 non-tuberculosis (non-TB) patients with positive T-SPOT results were included. The results of this study showed that ESAT-6 and CFP-10 in the T-SPOT.TB assay were significantly higher in the ATB group compared with the non-TB group, while PHA was lower in the ATB group. Results of ESAT-6, CFP-10 and PHA show a certain diagnostic performance, but moderate sensitivity and specificity. The TBAg/PHA ratio, a further calculation of ESAT-6, CFP-10 and PHA in T-SPOT.TB assay showed improved performance in the diagnosis of active Tuberculosis. If using the threshold value of 0.2004, the specificity and sensitivity of TBAg/PHA ratio in distinguishing ATB from non-TB were 92.3% and 74.4%, PPV was 95.4, PLR was 9.6. Conclusion By recalculating the results of T-SPOT.TB Assay, the TBAg/PHA ratio shows high prospect value in the diagnosis of active tuberculosis in high prediction areas.

In arid inland irrigated areas, the role of human activities on fluoride enrichment in groundwater is not fully understood. There is an extremely arid climate, high-intensity irrigation, and severe soil salinization in the Hotan Oasis within the Tarim Basin, Northwestern China. In this study, hydrogeochemistry and environmental isotope methods were combined to explore the distribution characteristics and controlling processes of fluoride enrichment in groundwater. The F

Background Given that there is no rapid and effective method for distinguishing active tuberculosis (ATB) from latent tuberculosis infection (LTBI), the discrimination between these two statuses remains challenging. This study sought to investigate the value of nutritional indexes and tuberculosis‐specific antigen/phytohemagglutinin ratio (TBAg/PHA ratio) for distinguishing ATB from LTBI. Methods Participants were consecutively recruited based on positive T‐SPOT.TB results between January 2018 and January 2020. ATB was diagnosed by positive mycobacterial culture and/or positive GeneXpert MTB/RIF, with clinical symptoms and radiological characteristics suggestive of ATB. Individuals with positive T‐SPOT.TB but without the evidence of ATB were defined as LTBI. Patients younger than 17 years and undergoing anti‐TB treatment were excluded. Results A total of 709 (312 ATB and 397 LTBI) and another 309 (120 ATB and 189 LTBI) subjects were respectively recruited from Tongji Hospital (Qiaokou cohort) and Sino‐French New City Hospital (Caidian cohort). The level of prealbumin was significantly lower in ATB than in LTBI. With a cut‐off value of 139 mg/L, the sensitivity and specificity of prealbumin in distinguishing ATB from LTBI were 50.96% (45.41%‐56.51%) and 91.69% (88.97%‐94.40%). Meanwhile, TBAg/PHA ratio was found statistically higher in ATB compared with LTBI. If using the threshold of 0.29, the sensitivity and specificity of TBAg/PHA ratio were 65.71% (60.44%‐70.97%) and 90.93% (88.11%‐93.76%), respectively. Moreover, the combination of prealbumin and TBAg/PHA ratio (obtaining by diagnostic model) yielded better specificity (90.18%, [87.25%‐93.10%]) and sensitivity (87.18%, [83.47%‐90.89%]), while the clinical utility index (CUI) positive and CUI negative were respectively 0.76 and 0.81. After anti‐TB treatment, TBAg/PHA ratio was declined while the level of prealbumin was restored (Wilcoxon test, P < 0.001). Furthermore, the performance of diagnostic model obtained in Qiaokou cohort was confirmed in Caidian cohort. Conclusions The diagnostic model based on combination of prealbumin and TBAg/PHA ratio is a rapid and accurate tool for discriminating ATB from LTBI.

Carbapenem-resistant organisms (CROs) are associated with considerable mortality clinically. There is a lack of effective tool to predict individual prognosis. We aim to determine if host immunity can be utilized to predict the prognosis of patients infected with CRO. From December 2018 to August 2019, we recruited CRO-infected patients to evaluate risk factors for 30-day mortality. Clinical, routine laboratory, immune and microbiological features were investigated and subjected to univariate and multivariate analyses. The final predictive models were established based on the regression coefficients of multivariate logistic regression. A total of 127 CRO-infected patients were enrolled in our study, including 85 survivors and 42 non-survivors. The number and IFN-γ producing ability of lymphocytes were remarkably decreased in non-survivors. The number of IFN-γ+CD4+ T cells could effectively predict 30-day mortality of CRO infection. Its area under the receiver operating characteristic (ROC) curve, sensitivity, specificity and accuracy, were 0.889 (95% confidence interval [CI], 0.834-0.945), 81.0, 80.0, and 80.3%, respectively. In multivariate analysis of laboratory parameters, IFN-γ+CD4+ T cell number and creatinine concentration were selected for the 2-marker model to predict prognosis fleetly. Its area under the ROC curve, sensitivity, specificity and accuracy were 0.894 (95% CI, 0.841-0.947), 83.3, 82.4, and 82.7%, respectively. Impaired lymphocyte function was an important factor to affect the outcome of CRO-infected patients. A 2-marker model based on the combination of IFN-γ+CD4+ T cell number and creatinine showed good performance in predicting the prognosis of CRO infection.

I read with interest the recent published article from Professor Robert L. Medcalf, entitled “Fibrinolysis and COVID‐19: a plasmin paradox” [1]. As an indirect marker of thrombin and plasmin activation, D‐dimer has been suggested to guide anticoagulant treat in COVID‐19 patients [2, 3]. However, D‐dimer may not be able to reflect accurate fibrinolysis status of COVID‐19 patients, and therefore can’t guide the possible antifibrinolysis or thrombolytic therapy in different stages of COVID‐19, as Professor Robert L. Medcalf discussed. Hence, we speculated that measuring direct markers of thrombin, plasmin and so on, may provide more therapeutic targets in COVID‐19 patients with coagulopathy.

Background The objective of this study is to report typical clinical and laboratory characteristics of three cases of keratitis caused by Pythium insidiosum in China. Case presentation Three Chinese patients of Han nationality diagnosed with Pythium keratitis from 2017 to 2019 were included. One 45-year-old female and one 55-year-old male were exposed to river water, and one 51-year-old female was burned by ash in the eyes. All of them are of Han ethnicity. Upon slit-lamp examination, subepithelial and superficial stromal opacities were observed in a reticular pattern. After conventional treatment with antifungal agents, the clinical status worsened and therapeutic penetrating keratoplasty was performed. Unfortunately, enucleation was performed to remove all infected tissue and relieve pain. Pythium insidiosum was identified in culture and confirmed by internal transcribed spacer ribosomal RNA gene sequencing analysis. Following the systemic and local antibiotic regimens, the patients were cured ultimately and no regression of infection was observed. Conclusions It is significant for ophthalmologists and microbiologist to be alert to this eye-threatening infection, especially in patients who are resistant to antifungal treatments and with water-related exposure.

Background There are currently rare satisfactory markers for predicting the death of patients with coronavirus disease 2019 (COVID-19). The aim of this study is to establish a model based on the combination of serum cytokines and lymphocyte subsets for predicting the prognosis of the disease. Methods A total of 739 participants with COVID-19 were enrolled at Tongji Hospital from February to April 2020 and classified into fatal (n = 51) and survived (n = 688) groups according to the patient’s outcome. Cytokine profile and lymphocyte subset analysis was performed simultaneously. Results The fatal patients exhibited a significant lower number of lymphocytes including B cells, CD4+ T cells, CD8+ T cells, and NK cells and remarkably higher concentrations of cytokines including interleukin-2 receptor, interleukin-6, interleukin-8, and tumor necrosis factor-α on admission compared with the survived subjects. A model based on the combination of interleukin-8 and the numbers of CD4+ T cells and NK cells showed a good performance in predicting the death of patients with COVID-19. When the threshold of 0.075 was used, the sensitivity and specificity of the prediction model were 90.20% and 90.26%, respectively. Meanwhile, interleukin-8 was found to have a potential value in predicting the length of hospital stay until death. Conclusions Significant increase of cytokines and decrease of lymphocyte subsets are found positively correlated with in-hospital death. A model based on the combination of three markers provides an attractive approach to predict the prognosis of COVID-19.

Background The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. Measure Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. Results A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. Conclusion Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies., The combination of NAT and serological testing for IgM antibody significantly improves the detection sensitivity of asymptomatic COVID‐19 infections, compared with NAT alone. S1‐specific IgM antibody response with rapid emergence and disappearance might be helpful to assist NAT for early identification of infectious individuals. A majority of asymptomatics induce very low levels of neutralizing antibody that disappear in two months.

BACKGROUND: The coronavirus disease 2019 (COVID-19), infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a severe outbreak throughout the world. The host immunity of COVID-19 patients is unknown. METHODS: The routine laboratory tests and host immunity in COVID-19 patients with different severity of illness were compared after patient admission. RESULTS: A total of 65 SARS-CoV-2–positive patients were classified as having mild (n = 30), severe (n = 20), and extremely severe (n = 15) illness. Many routine laboratory tests, such as ferritin, lactate dehydrogenase, and D-dimer, were increased in severe and extremely severe patients. The absolute numbers of CD4(+) T cells, CD8(+) T cells, and B cells were gradually decreased with increased severity of illness. The activation markers such as HLA-DR and CD45RO expressed on CD4(+) and CD8(+) T cells were increased in severe and extremely severe patients compared with mild patients. The costimulatory molecule CD28 had opposite results. The percentage of natural Tregs was decreased in extremely severe patients. The percentage of IFN-γ–producing CD8(+) T cells was increased in both severe and extremely severe patients compared with mild patients. The percentage of IFN-γ–producing CD4(+) T cells was increased in extremely severe patients. IL-2R, IL-6, and IL-10 were all increased in extremely severe patients. The activation of DC and B cells was decreased in extremely severe patients. CONCLUSION: The number and function of T cells are inconsistent in COVID-19 patients. The hyperfunction of CD4(+) and CD8(+) T cells is associated with the pathogenesis of extremely severe SARS-CoV-2 infection. FUNDING: This work was funded by the National Mega Project on Major Infectious Disease Prevention (2017ZX10103005-007) and the Fundamental Research Funds for the Central Universities (2019kfyRCPY098).

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a novel viral pneumonia (COVID-19), which is rapidly spreading throughout the world. The positive result of nucleic acid test is a golden criterion to confirm SARS-CoV-2 infection, but the detection features remain unclear. METHODS: We performed a retrospective analysis in 5630 high-risk individuals receiving SARS-CoV-2 nucleic acid tests in Wuhan, China, and investigated their characteristics and diagnosis rates. RESULTS: The overall diagnosis rate was 34.7% (1952/5630). Male (P = 0.025) and older populations (P = 2.525 × 10(–39)) were at significantly higher risk of SARS-CoV-2 infection. People were generally susceptible, and most cases concentrated in people of 30–79 years. Furthermore, we investigated the association between diagnosis rate and the amount of testing in 501 subjects. Results revealed a 1.27-fold improvement (from 27.9% to 35.5%) of diagnosis rate from testing once to twice (P = 5.847 × 10(–9)) and a 1.43-fold improvement (from 27.9% to 39.9%) from testing once to 3 times (P = 7.797 × 10(–14)). More than 3 testing administrations was not helpful for further improvement. However, this improvement was not observed in subjects with pneumonia (P = 0.097). CONCLUSION: All populations are susceptible to SARS-CoV-2 infection, and male and older-aged populations are at significantly higher risk. Increasing the amount of testing could significantly improve diagnosis rates, except for subjects with pneumonia. It is recommended to test twice in those high-risk individuals whose results are negative the first time, and performing 3 tests is better, if possible. FUNDING: This work was supported by National Mega Project on Major Infectious Disease Prevention (no. 2017ZX10103005-007) and National Key Research and Development Program of China (no. 2018YFE0204500).

Objectives To determine the epidemiological cut-off values (ECOFFs) of norvancomycin for Staphylococcus aureus, Staphylococcus epidermidis, Staphylococcus haemolyticus and Staphylococcus hominis. Methods We collected 1199 clinical isolates of Staphylococcus species from five laboratories located in four cities in China. MICs and inhibitory zone diameters of norvancomycin were determined by broth microdilution and the disc diffusion method, separately. ECOFFs of norvancomycin for four species were calculated by ECOFFinder software following EUCAST principles. Methicillin and vancomycin resistance genes (mecA/mecC and vanA/vanB/vanC/vanD/vanE) were screened for by PCR in all isolates. Pearson correlation and χ2 test were used to calculate the correlation of MICs and inhibition zone diameters, and MICs and resistance genes, respectively. Results MICs of norvancomycin for all strains from five laboratories fell in the range of 0.12–2 mg/L. ECOFFs of norvancomycin were determined to be 2 mg/L for S. epidermidis and S. haemolyticus and 1 mg/L for S. aureus and S. hominis. A weak correlation was observed between MIC values and zone diameters for S. haemolyticus (r = −0.36) and S. hominis (r = −0.26), while no correlation was found for S. epidermidis and S. aureus. The mecA gene was detected in 63.1% of Staphylococcus, whereas no isolate carried mecC, vanA, vanB, vanC, vanD or vanE. ECOFFs of norvancomycin were not correlated with mecA gene carriage in Staphylococcus species. Conclusions ECOFFs of norvancomycin for four Staphylococcus species were determined, which will be helpful to differentiate WT strains. The correlation of MICs and zone diameters of norvancomycin was weak in Staphylococcus species.

Background: In the recent outbreak of novel coronavirus infection in Wuhan, China, significantly abnormal coagulation parameters in severe novel coronavirus pneumonia (NCP) cases were a concern. Objectives: To describe the coagulation feature of patients with NCP. Methods: Conventional coagulation results and outcomes of 183 consecutive patients with confirmed NCP in Tongji hospital were retrospectively analyzed. Results: The overall mortality was 11.5%, the non-survivors revealed significantly higher D-dimer and fibrin degradation product (FDP) levels, longer prothrombin time and activated partial thromboplastin time compared to survivors on admission (P < .05); 71.4% of non-survivors and 0.6% survivors met the criteria of disseminated intravascular coagulation during their hospital stay. Conclusions: The present study shows that abnormal coagulation results, especially markedly elevated D-dimer and FDP are common in deaths with NCP.

Summary Objectives Distinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging. Methods The modified T-SPOT.TB assay was performed in 499 participants (243 ATB and 256 LTBI) and another 322 participants (162 ATB and 160 LTBI) who were diagnosed in Qiaokou (training) and Caidian (validation) cohort respectively. Results The mean spot sizes (MSS) of early secreted antigenic target 6 (ESAT-6) spot-forming cells (SFC) of T-SPOT.TB assay in ATB patients was significantly higher than that in LTBI individuals. 1.0 × 105 was the optimal number of cells added to phytohaemagglutinin (PHA) well for obtaining more accurate TB-specific antigen to phytohaemagglutinin (TBAg/PHA) ratio. The area under the curve of the diagnostic model by combination of ESAT-6 SFC MSS and modified TBAg/PHA ratio in distinguishing ATB from LTBI was 0.959 in training cohort, with a sensitivity of 90.12% and a specificity of 91.02% when a cutoff value of 0.46 was used. This diagnostic model showed similar performance in the validation cohort. The area under the curve, sensitivity, and specificity were 0.962, 93.21%, and 90.00%, respectively. Further flow cytometry analysis showed that ESAT-6 stimulation induced a significantly higher mean fluorescence intensity of IFN-γ+ cells in lymphocytes compared with culture filtrate protein 10 (CFP-10) stimulation. In contrast, CFP-10 stimulation induced a significantly higher percentage of IFN-γ+ cells in lymphocytes compared with ESAT-6 stimulation. Conclusions The combination of the MSS of ESAT-6 SFC and the modified TBAg/PHA ratio of T-SPOT.TB assay showed great value in discriminating ATB from LTBI.