Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at sqrt[s]=13  TeV and corresponding to an integrated luminosity of 137  fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bb[over ¯]. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be μ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst)  pb.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165  nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16  TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

Using immune clusters for classifying Mycobacterium tuberculosis infection

BACKGROUND

The differential diagnosis between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) is still a challenge worldwide.

METHODS

Immune indicators involved in innate, humoral, and cellular immune cells, as well as antigen-specific cells were simultaneously assessed in patients with ATB and LTBI.

RESULTS

Of 54 immune indicators, no indicator could distinguish ATB from LTBI, likely due to an obvious heterogeneity of immune indicators noticed in ATB patients. Cluster analysis of ATB patients identified three immune clusters with different severity. Cluster 1 (42.1 %) was a ''Treg/Th1/Tfh unbalance type" cluster, whereas cluster 2 (42.1 %) was an "effector type'' cluster, and cluster 3 was a ''inhibition type'' cluster (15.8 %) which showed the highest severity. A prediction model based on immune indicators was established and showed potential in classifying Mycobacterium tuberculosis infection.

CONCLUSIONS

We depicted the immune landscape of patients with ATB and LTBI. Three immune subtypes were identified in ATB patients with different severity.

Combined Measurement of the Higgs Boson Mass from the H→γγ and H→ZZ^{*}→4ℓ Decay Channels with the ATLAS Detector Using sqrt[s]=7, 8, and 13 TeV pp Collision Data

A measurement of the mass of the Higgs boson combining the H→ZZ^{*}→4ℓ and H→γγ decay channels is presented. The result is based on 140  fb^{-1} of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a center-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, performed at center-of-mass energies of 7 and 8 TeV, yielding a Higgs boson mass of 125.11±0.09(stat)±0.06(syst)=125.11±0.11  GeV. This corresponds to a 0.09% precision achieved on this fundamental parameter of the Standard Model of particle physics.

[Analysis of perrault syndrome caused by pathogenic variants in LARS2 and HARS2 genes]

Objective: To investigate the molecular etiology of Perrault syndrome by analyzing the clinical phenotype and pathogenic gene variants of 2 male patients with bilateral severe sensorineural deafness. Methods: Two male patients with Perrault syndrome characterized by severe sensonrineual deafness adimitted to the First Affiliated Hospital of Zhengzhou University between February 2021 and March 2022 were selected, and the clinical phenotype and pathogenic gene variants of them and their family members were summarized. The whole exome sequencing technology was used to screen the pathogenic variants of the probands, and the candidate variants were determined by combining with clinical phenotype. The probands and their family members were verified by the Sanger sequencing method. Results: The whole exome sequencing results showed that the proband of family 1 had a compound heterozygous variants of the LARS2 (NM_015340.4) gene c.1565C>A (p.Thr522Asn) and c.1079T>C (p.Ile360Thr). The reported pathogenic variant c.1565C>A came from the mother, and the novel variant c.1079T>C came from the father. The second proband harbored compound heterozygous variants of HARS2 gene (NM_012208.4) c.1273C>T (p.Arg425Trp) and c.1403G>C (p.Gly468Ala), with the former from the proband's mother, the latter from the father. The c.1273C>T was novel and c.1403G>C was the reported pathogenic variant. All above variants were respectively classified as pathogenic, uncertain significance, uncertain significance and likely pathogenic based on the ACMG guidelines. Conclusion: This study expands the mutational spectrum of LARS2 and HARS2 genes, which highlights that genetic testing plays an important role in the early diagnosis of syndromic deafness.

Aquilaria sinensis leaf tea affects the immune system and increases sleep in zebrafish

The importance of adequate sleep for good health cannot be overstated. Excessive light exposure at night disrupts sleep, therefore, it is important to find more healthy drinks that can promote sleep under sleep-disturbed conditions. The present study investigated the use of A. sinensis (Lour.) Spreng leaf tea, a natural product, to reduce the adverse effects of nighttime light on sleep. Here, Aquilaria sinensis leaf tea at 1.0 and 1.5 g/L significantly increased sleep time in zebrafish larvae (5-7 dpf) with light-induced sleep disturbance. Transcriptome sequencing and qRT-PCR analysis revealed a decrease in the immune-related genes, such as nfkbiab, tnfrsf1a, nfkbiaa, il1b, traf3, and cd40 in the 1.5 g/L Aquilaria sinensis leaf tea treatment group. In addition, a gene associated with sleep, bhlhe41, showed a significant decrease. Moreover, Aquilaria sinensis leaf tea suppressed the increase in neutrophils of Tg(mpo:GFP) zebrafish under sleep-disturbed conditions, indicating its ability to improve the immune response. Widely targeted metabolic profiling of the Aquilaria sinensis tea using ultra-performance liquid chromatography coupled with electrospray tandem mass spectrometry (UPLC-ESI-MS/MS) revealed flavonoids as the predominant component. Network pharmacological and molecular docking analyses suggested that the flavonoids quercetin and eupatilin in Aquilaria sinensis leaf tea improved the sleep of zebrafish by interacting with il1b and cd40 genes under light exposure at night. Therefore, the results of the study provide evidence supporting the notion that Aquilaria sinensis leaf tea has a positive impact on sleep patterns in zebrafish subjected to disrupted sleep due to nighttime light exposure. This suggests that the utilization of Aquilaria sinensis leaf tea as a potential therapeutic intervention for sleep disturbances induced by light may yield advantageous outcomes.

Analysis of the value of echocardiographic parameters in the early diagnosis of preterm infants with bronchopulmonary dysplasia

OBJECTIVE

The objective of this study was to investigate the role of echocardiographic parameters in diagnosing bronchopulmonary dysplasia (BPD) in preterm infants.

PATIENTS AND METHODS

Ninety preterm infants with a gestational age of less than 32 weeks and a weight less than 1.5 kg, admitted to the neonatal intensive care unit of the hospital between January 2020 and January 2021, were selected for the study. The study subjects were divided into two groups: a BPD group (54 cases, observation group) and a non-BPD group (36 cases, control group). The correlation between tricuspid regurgitation (TR) velocity and BPD was investigated by detecting the cardiac function of preterm infants in both groups using a color Doppler ultrasound diagnostic instrument and analyzing the cardiac ultrasound results. The early prediction efficiency of TR velocity (m/s) for BPD was evaluated using the receiver operator characteristic (ROC) curve.

RESULTS

The incidence of patent ductus arteriosus (PDA) and pulmonary hypertension (PH) in the observation group was significantly higher than that in the control group. The levels of left ventricular ejection fraction (LVEF) and left ventricular shorting fraction (LVFS) were significantly lower than those in the control group (p < 0.05). The incidence of patent foramen ovale (PFO), atrial septal defect (ASD), and ventricular septal defect (VSD) in the observation group were not significantly different from the control group (p > 0.05). The proportion of tricuspid regurgitation in the observation group was significantly higher than that in the control group, and the TR velocity was significantly higher than that in the control group. The Spearman correlation analysis showed that TR velocity (m/s) was positively correlated to BPD severity (r = 0.379, p < 0.05). The area under the curve (AUC) for predicting BPD with TR velocity was 0.735. The sensitivity and specificity were 88.0% and 62.6%, respectively, when the TR velocity was 1.45 m/s.

CONCLUSIONS

Echocardiography is useful for understanding the degree of impaired cardiac function in preterm infants and for early detection of PH, which may reduce the mortality rate to a certain extent. The risk of BPD is significantly increased when TR velocity is higher than 1.45 m/s.

[Investigation of newly diagnosed pneumoconiosis from artificial quartz stone manufacturers]

Artificial quartz dust exposure may cause associated pneumoconiosis. From November 2019 to July 2020, a total of 27 cases of silicosis associated with artificial quartz stone manufacturers were diagnosed and treated in the Occupational disease Department of Suzhou Fifth People's Hospital. The average age of onset was (46.8±6.6) years, and the average working age of dust exposure was (5.7±1.7) years.The main feature of high KV chest radiography is P/S shadow with strip shadow. CT imaging findings showed diffuse small nodules and ground glass shadows with band shadows. The lesions were mainly distributed in the upper lung, accompanied by pleural thickening, lymphadenopathy and calcification. The pulmonary function impairment was mainly mild restrictive ventilation disorder, and the bronchial mucosa longitudinal plica was the main manifestation under tracheoscopy. The age of silicosis of workers in artificial quartz stone production enterprises is younger, the working age of dust exposure is short, the lung function and bronchial mucosa have a certain degree of damage, and effective preventive measures should be taken in time.

Nanopore-based disease diagnosis using pathogen-derived tryptic peptides from serum

Nanopore sensors have shown great utility in nucleic acid detection and sequencing approaches. Recent studies also indicate that current signatures produced by peptide-nanopore interactions can distinguish high purity peptide mixtures, but the utility of nanopore sensors in clinical applications still needs to be explored due to the inherent complexity of clinical specimens. To fill this gap between research and clinical nanopore applications, we describe a methodology to select peptide biomarkers suitable for use in an immunoprecipitation-coupled nanopore (IP-NP) assay, based on their pathogen specificity, antigenicity, charge, water solubility and ability to produce a characteristic nanopore interaction signature. Using tuberculosis as a proof-of-principle example in a disease that can be challenging to diagnose, we demonstrate that a peptide identified by this approach produced high-affinity antibodies and yielded a characteristic peptide signature that was detectable over a broad linear range, to detect and quantify a pathogen-derived peptide from digested human serum samples with high sensitivity and specificity. This nanopore signal distinguished serum from a TB case, non-disease controls, and from a TB-case after extended anti-TB treatment. We believe this assay approach should be readily adaptable to other infectious and chronic diseases that can be diagnosed by peptide biomarkers.

CD39 pathway inhibits Th1 cell function in tuberculosis

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⁺ Th1 cells in comparison with CD39⁻ Th1 cells. Conversely, CD39 expression on Th1 cells was associated with diminished number of polyfunctional cells producing Th1‐type cytokines, and CD39⁺ Th1 cells showed obviously lower proliferation potential. Notably, tetramer analysis demonstrated a predominant CD39 expression on TB‐specific CD4⁺ cells, which was associated with higher apoptosis and lower cytokine‐producing ability. Transcriptome sequencing identified 27 genes that were differentially expressed between CD39⁺ and CD39⁻ Th1 cells, such as IL32, DUSP4 and RGS1. Inhibition of CD39 pathway could enhance the activation, proliferation and cytokine‐producing ability of Th1 cells. Furthermore, there was a significantly negative correlation between CD39 expression on Th1 cells and nutritional status indicators such as lymphocyte count and albumin levels, and we observed a significant decline in CD39 expression on Th1 cells after anti‐TB treatment. CD39 is predominantly expressed on TB‐specific Th1 cells and correlated with their exhausted function, which suggests that CD39 could serve as a prominent target for TB therapy.

[Value of radiomics model based on dynamic contrast-enhanced magnetic resonance imaging in differentiation fat-poor angiomyolipoma from alpha-fetoprotein-negative hepatocellular carcinoma in the background of non-cirrhotic liver]

Objective: To explore the value of radiomics model based on dynamic contrast-enhanced magnetic resonance imaging (MRI) in differentiation fat-poor angiomyolipoma (fp-AML) from alpha-fetoprotein-negative hepatocellular carcinoma (n-HCC) in the background of non-cirrhotic liver. Methods: The complete data of 121 patients from Guangdong Provincial People's Hospital, Zhongshan Hospital Affiliated to Fudan University and Sun Yat-sen University Cancer Center with hepatic fp-AML and n-HCC confirmed by pathology from October 2010 to July 2020 were retrospectively analyzed. Among them, 75 were males and 46 were females, aged from 23 to 80 (55±12) years. A total of 93 patients from Zhongshan Hospital Affiliated to Fudan University were divided into the training cohort (n=75) and internal test cohort (n=18) according to entry time, and the patients of other 2 hospitals were divided into external test cohort (n=28). The radiomics features were extracted from the preoperative triple-phase contrast-enhanced images. The feature selection algorithm based on Joint Mutual Information Maximisation (JMIM) was used to extract the optimal feature subset, and support vector machine (SVM) was used to build the radiomics model. The diagnostic performance of radiomics model was evaluated using the receiver operating characteristic (ROC) curve, and was compared with that of two radiologists. Results: In the internal cohort, the area under the curve (AUC) for the differential diagnosis between fp-AML and n-HCC of the radiomics model was 0.819 (with an accuracy of 72.2%), outperforming than radiologist 1 with 10 years of diagnostic experience (AUC=0.542, P=0.029) and radiologist 2 with 2 years of diagnostic experience (AUC=0.375, P=0.004). In the external cohort, the AUC of the radiomics model was 0.772 (with and accuracy of 71.4%), which was comparable to that of radiologist 1 (AUC=0.661, P=0.442) and better than that of radiologist 2 (AUC=0.400, P=0.008). Conclusion: The radiomics model based on dynamic contrast-enhanced MRI is of high accuracy for preoperatively differentiating hepatic fp-AML from n-HCC in the noncirrhotic liver.

[Risk factors of newly developed nonalcoholic fatty liver disease after pancreaticoduodenectomy]

Objective: To identify the risk factors of newly developed nonalcoholic fatty liver disease(NAFLD) after pancreaticoduodenectomy(PD). Methods: The clinical data of 130 patients who had undergone PD at Department of Hepatopancreatobiliary Surgery, Nanjing Drum Tower Hospital, the Affiliated Hospital of Medical School of Nanjing University from June 2018 to December 2020 were collected retrospectively. There were 74 males and 56 females, with age(M(IQR)) of 62(16) years (range: 22 to 84 years). Twenty-nine patients who developed NAFLD were divided into NAFLD group and 101 patients who did not suffer NAFLD were divided into no NAFLD group. Observation indications included:(1)preoperative demographics,intraoperative and postoperative characteristics; (2)the risk factors of newly developed NAFLD after PD. Count data were analyzed using χ² test or Fisher's exact test. Measurement data were analyzed by student t test or Mann-Whitney U test. Multivariate analysis was performed using Logistic regression model with a stepwise forward approach. Results: All 130 patients successfully underwent PD and 29 cases(22.3%) developed NAFLD in 6 months after PD. The results of univariate analysis showed that gender,diabetic mellitus,the level of triglyceride preoperatively,and pancreatic ductal adenocarcinoma were the related factors of the development of NAFLD after PD(t=-2.655, χ²=4.563,U=-2.192,χ²=7.044;all P<0.05).Multivariate analysis revealed that gender,body mass index,pancreatic ductal adenocarcinoma were independent risk factors for the development of NAFLD after PD(OR=2.849,1.214,4.165,all P<0.05). Conclusion: Gender, body mass index,pancreatic ductal adenocarcinoma were independent risk factors for the development of NAFLD after PD.

Diagnostic Model for Discrimination Between Tuberculous Meningitis and Bacterial Meningitis

Background

The 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.

Methods

Patients 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.

Results

A 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.

Conclusions

The diagnostic model established based on the combination of four indicators had excellent utility in the discrimination between TBM and BM.

Combination of HLA-DR on Mycobacterium tuberculosis-Specific Cells and Tuberculosis Antigen/Phytohemagglutinin Ratio for Discriminating Active Tuberculosis From Latent Tuberculosis Infection

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.

The Dynamic Immunological Parameter Landscape in Coronavirus Disease 2019 Patients With Different Outcomes

Objectives

The longitudinal and systematic evaluation of immunity in coronavirus disease 2019 (COVID-19) patients is rarely reported.

Methods

Parameters involved in innate, adaptive, and humoral immunity were continuously monitored in COVID-19 patients from onset of illness until 45 days after symptom onset.

Results

This 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.

Conclusions

This study systemically characterizes the kinetics of immunity of COVID-19, highlighting the importance of immunity in patient prognosis.

Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection

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.

Bacterial characteristics of carbapenem-resistant Enterobacteriaceae (CRE) colonized strains and their correlation with subsequent infection

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 <  0.001). Univariate analysis showed that 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.

Lymphocyte-Related Immunological Indicators for Stratifying Mycobacterium tuberculosis Infection

Background

Easily 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).

Methods

A 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.

Results

Compared 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%).

Conclusions

Our study demonstrated that the immunodiagnostic model established by the combination of lymphocyte-related indicators could facilitate the status differentiation of MTB infection.

Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection

Background

Distinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.

Methods

Between 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.

Results

Significant 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.

Conclusions

The diagnostic model based on combination of BRE and T-SPOT could provide a reliable differentiation between ATB and LTBI.

Evaluation of a serum-based antigen test for tuberculosis in HIV-exposed infants: a diagnostic accuracy study

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.

[The prognostic impact of diabetic mellitus and hyperglycemia during DLBCL treatment on patients with diffuse large B-cell lymphoma]

目的

探讨弥漫大B细胞淋巴瘤（DLBCL）患者的临床特征和预后因素，评估合并糖尿病（DM）及治疗过程中发生血糖升高对DLBCL预后的影响。

方法

回顾性收集2009年1月1日至2019年12月31日天津医科大学肿瘤医院及中山大学肿瘤防治中心收治的481例初诊DLBCL患者的临床资料，重点关注其治疗前及治疗中的血糖水平，采用Cox回归风险模型进行单因素分析评估预后影响因素，采用Kaplan-Meier法绘制生存曲线分析血糖异常对DLBCL患者总生存（OS）、无进展生存（PFS）的影响。

结果

82例（17.0％）患者在诊断DLBCL前患DM，88例（18.3％）患者在DLBCL治疗过程中至少发生一次血糖升高。单因素分析显示，年龄、Ann-Arbor分期、IPI评分、是否合并DM与OS、PFS相关（P值均<0.05）。组间比较显示，合并DM组与治疗过程中血糖升高组的OS和PFS均较无血糖异常组差（OS：P值分别为0.001、0.003，PFS：P值均<0.001），合并DM组与治疗过程中血糖升高组相比OS和PFS的差异均无统计学意义（P值分别为0.557、0.463）。化疗期间血糖控制良好组的OS和PFS优于血糖控制差组（OS：P＝0.037，PFS：P＝0.007）。

结论

合并DM是影响DLBCL患者预后的重要因素，治疗过程中血糖升高与DLBCL患者的不良预后相关。

Lymphocyte Non-Specific Function Detection Facilitating the Stratification of Mycobacterium tuberculosis Infection

Background

Inadequate tuberculosis (TB) diagnostics, especially for discrimination between active TB (ATB) and latent TB infection (LTBI), are major hurdle in the reduction of the disease burden. The present study aims to investigate the role of lymphocyte non-specific function detection for TB diagnosis in clinical practice.

Methods

A total of 208 participants including 49 ATB patients, 64 LTBI individuals, and 95 healthy controls were recruited at Tongji hospital from January 2019 to October 2020. All subjects were tested with lymphocyte non-specific function detection and T-SPOT assay.

Results

Significantly positive correlation existed between lymphocyte non-specific function and phytohemagglutinin (PHA) spot number. CD4⁺ T cell non-specific function showed the potential for differentiating patients with negative T-SPOT results from those with positive T-SPOT results with an area under the curve (AUC) of 0.732 (95% CI, 0.572-0.893). The non-specific function of CD4⁺ T cells, CD8⁺ T cells, and NK cells was found significantly lower in ATB patients than in LTBI individuals. The AUCs presented by CD4⁺ T cell non-specific function, CD8⁺ T cell non-specific function, and NK cell non-specific function for discriminating ATB patients from LTBI individuals were 0.845 (95% CI, 0.767-0.925), 0.770 (95% CI, 0.683-0.857), and 0.691 (95% CI, 0.593-0.789), respectively. Application of multivariable logistic regression resulted in the combination of CD4⁺ T cell non-specific function, NK cell non-specific function, and culture filtrate protein-10 (CFP-10) spot number as the optimally diagnostic model for differentiating ATB from LTBI. The AUC of the model in distinguishing between ATB and LTBI was 0.939 (95% CI, 0.898-0.981). The sensitivity and specificity were 83.67% (95% CI, 70.96%-91.49%) and 90.63% (95% CI, 81.02%-95.63%) with the threshold as 0.57. Our established model showed superior performance to TB-specific antigen (TBAg)/PHA ratio in stratifying TB infection status.

Conclusions

Lymphocyte non-specific function detection offers an attractive alternative to facilitate TB diagnosis. The three-index diagnostic model was proved to be a potent tool for the identification of different events involved in TB infection, which is helpful for the treatment and management of patients.

Using Routine Laboratory Markers and Immunological Indicators for Predicting Pneumocystis jiroveci Pneumonia in Immunocompromised Patients

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.

Combination of prealbumin and tuberculosis-specific antigen/phytohemagglutinin ratio for discriminating active tuberculosis from latent tuberculosis infection

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.

Machine Learning-Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study

BACKGROUND AND PURPOSE

Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic information based on machine learning techniques and to test the models in external validation datasets.

MATERIALS AND METHODS

From January 2010 to December 2016, five hundred four consecutive patients with only small aneurysms (<5 mm) detected by CTA and invasive cerebral angiography (or surgery) were retrospectively enrolled and randomly split into training (81%) and internal validation (19%) sets to derive and validate the proposed machine learning models (support vector machine, random forest, logistic regression, and multilayer perceptron). Hemodynamic parameters were obtained using computational fluid dynamics simulation. External validation was performed in other hospitals to test the models.

RESULTS

The support vector machine performed the best with areas under the curve of 0.88 (95% CI, 0.85-0.92) and 0.91 (95% CI, 0.74-0.98) in the training and internal validation datasets, respectively. Feature ranks suggested hemodynamic parameters, including stable flow pattern, concentrated inflow streams, and a small (<50%) flow-impingement zone, and the oscillatory shear index coefficient of variation, were the best predictors of aneurysm rupture. The support vector machine showed an area under the curve of 0.82 (95% CI, 0.69-0.94) in the external validation dataset, and no significant difference was found for the areas under the curve between internal and external validation datasets (P = .21).

CONCLUSIONS

This study revealed that machine learning had a good performance in predicting the rupture status of small aneurysms in both internal and external datasets. Aneurysm hemodynamic parameters were regarded as the most important predictors.

Cognitive ageing is premature among a community sample of optimally treated people living with HIV

OBJECTIVES

Evidence of premature cognitive ageing amongst people living with HIV (PLHIV) remains controversial due to previous research limitations including underpowered studies, samples with suboptimal antiretroviral access, varying rate of virological control, high rate of AIDS, over-representation of non-community samples, and inclusion of inappropriate controls. The current study addresses these limitations, while also considering mental health and non-HIV comorbidity burden to determine whether PLHIV showed premature cognitive ageing compared with closely comparable HIV-negative controls.

METHODS

This study enrolled 254 PLHIV [92% on antiretroviral therapy; 84% with HIV RNA < 50 copies/mL; 15% with AIDS) and 72 HIV-negative gay and bisexual men [mean (SD) age = 49 (10.2) years] from a single primary care clinic in Sydney, Australia. Neurocognitive function was evaluated with the Cogstate Computerized Battery (CCB) at baseline and 6 months after. Linear mixed-effects (LME) models examined main and interaction effects of HIV status and chronological age on the CCB demographically uncorrected global neurocognitive z-score (GZS), adjusting for repeated testing, and then adjusting sequentially for HIV disease markers, mental health and comorbidities.

RESULTS

HIV status and age interacted with a lower GZS (β = -0.43, P < 0.05). Higher level of anxiety symptoms (β = -0.11, P < 0.01), historical AIDS (β = -0.12, P < 0.05) and historical HIV brain involvement (β = -0.12, P < 0.05) were associated with lower GZS.

CONCLUSIONS

We found a robust medium-sized premature ageing effect on cognition in a community sample with optimal HIV care. Our study supports routine screening of cognitive and mental health among PLHIV aged ≥ 50 years.

[Abnormalities of white matter differentiate the Parkinson variant of multiple system atrophy from Parkinson's disease]

Objective: To identify objective markers between the Parkinson variant of multiple system atrophy (MSA-P) and Parkinson's disease (PD). Methods: Retrospective analysis was performed on 10 patients with MSA-P, 15 patients with PD, and 15 healthy control group during the period from August 2016 to February 2019 in Baoshan Branch of Shanghai First People's Hospital.We combined the novel tract based spatial statistics (TBSS) and region of interest (ROI) analyses for the first time to investigate three groups with diffusion tensor imaging. By TBSS, we performed pairwise comparisons of mean diffusivity and fractional anisotropy (FA) maps. The clusters with significant differences between MSA-P and PD were used as ROIs for further analyses. Results: FA values in the left anterior thalamic radiation(ATR) (ROI values were 0.371(0.287-0.535), 0.472(0.390-0.594), 0.473(0.388-0.555); P values were 0.008, 0.008) and left superior longitudinal fasciculus (SLF)(ROI values were 0.397(0.291-0.469), 0.456(0.338-0.560), 0.473(0.427-0.530); P values were 0.013,<0.001) were significantly decreased in MSA-P compared with PD or controls, and significantly correlated with clinical data((r =-0.807, P =0.005),(r =-0.455, P =0.022)). Conclusion: Our findings indicate the abnormalities of left ATR and left SLF as specific biomarkers for differential diagnosis.

Diagnostic Value of T-SPOT.TB Assay for Tuberculous Peritonitis: A Meta-Analysis

Background: Tuberculous peritonitis (TP) is a common form of abdominal tuberculosis (TB). Diagnosing TP remains challenging in clinical practice. The aim of the present meta-analysis was to evaluate the diagnostic accuracy of peripheral blood (PB) T-SPOT and peritoneal fluid (PF) T-SPOT for diagnosing TP.

Methods: PubMed, EmBase, Cochrane, Scopus, Google scholar, China national knowledge internet, and Wan-Fang databases were searched for relevant articles from August 1, 2005 to July 5, 2020. Statistical analysis was performed using Stata, Revman, and Meta-Disc software. Diagnostic parameters including pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were determined. Summary receiver operating characteristic curve was used to determine the area under the curve (AUC).

Results: Twelve studies were eligible and included in the meta-analysis. The analysis showed that the pooled sensitivity and specificity of PB T-SPOT in diagnosing TP were 0.91 (95% CI, 0.88–0.94) and 0.78 (95% CI, 0.73–0.81), respectively, while the pooled PLR, NLR, and DOR were 4.05 (95% CI, 2.73–6.01), 0.13 (95% CI, 0.07–0.23), and 37.8 (95% CI, 15.04–94.98), respectively. On the other hand, the summary estimates of sensitivity, specificity, PLR, NLR, and DOR of PF T-SPOT for TP diagnosis were 0.90 (95% CI, 0.85–0.94), 0.78 (95% CI, 0.72–0.83), 6.35 (95% CI, 2.67–15.07), 0.14 (95% CI, 0.09–0.21), and 58.22 (95% CI, 28.76–117.83), respectively. Furthermore, the AUC of PB T-SPOT and PF T-SPOT for TP diagnosis were 0.91 and 0.94, respectively.

Conclusions: Our results indicate that both PB T-SPOT and PF T-SPOT can be served as sensitive approaches for the diagnosis of TP. However, the unsatisfactory specificities of these two methods limit their application as rule-in tests for TP diagnosis. Furthermore, the standardization of the operating procedure of PF T-SPOT is further needed.

[Evaluation of drug-drug interactions between yimitasvir phosphate capsules with sofosbuvir tablets, omeprazole magnesium enteric-coated tablets, and rosuvastatin calcium tablets]

Objective: To evaluate the drug-drug interactions and the tolerability of combined medication between yimitasvir phosphate capsules with sofosbuvir tablets, omeprazole magnesium enteric-coated tablets, and rosuvastatin calcium tablets in healthy volunteers. Methods: A randomized, open, and continuous administration design was used in trial 1 (yimitasvir phosphate capsules with sofosbuvir tablets). 28 subjects were randomly divided into two groups. A non-randomized, open design was used in trial 2 (yimitasvir phosphate capsules with omeprazole magnesium enteric-coated tablets), and included 42 subjects divided into three groups. The open design method was used in trial 3 (yimitasvir phosphate capsules with rosuvastatin calcium tablets), and included 14 subjects. The plasma concentrations of yimitasvir phosphate, sofosbuvir and their main metabolites GS-331007, omeprazole and rosuvastatin were validated by a liquid chromatography/tandem mass spectrometry (LC-MS/MS). The pharmacokinetic parameters were calculated by Phoenix winNonlin software. Results: (1) in trial 1, after single and co-administration, the 90% CI of sofosbuvir C(max) and AUC(0-tau) geometric mean ratio (GMR) were 152.0% (118.0% ~ 197.0%) and 230.0% (184.0% ~ 287.0%), with an increase of 52.0% and 130.0% compared to single dose of sofosbuvir, respectively. The 90% CI of GS-331007 C(max) GMR was 74.0% (67.5% ~ 81.2%) and reduced by 26% compared to single dose of sofosbuvir. (2) in trial 2, the 90% CI of C(max) GMR after yimitasvir single or co-administration at the same time, with a 4-hours interval, or with a 12- hours interval were 68.9% (44.5% ~ 106.7%) , 64.0% (43.8% ~ 93.6%) and 56.4%(38.9% ~ 81.9%), and the 90% CI of AUC(0-t) GMR were 68.6% (46.5% ~ 101.2%), 68.3% (47.6% ~ 98.0%) and 60.5% (41.8% ~ 87.5%), respectively. Compared with single dose of yimitasvir, the C(max) and AUC(0-t) were decreased by 31.1% and 31.4%, 36.0% and 31.7%, 43.6% and 39.5%, respectively. (3) In trial 3, after single and co-administration, the 90% CI of rosuvastatin C(max) and AUC(0-72) GMR were 172.4% (153.6% ~ 193.5%) and 158.0% (144.3% ~ 172.9%), respectively, with an increase of 74.9% and 60.5% compared to single dose of rosuvastatin. There were no serious adverse events and adverse events leading to withdrawal from the trial. Conclusion: Yimitasvir phosphate capsules have drug-drug interactions with sofosbuvir tablets, omeprazole magnesium enteric-coated tablets, and rosuvastatin calcium tablets.

First Report of Black Spot Caused by Neoscytalidium dimidiatum on Sisal in Guangxi, China

Sisal (Agave sisalana Perrine) is an important hard fiber crop that is widely planted in Guangxi, Guangdong, Hainan, Yunnan, and Fujian provinces, China. In July 2019, a new leaf disease of sisal with a disease incident of about 36% was found in Guangxi (Fig.1a~d). The oval or circular black lesions were 2.3 cm to 15.9 cm in length and 1.6 cm to 5.5 cm in width on both sides of the diseased leaves. The central part of the lesions was slightly hollow. The lesions continuously enlarged and ultimately penetrated the leaves. Reddish brown and dark mucus was secreted from the lesions. The junction of lesions and healthy parts was reddish brown to yellow. The diseased leaf fiber and mesophyll tissues were reddish brown and necrotic. Fresh leaf yield was reduced about 30% by the disease, and fiber quality was significantly compromised every year in Guangxi. Six kinds of fungi distinguished by their morphology, size and color of the colonies were isolated from diseased leaf tissues of 60 sisal plants sampled from five different farms in Guangxi. Isolate JMHB1 was isolated at a rate of 95.67%. The isolate JMHB1 was initially white with dense and hairy aerial mycelium, gradually turning dark grey to olive green on PDA (Fig. 2). Conidia, arthrospores, and chlamydospores were observed on PDA in culture (Fig. 3). The conidia formed arthric chains, disarticulating, cylindrical-truncate, oblong-obtuse to doliiform, colorless and transparent, zero- to one-septate, and averaging 4.4 to 13.8 µm × 2.2 to 5.6 µm (n=100). Arthrospores were short columnar, pigmented and transparent, single or formed arthric chains, averaging 5.5 to 17.9 µm × 2.1 to 3.5 µm (n=100). Chlamydospores were dark brown, round or oval, averaging 4.5 to 9.6 µm × 4.5 to 8.6 µm (n=100). Pathogenicity testing was conducted by inoculating 3-year-old healthy sisal plants with PDA plugs (5 × 5 mm) on which the fungus had grown for 5 days. Nine healthy plants were wounded on the leaves with a sterile needle, and mycelial plugs were placed on the wounds, covered with sterile moist cotton, and wrapped with parafilm. Nine control plants were wounded and treated with PDA plugs as the negative control. The test was repeated three times. All treated plants were kept in a greenhouse at ~28 ℃ and 40% RH. After 5 days, only leaves inoculated with isolate JMHB1 showed lesions similar to symptoms observed in the field (Fig.1e~f). The fungus was re-isolated from all nine diseased plants, and no symptoms were observed on the leaves of control plants. Molecular identification of the fungus was made by PCR amplification of the internal transcribed spacer (ITS) region of rDNA, EF1-α gene and β-tubulin gene using primers ITS1/ITS4 (White et al. 1990), EFl-728F/EF1-986R (Carbone and Kohn 1999), TUB2Fd/TUB4Rd (Aveskamp et al. 2009) respectively. The ITS (MT705646), EF1-α (MT733516) and β-tubulin (MT773603) sequences of JMHB1 were similar to the ITS (AY819727), EF1-α (EU144063) and β-tubulin (KF531800) sequences of the epitype of Neoscytalidium dimidiatum (CBS 499.66) with 100%, 99.65% and 99.02% identity, respectively. Based on pathogenicity testing, morphological characteristics, and molecular identification, the pathogen of sisal causing black spot was identified as N. dimidiatum (Penz.) Crous & Slippers (Crous et al. 2006). To our knowledge, this is the first report of black spot caused by N. dimidiatum on sisal in China. Sisal is the main economic crop in arid and semi-arid areas that is widely planted in several provinces of southern China. The serious occurrence of the disease caused by N. dimidiatum has greatly affected the development of sisal industry and local economic income in China. Identification of the pathogen of the disease is of great significance to guide disease control, increase farmers' income and promote the development of sisal industry. References: Aveskamp, M. M., et al. 2009. Mycologia, 101: 363. https://doi.org/10.3852/08-199. Carbone, I., and Kohn, L. M. 1999. Mycologia, 91:553. https://doi.org/10.1080/00275514.1999. 12061051. Crous, P. W., et al. 2006. Stud. Mycol. 55:235. https://doi.org/10.3114/sim.55.1.235. White, T. J., et al. 1990. PCR Protocols: A Guide to Methods and Applications. Academic Press, San Diego, Page 315. doi.org/10.1002/mrd.1080280418. Supplemental photographs: Fig. 1 Symptoms of sisal black spot disease a, b, c, d showed symptoms in the field, e and f were symptoms after inoculating Neoscytalidium dimidiatum JMHB1. a, c, and e were the front of the lesions, b, d, and f were the back of the lesions. Fig. 2 Primary colony (a) and old colony (b) of Neoscytalidium dimidiatum JMHB1 Fig. 3 Arthrospores (a), conidia and chlamydospores (b) of Neoscytalidium dimidiatum JMHB1.

The Effect of Host Immunity on Predicting the Mortality of Carbapenem-Resistant Organism Infection

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.

Diagnostic Accuracy of T-SPOT.TB Assay for Tuberculous Meningitis: An Updated Meta-Analysis

Background: The role of T-SPOT.TB (T-SPOT) assay for tuberculous meningitis (TBM) diagnosis has not been fully assessed. Here, we conducted an updated meta-analysis to evaluate the diagnostic accuracy of peripheral blood (PB) T-SPOT and cerebrospinal fluid (CSF) T-SPOT for diagnosing TBM. Methods: Relevant studies in the PubMed database, EmBase database, Cochrane database, Scopus database, Google Scholar, China National Knowledge Internet, and Wan-Fang database were retrieved from August 1, 2005, to June 22, 2020. Statistical analysis was performed using Stata, Revman, and Meta-Disc software. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), summary receiver operating characteristic curves, and the area under the curve were determined and analyzed. Results: A total of 27 studies were eligible for inclusion within the meta-analysis. The pooled sensitivity and specificity of PB T-SPOT for TBM diagnosis were 0.78 (95% CI, 0.76-0.81) and 0.68 (95% CI, 0.66-0.71), respectively, whereas the pooled PLR, NLR, and DOR were 2.80 (95% CI, 2.29-3.42), 0.32 (95% CI, 0.27-0.38), and 10.08 (95% CI, 7.21-14.08), respectively. On the other hand, the pooled sensitivity and specificity of CSF T-SPOT on diagnosing TBM were 0.76 (95% CI, 0.72-0.80) and 0.88 (95% CI, 0.85-0.90), respectively, whereas the pooled PLR, NLR, and DOR were 5.92 (95% CI, 4.25-8.25), 0.28 (95% CI, 0.21-0.39), and 29.05 (95% CI, 16.40-51.45), respectively. The area under the summary receiver operating characteristic curve values of PB T-SPOT and CSF T-SPOT for TBM diagnosis were 0.83 (95% CI, 0.80-0.86) and 0.92 (95% CI, 0.89-0.94), respectively. Conclusions: CSF T-SPOT showed a higher specificity compared with PB T-SPOT for diagnosing TBM. Both two T-SPOT assays have considerable potential in improving the diagnosis of TBM. Furthermore, the standardization of the operating procedure is further needed when performing CSF T-SPOT.

Prediction Model Based on the Combination of Cytokines and Lymphocyte Subsets for Prognosis of SARS-CoV-2 Infection

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.

Prealbumin as a Predictor of Prognosis in Patients With Coronavirus Disease 2019

Background: The predictive value of prealbumin for the prognosis of coronavirus disease 2019 (COVID-19) has not been extensively investigated.

Methods: A total of 1,115 patients with laboratory-confirmed COVID-19 were enrolled at Tongji hospital from February to April 2020 and classified into fatal (n = 129) and recovered (n = 986) groups according to the patient's outcome. Prealbumin and other routine laboratory indicators were measured simultaneously.

Results: The level of prealbumin on admission was significantly lower in fatal patients than in recovered patients. For predicting the prognosis of COVID-19, the performance of prealbumin was better than most routine laboratory indicators, such as albumin, lymphocyte count, neutrophil count, hypersensitive C-reactive protein, d-dimer, lactate dehydrogenase, creatinine, and hypersensitive cardiac troponin I. When a threshold of 126 mg/L was used to discriminate between fatal and recovered patients, the sensitivity and specificity of prealbumin were, respectively, 78.29 and 90.06%. Furthermore, a model based on the combination of nine indexes showed an improved performance in predicting the death of patients with COVID-19. Using a cut-off value of 0.19, the prediction model was able to distinguish between fatal and recovered individuals with a sensitivity of 86.82% and a specificity of 90.37%.

Conclusions: A lower level of prealbumin on admission may indicate a worse outcome of COVID-19. Immune and nutritional status may be vital factors for predicting disease progression in the early stage of COVID-19.

A combination of iron metabolism indexes and tuberculosis-specific antigen/phytohemagglutinin ratio for distinguishing active tuberculosis from latent tuberculosis infection

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.

The laboratory tests and host immunity of COVID-19 patients with different severity of illness

BACKGROUNDThe 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.METHODSThe routine laboratory tests and host immunity in COVID-19 patients with different severity of illness were compared after patient admission.RESULTSA 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.CONCLUSIONThe 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.FUNDINGThis 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).

Using IL-2R/lymphocytes for predicting the clinical progression of patients with COVID-19

Effective laboratory markers for the estimation of disease severity and predicting the clinical progression of coronavirus disease-2019 (COVID-19) is urgently needed. Laboratory tests, including blood routine, cytokine profiles and infection markers, were collected from 389 confirmed COVID-19 patients. The included patients were classified into mild (n = 168), severe (n = 169) and critical groups (n = 52). The leukocytes, neutrophils, infection biomarkers [such as C-reactive protein (CRP), procalcitonin (PCT) and ferritin] and the concentrations of cytokines [interleukin (IL)-2R, IL-6, IL-8, IL-10 and tumor necrosis factor (TNF)-α] were significantly increased, while lymphocytes were significantly decreased with increased severity of illness. The amount of IL-2R was positively correlated with the other cytokines and negatively correlated with lymphocyte number. The ratio of IL-2R to lymphocytes was found to be remarkably increased in severe and critical patients. IL-2R/lymphocytes were superior compared with other markers for the identification of COVID-19 with critical illness, not only from mild but also from severe illness. Moreover, the cytokine profiles and IL-2R/lymphocytes were significantly decreased in recovered patients, but further increased in disease-deteriorated patients, which might be correlated with the outcome of COVID-19. Lymphopenia and increased levels of cytokines were closely associated with disease severity. The IL-2R/lymphocyte was a prominent biomarker for early identification of severe COVID-19 and predicting the clinical progression of the disease.