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Abstract Background Immune checkpoint inhibitors, such as anti-programmed cell death-1 (PD-1) and PD-1 ligand-1 (PD-L1) antibodies, have achieved breakthrough results in improving long-term survival rates in lung cancer. Although high levels of PD-L1 expression and tumor mutational burden have emerged as pivotal biomarkers, not all patients derive lasting benefits, and resistance to immune checkpoint blockade remains a prevalent issue. Comprehending the immunological intricacies of lung cancer is crucial for uncovering the mechanisms that govern responses and resistance to immunomodulatory treatments. This study aimed to explore the potential of peripheral immune markers in predicting treatment efficiency among lung cancer patients undergoing PD-1/PD-L1 checkpoint inhibitors. Methods This study enrolled 71 lung cancer patients undergoing PD-1/PD-L1 inhibitor therapy and 20 healthy controls. Immune cell subsets (CD4 + T cells, CD8 + T cells, B cells, NK cells, and NKT cells), phenotypic analysis of T cells and B cells, and PMA/Ionomycin-stimulated lymphocyte function assay were conducted. Results Lung cancer patients exhibited significant alterations in immune cell subsets, notably an increased percentage of Treg cells. Post-treatment, there were substantial increases in absolute numbers of CD3 + T cells, CD8 + T cells, and NKT cells, along with heightened HLA-DR expression on CD3 + T and CD8 + T cells. Comparison between complete remission and non-complete remission (NCR) groups showed higher Treg cell percentages and HLA-DR + CD4 + T cells in the NCR group. Conclusion The study findings suggest potential predictive roles for immune cell subsets and phenotypes, particularly Treg cells, HLA-DR + CD4 + T cells, and naïve CD4 + T cells, in evaluating short-term PD-1/PD-L1 therapy efficacy for lung cancer patients. These insights offer valuable prospects for personalized treatment strategies and underscore the importance of immune profiling in lung cancer immunotherapy.

BackgroundHepatocellular carcinoma (HCC) poses a significant global health challenge due to its poor prognosis and limited therapeutic modalities. Anoikis and ErbB signaling pathways are pivotal in cancer cell proliferation and metastasis, but their relevance in HCC remains insufficiently explored.MethodsThis study evaluates the prognostic significance of anoikis and ErbB signaling pathways in HCC by utilizing data from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), three additional independent validation cohorts, and an in-house cohort. Advanced bioinformatics analyses and 167 machine learning models based on leave-one-out cross-validation (LOOCV) were used to predict HCC prognosis and assess outcomes of immune-targeted therapies. Additionally, key biological processes of the anoikis and ErbB signaling pathways in HCC were further investigated.ResultsThe single sample Gene Set Enrichment Analysis revealed a strong correlation between upregulated ErbB signaling in high anoikis-expressing tumors and poor clinical outcomes. The development of the Anoikis-ErbB Related Signature (AERS) using the LASSO + RSF model demonstrated robust predictive capabilities, as validated across multiple patient cohorts, and proved effective in predicting responses to immune-targeted therapies. Further investigation highlighted activated NOTCH signaling pathways and decreased macrophage infiltration was associated with resistance to sorafenib and immune checkpoint inhibitors, as evidenced by bulk and single-cell RNA sequencing (scRNA-seq).ConclusionAERS provides a novel tool for clinical prognosis and paves the way for immune-targeted therapeutic approaches, underscoring the potential of integrated molecular profiling in enhancing treatment strategies for HCC.

BackgroundRadiotherapy (RT) is a critical component of treatment for locally advanced rectal cancer (LARC), though patient response varies significantly. The variability in treatment outcomes is partly due to the resistance conferred by cancer stem cells (CSCs) and tumor immune microenvironment (TiME). This study investigates the role of EIF5A in radiotherapy response and its impact on the CSCs and TiME.MethodsPredictive models for preoperative radiotherapy (preRT) response were developed using machine learning, identifying EIF5A as a key gene associated with radioresistance. EIF5A expression was analyzed via bulk RNA-seq and single-cell RNA-seq (scRNA-seq). Functional assays and in vivo experiments validated EIF5A’s role in radioresistance and TiME modulation.ResultsEIF5A was significantly upregulated in radioresistant colorectal cancer (CRC) tissues. EIF5A knockdown in CRC cell lines reduced cell viability, migration, and invasion after radiation, and increased radiation-induced apoptosis. Mechanistically, EIF5A promoted cancer stem cell (CSC) characteristics through the Hedgehog signaling pathway. Analysis of the TiME revealed that the radiation-resistant group had an immune-desert phenotype, characterized by low immune cell infiltration. In vivo experiments showed that EIF5A knockdown led to increased infiltration of CD8+ T cells and M1 macrophages, and decreased M2 macrophages and Tregs following radiation therapy, thereby enhancing the radiotherapy response.ConclusionEIF5A contributes to CRC radioresistance by promoting CSC traits via the Hedgehog pathway and modulating the TiME to an immune-suppressive state. Targeting EIF5A could enhance radiation sensitivity and improve immune responses, offering a potential therapeutic strategy to optimize radiotherapy outcomes in CRC patients.

BackgroundTransarterial chemo(embolization) is preferred for treating unresectable hepatocellular carcinoma (uHCC); however, because of emerging immune-targeted therapies, its efficacy is at stake. This systematic review pioneers to evaluate the clinical efficacy and safety of transarterial chemo(embolization) combined with immune-targeted therapy for uHCC patients.MethodsPubMed, Embase, and Cochrane Library were searched for studies comparing immune-targeted therapy with or without transarterial chemo(embolization) until 31 May 2024. The complete response (CR) rate, objective response rate (ORR), and disease control rate (DCR) were considered to be the primary outcomes calculated for the clinical outcomes of transarterial chemo(embolization) combined with immune-targeted therapy, along with progression-free survival (PFS) and overall survival (OS). The incidence of treatment-related severe adverse events was set as the major measure for the safety outcome.ResultsSixteen studies, encompassing 1,789 patients receiving transarterial chemo(embolization) plus immune-targeted therapy and 1,215 patients receiving immune-targeted therapy alone, were considered eligible. The combination of transarterial chemo(embolization) and immune-targeted therapy demonstrated enhanced outcomes in CR (OR = 2.12, 95% CI = 1.35–3.31), ORR (OR = 2.78, 95% CI = 2.15–3.61), DCR (OR = 2.46, 95% CI = 1.72–3.52), PFS (HR = 0.59, 95% CI = 0.50–0.70), and OS (HR = 0.51, 95% CI = 0.44–0.59), albeit accompanied by a surge in ALT (OR = 2.17, 95% CI = 1.28–3.68) and AST (OR = 2.28, 95% CI = 1.42–3.65). The advantages of additional transarterial chemo(embolization) to immune-targeted therapy were also verified in subgroups of first-line treatment, intervention techniques, with or without extrahepatic metastasis, Child–Pugh grade A or B, and with or without tumor thrombus.ConclusionThe combination of transarterial chemo(embolization) and immune-targeted therapy seems to bolster local control and long-term efficacy in uHCC, albeit at the expense of hepatic complications.Systematic review registrationhttp://www.crd.york.ac.uk/PROSPERO/, identifier 474669.

ABSTRACTHost immune dysfunction plays a crucial role in the onset, progression, and outcome of hemophagocytic lymphohistiocytosis (HLH). This study aimed to comprehensively evaluate the peripheral immune profiles in patients with newly diagnosed secondary hemophagocytic lymphohistiocytosis (sHLH), and explore their predictive value for patient prognosis. A total of 77 patients with sHLH were enrolled in this study, with 31 of them experiencing mortality. Flow cytometry was used to assess the percentages, absolute numbers, and phenotypes of lymphocyte subsets. Simultaneously, cytokine levels and routine laboratory indicators were also collected. In sHLH patients, lymphocyte subset absolute numbers were significantly impaired, accompanied by T cell hyperactivation, B cell hyperactivation, and increased plasmablast proliferation. Prognostic analysis revealed that lower CD8+ T cell percentages, elevated APTT, IL-6, IL-10 levels, and increased CD4+CD28null T cell proportions were associated with poor patient outcomes. The study demonstrates dysregulation in the counts and phenotypes of lymphocyte subsets in sHLH patients. Several key factors, including IL-6, IL-10, APTT, and various T cell percentages, have potential as prognostic markers and therapeutic targets in sHLH.

Objective: The purpose of this study was to determine the analgesic effect of a flurbiprofen ester injection via continuous intravenous drip during transvaginal 4-dimensional hysterosalpingography (TVS 4D-HyCoSy). Methods: Two hundred thirty patients who underwent TVS 4D-HyCoSy for infertility from May 2018 to August 2021 at our hospital were selected. The participants were grouped based on tubal patency, flurbiprofen ester use, and uterine cannula diameter, as follows: bilateral tubal patency group; non-bilateral tubal patency group; atropine group; atropine + flurbiprofen ester group; coarse tube group; and fine tube group. The analgesic effect during TVS 4D-HyCoSy and pain relief were compared between groups using visual analog scoring (NRS). Additionally, the incidence of adverse effects was recorded and factors related to the influence of pain were analyzed. Results: 1. Tubal patency reduced pain during ultrasound tubal examination, flurbiprofenate provided significant analgesia after ultrasound tubalography and reduced adverse effects (P < 0.001). 2. The tube diameter thickness had no effect on tubal ultrasonography procedure-related pain. 3. Multivariable analysis of pain relief during imaging suggested that the use of flurbiprofen for bilateral tubal patency had a significant positive effect on pain relief within 30 min after the examination with an AUC of 0.732 (95% CI: 0.665–0.798). Conclusion: A flurbiprofen ester continuous intravenous drip had a good analgesic effect in patients with TVS 4D-HyCoSy. Specifically, the pain relief effect after examination was significant and reduced the incidence of adverse reactions during the contrast examination. Flurbiprofen ester can be administered independently and is worthy of clinical promotion and application.

In order to achieve impact load localization of complex structures such as ships, this paper proposes a multi-scale feature fusion convolutional neural network (MSFF-CNN) method for impact load localization. An end-to-end machine learning model is used, where the raw vibration signals of impact loads are directly fed into the network model to avoid the process of feature extraction. Automatic feature learning and feature concatenation of the signal are achieved through four independent convolutional layers, each using a different size of convolutional kernel. Data normalization and L2 regularization techniques are introduced to enhance the data and prevent overfitting. Classification and localization of impact loads are accomplished using a softmax classification layer. Validation experiments are carried out using a ship’s stern compartment model. Our results show that the classification and localization accuracy of the impact load sample group of MSFF-CNN reaches 94.29% compared with a traditional CNN. The method further improves the ability of the network to extract state features, takes local perception and global vision into account, effectively improves the classification ability of the model, and has good prospects for engineering applications.

In addressing the challenging issue of impact source localization for large-scale anisotropic stiffened compartmental cylindrical shell structures, this paper presents a novel impact localization method. The method is based on a time-reversal virtual focusing triangulation approach and does not rely on prior knowledge of the structure or specific measurements of wave velocity. By employing energy power filtering to select key sensors, wavelet packet decomposition is utilized to extract narrowband Lamb wave signals, which are then synthesized. Further enhancement of signal recognition is achieved through time-reversal amplification techniques. Experimental results demonstrate that under non-motorized operating conditions, this method achieves an average error of 0.89 m. Under motorized operating conditions, the average error is 1.12 m. Although the presence of background noise leads to an increase in error, the overall localization performance is superior to traditional triangulation methods. Additionally, selecting the top three sensors in terms of energy power ranking can more accurately record impact response.

Objective Systemic autoimmune rheumatic diseases (SARDs) encompass a diverse group of complex conditions with overlapping clinical features, making accurate diagnosis challenging. This study aims to develop a multiclass machine learning (ML) model for early-stage SARDs classification using accessible laboratory indicators.Methods A total of 925 SARDs patients were included, categorised into SLE, Sjögren’s syndrome (SS) and inflammatory myositis (IM). Clinical characteristics and laboratory markers were collected and nine key indicators, including anti-dsDNA, anti-SS-A60, anti-Sm/nRNP, antichromatin, anti-dsDNA (indirect immunofluorescence assay), haemoglobin (Hb), platelet, neutrophil percentage and cytoplasmic patterns (AC-19, AC-20), were selected for model building. Various ML algorithms were used to construct a tripartite classification ML model.Results Patients were divided into two cohorts, cohort 1 was used to construct a tripartite classification model. Among models assessed, the random forest (RF) model demonstrated superior performance in distinguishing SLE, IM and SS (with area under curve=0.953, 0.903 and 0.836; accuracy= 0.892, 0.869 and 0.857; sensitivity= 0.890, 0.868 and 0.795; specificity= 0.910, 0.836 and 0.748; positive predictive value=0.922, 0.727 and 0.663; and negative predictive value= 0.854, 0.915 and 0.879). The RF model excelled in classifying SLE (precision=0.930, recall=0.985, F1 score=0.957). For IM and SS, RF model outcomes were (precision=0.793, 0.950; recall=0.920, 0.679; F1 score=0.852, 0.792). Cohort 2 served as an external validation set, achieving an overall accuracy of 87.3%. Individual classification performances for SLE, SS and IM were excellent, with precision, recall and F1 scores specified. SHAP analysis highlighted significant contributions from antibody profiles.Conclusion This pioneering multiclass ML model, using basic laboratory indicators, enhances clinical feasibility and demonstrates promising potential for SARDs classification. The collaboration of clinical expertise and ML offers a nuanced approach to SARDs classification, with potential for enhanced patient care.

Background: This study aimed to assess the diagnostic value of Krebs von den Lungen-6 (KL-6), Surfactant protein-A (SP-A), SP-D and molecular matrixmetalloproteinase-7 (MMP-7) in discriminating patients with interstitial lung diseases (ILDs) from disease control subjects. Methods: Serum levels of KL-6, SP-A, SP-D and MMP-7 were measured in both the ILD and non-ILD (NILD) groups. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic potential of these markers and laboratory indices. High-resolution computed tomography (HRCT) fibrosis scores were determined, and their correlation with the serum markers was analyzed. Results: Serum levels of KL-6 and MMP-7 were significantly elevated in the ILD group compared to the control group, while no significant differences were observed for SP-A and SP-D. ROC analysis of KL-6 demonstrated superior diagnostic accuracy, with a sensitivity of 76.36%, specificity of 91.07%, and an area under curve (AUC) of 0.902 (95%CI 0.866–0.945). These findings were consistent across an additional cohort. Correlation analysis revealed a link between KL-6 levels at initial diagnosis and HRCT fibrosis scores, indicating disease severity. Moreover, a negative correlation was found between KL-6 and pulmonary function indices, reflecting disease progression. Patients with increased 12-month HRCT fibrosis score showed higher lactate dehydrogenase (LDH) levels, with LDH exhibiting an AUC of 0.767 (95% CI: 0.520–0.927) as a predictor of progression. Conclusions: Serum KL-6 detection proves to be a valuable tool for accurately distinguishing ILDs from control subjects. While KL-6 shows a correlation with HRCT fibrosis scores and a negative association with pulmonary function indices, its predictive value for ILDs prognosis is limited. Trial registration: This study received retrospective approval from the Ethical Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (institutional review board ID: TJ-IRB20210331, date: 2021.03.30).

In order to comprehensively evaluate and analyze the effectiveness of various heuristic intelligent optimization algorithms, this research employed particle swarm optimization, wind driven optimization, grey wolf optimization, and one-to-one-based optimizer as the basis. It applied 22 benchmark test functions to conduct a comparison and analysis of performance for these algorithms, considering descriptive statistics such as convergence speed, accuracy, and stability. Additionally, time and space complexity calculations were employed, alongside the nonparametric Friedman test, to further assess the algorithms. Furthermore, an investigation into the impact of control parameters on the algorithms’ output was conducted to compare and analyze the test results under different algorithms. The experimental findings demonstrate the efficacy of the aforementioned approaches in comprehensively analyzing and comparing the performance on different types of intelligent optimization algorithms. These results illustrate that algorithm performance can vary across different test functions. The one-to-one-based optimizer algorithm exhibited superior accuracy, stability, and relatively lower complexity.

BackgroundThe accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the key to control Coronavirus Disease-2019 (COVID-19). The performance of different antibody detection methods for diagnosis of COVID-19 is inconclusive.MethodsBetween 16 February and 28 February 2020, 384 confirmed COVID-19 patients and 142 healthy controls were recruited. 24 different serological tests, including 4 enzyme-linked immunosorbent assays (EIAs), 10 chemiluminescent immunoassays (CLIAs), and 10 lateral flow immunoassays (LFIAs), were simultaneously performed.ResultsThe sensitivities of anti-SARS-CoV-2 IgG and IgM antibodies with different reagents ranged from 75 to 95.83% and 46.09 to 92.45%, respectively. The specificities of both anti-SARS-CoV-2 IgG and IgM were relatively high and comparable among different reagents, ranged from 88.03 to 100%. The area under the curves (AUCs) of different tests ranged from 0.733 to 0.984, and the AUCs of EIAs or CLIAs were significantly higher than those of LFIAs. The sensitivities of both IgG and IgM gradually increased with increase of onset time. After 3–4 weeks, the sensitivities of anti-SARS-CoV-2 IgG were maintained at a certain level but the sensitivities of IgM were gradually decreased. Six COVID-19 patients who displayed negative anti-SARS-CoV-2 results were associated with the factors such as older age, having underlying diseases, and using immunosuppressant.ConclusionBesides the purpose of assessing the impact of the SARS-CoV-2 pandemic in the population, SARS-CoV-2 antibody assays may have an adjunct role in the diagnosis and exclusion of COVID-19, especially by using high-throughput technologies (EIAs or CLIAs).

Abstract Background This study aimed to analyze the lymphocyte subsets, their activities and their dynamic changes during immunochemotherapy in patients newly diagnosed with diffuse large B cell lymphoma (DLBCL). Methods Patients with DLBCL (n = 33) were included in the present study. Their peripheral lymphocyte subsets, phenotypes and functions were detected using flow cytometry. The dynamic results of lymphocyte activities were available for 18 patients. Results Compared with healthy controls (HCs), the counts of CD3+, CD4+, and CD8+ T cells as well as those NK cells decreased in patients newly diagnosed with DLBCL, mainly attributed to patients with high risk of prognosis assessed by International Prognostic Index (IPI) score. Lymphocyte counts didn’t present significant difference between high risk (IPI scores 3–5) and low risk patients (IPI scores 0–2), but CD4+ T cells and CD8+ T cells expressed higher levels of CD28 and HLA-DR, respectively, in patients with IPI score ranging from 3 to 5. Patients at high risk harbored higher percentage of regulatory T cells (Tregs), and their CD4+ and CD8+ T cells produced lower levels of IFN-γ, reflecting an impaired cellular immune response. The dynamic changes of lymphocyte numbers and functions during treatment were further investigated. Total counts of CD3+, CD4+, CD8+ T and NK cells progressively decreased because of the cytotoxicity of chemotherapy and then gradually recovered after six cycles treatment (rituximab combined with cyclophosphamide, doxorubicin, vincristine and prednisone, R-CHOP). The functions of CD4+ and CD8+ T cells recovered by the end of two cycles R-CHOP treatment, although NK cell function was not significantly affected throughout treatment. These results suggest that the counts and functions of lymphocytes are significantly decreased in patients with DLBCL, particularly those of CD4+ and CD8+ T cells. Conclusions The absolute counts and functions of CD4+, CD8+ T cells, which were significantly lower in patients with DLBCL, gradually recovered after effective treatment. Therefore, combined detection of T cell counts and functions are critically important for administering effective personalized immunotherapy as well as for identifying new prognostic markers or DLBCL.

BackgroundOvertreatment of axillary lymph node dissection (ALND) may occur in patients with axillary positive sentinel lymph node (SLN) but negative non-SLN (NSLN). Developing a magnetic resonance imaging (MRI)-based radiomics nomogram to predict axillary NSLN metastasis in patients with SLN-positive breast cancer could effectively decrease the probability of overtreatment and optimize a personalized axillary surgical strategy.MethodsThis retrospective study included 285 patients with positive SLN breast cancer. Fifty five of them had metastatic NSLNs and 230 had non-metastatic NSLNs. MRI-based radiomic features of primary tumors were extracted and MRI morphologic findings of the primary tumor and axillary lymph nodes were assessed. Four models, namely, a radiomics signature, an MRI-clinical nomogram, and two MRI-clinical-radiomics nomograms were established based on MRI morphologic findings, clinicopathologic characteristics, and MRI-based radiomic features to predict the NSLN status. The optimal predictors in each model were selected using the 5-fold cross-validation (CV) method. Their predictive performances were determined by the receiver operating characteristic (ROC) curves analysis. The area under the curves (AUCs) of different models was compared by the Delong test. Their discrimination capability, calibration curve, and clinical usefulness were also assessed.ResultsThe 5-fold CV analysis showed that the AUCs ranged from 0.770 to 0.847 for the radiomics signature, from 0.720 to 0.824 for the MRI-clinical nomogram, from 0.843 to 0.932 for the MRI-clinical-radiomics nomogram. The optimal predictive factors in the radiomics signature, MRI-clinical nomogram, and MRI-clinical-radiomics nomogram were one texture feature of diffusion-weighted imaging (DWI), two clinicopathologic features together with one MRI morphologic finding, and the DWI-based texture feature together with the two clinicopathologic features plus the one MRI morphologic finding, respectively. The MRI-clinical-radiomics nomogram with CA 15-3 included achieved the highest AUC compared with the radiomics signature (0.868 vs. 0.806, P

Background: Early and accurate diagnosis of tuberculous pleurisy (TP) remains a challenge. The aim of the present study is to evaluate the performance of the pleural fluid (PF) T-SPOT and interferon-gamma (IFN-γ) for TP diagnosis in high tuberculosis (TB) burden settings. Methods: In total, 214 and 217 subjects suspected of TP were prospectively enrolled in the Wuhan (training) cohort and Changchun (validation) cohort, respectively. All patients were examined with PF T-SPOT, IFN-γ, and other traditional tests simultaneously. Results: The receiver-operating characteristic (ROC) curve analysis showed that the area under the curve (AUC), sensitivity, and specificity of TB-specific antigen (TBAg) spot-forming cells (SFC) (the larger of early secreted antigenic target 6 and culture filtrate protein 10 SFC in PF T-SPOT assay) for TP diagnosis were 0.972, 92.86%, and 92.16%, respectively, with a cutoff value of 35 in the Wuhan cohort. Meanwhile, when a threshold value of 95 ng/mL was set, the AUC, sensitivity, and specificity of IFN-γ to diagnose TP were 0.951, 86.61%, and 90.20%, respectively. Moreover, the diagnostic model based on the combination of TBAg SFC and IFN-γ showed an AUC of 0.983 for differentiating TP from non-TP, with 95.54% sensitivity and 95.10% specificity when a cutoff value of 0.32 was used in the Wuhan cohort. Excellent diagnostic accuracy was also observed in the Changchun cohort. When applying the cutoff value obtained from the Wuhan cohort, the AUC, sensitivity, and specificity of the diagnostic model were 0.995, 95.08%, and 97.89%, respectively. Conclusions: The performance of PF T-SPOT was comparable to IFN-γ in diagnosing TP. However, using the diagnostic model established by the combination of these two assays can achieve a more accurate diagnosis of TP.

This paper presents a compact circularly polarized microstrip antenna for radio frequency identification (RFID) readers. The dimensions of the proposed antenna are reduced by etching a cross slot in the radiation patch and loading four grounded coupling patches on the four corners of the radiation patch. An inverted Z-shaped coupling feedline is used to realize circularly polarized operation. The measured -10 dB |S11| bandwidth, 3-dB axial ratio bandwidth and maximum gain are 872-1095 MHz, 888-933 MHz, and 5.52 dBi, respectively, at 922 MHz frequency. The overall dimension of the proposed antenna is 0.36 λgX 0.36 λgX 0.05 λg (λg is the guide wavelength at the center frequency of 915 MHz). The proposed antenna has small size with good overall performance and is suitable for compact RFID devices.

BackgroundThis study aimed to assess the host immune signatures associated with EBV infection and its clinical value in indicating the severity of children with acute infectious mononucleosis (IM).MethodsTwenty-eight pediatric patients with IM aged 3–8 years were enrolled. The immune phenotypes and cytokine secretion capability of T cells were detected.ResultsThe percentages and absolute numbers of CD3+ and CD8+ T cells were significantly increased in IM patients compared with HCs. The percentages of Naïve CD4+ and CD8+ T cells were decreased but with increased percentages of memory CD4+ and CD8+ T subsets. Our results showed the upregulation of active marker HLA-DR, TCR-αβ, and inhibitory receptors PD-1, TIGIT in CD8+ T cells from IM patients, which suggested that effective cytotoxic T cells were highly against EBV infection. However, EBV exposure impaired the cytokine (IFN-γ, IL-2, and TNF-α) secretion capability of CD4+ and CD8+ T cells after stimulation with PMA/ionomycin in vitro. Multivariate analysis revealed that the percentage of HLA-DR+ CD8+ T cells was an independent prognostic marker for IM. The percentage of HLA-DR+ CD8+ T cells was significantly correlated with high viral load and abnormal liver function results.ConclusionRobust expansion and upregulation of HLA-DR in CD8+ T cells, accompanied with impaired cytokine secretion, were typical characteristics of children with acute IM. The percentage of HLA-DR+ CD8+ T cells might be used as a prominent marker not only for the early diagnosis but also for indicating the severity of IM.

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.

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.

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.

A compact low-profile square ring antenna with unidirectional radiation and dual circular polarization (CP) is proposed for uses in radio frequency identification (RFID) readers. A small size conducting plane are slotted and placed underneath the ring antenna as a reflector to achieve low profile and unidirectional radiation. A branch line coupler is meandered inside the ring radiator to save space and generate dual circular polarization. Four inverted L-shaped strips are introduced to overcome the negative effects of tight coupling between the radiator and reflector. The measured -10 dB impedance bandwidth of |S11|, 3 dB axial ratio (AR) bandwidth and maximum gain are of 850-1060 MHz, 876-1084 MHz and 5.62dBi, respectively. The lowest measured gain values in RFID band of 900-930 MHz is 4.54dBi and the overall size is 0.31 λ0 ×0.31 λ0 ×0.034 λ0 (λ0 is denoted the wavelength at center frequency). The proposed antenna has not only the lowest profile but also the best overall performances. It is an excellent antenna that can be fitted where there is a limited space in RFID system.

BackgroundPneumocystis 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.MethodsPatients 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.ResultsA 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).ConclusionsA 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.

BackgroundInadequate 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.MethodsA 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.ResultsSignificantly 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.ConclusionsLymphocyte 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.

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.

Abstract Objectives This study aimed to determine the IgM and IgG responses against severe acute respiratory syndrome coronavirus (SARS‐CoV)‐2 in coronavirus disease 2019 (COVID‐19) patients with varying illness severities. Methods IgM and IgG antibody levels were assessed via chemiluminescence immunoassay in 338 COVID‐19 patients. Results IgM levels increased during the first week after SARS‐CoV‐2 infection, peaked 2 weeks and then reduced to near‐background levels in most patients. IgG was detectable after 1 week and was maintained at a high level for a long period. The positive rates of IgM and/or IgG antibody detections were not significantly different among the mild, severe and critical disease groups. Severe and critical cases had higher IgM levels than mild cases, whereas the IgG level in critical cases was lower than those in both mild and severe cases. This might be because of the high disease activity and/or a compromised immune response in critical cases. The IgM antibody levels were slightly higher in deceased patients than recovered patients, but IgG levels in these groups did not significantly differ. A longitudinal detection of antibodies revealed that IgM levels decreased rapidly in recovered patients, whereas in deceased cases, either IgM levels remained high or both IgM and IgG were undetectable during the disease course. Conclusion Quantitative detection of IgM and IgG antibodies against SARS‐CoV‐2 quantitatively has potential significance for evaluating the severity and prognosis of COVID‐19.

Extrapulmonary tuberculosis (EPTB) has become more common in recent years; however, the diagnosis of EPTB remains a challenge. In this study, we analyzed the performance of the ratio of TB-specific antigen (TBAg) to phytohemagglutinin (PHA) (TBAg/PHA ratio) in T-SPOT.TB (T-SPOT) assay for diagnosis and treatment monitoring of EPTB. Between 2012 and 2017, 734 EPTB patients were diagnosed and recruited from Tongji hospital, and 1,137 suspected EPTB patients who had other diagnoses were recruited as non-EPTB controls. To validate the study, another small group of EPTB patients and non-EPTB controls were recruited from Sino-French New City Branch of Tongji Hospital. The positive rate of peripheral blood T-SPOT in EPTB and non-EPTB were 88.15 and 32.28%. In T-SPOT positive patients, the direct T-SPOT results had limited value in distinguishing these two conditions. A further calculation of the TBAg/PHA ratio of T-SPOT showed improved performance in each form of EPTB. If using 0.20 as the threshold value of the TBAg/PHA ratio, the pooled sensitivity and specificity were 70.79 and 91.55% in distinguishing EPTB from non-EPTB. The validation results showed a better performance of the TBAg/PHA ratio in distinguishing these two conditions, with a sensitivity and specificity of 81.82 and 97.56%, respectively. Comparing with directly using T-SPOT results, the TBAg/PHA ratio was less affected by immunosuppression. Furthermore, PHA value reflected immunosuppression and could help to judge the credibility of T-SPOT results in EPTB patients with different immune status. The TBAg/PHA ratio was significantly decreased during anti-tuberculosis (TB) treatment, which suggests that it can also be used to monitor therapeutic efficacy. These data provide new insights into the role of T-SPOT assay in TB disease, and the TBAg/PHA ratio might be a useful tool for diagnosis and treatment monitoring of EPTB.

Sepsis is an exaggerated inflammatory condition response to different microorganisms with high mortality rates and extremely poor prognosis. Natural killer (NK) cells have been reported to be the major producers of IFN-γ and key players in promoting systematic inflammation in lipopolysaccharide (LPS)-induced endotoxic shock. T-cell immunoglobulin and mucin domain (Tim)-3 pathway has been demonstrated to play an important role in the process of sepsis, however, the effect of Tim-3 on NK cell function remains largely unknown. In this study, we observed a dynamic inverse correlation between Tim-3 expression and IFN-γ production in NK cells from LPS-induced septic mice. Blockade of the Tim-3 pathway could increase IFN-γ production and decrease apoptosis of NK cells in vitro, but had no effect on the expression of CD107a. Furthermore, NK cell cytotoxicity against K562 target cells was enhanced after blocking Tim-3 pathway. In conclusion, our results suggest that Tim-3 pathway plays an inhibitory role in NK cell function, which might be a potential target in modulating the excessive inflammatory response of LPS-induced endotoxic shock.

Background: Transarterial chemo(embolization) is preferred for treating unresectable hepatocellular carcinoma (uHCC); however, because of emerging immune-targeted therapies, its efficacy is at stake. This systematic review pioneers to evaluate the clinical efficacy and safety of transarterial chemo (embolization) combined with immune-targeted therapy for uHCC patients. Methods: PubMed, Embase, and Cochrane Library were searched for studies comparing immune-targeted therapy with or without transarterial chemo (embolization) until 31 May 2024. The complete response (CR) rate, objective response rate (ORR), and disease control rate (DCR) were considered to be the primary outcomes calculated for the clinical outcomes of transarterial chemo (embolization) combined with immune-targeted therapy, along with progressionfree survival (PFS) and overall survival (OS). The incidence of treatment-related severe adverse events was set as the major measure for the safety outcome. Results: Sixteen studies, encompassing 1,789 patients receiving transarterial chemo(embolization) plus immune-targeted therapy and 1,215 patients receiving immune-targeted therapy alone, were considered eligible. The combination of transarterial chemo(embolization) and immune-targeted therapy demonstrated enhanced outcomes in CR (OR = 2.12, 95% CI = 1.35-3.31), ORR (OR = 2.78, 95% CI = 2.15-3.61), DCR (OR = 2.46, 95% CI = 1.72-3.52), PFS (HR = 0.59, 95% CI = 0.50-0.70), and OS (HR = 0.51, 95% CI = 0.44-0.59), albeit accompanied by a surge in ALT (OR = 2.17, 95% CI = 1.28-3.68) and AST (OR = 2.28, 95% CI = 1.42-3.65). The advantages of additional transarterial chemo(embolization) to immune-targeted therapy were also verified in subgroups of first-line treatment, intervention techniques, with or without extrahepatic metastasis, Child-Pugh grade A or B, and with or without tumor thrombus. Conclusion: The combination of transarterial chemo(embolization) and immune-targeted therapy seems to bolster local control and long-term efficacy in uHCC, albeit at the expense of hepatic complications. [ABSTRACT FROM AUTHOR]

We aimed to analyze and investigate the clinical factors that influence the occurrence of liver metastasis in locally advanced rectal cancer patients, with an attempt to assist patients in devising the optimal imaging-based follow-up nursing. Between June 2011 and May 2021, patients with rectal cancer at our hospital were retrospectively analyzed. A random survival forest model was developed to predict the probability of liver metastasis and provide a practical risk-based approach to surveillance. The results indicated that age, perineural invasion, and tumor deposit were significant factors associated with the liver metastasis and survival. The liver metastasis risk of the low-risk group was higher at 6-21 months, with a peak occurrence time in the 15th month. The liver metastasis risk of the high-risk group was higher at 0-24 months, with a peak occurrence time in the 8th month. In general, our clinical model could predict liver metastasis in rectal cancer patients. It provides a visualization tool that can aid physicians and nurses in making clinical decisions, by detecting the probability of liver metastasis. [ABSTRACT FROM AUTHOR]