A ß-Galactosidase-Activated Fluorogenic Reporter for the Detection of Gastric Cancer In Vivo and in Urine.

Although gastric cancer (GC) is one of the most frequent malignant tumors in the digestive tract with high morbidity and mortality, it remains a diagnostic dilemma due to its reliance on invasive biopsy or insensitive assays. Herein, we report a fluorescent gastric cancer reporter (FGCR) with activatable near-infrared fluorescence (NIRF) signals and high renal-clearance efficiency for the detection of orthotopic GC in a murine model via real-time imaging and remote urinalysis. In the presence of gastric-tumor-associated ß-galactosidase (ß-Gal), FGCR can be fluorescently activated for in vivo NIRF imaging. Relying on its high renal-clearance efficiency (∼95% ID), it can be rapidly excreted through kidneys to urine for the ultrasensitive detection of tumors with a diameter down to ∼2.1 mm and for assessing the prognosis of oxaliplatin-based chemotherapy. This study not only provides a new approach for noninvasive auxiliary diagnosis and prognosis of GC but also provides guidelines for the development of fluorescence probes for cancer diagnosis.

Tailored Zwitterionic Hemicyanine Reporters for Early Diagnosis and Prognostic Assessment of Acute Renal Failure.

Drug-induced renal failure (DIRF) poses a serious medical complication with high mortality risk. However, early diagnosis or prognosis of DIRF remain challenging, as current methods rely on detecting late-stage biomarkers. Herein we present a library of zwitterionic unimolecular hemicyanines (ZCs) available for constructing activatable reporters to detect DIRF since its initial stage. Zwitterionic properties of these probes are achieved through interspersedly integrating alkyl sulfonates and quaternary ammonium cations onto hemicyanine skeleton, which result in record low plasma protein binding (<5 %) and remarkable renal clearance efficiencies (≈96 %). An activatable reporter ZCRR is further developed by masking the optimal candidate ZC6 with a tetrapeptide specifically cleavable by caspase-8, an initiating indicator of apoptosis. In living mice with cisplatin-induced DIRF, systematically administered ZCRR efficiently accumulates in kidneys and responds to elevated caspase-8 for near-infrared fluorescence signals 'turn-on', enabling sensitive detection of intrarenal apoptosis 60 h earlier than clinical methods, and precise evaluation of apoptosis remediation effects by different medications on DIRF mice. As it's urinary excretable, ZCRR also allows for remote detection of DIRF and predicting renoprotective efficacy through in vitro optical urinalysis. This study thus presents unimolecular renal clearable scaffolds that are applicable to developing versatile activatable reporters for renal diseases management.

Size-Transformable Superoxide-Triggered Nanoreporters for Crosstalk-Free Dual Fluorescence/Chemiluminescence Imaging and Urinalysis in Living Mice.

Chemiluminescence imaging has been recognized as a valuable tool for ultrasensitive detection of physio-pathological events through elimination of background autofluorescence. However, most chemiluminescent nanoprobes suffer from shallow imaging depths and slow clearance from living bodies, which impede their use in clinical settings. We herein report size-transformable nanoreporters (ADN1 and ADN2) that could be activated at disease site by superoxide anion (O2 ⋅- ) to trigger nanostructure disassembly into renal excretable fluorescent fragments as well as chemiluminescence turn-on for crosstalk-free duplex chemo-fluorescence imaging and in vitro urinalysis. In peritonitis mouse model, we demonstrate that the representative nanoreporter ADN1 spontaneously accumulates at the disrupted peritoneum and is cleaved by upregulated O2 ⋅- to initiate depolymerization and result in red chemiluminescence at 620 nm, enabling sensitive detection of peritonitis at least 19 h earlier than gold standard histological assays. Additionally, the incorporation of a near-infrared (NIR) dye into ADN1 results in ADN2 exhibiting intense and red-shifted chemiluminescence at ≈800 nm, which permits early detection of deeply seated diseases such as drug-induced hepatotoxicity. This study thus showcases a modular design strategy that is not only applicable to developing versatile chemiluminescent nanoprobes with switchable pharmacokinetics for early disease diagnosis, but also promising for future clinical translations.

GAPSO-Optimized Fuzzy PID Controller for Electric-Driven Seeding.

To improve the seeding motor control performance of electric-driven seeding (EDS), a genetic particle swarm optimization (GAPSO)-optimized fuzzy PID control strategy for electric-driven seeding was designed. Since the parameters of the fuzzy controller were difficult to determine, two quantization factors were applied to the input of the fuzzy controller, and three scaling factors were introduced into the output of fuzzy controller. Genetic algorithm (GA) and particle swarm optimization (PSO) were combined into GAPSO by a genetic screening method. GAPSO was introduced to optimize the initial values of the two quantization factors, three scaling factors, and three characteristic functions before updating. The simulation results showed that the maximum overshoot of the GAPSO-based fuzzy PID controller system was 0.071%, settling time was 0.408 s, and steady-state error was 3.0693 × 10-5, which indicated the excellent control performance of the proposed strategy. Results of the field experiment showed that the EDS had better performance than the ground wheel chain sprocket seeding (GCSS). With a seeder operating speed of 6km/h, the average qualified index (Iq) was 95.83%, the average multiple index (Imult) was 1.11%, the average missing index (Imiss) was 3.23%, and the average precision index (Ip) was 14.64%. The research results provide a reference for the parameter tuning mode of the fuzzy PID controller for EDS.

Engineering Cyanine- and Hemicyanine-Based Probes for Optical Imaging of Kidney Diseases.

Molecular optical probes play pivotal roles in in vivo imaging of biomarkers associated to kidney diseases. Relying on structural tunability and high fluorescence quantum yields, versatile optical probes have been constructed on cyanine or hemicyanine-based scaffold in recent years. This review summaries the recent progress on the development of optical probes for imaging of kidney diseases, particularly through near-infrared fluorescence, chemiluminescence and photoacoustic imaging modalities. The chemical design and sensing mechanisms are discussed along with applications in the detection of renal cell carcinoma and acute kidney injury. This progress provides insights and directions for the development of next generation kidney-targeted probes and for pushing their further applications in preclinical and clinical research.

Calibration and test of contact parameters for alfalfa stalk at primary florescence based on discrete element method.

In view of the lack of accurate models for discrete element simulation in the current research and development process of forage harvesting and crushing machinery, the contact parameters were calibrated based on Hertz-Mindlin (no slip) contact model by EDEM simulation software with alfalfa stalk at primary florescence as the research object. Based on the angle of repose, the restitution coefficient, static friction coefficient, rolling friction coefficient of alfalfa stalks were determined through the Placket-Burman test, steepest ascent test and Box-Behnken test. The simulation test of the repose angle was carried out with the determined contact parameters. The results showed that the relative error between the simulated repose angle and the physical test repose angle was 0.48%, which indicated that the calibrated contact parameters could truly reflect the physical characteristics of alfalfa stalks at the primary florescence. It provided a reliable model and parameter calibration method for the discrete element simulation in the research and development process of forage machinery, and also provided a reference for the research and optimization design of forage harvesting, crushing and processing machinery.

[Immunophenotypic and Clinical Characteristics of SET-CAN Fusion Gene Positive Acute Leukemia Patients].

OBJECTIVE: To analyze the flow immunophenotype and clinical characteristics of leukemia patients with positive SET-CAN fusion gene. METHODS: A total of 7 newly diagnosed acute leukemia patients with SET-CAN fusion gene admitted to Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology from February 2016 to February 2020 were collected. Multiplex reverse transcriptase-polymerase chain reaction (RT-PCR) was used to detect the expression of SET-CAN fusion gene. The immunophenotype was detected by four-color flow cytometry. The case information of 17 literatures published at home and abroad was extracted for statistical analysis. RESULTS: Among the 7 patients, 2 cases were diagnosed as mixed phenotype acute leukemia (MPAL), 2 cases as acute myeloid leukemia (AML), and 3 cases as T-acute lymphoblastic leukemia (ALL)/lymphoblastic lymphoma (LBL). Leukemia cells in bone marrow specimens of all cases expressed or partially expressed CD34, CD33 and CD7. CD5 and cytoplasmic CD3 were expressed in 5 patients except 2 patients diagnosed with AML. Bone marrow and lymph node specimens were both detected in 2 patients, and the immunophenotypes of the two specimens were not completely consistent, with differences in lineage or maturity related markers. Two patients with MPAL showed differentiated response to treatment. One AML patient gave up treatment, and another AML patient with FLT3-ITD gene mutation had a poor prognosis. All three T-ALL/LBL patients maintained a long duration of remission after induced remission, and one case underwent allogeneic hematopoietic stem cell transplantation. CONCLUSIONS: There are common characteristics of immunophenotype in patients with positive SET-CAN fusion gene. Differential expression of immunophenotype in samples from different parts is observed in some cases. The prognosis of these diseases varies.

Multicolor flow cytometric assessment of Ki67 expression and its diagnostic value in mature B-cell neoplasms.

Background: There is no unified standard data about the sensitivity and specificity regarding flow cytometry analysis of Ki67 expression during lymphoma diagnoses. Objective: This evaluated the efficacy of multicolor flow cytometry (MFC) in an estimate of the proliferative activity of B-cell non-Hodgkin lymphoma by comparing the expression of Ki67 using MFC and immunohistochemicals (IHC). Method: A total of 559 patients with non-Hodgkin B-cell lymphoma were immunophenotyped using sensitive MFC, of which 517 were newly diagnosed and 42 were transformed lymphomas. Test samples include peripheral blood, bone marrow, various body fluids, and tissues. Through MFC multi-marker accurate gating, abnormal mature B lymphocytes with restricted expression of the light chain were screened. Ki67 was added to determine the proliferation index; the positive rate of Ki67 in tumor B cells was evaluated by cell grouping and internal control. For tissue specimens, MFC and IHC analyses were performed simultaneously to assess the Ki67 proliferation index. Results: The positive rate of Ki67 by MFC was correlated with the subtype and aggressiveness of B-cell lymphoma. Ki67 could distinguish indolent lymphomas from aggressive subtypes with a cut-off value of 21.25%, and differentiate transformation from indolent lymphoma with a cut-off value of 7.65%. The expression of Ki67 by MFC (regardless of the type of samples)was highly agreement with the Ki67 proliferative index of tissue samples assessed by pathologic immunohistochemistry. MFC showed a fairly constant negative bias in evaluating tissue or bone marrow samples, compared with IHC. Conclusions: Ki67 is a valuable flow marker that can distinguish between indolent and aggressive types of lymphoma and assess whether indolent lymphomas are transformed. Using MFC to evaluate the positive rate of Ki67 is important in clinical settings. MFC has unique advantages in judging the aggressiveness of lymphoma in samples of bone marrow, peripheral blood, pleural and ascites, and cerebrospinal fluid. This is particularly important when tissue samples cannot be obtained, making it an important supplement for pathologic examination.

Emotion Analysis Model of Microblog Comment Text Based on CNN-BiLSTM.

Aiming at the problems of over reliance on labor and low generalization of traditional emotion analysis methods based on dictionary and machine learning, an emotion analysis model of microblog comment text based on deep learning is proposed. Firstly, text is obtained through microblog crawler program. After data preprocessing, including data cleaning, Chinese word segmentation, removal of stop words, and so on, the Skip-gram model is used for word vector training on a large-scale unmarked corpus, and then the trained word vector is used as the text input of CNN-BiLSTM model, which combines Bidirectional Long-Short Term Memory (BiLSTM) neural network and Convolution Neural Network (CNN). Considering the historical context information and the subsequent context information, BiLSTM can better use the temporal relationship of text to learn sentence semantics. CNN can extract hidden features from the text and combine them. Finally, after Adamax optimization training, the emotion type of microblog comment text is output. The proposed model combines the learning advantages of BiLSTM and CNN. The overall accuracy of text emotion analysis has been greatly improved, with an accuracy of 0.94 and an improvement of 8.51% compared with the single CNN model.

PD-1 combined with TRBC1 and pan-T cell antibodies for robustly monitoring angioimmunoblastic T-cell lymphoma.

Background: The diagnosis of AITL is challenging. It may be delayed or even missed due to critical clinical conditions and its histologic and immunophenotypic overlap with other neoplastic and reactive lymphoid proliferations. Objective: The key objective is to obtain an efficient diagnosis, sensitive disease monitoring and treatment efficacy assessment of AITL using multiparameter flow cytometry (MFC). Methods: In total, 167 de novo AITL patients were immunophenotypically profiled using sensitive MFC. We precisely identified the aberrant T-cell populations of AITL and performed an in-depth description of their phenotypic characteristics in comparison with their residual normal CD4+ T cells. A comparison of Programmed death receptor-1 (PD-1) expression was performed among AITL and other T-cell lymphomas. Results: MFC detected a neoplastic T-cell population in 94.1% (80/85) of tissue, 71.5% (108/151) of bone marrow (BM), 100% (8/8) of peripheral blood (PB) and 78.6% (11/14) of body fluid samples. The most frequent immunophenotypic aberrations included the absence and diminished expression of CD3 (71.25% in tissues, 71.3% in BM, 75% in PB, 81.8% in hydrothorax and ascites specimens), followed by the loss or partial loss of CD7 (71.25% in LN, 67.6% in BM, 50% in PB, 81.8% in hydrothorax and ascites specimens). The immunophenotyping of neoplastic T-cell populations showed a high degree of similarity among different sites of the same patient and they might change over time but were relatively stable. Bright PD-1 expression showed high sensitivity and specificity in differentiating AITL from other T-cell lymphomas. In 14 AITL patients, neoplastic T-cell populations were initially missed by T-cell screening tube but were successfully discovered by bright PD-1 expression. Conclusion: T-cell screening tube can reliably screen neoplastic T-cell populations in AITL patients with typical immunophenotyping, such as loss of surface CD3 and loss of CD7 with a relatively high ratio. Bright PD-1 expression is essential for identifying aberrant T cells in almost all AITLs. The clonality assessment antibody TRBC1 is efficient for robustly and cheaply assessing T-cell clonality. Using PD-1 and TRBC1 combined with pan-T cell antibodies can make a precise diagnosis of AITL and also sensitively monitor minimal residual disease regardless of the antigenic drift of the neoplastic T cells.

Mutations in the BCR-ABL1 kinase domain in patients with chronic myeloid leukaemia treated with TKIs or at diagnosis.

The aim of the present study was to analyse the incidence of mutations in the BCR-ABL1 kinase region in patients with newly diagnosed or treated chronic myeloid leukaemia (CML), and the association between mutations clinicopathological characteristics. Samples were collected for mutation analysis from patients who exhibited tyrosine kinase inhibitor resistance following treatment or were in the accelerated or blast phase at diagnosis. The mutations in the breakpoint cluster region (BCR)-ABL proto-oncogene 1 (ABL1) kinase domain were evaluated using conventional sequencing or ultra-deep sequencing (UDS) of peripheral blood samples. Sanger sequencing and UDS of the cDNA region corresponding to the BCR-ABL1 kinase domain was performed. χ2 test was used to assess the association of categorical variables between the mutated and non-mutated groups. In addition, the Kaplan-Meier method was applied to generate the survival curves. Sequencing detected 28 different mutations in 54 of the 175 (30.86%) patients with CML. A total of 14 (8.0%) patients presented with the T315I mutation, accounting for the largest proportion in the mutated group. Eight patients (4.6%) presented with more than one mutation, three (37.5%) of whom harboured T315I coexisting with other mutations, and for nine (5.1%) patients, the results differed between conventional sequencing and UDS, with the mutations being missed by conventional sequencing. The results form this study suggested that programing mutation analysis in patients with chronic myeloid leukaemia timely may guide the choice of TKIs.

Leukemia cell-derived microvesicles induce T cell exhaustion via miRNA delivery.

T cell function in cancer patients is usually impaired due to the constitutive activation of immune checkpoint inhibitors. This state is known as 'exhaustion' and is often associated with the inefficient control of tumors or persistent infections. In this work, we investigated the role of leukemia cell-derived microvesicles (MVs) in T cell exhaustion. Following incubation with MVs from various sources, all T cell subtypes exhibited the exhaustion phonotype and impaired cytokine secretion in vitro. Mice models also showed the connection between immune checkpoint inhibitors and MV injection. Sequencing and bioinformatics analyses indicated that a number of transcription factors and microRNAs (miRNAs) were attributable to the dysregulation of pathways and exhaustion in T cells. Further work revealed that functional miR-92a-3p, miR-21-5p, miR-16-5p, miR-126 and miR-182-5p in MVs could be delivered into T cells to induce the exhaustion phenotype. SerpinB2, IL-1ß and CXCL5, which are mediators of the NF-κB pathway, were identified as the targets of the miRNAs mentioned above. We demonstrated that leukemia-derived MVs could initiate T cell exhaustion via the progressive temporal delivery of multiple exogenous miRNAs into T cells and the subsequent interaction of these miRNAs with their targets. Therefore, MVs can be expected not only to become new indicators of the T cell status in patients but also to be used as novel targets for personalized patient treatment.

A three-stage wavelength selection algorithm for near-infrared spectroscopy calibration.

The near-infrared spectral data is highly high dimensional and contains redundant information, it is necessary to identify the most representative characteristic wavelengths before modeling to improve model accuracy and reliability. At present, there are many methods for selecting the characteristic wavelengths of NIR spectroscopy, but the collinearity among wavelengths is still a main issue that leads to poor model effects. Therefore, this study proposes a three-stage wavelength selection algorithm (Stage III) to reduce redundancy in NIR spectral data and collinearity between wavelength variables, resulting in a simpler and more accurate predictive model. The research uses a public NIR data set of corn samples as its subject. Initially, the wavelengths with the higher correlation coefficients are chosen after calculating the relationship coefficients between every wavelength vector and the concentration vector. On this basis, the correlation coefficients between the vectors of each wavelength point are calculated, and those wavelength points with smaller correlation coefficients with other wavelength points are selected. Ultimately, the stepwise regression analysis selects the wavelengths that provide substantial value to the model as the variables for modeling, leading to the development of a multiple linear regression model. The results show that the model using the three-stage wavelength selection algorithm outperforms those using the full spectrum, Stages I and Stage II, and the coefficient of determination of the test set of the Stage III-MLR model achieved an accuracy of 0.9360. Instead of the successive projections algorithm (SPA), uninformative variable elimination (UVE), and competitive adaptive reweighted sampling (CARS), Stage III is better in the model prediction accuracy. Therefore, the three-stage wavelength selection algorithm is an effective wavelength selection algorithm that can effectively model NIR spectroscopy, reduce the collinearity between the wavelength variables, simplify the complexity of the model, and improve the prediction precision of the model.