Analysis of cuproptosis-related genes in prognosis and immune infiltration in grade 4 diffuse gliomas.

Background: Grade 4 diffuse gliomas are highly malignant tumours with poor prognosis. Cuproptosis is a novel form of cell death. Cuproptosis genes are associated with various tumours and affect the prognosis of patients with these tumours. However, the relationship between cuproptosis and grade 4 diffuse gliomas remains unclear. Methods: Differentially expressed genes associated with cuproptosis in grade 4 diffuse gliomas were identified. Second, the prognostic model was established by univariate and multivariate COX regression analyses, and the genes (p < 0.05) were selected for subsequent analysis. The endpoint of the study was death. Single-gene analysis was performed in accordance with the expression levels of SLC31A1. Third, based on the expression levels of SLC31A1, gene function enrichment, drug sensitivity, and immune cell infiltration analyses were performed. Finally, the expression and biological functions of SLC31A1 in grade 4 diffuse gliomas were identified using immunohistochemical staining, qRT-PCR, and related biological experiments. Results: We identified six coproptosis genes in the grade 4 diffuse gliomas dataset (SLC31A1, PDHA1, GLS, FDX1, LIPT1, and ATP7B). The six key cuproptosis genes of grade 4 diffuse gliomas were analysed using univariate COX analysis. Basic patient data, including age, race, year of diagnosis, sex, and treatment, were included in the univariate COX analysis. Then, multivariate COX analysis was performed for the factors with p < 0.2 in the univariate COX analysis. Age, year of diagnosis, and SLC31A1, PDHA1, and FDX1 levels were found to be independent prognostic factors. A nomogram was constructed using these 5 factors. Through experiments, we found that SLC31A1 had a higher expression level in cancer tissue than that near cancer among the three genes, SLC31A1, PDHA1, and FDX1; therefore, we focused on SLC31A1. According on the expression level of SLC31A1, we performed gene function enrichment, drug sensitivity, and immune cell infiltration analyses. Navitoclax was the most sensitive drug. Differential gene function enrichment was observed for metalloendopeptidase activity. SLC31A1 is expressed in dendritic cells, macrophages, neutrophils, and CD8+T cells. SLC31A1 is highly expressed in grade 4 diffuse gliomas, whereas SLC31A1 knockdown significantly reduces cell proliferation and mobility. Conclusions: Age, year of diagnosis, and SLC31A1, PDHA1, and FDX1 expression were independent prognostic factors. A nomogram was constructed based on age, year of diagnosis, and SLC31A1, PDHA1, and FDX1 levels. Through analysis and experimental verification, SLC31A1 was found to affect the prognosis and progression of patients with grade 4 diffuse gliomas and was associated with immune cell infiltration.

Measuring Greenspace in Rural Areas for Studies of Birth Outcomes: A Comparison of Street View Data and Satellite Data.

Using street view data, in replace of remotely sensed (RS) data, to study the health impact of greenspace has become popular. However, direct comparisons of these two methods of measuring greenspace are still limited, and their findings are inconsistent. On the other hand, almost all studies of greenspace focus on urban areas. The effectiveness of greenspace in rural areas remains to be investigated. In this study, we compared measures of greenspace based on the Google Street View data with those based on RS data by calculating the correlation between the two and evaluating their associations with birth outcomes. Besides the direct measures of greenness, we also compared the measures of environmental diversity, calculated with the two types of data. Our study area consists of the States of New Hampshire and Vermont, USA, which are largely rural. Our results show that the correlations between the two types of greenness measures were weak to moderate, and the greenness at an eye-level view largely reflects the immediate surroundings. Neither the street view data- nor the RS data-based measures identify the influence of greenspace on birth outcomes in our rural study area. Interestingly, the environmental diversity was largely negatively associated with birth outcomes, particularly gestational age. Our study revealed that in rural areas, the effectiveness of greenspace and environmental diversity may be considerably different from that in urban areas.

Prognostic and immunological implications of glutathione metabolism genes in lung adenocarcinoma: A focus on the core gene SMS and its impact on M2 macrophage polarization.

Glutathione metabolism (GM) is a crucial part of various metabolic and pathophysiological processes. However, its role in lung adenocarcinoma (LUAD) has not been comprehensively studied. This study aimed to explore the potential relationship between GM genes, the prognosis, and the immune microenvironment of patients with LUAD. We constructed a risk signature model containing seven GM genes using Lasso combined Cox regression and validated it using six GEO datasets. Our analysis showed that it is an independent prognostic factor. Functional enrichment analysis revealed that the GM genes were significantly enriched in cell proliferation, cell cycle regulation, and metabolic pathways. Clinical and gene expression data of patients with LUAD were obtained from the TCGA database and patients were divided into high- and low-risk groups. The high-risk patient group had a poor prognosis, reduced immune cell infiltration, poor response to immunotherapy, high sensitivity to chemotherapy, and low sensitivity to targeted therapy. Subsequently, single-cell transcriptome analysis using the GSE143423 and GSE127465 datasets revealed that the core SMS gene was highly enriched in M2 Macrophages. Finally, nine GEO datasets and multiple fluorescence staining revealed a correlation between the SMS expression and M2 macrophage polarization. Our prognostic model in which the core SMS gene is closely related to M2 macrophage polarization is expected to become a novel target and strategy for tumor therapy.

Identification of a multidrug resistance genomic island harboring a nonfunctional optrA gene in Campylobacter coli of chicken origin.

Campylobacter spp., such as Campylobacter jejuni and Campylobacter coli, are important zoonotic Gram-negative pathogens that cause acute intestinal diseases in humans. In this study, a retrospective analysis was conducted on previously collected Campylobacter isolates from antimicrobial resistance surveillance. A total of 29 optrA-positive C. coli strains were identified and subjected to second-generation sequencing. Multilocus sequence typing and single nucleotide polymorphism analyses demonstrated that the 29 optrA-positive isolates were genetically homogeneous. Notably, among the 29 isolated strains, the ΔoptrA variants exhibit a nonsense mutation at position 979 where the base C is substituted by T, leading to the formation of a premature termination codon. The alignment of sequences and genetic environmental characteristics suggested that ΔoptrA located on a chromosomally carried multidrug-resistant genomic island. There are other resistant genes on the multidrug resistance genomic island, such as aph(2'')-If, aph(3')-III, aadE, tet(O), tet(L), cat, erm(A), optrA and blaOXA-61. As a result, the 29 ΔoptrA-positive strains displayed susceptibility to both florfenicol and linezolid. The ΔoptrA gene is linked to the erm(A) gene, resulting in the formation of translocatable unit (TU) that are encompassed by two copies of IS1216 mobile elements. Multiple occurrences of similar TUs have been documented in numerous C. coli and provided evidence for the significance of TUs in facilitating the transfer of drug resistance genes in C. coli.

Impact of plasma Epstein-Barr virus DNA in posttreatment nasopharyngeal carcinoma patients after SARS-CoV-2 infection.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is prevalent in southern China. EBV DNA is the most useful biomarker in NPC. However, the value of EBV DNA in posttreatment NPC patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains unclear. METHODS: Sixty-four eligible NPC patients were enrolled between December 2022 and February 2023. Patients who met the following criteria were included: had non-metastatic NPC, completed radical treatment, were first firstly infected with SARS-CoV-2 and their EBV DNA changed from undetectable to detectable. RESULTS: At the end of follow-up, 81.25% (52/64) of patients were confirmed not to relapse with undetectable EBV DNA (no-relapse). In addition, 18.75% (12/64) of patients experienced relapse with consistent detection of EBV DNA (yes-relapse). For all 64 patients, the average time from diagnosis of coronavirus disease 2019 (COVID-19) to detection of detectable EBV DNA was 35.41 days (2 to 139 days). For 52 no-relapse patients, the average time from EBV DNA changing from detectable to undetectable was 63.12 days (6 to 147 days). The levels of EBV DNA were greater in yes-relapse patients than that in no-relapse patients, and the average of EBV DNA levels were 1216 copies/ml and 53.18 copies/ml, respectively. Using 62.3 copies/mL as the threshold, the area under the curve for EBV DNA was 0.88 for distinguishing yes-relapse patients from no-relapse patients. The sensitivity and specificity were 81.97% (95% CI 0.71-0.95) and 86.67% (95% CI 0.70-0.95), respectively. CONCLUSION: For NPC patients infected with SARS-CoV-2, EBV DNA alone is insufficient for monitoring relapse after radical therapy. Long-term follow-up and underlying mechanistic investigations of EBV DNA changes are urgently needed.

Plasma Epstein-Barr virus microRNA BART8-3p as a potential biomarker for detection and prognostic prediction in early nasopharyngeal carcinoma.

Epstein-Barr virus (EBV) encoded microRNA BART8-3p (miR-BART8-3p) was significantly associated with the metastasis in nasopharyngeal carcinoma (NPC). To explore the clinical values of plasma miR-BART8-3p in patients with early NPC. We retrospectively analyzed 126 patients with stage I and II NPC. A receiver operating characteristic curve was used to examine the diagnostic performance. Kaplan‒Meier analysis was applied to determine survival differences. Cox regression was used for univariate and multivariate analyses. Compared to healthy subjects, plasma EBV miR-BART8-3p was highly expressed in early NPC patients. The sensitivity, specificity, and area under the curve value of plasma miR-BART8-3p combined with plasma EBV DNA was up to 88.9%, 94.4%, and 0.931. Compared to patients with low expression of miR-BART8-3p, patients with high expression of miR-BART8-3p had poorer 5-year overall survival (OS) (98.9% vs. 91.1%, P = 0.025), locoregional recurrence-free survival (LRRFS) (100% vs. 83.9%, P < 0.001) and distant metastasis-free survival (DMFS) (98.9% vs. 88.0%, P = 0.006). Risk stratification analysis revealed that high-risk patients (with high levels of EBV DNA and miR-BART8-3p) had inferior OS, LRRFS, and DMFS than low-risk patients (without high levels of EBV DNA and miR-BART8-3p). Multivariate analysis verified that the high-risk group was an unfavorable factor for OS, LRRFS, and DMFS. A combination of plasma EBV miR-BART8-3p and EBV DNA could be a potential biomarker for the diagnosis and prognosis in early NPC.

A deep learning-based automatic image quality assessment method for respiratory phase on computed tomography chest images.

Background: Computed tomography (CT) chest scans have become commonly used in clinical diagnosis. Image quality assessment (IQA) for CT images plays an important role in CT examination. It is worth noting that IQA is still a manual and subjective process, and even experienced radiologists make mistakes due to human limitations (fatigue, perceptual biases, and cognitive biases). There are also kinds of biases because of poor consensus among radiologists. Excellent IQA methods can reliably give an objective evaluation result and also reduce the workload of radiologists. This study proposes a deep learning (DL)-based automatic IQA method, to assess whether the image quality of respiratory phase on CT chest images are optimal or not, so that the CT chest images can be used in the patient's physical condition assessment. Methods: This retrospective study analysed 212 patients' chest CT images, with 188 patients allocated to a training set (150 patients), validation set (18 patients), and a test set (20 patients). The remaining 24 patients were used for the observer study. Data augmentation methods were applied to address the problem of insufficient data. The DL-based IQA method combines image selection, tracheal carina segmentation, and bronchial beam detection. To automatically select the CT image containing the tracheal carina, an image selection model was employed. Afterward, the area-based approach and score-based approach were proposed and used to further optimize the tracheal carina segmentation and bronchial beam detection results, respectively. Finally, the score about the image quality of the patient's respiratory phase images given by the DL-based automatic IQA method was compared with the mean opinion score (MOS) given in the observer study, in which four blinded experienced radiologists took part. Results: The DL-based automatic IQA method achieved good performance in assessing the image quality of the respiratory phase images. For the CT sequence of the same patient, the DL-based IQA method had an accuracy of 92% in the assessment score, while the radiologists had an accuracy of 88%. The Kappa value of the assessment score between the DL-based IQA method and radiologists was 0.75, with a sensitivity of 85%, specificity of 91%, positive predictive value (PPV) of 92%, negative predictive value (NPV) of 93%, and accuracy of 88%. Conclusions: This study develops and validates a DL-based automatic IQA method for the respiratory phase on CT chest images. The performance of this method surpassed that of the experienced radiologists on the independent test set used in this study. In clinical practice, it is possible to reduce the workload of radiologists and minimize errors caused by human limitations.

Ehrlichia chaffeensis Etf-3 Induces Host RAB15 Upregulation for Bacterial Intracellular Growth.

Ehrlichia chaffeensis infects human monocytes or macrophages and causes human monocytic ehrlichiosis (HME), an emerging life-threatening zoonosis. After internalization, E. chaffeensis resides in membrane-bound inclusions, E. chaffeensis-containing vesicles (ECVs), which have early endosome-like characteristics and fuse with early autophagosomes but not lysosomes, to evade host innate immune microbicidal mechanisms and obtain nutrients for bacterial intracellular growth. The mechanisms exploited by E. chaffeensis to modulate intracellular vesicle trafficking in host cells have not been comprehensively studied. Here, we demonstrate that E. chaffeensis type IV secretion system (T4SS) effector Etf-3 induces RAB15 upregulation in host cells and that RAB15, which is localized on ECVs, inhibits ECV fusion with lysosomes and induces autophagy. We found that E. chaffeensis infection upregulated RAB15 expression using qRT-PCR, and RAB15 was colocalized with E. chaffeensis using confocal microscopy. Silence of RAB15 using siRNA enhanced ECV maturation to late endosomes and fusion with lysosomes, as well as inhibited host cell autophagy. Overexpression of Etf-3 in host cells specifically induced RAB15 upregulation and autophagy. Our findings deepen the understanding of E. chaffeensis pathogenesis and adaptation in hosts as well as the function of RAB15 and facilitate the development of new therapeutics for HME.

Targeting PARP14 with lomitapide suppresses drug resistance through the activation of DRP1-induced mitophagy in multiple myeloma.

Multiple myeloma (MM) is a hematological malignancy that remains incurable, primarily due to the high likelihood of relapse or development of resistance to current treatments. To explore and discover new medications capable of overcoming drug resistance in MM, we conducted cell viability inhibition screens of 1504 FDA-approved drugs. Lomitapide, a cholesterol-lowering agent, was found to exhibit effective inhibition on bortezomib-resistant MM cells in vitro and in vivo. Our data also indicated that lomitapide decreases the permeability of the mitochondrial outer membrane and induces mitochondrial dysfunction in MM cells. Next, lomitapide treatment upregulated DRP1 and PINK1 expression levels, coupled with the mitochondrial translocation of Parkin, leading to MM cell mitophagy. Excessive mitophagy caused mitochondrial damage and dysfunction induced by lomitapide. Meanwhile, PARP14 was identified as a direct target of lomitapide by SPR-HPLC-MS, and we showed that DRP1-induced mitophagy was crucial in the anti-MM activity mediated by PARP14. Furthermore, PARP14 is overexpressed in MM patients, implying that it is a novel therapeutic target in MM. Collectively, our results demonstrate that DRP1-mediated mitophagy induced by PARP14 may be the cause for mitochondrial dysfunction and damage in response to lomitapide treatment.

An in silico modeling approach to understanding the dynamics of the post-burn immune response.

Introduction: Burns are characterized by a massive and prolonged acute inflammation, which persists for up to months after the initial trauma. Due to the complexity of the inflammatory process, Predicting the dynamics of wound healing process can be challenging for burn injuries. The aim of this study was to develop simulation models for the post-burn immune response based on (pre)clinical data. Methods: The simulation domain was separated into blood and tissue compartments. Each of these compartments contained solutes and cell agents. Solutes comprise pro-inflammatory cytokines, anti-inflammatory cytokines and inflammation triggering factors. The solutes diffuse around the domain based on their concentration profiles. The cells include mast cells, neutrophils, and macrophages, and were modeled as independent agents. The cells are motile and exhibit chemotaxis based on concentrations gradients of the solutes. In addition, the cells secrete various solutes that in turn alter the dynamics and responses of the burn wound system. Results: We developed an Glazier-Graner-Hogeweg method-based model (GGH) to capture the complexities associated with the dynamics of inflammation after burn injuries, including changes in cell counts and cytokine levels. Through simulations from day 0 - 4 post-burn, we successfully identified key factors influencing the acute inflammatory response, i.e., the initial number of endothelial cells, the chemotaxis threshold, and the level of chemoattractants. Conclusion: Our findings highlight the pivotal role of the initial endothelial cell count as a key parameter for intensity of inflammation and progression of acute inflammation, 0 - 4 days post-burn.

Identification of SLC12A8 as a valuable prognostic biomarker and immunotherapeutic target by comprehensive pan-cancer analysis.

Solute carrier family 12 member 8 (SLC12A8) is a nicotinamide mononucleotide transporter. Despite emerging evidence supporting its potential involvement in oncogenesis, a systematic pan-cancer analysis of SLC12A8 has not been performed. Thus, this research aimed to explore the prognostic implications of SLC12A8 and assess its possible immune-related functions across 33 different tumor types. And multiple datasets were retrieved from the databases of TCGA, GTEx, Broad Institute CCLE, TISCH, HPA, and GDSC2. After this data acquisition, bioinformatics analyses were conducted to assess the potential involvement of SLC12A8 in cancer pathogenesis. These analyses focused on examining the relationship between SLC12A8 and prognosis, drug sensitivity, chemotherapy response, immune checkpoints (ICPs), immune cell infiltration, and immunotherapy efficacy across various tumor types. Furthermore, experimental methods such as EdU assay, wound healing assay, and transwell assay were conducted to evaluate the cell proliferative and invasive abilities. Finally, the data analysis demonstrated that SLC12A8 was differentially expressed and predicted unfavorable survival outcomes in the majority of the tumor types in the TCGA dataset. Furthermore, a notable upregulation in the expression of SLC12A8 mRNA and protein was observed in cancer tissues compared to normal tissues. Additionally, the SLC12A8 levels demonstrated a strong association with ICPs, chemokines, immune-activating genes, immune-suppressive genes, chemokine receptors, chemotherapy response, and immunotherapy efficacy. In vitro experiments substantiated that knockdown of SLC12A8 restricted the malignant phenotypes of MDA-MB-231 and BT-549 cells. So SLC12A8 holds promise as a cancer biomarker with the capacity to interact with other ICPs to synergistically regulate the immune microenvironment. Thus, the identification of SLC12A8 contributes to the development of novel therapeutic strategies for enhancing the efficacy of immunotherapy.

In-depth analysis of prognostic markers associated with the tumor immune microenvironment and genetic mutations in breast cancer based on an NK cell-related risk model.

The natural killer (NK) cell population is unique because it consists of innate lymphocytes capable of detecting and eliminating tumors and virus-infected cells. This research aims to identify a new prognostic signal in breast cancer (BRCA) based on NK-cell-related genes (NKRGs). A variety of sequencing and gene mutation data, along with clinical information, were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Database (GEO). COX regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were conducted to identify prognostic genes. In addition, the immune-related analysis was performed to evaluate the association between the immune microenvironment and clusters and risk model. The Edu assay, colony assay, wound healing assay, and transwell assay were performed to evaluate the cell proliferative and invasive abilities. A 4-NKRG-based prognostic model was constructed. Patients in high-risk groups were associated with poorer OS in TCGA and GSE42568. Further, a nomogram was constructed for better prediction of the prognosis of patients with BRCA. Finally, it was discovered that the over-expression of IFNE could suppress the proliferative and invasive abilities of BRCA cells, which might be a promising biomarker for patients with BRCA. As a result, we developed a novel 4-NKRG signal and nomogram capable of predicting the prognosis of patients with BRCA. Additionally, this model was closely associated with the immune microenvironment, which opened new therapeutic avenues for the treatment of cancer in the future.

Ochrolines A-C, three new indole diketopiperazines from cultures of endophytic fungi Bionectria ochroleuca SLJB-2.

Three new indole diketopiperazines, ochrolines A-C (1-3), along with three known compounds (4-6), were isolated and identified from the EtOAc extract of the solid fermentation of Bionectria ochroleuca SLJB-2. Notably, compound 1 featured a natural rarely-occurring caged skeleton with a 6/5/6/7 heterotetracyclic bridged ring system. The structures including absolute configurations of 1-3 were fully accomplished by extensive spectroscopic analyses, DFT GIAO 13C NMR and electronic circular dichroism (ECD) calculations. The plausible biogenetic pathways of these new indole diketopiperazines were also proposed. Moreover, the cytotoxic activity screening revealed that compound 2 exhibited moderate inhibitory effect against A549 with inhibition rate of 57.44% at the concentration of 50 µM and compound 1 exhibited mild inhibitory activities against A549, Hela and MCF-7.

iGly-IDN: Identifying Lysine Glycation Sites in Proteins Based on Improved DenseNet.

Lysine glycation is one of the most significant protein post-translational modifications, which changes the properties of the proteins and causes them to be dysfunctional. Accurately identifying glycation sites helps to understand the biological function and potential mechanism of glycation in disease treatments. Nonetheless, the experimental methods are ordinarily inefficient and costly, so effective computational methods need to be developed. In this study, we proposed the new model called iGly-IDN based on the improved densely connected convolutional networks (DenseNet). First, one hot encoding was adopted to obtain the original feature maps. Afterward, the improved DenseNet was adopted to capture feature information with the importance degrees during the feature learning. According to the experimental results, Acc reaches 66%, and Mathews correlation coefficient reaches 0.33 on the independent testing data set, which indicates that the iGly-IDN can provide more effective glycation site identification than the current predictors.

Highly efficient activation of periodate by a manganese-modified biochar to rapidly degrade methylene blue.

In this study, the manganese oxide/biochar composites (Mn@BC) were synthesized from Phytolacca acinosa Roxb. The Mn@BC was analyzed via techniques of Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction analysis (XRD). The results show that MnOx is successfully loaded on the surface of BC, and the load of MnOx can increase the number of surface functional groups of BC. X-ray photoelectron spectroscopy (XPS) shows that MnOx loaded on BC mainly exists in three valence forms: Mn(Ⅱ), Mn(Ⅲ), and Mn(Ⅳ). The ability of Mn@BC to activate periodate (PI) was studied by simulating the degradation of methylene blue (MB) dye. The degradation experiment results showed that the MB removal rate by the Mn@BC/PI system reached 97.4% within 30 min. The quenching experiment and electron paramagnetic resonance (EPR) analysis confirmed that Mn@BC can activate PI to produce iodate (IO3•), singlet oxygen (1O2), and hydroxyl radical (•OH), which can degrade MB during the reaction. Response surface methodology (RSM) based on Box-Behnken Design (BBD) was used to determine the interaction between pH, Mn@BC and PI concentration in the Mn@BC/PI system, and the optimum technological parameters were determined. When pH = 5.4, Mn@BC concentration 0.56 mg/L, PI concentration 1.1 mmol/L, MB removal rate can reach 98.05%. The cyclic experiments show that Mn@BC can be reused. After four consecutive runs, the removal rate of MB by the Mn@BC/PI system is still 82%, and the Mn@BC/PI system also shows high performance in treating MB in actual water bodies and degrading other pollutants. This study provides a practical method for degrading dyes in natural sewage.

Deep learning-driven multi-view multi-task image quality assessment method for chest CT image.

BACKGROUND: Chest computed tomography (CT) image quality impacts radiologists' diagnoses. Pre-diagnostic image quality assessment is essential but labor-intensive and may have human limitations (fatigue, perceptual biases, and cognitive biases). This study aims to develop and validate a deep learning (DL)-driven multi-view multi-task image quality assessment (M[Formula: see text]IQA) method for assessing the quality of chest CT images in patients, to determine if they are suitable for assessing the patient's physical condition. METHODS: This retrospective study utilizes and analyzes chest CT images from 327 patients. Among them, 1613 images from 286 patients are used for model training and validation, while the remaining 41 patients are reserved as an additional test set for conducting ablation studies, comparative studies, and observer studies. The M[Formula: see text]IQA method is driven by DL technology and employs a multi-view fusion strategy, which incorporates three scanning planes (coronal, axial, and sagittal). It assesses image quality for multiple tasks, including inspiration evaluation, position evaluation, radiation protection evaluation, and artifact evaluation. Four algorithms (pixel threshold, neural statistics, region measurement, and distance measurement) have been proposed, each tailored for specific evaluation tasks, with the aim of optimizing the evaluation performance of the M[Formula: see text]IQA method. RESULTS: In the additional test set, the M[Formula: see text]IQA method achieved 87% precision, 93% sensitivity, 69% specificity, and a 0.90 F1-score. Extensive ablation and comparative studies have demonstrated the effectiveness of the proposed algorithms and the generalization performance of the proposed method across various assessment tasks. CONCLUSION: This study develops and validates a DL-driven M[Formula: see text]IQA method, complemented by four proposed algorithms. It holds great promise in automating the assessment of chest CT image quality. The performance of this method, as well as the effectiveness of the four algorithms, is demonstrated on an additional test set.

Three new metabolites from the endophyte Fusarium proliferatum T2-10.

One new cyclopeptide, cyclo-(L-Trp-L-Phe-L-Phe) (1), one new 2-pyridone derivative, fusarone A (3), and one new natural indole derivative, ethyl 3-indoleacetate (4), along with six known compounds were isolated from the endophytic fungus Fusarium proliferatum T2-10. The planar structures of three new compounds were identified by spectral methods including 1D and 2D NMR techniques, and the absolute configuration of compound 1 was elucidated by Marfey-MS method. In addition, all compounds were evaluated for their cytotoxic and antibacterial activities in vitro. Compound 2 showed remarkable cytotoxic activities against two human hepatoma cell lines SMMC7721 and HepG2 with IC50 values of 5.89 ± 0.74 and 6.16 ± 0.52 µM, and showed moderate antibacterial activities against Staphylococcus aureus and Enterococcus faecalis with MIC values of 7.81 and 15.62 µg/mL, respectively.

Enhanced tumor immunotherapy by polyfunctional CD19-CAR T cells engineered to secrete anti-CD47 single-chain variable fragment.

A high recurrence rate of non-Hodgkin's lymphoma (NHL) following chimeric antigen receptor T (CAR T) cell treatment remains a bottleneck, and immunosuppressive tumor microenvironment (TME) compromising CAR T cell efficacy in NHL is the primary cause of relapse. Accordingly, modifying the structure of CAR T cells to attenuate the inhibitory effect of TME thus reducing recurrence rate is a valuable research topic. CD47 has been proved to be a promising therapeutic target and is crucial in regulating macrophage function. Herein, we engineered CD19-CAR T cells to secrete an anti-CD47 single-chain variable fragment (scFv) and validated their function in enhancing antitumor efficacy, regulating T cells differentiation, modifying phagocytosis and polarization of macrophages by in vitro and in vivo researches. The efficacy was analogous or preferable to the combination of CAR T cells and CD47 antibody. Of note, anti-CD47 scFv secreting CAR T cells exert a more potent immune response following specific antigen stimulation compared with parental CAR T cells, characterized by more efficient degranulation and cytokine production with polyfunctionality. Furthermore, locally delivering anti-CD47 by CAR T cells potentially limits toxicities relevant to systemic antibody treatment. Collectively, our research provides a more effective and safer CAR T cell transformation method for enhancing tumor immunotherapy.

Classification and Authentication of Lonicerae Japonicae Flos and Lonicerae Flos by Using 1H-NMR Spectroscopy and Chemical Pattern Recognition Analysis.

Lonicerae japonicae flos and Lonicerae flos are increasingly widely used in food and traditional medicine products around the world. Due to their high demand and similar appearance, they are often used in a confused or adulterated way; therefore, a rapid and comprehensive analytical method is highly required. In this case, the comparative analysis of a total of 100 samples with different species, growth modes, and processing methods was carried out by nuclear magnetic resonance (1H-NMR) spectroscopy and chemical pattern recognition analysis. The obtained 1H-NMR spectrums were employed by principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), orthogonal partial least-squares discriminant analysis (OPLS-DA), and linear discriminant analysis (LDA). Specifically, after the dimensionality reduction of data, linear discriminant analysis (LDA) exhibited good classification abilities for the species, growth modes, and processing methods. It is worth noting that the sample prediction accuracy from the testing set and the cross-validation predictions of the LDA models were higher than 95.65% and 98.1%, respectively. In addition, the results showed that macranthoidin A, macranthoidin B, and dipsacoside B could be considered as the main differential components of Lonicerae japonicae flos and Lonicerae Flos, while secoxyloganin, secologanoside, and sweroside could be responsible for distinguishing cultivated and wild Lonicerae japonicae Flos. Accordingly, 1H-NMR spectroscopy combined with chemical pattern recognition gives a comprehensive overview and provides new insight into the quality control and evaluation of Lonicerae japonicae flos.