Development of a novel prognostic signature based on single-cell combined bulk RNA analysis in breast cancer.

BACKGROUND: Breast cancer (BC), a malignant tumor, is a significant cause of death and disability among women globally. Recent research indicates that copy number variation plays a crucial role in tumor development. In this study, we employed the Single-Cell Variational Aneuploidy Analysis (SCEVAN) algorithm to differentiate between malignant and non-malignant cells, aiming to identify genetic signatures with prognostic relevance for predicting patient survival. METHODS: We analyzed gene expression profiles and associated clinical data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Using the SCEVAN algorithm, we distinguished malignant from non-malignant cells and investigated cellular interactions within the tumor microenvironment (TME). We categorized TCGA samples based on differentially expressed genes (DEGs) between these cell types. Subsequent Kyoto Encyclopedia of Genes and Genomes pathway analysis was conducted. Additionally, we developed polygenic models for the DEGs using least absolute shrinkage and selection operator-penalized Cox regression analysis. To assess the prognostic accuracy of these characteristics, we generated Kaplan-Meier and receiver operating characteristic curves from training and validation datasets. We also monitored the expression variations of prognostic genes across the pseudotime of malignant cells. Patients were divided into high-risk and low-risk groups based on median risk scores to compare their TME and identify potential therapeutic agents. Lastly, polymerase chain reaction was used to validate seven pivotal genes. RESULTS: The SCEVAN algorithm identified distinct malignant and non-malignant cells in GSE180286. Cellchat analysis revealed significantly increased cellular communication, particularly between fibroblasts, endothelial cells and malignant cells. The DEGs were predominantly involved in immune-related pathways. TCGA samples were classified into clusters A and B based on these genes. Cluster A, enriched in immune pathways, was associated with poorer prognosis, whereas cluster B, predominantly involved in circadian rhythm pathways, showed better outcomes. We constructed a 14-gene prognostic signature, validated in a 1:1 internal TCGA cohort and external GEO datasets (GSE42568 and GSE146558). Kaplan-Meier analysis confirmed the prognostic signature's accuracy (p < 0.001). Receiver operating characteristic curve analysis demonstrated the predictive reliability of these prognostic features. Single-cell pseudotime analysis with monocle2 highlighted the distinct expression trends of these genes in malignant cells, underscoring the intratumoral heterogeneity. Furthermore, we explored the differences in TME between high- and low-risk groups and identified 16 significantly correlated drugs. CONCLUSION: Our findings suggest that the 14-gene prognostic signature could serve as a novel biomarker for forecasting the prognosis of BC patients. Additionally, the immune cells and pathways in different risk groups indicate that immunotherapy may be a crucial component of treatment strategies for BC patients.

Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.

Background Preoperative discrimination of preinvasive, minimally invasive, and invasive adenocarcinoma at CT informs clinical management decisions but may be challenging for classifying pure ground-glass nodules (pGGNs). Deep learning (DL) may improve ternary classification. Purpose To determine whether a strategy that includes an adjudication approach can enhance the performance of DL ternary classification models in predicting the invasiveness of adenocarcinoma at chest CT and maintain performance in classifying pGGNs. Materials and Methods In this retrospective study, six ternary models for classifying preinvasive, minimally invasive, and invasive adenocarcinoma were developed using a multicenter data set of lung nodules. The DL-based models were progressively modified through framework optimization, joint learning, and an adjudication strategy (simulating a multireader approach to resolving discordant nodule classifications), integrating two binary classification models with a ternary classification model to resolve discordant classifications sequentially. The six ternary models were then tested on an external data set of pGGNs imaged between December 2019 and January 2021. Diagnostic performance including accuracy, specificity, and sensitivity was assessed. The χ2 test was used to compare model performance in different subgroups stratified by clinical confounders. Results A total of 4929 nodules from 4483 patients (mean age, 50.1 years ± 9.5 [SD]; 2806 female) were divided into training (n = 3384), validation (n = 579), and internal (n = 966) test sets. A total of 361 pGGNs from 281 patients (mean age, 55.2 years ± 11.1 [SD]; 186 female) formed the external test set. The proposed strategy improved DL model performance in external testing (P < .001). For classifying minimally invasive adenocarcinoma, the accuracy was 85% and 79%, sensitivity was 75% and 63%, and specificity was 89% and 85% for the model with adjudication (model 6) and the model without (model 3), respectively. Model 6 showed a relatively narrow range (maximum minus minimum) across diagnostic indexes (accuracy, 1.7%; sensitivity, 7.3%; specificity, 0.9%) compared with the other models (accuracy, 0.6%-10.8%; sensitivity, 14%-39.1%; specificity, 5.5%-17.9%). Conclusion Combining framework optimization, joint learning, and an adjudication approach improved DL classification of adenocarcinoma invasiveness at chest CT. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Sohn and Fields in this issue.

Unenhanced computed tomography radiomics help detect endoleaks after endovascular repair of abdominal aortic aneurysm.

OBJECTIVES: To explore the feasibility of unenhanced CT images for endoleak detection of abdominal aortic aneurysm (AAA) after endovascular repair (EVAR). METHODS: Patients who visited our hospital after EVAR from July 2014 to September 2021 were retrospectively collected. Two radiologists evaluated the presence or absence of endoleaks using the combination of contrast-enhanced and unenhanced CT as the referenced standard. After segmenting the aneurysm sac of the unenhanced CT, the radiomic features were automatically extracted from the region of interest. Histogram features of patients with and without endoleak were statistically analyzed to explore the differences between the two groups. Twelve common machine learning (ML) models based on radiomic features were constructed to evaluate the performance of endoleak detection with unenhanced CT images. RESULTS: The study included 216 patients (69 ± 8 years; 191 men) with AAA, including 64 patients with endoleaks. A total of 1955 radiomic features of unenhanced CT were extracted. Compared with patients without endoleak, the aneurysm sac outside the stent of patients with endoleak had higher CT attenuation (41.7 vs. 33.6, p < 0.001) with smaller dispersion (51.5 vs. 58.8, p < 0.001). The average area under the curve (AUC) of the ML models constructed with unenhanced CT radiomics was 0.86 ± 0.05, the accuracy was 81% ± 4, the sensitivity was 88% ± 10, and the specificity was 78% ± 5. When fixing the sensitivity to > 90% (92% ± 2), the models retained specificity at 72% ± 10. CONCLUSIONS: Unenhanced CT features exhibit significant differences between patients with and without endoleak and can help detect endoleaks in AAA after EVAR with high sensitivity. CLINICAL RELEVANCE STATEMENT: Unenhanced CT radiomics can help provide an alternative method of endoleak detection in patients who have adverse reactions to contrast media. This study further exploits the value of unenhanced CT examinations in the clinical management and surveillance of postoperative abdominal aortic aneurysm. KEY POINTS: • Unenhanced CT features of the aneurysm sac outside the stent exhibit significant differences between patients with and without endoleak. The endoleak group showed higher unenhanced CT attenuation (41.7 vs 33.6, p < .001) with smaller dispersion (51.5 vs 58.8, p < .001) than the nonendoleak group. • Unenhanced CT radiomics can help detect endoleaks after intervention. The average area under the curve (AUC) of twelve common machine learning models constructed with unenhanced CT radiomics was 0.86 ± 0.05, the average accuracy was 81% ± 4. • When fixing the sensitivity to > 90% (92% ± 2), the machine learning models retained average specificity at 72% ± 10.

Graphene Far-Infrared Irradiation Can Effectively Relieve the Blood Pressure Level of Rat Untr-HT in Primary Hypertension.

Graphene, when electrified, generates far-infrared radiation within the wavelength range of 4 µm to 14 µm. This range closely aligns with the far-infrared band (3 µm to 15 µm), which produces unique physiological effects. Contraction and relaxation of vascular smooth muscle play a significant role in primary hypertension, involving the nitric oxide-soluble guanylate cyclase-cyclic guanosine monophosphate pathway and the renin-angiotensin-aldosterone system. This study utilized spontaneously hypertensive rats (SHRs) as an untr-HT to investigate the impact of far-infrared radiation at specific wavelengths generated by electrified graphene on vascular smooth muscle and blood pressure. After 7 weeks, the blood pressure of the untr-HT group rats decreased significantly with a notable reduction in the number of vascular wall cells and the thickness of the vascular wall, as well as a decreased ratio of vessel wall thickness to lumen diameter. Additionally, blood flow perfusion significantly increased, and the expression of F-actin in vascular smooth muscle myosin decreased significantly. Serum levels of angiotensin II (Ang-II) and endothelin 1 (ET-1) were significantly reduced, while nitric oxide synthase (eNOS) expression increased significantly. At the protein level, eNOS expression decreased significantly, while α-SMA expression increased significantly in aortic tissue. At the gene level, expressions of eNOS and α-SMA in aortic tissue significantly increased. Furthermore, the content of nitric oxide (NO) in the SHR's aortic tissue increased significantly. These findings confirm that graphene far-infrared radiation enhances microcirculation, regulates cytokines affecting vascular smooth muscle contraction, and modifies vascular morphology and smooth muscle phenotype, offering relief for primary hypertension.

Oxymatrine Modulation of TLR3 Signaling: A Dual-Action Mechanism for H9N2 Avian Influenza Virus Defense and Immune Regulation.

In our research, we explored a natural substance called Oxymatrine, found in a traditional Chinese medicinal plant, to fight against a common bird flu virus known as H9N2. This virus not only affects birds but can also pose a threat to human health. We focused on how this natural compound can help in stopping the virus from spreading in cells that line the lungs of birds and potentially humans. Our findings show that Oxymatrine can both directly block the virus and boost the body's immune response against it. This dual-action mechanism is particularly interesting because it indicates that Oxymatrine might be a useful tool in developing new ways to prevent and treat this type of bird flu. Understanding how Oxymatrine works against the H9N2 virus could lead to safer and more natural ways to combat viral infections in animals and humans, contributing to the health and well-being of society. The H9N2 Avian Influenza Virus (AIV) is a persistent health threat because of its rapid mutation rate and the limited efficacy of vaccines, underscoring the urgent need for innovative therapies. This study investigated the H9N2 AIV antiviral properties of Oxymatrine (OMT), a compound derived from traditional Chinese medicine, particularly focusing on its interaction with pulmonary microvascular endothelial cells (PMVECs). Employing an array of in vitro assays, including 50% tissue culture infectious dose, Cell Counting Kit-8, reverse transcription-quantitative polymerase chain reaction, enzyme-linked immunosorbent assay, and Western blot, we systematically elucidated the multifaceted effects of OMT. OMT dose-dependently inhibited critical antiviral proteins (PKR and Mx1) and modulated the expression of type I interferons and key cytokines (IFN-α, IFN-ß, IL-6, and TNF-α), thereby affecting TLR3 signaling and its downstream elements (NF-κB and IRF-3). OMT's antiviral efficacy extended beyond TLR3-mediated responses, suggesting its potential as a versatile antiviral agent. This study not only contributes to the growing body of research on the use of natural compounds as antiviral agents but also underscores the importance of further investigating the broader application of OMT for combating viral infections.

CT-based radiomics nomogram for prediction of survival after transarterial chemoembolization with drug-eluting beads in patients with hepatocellular carcinoma and portal vein tumor thrombus.

OBJECTIVES: To develop and validate a CT-based radiomics model for the prediction of the overall survival (OS) of patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT) treated with drug-eluting beads transarterial chemoembolization (DEB-TACE). METHODS: Patients were retrospectively enrolled from two institutions for the constitution of training (n = 69) and validation (n = 31) cohorts with a median follow-up of 15 months. A total of 396 radiomics features were extracted from each baseline CT image. Features selected by variable importance and minimal depth were used for random survival forest model construction. The performance of the model was assessed using the concordance index (C-index), calibration curves, integrated discrimination index (IDI), net reclassification index (NRI), and decision curve analysis. RESULTS: Type of PVTT and tumor number were proved to be significant clinical indicators for OS. Arterial phase images were used to extract radiomics features. Three radiomics features were selected for model construction. The C-index for the radiomics model was 0.759 in the training cohort and 0.730 in the validation cohort. To improve the predictive performance, clinical indicators were integrated into the radiomics model to form a combined model with a C-index of 0.814 in the training cohort and 0.792 in the validation cohort. The IDI was significant in both cohorts for the combined model versus the radiomics model in predicting 12-month OS. CONCLUSIONS: Type of PVTT and tumor number affected the OS of HCC patients with PVTT treated with DEB-TACE. Moreover, the combined clinical-radiomics model had a satisfactory performance. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics nomogram, which consisted of 3 radiomics features and 2 clinical indicators, was recommended to predict 12-month overall survival of patients with hepatocellular carcinoma and portal vein tumor thrombus initially treated with drug-eluting beads transarterial chemoembolization. KEY POINTS: • Type of portal vein tumor thrombus and tumor number were significant predictors of the OS. • Integrated discrimination index and net reclassification index provided a quantitative evaluation of the incremental impact added by new indicators for the radiomics model. • A nomogram based on a radiomics signature and clinical indicators showed satisfactory performance in predicting OS after DEB-TACE.

A pre-treatment CT-based weighted radiomic approach combined with clinical characteristics to predict durable clinical benefits of immunotherapy in advanced lung cancer.

OBJECTIVES: To develop a pre-treatment CT-based predictive model to anticipate inoperable lung cancer patients' progression-free survival (PFS) to immunotherapy. METHODS: This single-center retrospective study developed and cross-validated a radiomic model in 185 patients and tested it in 48 patients. The binary endpoint is the durable clinical benefit (DCB, PFS ≥ 6 months) and non-DCB (NDCB, PFS < 6 months). Radiomic features were extracted from multiple intrapulmonary lesions and weighted by an attention-based multiple-instance learning model. Aggregated features were then selected through L2-regularized ridge regression. Five machine-learning classifiers were conducted to build predictive models using radiomic and clinical features alone and then together. Lastly, the predictive value of the model with the best performance was validated by Kaplan-Meier survival analysis. RESULTS: The predictive models based on the weighted radiomic approach showed superior performance across all classifiers (AUCs: 0.75-0.82) compared with the largest lesion approach (AUCs: 0.70-0.78) and the average sum approach (AUCs: 0.64-0.80). Among them, the logistic regression model yielded the most balanced performance (AUC = 0.87 [95%CI 0.84-0.89], 0.75 [0.68-0.82], 0.80 [0.68-0.92] in the training, validation, and test cohort respectively). The addition of five clinical characteristics significantly enhanced the performance of radiomic-only model (train: AUC 0.91 [0.89-0.93], p = .042; validation: AUC 0.86 [0.80-0.91], p = .011; test: AUC 0.86 [0.76-0.96], p = .026). Kaplan-Meier analysis of the radiomic-based predictive models showed a clear stratification between classifier-predicted DCB versus NDCB for PFS (HR = 2.40-2.95, p < 0.05). CONCLUSIONS: The adoption of weighted radiomic features from multiple intrapulmonary lesions has the potential to predict long-term PFS benefits for patients who are candidates for PD-1/PD-L1 immunotherapies. KEY POINTS: • Weighted radiomic-based model derived from multiple intrapulmonary lesions on pre-treatment CT images has the potential to predict durable clinical benefits of immunotherapy in lung cancer. • Early line immunotherapy is associated with longer progression-free survival in advanced lung cancer.

Potential Involvement of Organic Anion Transporters in Drug Interactions with Shuganning Injection, a Traditional Chinese Patent Medicine.

Traditional Chinese medicine injections have been widely used in China for the treatment of various diseases. Transporter-mediated drug-drug interactions are a major contributor to adverse drug reactions. However, the research on transporter-mediated Traditional Chinese medicine injection-drug interactions is limited. Shuganning injection is a widely used Traditional Chinese medicine injection for treating various liver diseases. In this study, we investigated the inhibitory effect of Shuganning injection and its four main ingredients (baicalin, geniposide, chlorogenic acid, and oroxylin A) on 9 drug transporters. Shuganning injection strongly inhibited organic anion transporter 1 and organic anion transporter 3 with IC50 values < 0.1% (v/v), and moderately inhibited organic anion transporter 2, organic anion transporting-polypeptide 1B1, and organic anion transporting-polypeptide 1B3 with IC50 values < 1.0%. Baicalin, the most abundant bioactive ingredient in the Shuganning injection, was identified as both an inhibitor and substrate of organic anion transporter 1, organic anion transporter 3, and organic anion transporting-polypeptide 1B3. Oroxylin A had the potential to act as both an inhibitor and substrate of organic anion transporting-polypeptide 1B1 and organic anion transporting-polypeptide 1B3. In contrast, geniposide and chlorogenic acid had no significant inhibitory effect on drug transporters. Notably, Shuganning injection markedly altered the pharmacokinetics of furosemide and atorvastatin in rats. Using Shuganning injection as an example, our findings support the implementation of transporter-mediated Traditional Chinese medicine injection-drug interactions in the development of Traditional Chinese medicine injection standards.

Simulation video: a tool to evaluate communications skills in radiologist residents.

BACKGROUND: Effective communication is a crucial component of radiology resident training, and many different aspects need to be explored when teaching and evaluating communication skills. To ensure that radiology residents' communication skill levels can be measured accurately, a standardized evaluation tool has been introduced. In twenty hospitals in Beijing, simulation videos have been developed as a way to assess the communication skills of radiology residents during their certification exams, to minimize evaluating biases. This study aims to assess the performance of a simulation video model in evaluating communications skills compared to the standard patient model. METHODS: This is a retrospective observational study. The performance of standard patient and simulation video models was evaluated through an eight-year examination of communication skills in radiology residents. From 2014 to 2021, communications skill tests were administered to 1003 radiology residents in 20 hospitals in Beijing. The standardized patient (SP) model was applied in 2014, and simulation videos were used from 2015 to 2021. The difficulty and discrimination radio of the tests were evaluated. The subjective survey for candidates on two models of communication skills evaluation was performed and analyzed. RESULTS: The simulation video model evaluation demonstrated stable difficulty (ranging from 0.92 to 0.98) and discrimination ratio (ranging from 0.37 to 0.49), except for minor exceptions of discrimination in 2019 (0.58) and 2020 (0.20). Furthermore, the Kruskal-Wallis H test revealed no significant differences in average scores between 2016 (93.9 ± 4.6) and 2018 (94.5 ± 4.2), 2016 and 2019 (97.3 ± 3.9), 2017 (97.0 ± 5.6) and 2019, 2017 and 2020 (97.7 ± 4.7), as well as 2019 and 2020 exams (all p ≥ 0.05). In addition, candidates who responded to the survey preferred the simulation video model (with a 77.2% response rate), with 62.7% choosing it over the SP model for communication skills evaluation. CONCLUSION: The simulation video demonstrated a stable and better acceptable construct for assessing radiology residents' communication skills.

DIW1 encoding a clade I PP2C phosphatase negatively regulates drought tolerance by de-phosphorylating TaSnRK1.1 in wheat.

Drought seriously impacts wheat production (Triticum aestivum L.), while the exploitation and utilization of genes for drought tolerance are insufficient. Leaf wilting is a direct reflection of drought tolerance in plants. Clade A PP2Cs are abscisic acid (ABA) co-receptors playing vital roles in the ABA signaling pathway, regulating drought response. However, the roles of other clade PP2Cs in drought tolerance, especially in wheat, remain largely unknown. Here, we identified a gain-of-function drought-induced wilting 1 (DIW1) gene from the wheat Aikang 58 mutant library by map-based cloning, which encodes a clade I protein phosphatase 2C (TaPP2C158) with enhanced protein phosphatase activity. Phenotypic analysis of overexpression and CRISPR/Cas9 mutant lines demonstrated that DIW1/TaPP2C158 is a negative regulator responsible for drought resistance. We found that TaPP2C158 directly interacts with TaSnRK1.1 and de-phosphorylates it, thus inactivating the TaSnRK1.1-TaAREB3 pathway. TaPP2C158 protein phosphatase activity is negatively correlated with ABA signaling. Association analysis suggested that C-terminal variation of TaPP2C158 changing protein phosphatase activity is highly correlated with the canopy temperature, and seedling survival rate under drought stress. Our data suggest that the favorable allele with lower phosphatase activity of TaPP2C158 has been positively selected in Chinese breeding history. This work benefits us in understanding the molecular mechanism of wheat drought tolerance, and provides elite genetic resources and molecular markers for improving wheat drought tolerance.

[CT-Based Weighted Radiomic Score Predicts Tumor Response to Immunotherapy in Non-Small Cell Lung Cancer].

Objective To develop a CT-based weighted radiomic model that predicts tumor response to programmed death-1(PD-1)/PD-ligand 1(PD-L1)immunotherapy in patients with non-small cell lung cancer.Methods The patients with non-small cell lung cancer treated by PD-1/PD-L1 immune checkpoint inhibitors in the Peking Union Medical College Hospital from June 2015 to February 2022 were retrospectively studied and classified as responders(partial or complete response)and non-responders(stable or progressive disease).Original radiomic features were extracted from multiple intrapulmonary lesions in the contrast-enhanced CT scans of the arterial phase,and then weighted and summed by an attention-based multiple instances learning algorithm.Logistic regression was employed to build a weighted radiomic scoring model and the radiomic score was then calculated.The area under the receiver operating characteristic curve(AUC)was used to compare the weighted radiomic scoring model,PD-L1 model,clinical model,weighted radiomic scoring + PD-L1 model,and comprehensive prediction model.Results A total of 237 patients were included in the study and randomized into a training set(n=165)and a test set(n=72),with the mean ages of(64±9)and(62±8)years,respectively.The AUC of the weighted radiomic scoring model reached 0.85 and 0.80 in the training set and test set,respectively,which was higher than that of the PD-L1-1 model(Z=37.30,P<0.001 and Z=5.69,P=0.017),PD-L1-50 model(Z=38.36,P<0.001 and Z=17.99,P<0.001),and clinical model(Z=11.40,P<0.001 and Z=5.76,P=0.016).The AUC of the weighted scoring model was not different from that of the weighted radiomic scoring + PD-L1 model and the comprehensive prediction model(both P>0.05).Conclusion The weighted radiomic scores based on pre-treatment enhanced CT images can predict tumor responses to immunotherapy in patients with non-small cell lung cancer.

IFN-γ differential expression in the hypothalamus-pituitary-ovary axis of thyroidectomized rats.

IFN-γ is critical for both thyroid and ovarian function, while thyroxine, secreted from the thyroid gland, regulates the ovarian function via the hypothalamus-pituitary -ovary axis. However, the effect of thyroxine on INF-γ involved in the regulation of hypothalamic pituitary ovarian axis ovarian function is hitherto unknown. Therefore, we set up three groups including a sham-operated group, an experimental thyroidectomized group, and an experimental thyroidectomized group treated with T4 to reveal the IFN-γ expression levels in the in the hypothalamus, pituitary gland, and ovary by immunohistochemical staining, RT-PCR, and Western blotting. IFN-γ-like immunoreactive-positive substances were visualized in the hypothalamus, pituitary gland, and ovary, which were located mainly in the cytoplasm of the hypothalamic neurons anterior pituitary cells, luteal cells, and theca cells in the ovary of hypothyroidism rats, respectively. RT-PCR and Western blotting showed that the rats in the experimental thyroidectomized group treated with T4 had significantly elevated expression of IFN-γ at both the mRNA and protein levels. Thyroxine affects the expression of IFN-γ in the thalamus-pituitary-ovarian axis, which may influence the secretion of IFN-γ to regulate ovarian function during hypothyroidism. This work highlights the potential effect of thyroxine on the involvement of INF-γ in the modulation of the ovarian function in the hypothalamic-pituitary-ovarian axis.

Coenzyme self-sufficiency system-recent advances in microbial production of high-value chemical phenyllactic acid.

Phenyllactic acid (PLA), a natural antimicrobial substance, has many potential applications in the food, animal feed, pharmaceutical and cosmetic industries. However, its production is limited by the complex reaction steps involved in its chemical synthesis. Through advances in metabolic engineering and synthetic biology strategies, enzymatic or whole-cell catalysis was developed as an alternative method for PLA production. Herein, we review recent developments in metabolic engineering and synthetic biology strategies that promote the microbial production of high-value PLA. Specially, the advantages and disadvantages of the using of the three kinds of substrates, which includes phenylpyruvate, phenylalanine and glucose as starting materials by natural or engineered microbes is summarized. Notably, the bio-conversion of PLA often requires the consumption of expensive coenzyme NADH. To overcome the issues of NADH regeneration, efficiently internal cofactor regeneration systems constructed by co-expressing different enzyme combinations composed of lactate dehydrogenase with others for enhancing the PLA production, as well as their possible improvements, are discussed. In particular, the construction of fusion proteins with different linkers can achieve higher PLA yield and more efficient cofactor regeneration than that of multi-enzyme co-expression. Overall, this review provides a comprehensive overview of PLA biosynthesis pathways and strategies for increasing PLA yield through biotechnology, providing future directions for the large-scale commercial production of PLA and the expansion of downstream applications.

Reduced radiotherapy clinical benefit for primary Waldeyer's ring diffuse large B-cell lymphoma in the rituximab era.

This study aimed to identify the prognostic factors in patients with Waldeyer's ring diffuse large B-cell lymphoma (WR-DLBCL), comparing the efficacy of radiotherapy (RT) for the WR-DLBCL patients in the pre-rituximab and rituximab eras. We conducted a retrospective analysis of 134 patients diagnosed with WR-DLBCL. Univariate and multivariate analyses were performed to identify the prognostic factors for WR-DLBCL. Then, we divided these patients into the rituximab plus chemotherapy group (R-chemotherapy) (n = 88) and chemotherapy group (n = 46), and the Kaplan-Meier and Cox regression model analyses were applied to investigate the treatment value of RT in both the groups. Multivariate analysis revealed international prognostic index (IPI) ≥ 3 and chemotherapy without rituximab as significant risk factors for the progression-free survival (PFS, IPI ≥ 3: p = 0.001; chemotherapy without rituximab: p = 0.002) and overall survival (OS, IPI ≥ 3, p < 0.001; chemotherapy without rituximab, p = 0.024). Rituximab combined with chemotherapy significantly improved PFS (p = 0.002) and OS (p = 0.006) in these patients. RT did not significantly contribute to the survival in the overall cohort analysis, whereas in the subgroup analysis, RT significantly improved the PFS (p = 0.025) and OS (p = 0.029) for the patients in the chemotherapy group, but not in the R-chemotherapy group. In conclusion, the WR-DLBCL patients could benefit from RT in the pre-rituximab era, whereas the addition of rituximab to chemotherapy significantly improved the survival of WR-DLBCL patients, and the clinical benefit of RT was reduced.

Pulmonary endothelium-derived PD-L1 induced by the H9N2 avian influenza virus inhibits the immune response of T cells.

BACKGROUND: The PD-1/PD-L1 pathway is an inhibitory signaling pathway that maintains the balance between the immune response and immunotolerance, and its overactivation in cancer and viral infections inhibits T cell function. The target cells of various viruses, microvascular endothelial cells (MECs) have been shown to be key regulatory points in immune regulation and virion diffusion in vivo during infection with multiple influenza virus subtypes. Furthermore, avian influenza virus (AIV) infection can induce immunosuppression by causing imbalances in immune responses and immune organ damage. Thus, the aim of this study was to investigate whether the H9N2 virus inhibited the immune function of T cells that migrated across MECs by upregulating PD-L1 expression on MECs. METHODS: The susceptibility of rat pulmonary microvascular endothelial cells (RPMECs) to the H9N2 virus was evaluated by a plaque-forming assay and immunofluorescence staining. Then, we quantified the mRNA and protein levels of PD-L1 in RPMECs induced by H9N2 virus infection using quantitative real-time PCR and flow cytometry. The interaction between the activated T cells and RPMECs infected with the H9N2 virus was revealed using a coculture system. The effect of endothelial-derived PD-L1 on T cell function was investigated by using ELISA and flow cytometry with or without a PD-L1-specific antibody. RESULTS: Surface staining and the plaque-forming assay showed that the H9N2 virus infected and replicated in RPMECs. Both the PD-L1 mRNA level and PD-L1 protein level were upregulated in RPMECs infected with the H9N2 virus. H9N2 virus-induced PD-L1 expression significantly reduced the secretions of IL-2, IFN-γ and granzyme B and perforin expression in T cells. The above data were significantly increased after treatment with an anti-PD-L1 antibody, confirming the above mentioned findings. In addition, the induction of PD-L1 expression decreased the proliferative capacity of the cocultured T cells but did not affect the apoptosis rate of T cells. CONCLUSIONS: Taken together, the results suggest that the H9N2 virus is able to inhibit the T cell immune response by upregulating PD-L1 expression in pulmonary microvascular endothelial cells.

Synchronous vasomotion of skin microvessels at acupoints on the twelve main meridians of beagle dogs.

BACKGROUND/PURPOSE: Synchronous microvascular vasomotion was detected at acupoints in our previous human study. This present study aimed to characterize the skin microvascular vasomotion at acupoints on the twelve meridians of beagle dogs. MATERIALS AND METHODS: Two acupoints were selected on each meridian and exactly located at the rosy red spots by an electrochemical color-appearing method, where the electrical resistance was measured. The skin blood flow at acupoints was recorded by laser Doppler flowmetry (LDF), and microvascular vasomotion was analyzed according to LDF waveforms. RESULTS: The skin electrical resistance at acupoints was significantly lower than that at control non-acupoints. The LDF waveforms at acupoints were sinusoidal, which showed the synchronization of the microvascular vasomotion. The spectral analysis revealed that the vasomotion frequencies at acupoints on the same meridian were identical but not among different meridians, and the frequencies on the twelve main meridians displayed a constant order. CONCLUSION: The skin microvascular vasomotion is synchronous at acupoints of beagle dogs and has a specific frequency along the meridian, and the electrochemical color-appearing method is a feasible strategy for the precise and visual location of acupoints. The study provides evidence for the universality of synchronous vasomotion of skin microvessels at acupoints.

Tumor CD73/A2aR adenosine immunosuppressive axis and tumor-infiltrating lymphocytes in diffuse large B-cell lymphoma: correlations with clinicopathological characteristics and clinical outcome.

Novel immune checkpoint blockades, including those targeting CD73 and A2aR, are being evaluated in malignancies in clinical trials. Here, we investigated the expression of CD73 and A2aR as well as tumor-infiltrating lymphocytes (TILs), and analyzed their correlations with clinicopathological characteristics and survival in diffuse large B-cell lymphoma (DLBCL). We found that CD73 expression on tumor cells, rather than the total protein and gene levels of CD73, was associated with survival. Patients with CD73+ /Pax-5+ (median survival, 57.8 months; 95% CI, 46.4-69.3) experienced significantly poorer outcomes than those with CD73- /Pax-5+ (median survival, 73.5 months; 95% CI, 65.9-81.2). Additionally, A2aR expression on both total TILs and CD8+ TILs was correlated with survival. Patients with A2aR+ TILs (median survival, 53.3 months; 95% CI, 40.6-66.0) had a significantly shorter survival time than patients with A2aR- TILs (median survival, 74.5 months; 95% CI, 67.5-81.5). Spearman's rank test showed that CD73 expression on tumor cells was positively correlated with A2aR expression on TILs (R = 0.395, p = 0.001). We further found that patients could be more precisely stratified through the combination of CD73 tumor cell expression and A2aR TILs expression, and patients with CD73+ /Pax-5+ and A2aR+ TILs experienced the worst outcome. We also revealed that patients with CD73+ /Pax-5+ and low CD8+ TILs or low absolute lymphocyte counts had unfavorable outcomes. Overall, our findings uncovered that patients with CD73+ on tumor cells as well as A2aR+ on TILs or low CD8+ TILs exhibited inferior survival, supporting potential combination strategies using CD73/A2aR immunosuppressive blockades as treatment options for DLBCL patients.

Production of nonnatural straight-chain amino acid 6-aminocaproate via an artificial iterative carbon-chain-extension cycle.

Bioplastics produced from microbial source are promising green alternatives to traditional petrochemical-derived plastics. Nonnatural straight-chain amino acids, especially 5-aminovalerate, 6-aminocaproate and 7-aminoheptanoate are potential monomers for the synthesis of polymeric bioplastics as their primary amine and carboxylic acid are ideal functional groups for polymerization. Previous pathways for 5-aminovalerate and 6-aminocaproate biosynthesis in microorganisms are derived from L-lysine catabolism and the citric acid cycle, respectively. Here, we show the construction of an artificial iterative carbon-chain-extension cycle in Escherichia coli for simultaneous production of a series of nonnatural amino acids with varying chain length. Overexpression of L-lysine α-oxidase in E. coli yields 2-keto-6-aminocaproate (2K6AC) as a non-native substrate for the artificial iterative carbon-chain-extension cycle. The chain-extended α-ketoacid products are decarboxylated and oxidized by an α-ketoacid decarboxylase and an aldehyde dehydrogenase, respectively, to yield their corresponding nonnatural straight-chain amino acids. The engineered system demonstrated simultaneous in vitro production of 99.16 mg/L of 5-aminovalerate, 46.96 mg/L of 6-aminocaproate and 4.78 mg/L of 7-aminoheptanoate after 8 h of enzyme catalysis starting from 2K6AC as the substrate. Furthermore, simultaneous production of 2.15 g/L of 5-aminovalerate, 24.12 mg/L of 6-aminocaproate and 4.74 mg/L of 7-aminoheptanoate was achieved in engineered E. coli. This work illustrates a promising metabolic-engineering strategy to access other medium-chain organic acids with -NH2, -SCH3, -SOCH3, -SH, -COOH, -COH, or -OH functional groups through carbon-chain-elongation chemistry.

Plasma soluble programmed death ligand 1 levels predict clinical response in peripheral T-cell lymphomas.

Immune checkpoints, including PD-1/PD-L1, play an important role in immunosuppression in various malignancies. Elevated levels of soluble programmed death ligand 1 (sPD-L1) are associated with worse prognosis in multiple myeloma and diffuse large B cell lymphoma. Herein, the purpose of this study is to investigate the relationships between plasma sPD-L1 levels and clinical response in peripheral T-cell lymphoma (PTCL) patients. A total of 37 PTCL patients and 20 healthy volunteers were enrolled. Peripheral blood from patients was collected prior to systemic therapy. Plasma levels of sPD-L1 and IFN-γ were measured by enzyme-linked immunosorbent assay (ELISA). PD-L1 expression in tissues was detected by immunohistochemistry (IHC). Clinical response for patients was evaluated. ONCOMINE database analyses showed that PD-L1 mRNA expression was significantly upregulated in PTCLs. The median sPD-L1 level was 0.729 ng/mL for 20 healthy volunteers and 1.696 ng/mL for 37 PTCL patients which was significantly higher than that in healthy volunteers (0.000). The sPD-L1 level was positively correlated with IFN-γ level (0.000, r = 0.849) and was also positively associated with clinical staging (0.045), LDH level (0.003), and ß2-MG level (0.045). Patients with high sPD-L1 level had lower overall response rate than those with low sPD-L1 level (88.9% vs 50.0%, 0.022) and tended to have poorer PFS and OS. PD-L1 expression in tissues matched very well with the sPD-L1 level in PTCL patients. In conclusion, PTCL patients had higher sPD-L1 level compared with healthy volunteers. High sPD-L1 level was correlated with worse clinical response, suggesting that sPD-L1 level was an underlying plasma biomarker to predict the prognosis for PTCL patients.

Predictive accuracy of serum total calcium for both critically high and critically low ionized calcium in critical illness.

BACKGROUND: The accuracy of total calcium and its corrected value for predicting critically high and critically low ionized calcium in critical illness is controversial. The aim of this study was to investigate whether the concentration of total serum calcium, either corrected for albumin or not, could predict critically high or low values in critical illness. METHODS: This report describes a retrospective study using the Medical Information Mart for Intensive Care (MIMIC) III database. Test panels that contained serum albumin, total calcium, and ionized calcium (named ATI panels) with order time intervals of less than one hour were extracted. The predictive accuracy of total calcium, either corrected for albumin or not, was assessed using receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 12 118 ATIs with 103 critically low and 92 critically high ionized calcium results were extracted. The areas under ROC curves (AUCs) of corrected and uncorrected total calcium for predicting critically low ionized calcium were 0.69 (95% CI: 0.61-0.76) and 0.70 (95% CI: 0.63-0.78), respectively. For predicting critically high ionized calcium, the AUCs were 0.98 (95% CI: 0.97-1.00) and 0.97 (95% CI: 0.95-1.00), respectively. With positive predictive values (PPVs) of 0.05 and 0.10, the sensitivities (both corrected and uncorrected) were approximately 0.50 for predicting critically low ionized calcium and 0.95 for predicting critically high ionized calcium. CONCLUSIONS: Total calcium, either corrected for albumin or not, is not a reliable test to predict critically low ionized calcium in critical illness. Total calcium's predictive accuracy for critically high ionized calcium is high.