The efficient production of L-glutamate is dependent on the product's rapid efflux, hence researchers have recently concentrated on artificially modifying its transport system and cell membrane wall structure. Considering the unique composition and structure of the cell wall of Corynebacterium glutamicum, we investigated the effects of CmpLs on L-glutamate synthesis and transport in SCgGC7, a constitutive L-glutamate efflux strain. First, the knockout strains of CmpLs were constructed, and it was confirmed that the deletion of CmpL1 and CmpL4 significantly improved the performance of L-glutamate producers. Next, temperature-sensitive L-glutamate fermentation with the CmpL1 and CmpL4 knockout strains were carried out in 5 L bioreactors, where the knockout strains showcased temperature-sensitive characteristics and enhanced capacities for L-glutamate production under high temperatures. Notably, the CmpL1 knockout strain outperformed the control strain in terms of L-glutamate production, showing production and yield increases of 69.2% and 55.3%, respectively. Finally, the intracellular and extracellular metabolites collected at the end of the fermentation process were analyzed. The modification of CmpLs greatly improved the L-glutamate excretion and metabolic flux for both L-glutamate production and transport. Additionally, the CmpL1 knockout strain showed decreased accumulation of downstream metabolites of L-glutamate and intermediate metabolites of tricarboxylic acid (TCA) cycle, which were consistent with its high L-glutamate biosynthesis capacity. In addition to offering an ideal target for improving the stability and performance of the industrial strains for L-glutamate production, the functional complementarity and redundancy of CmpLs provide a novel target and method for improving the transport of other metabolites by modification of the cell membrane and cell wall structures in C. glutamicum.
Corynebacterium glutamicum/genetics* ; Glutamic Acid/biosynthesis* ; Fermentation ; Metabolic Engineering ; Bacterial Proteins/metabolism* ; Bioreactors/microbiology* ; Gene Knockout Techniques

Objective To explore the method of objective identification of color information in sublingual veins diagnosis of TCM.Methods Combined with computer vision,compact fully convolution networks(CFCNs)and 19 deep learning classification models were used for study,and a double pulse rectangle algorithm was designed as a means of segmentation and recognition of sublingual veins and color information extraction.Results The accuracy of segmentation of tongue bottom obtained by the method of removing reflection + data expanding + data post-processing was 0.955 9,F1 value was 0.947 3,and mIoU value was 0.900 0.The accuracy of segmentation of sublingual veins obtained by the method of removing reflection + tongue input + data expanding + corrosion expansion was 0.778 4,F1 value was 0.738 3 and mIoU value was 0.585 1,which were obviously superior to the current classic or improved U-net model.On the color classification of sublingual veins,the best classification model was DenseNet161-bc-early_stopping with an accuracy rate of 0.803 7.Conclusion The deep learning method has a certain effect on identifying the color information of sublingual veins in TCM,which provides a new method for the research of quantitative color detection technology of sublingual veins diagnosis in TCM.

Objective:To investigate the correlation between peripheral blood lymphocyte immunophenotyping,cytokine levels before and after immune and anti-angiogenesis combined therapy,and treatment efficacy as well as prognosis in patients with advanced mucosal melanoma.Methods:A total of 28 patients with advanced mucosal melanoma admitted to the Drum Tower Hospital of Nanjing University School of Medicine from April 2019 to June 2022 were included in this analysis.All patients received combined treatment of camrelizumab(PD-1 inhibitor)and apatinib(anti-angiogenic drug).Peripheral blood samples were collected before treatment and after two cycles of treatment for lymphocyte immunophenotyping and cytokine level testing.The correlation between these immune markers and treatment efficacy as well as patient prognosis was evaluated.Results:After two cycles of treatment with camrelizumab and apatinib in patients with mucosal melanoma,the proportion of PD-1 positive cytotoxic T lymphocytes(CD3+CD8+CD279+cells)in peripheral blood was significantly reduced(P<0.001),while the proportion of NK cells(CD3-CD16+CD56+cells)was significantly increased(P=0.0054).Pre-treatment peripheral blood IFN-γ levels were found to be associated with overall survival(OS)(P=0.013).Patients with low IFN-γ levels had a median OS of 329 days,while the median OS for patients with high IFN-γ levels was not reached.Higher baseline IFN-γ levels were associated with a greater benefit in progression-free survival(PFS).Conclusion:The proportion of PD-1-positive T lymphocytes,NK cells and IFN-γ levels in peripheral blood may have predictive value for the efficacy and prognosis of advanced mucosal melanoma patients undergoing immunotherapy and anti-angiogenesis combined therapy.Future large-sample studies are needed to better characterize the clinical potential of these markers.

Petrochemical-derived polyester plastics such as polyethylene terephthalate (PET) and polybutylene adipate terephthalate (PBAT) have been widely used. However, the difficulty to be degraded in nature (PET) or the long biodegradation cycle (PBAT) resulted in serious environmental pollution. In this connection, treating these plastic wastes properly becomes one of the challenges of environment protection. From the perspective of circular economy, biologically depolymerizing the waste of polyester plastics and reusing the depolymerized products is one of the most promising directions. Recent years have seen many reports on polyester plastics degrading organisms and enzymes. Highly efficient degrading enzymes, especially those with better thermal stability, will be conducive to their application. The mesophilic plastic-degrading enzyme Ple629 from the marine microbial metagenome is capable of degrading PET and PBAT at room temperature, but it cannot tolerate high temperature, which hampers its potential application. On the basis of the three-dimensional structure of Ple629 obtained from our previous study, we identified some sites which might be important for its thermal stability by structural comparison and mutation energy analysis. We carried out transformation design, and performed expression, purification and thermal stability determination of the mutants. The melting temperature (T_m) values of mutants V80C and D226C/S281C were increased by 5.2 ℃ and 6.9 ℃, respectively, and the activity of mutant D226C/S281C was also increased by 1.5 times compared with that of the wild-type enzyme. These results provide useful information for future engineering and application of Ple629 in polyester plastic degradation.
Plastics/metabolism* ; Polyethylene Terephthalates/metabolism* ; Biodegradation, Environmental ; Metagenome

To explore the changes in metabolites in the greasy tongue coating in patients with chronic gastritis.

The ensemble empirical mode decomposition (EEMD) can be used to overcome the mode mixing problem of empirical mode decomposition (EMD) effectively. The EEMD method and Hilbert-Huang Transform (HHT) can be used to analyze pulse signals of Traditional Chinese Medicine (TCM). The amplitudes of the added white noise were about 0.1 and 0.2 time standard deviation of the investigated signal respectively. The difference of average frequency and average energy of every mode between normal pulse, slippery pulse, wiry pulse and wiry-slippery pulse were demonstrated based on different amplitudes of the added white noise. The results showed that it is more in line with clinical practice when the amplitude of the added white noise is about 0.2 time standard deviation of the investigated signal.
Algorithms ; Artifacts ; Diagnosis, Differential ; Humans ; Medicine, Chinese Traditional ; methods ; Pulse ; Signal Processing, Computer-Assisted

The lip color of a person is closely related to his or her health in the visual diagnosis of traditional Chinese medicine (TCM). The traditional method to judge the color of lips is through observing by a TCM doctor. The diagnosis result is affected not only by the doctor's knowledge and diagnosis experience, but also by the light, temperature and other environmental impacts. For these reasons, sometimes different doctors may make different judgement for the same lips. So it is urgently needed that an objective evaluation as reference for doctors can be obtained. A method based on support vector machine (SVM) that classifies lip color by computer automatically is presented in the present paper. Firstly, nine features of lip color in Hue, Saturation and Intensity (HSI) color space were extracted. Then, according to different combinations of these features five different experiments were conducted. By comparing the results of these experiments, it was discovered that the mean value is one of the most important features for the lip color. The overall effect of classification is better when the mean value and variance of HSI were chosen than other characteristics. In addition, experiments results demonstrated that the accuracy rate of classification is not improved when more features were adopted. The objective of the present paper is to select the appropriate characteristics and to combine them effectively to classify lip colors.
Color ; Diagnosis, Differential ; Lip ; Medicine, Chinese Traditional ; methods ; Pattern Recognition, Automated ; methods ; Support Vector Machine

Objective To Screen serum protein markers related to CRF and establish a diagnosis model,exploring and discussing its significance in serodiagnosis by comparing differences of serum protein spectrum expression between patients with chronic renal failure (CRF) and control group.Methods The trial included 62 CRF patients and 28 control ones.Serum samples were tested by surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS).The data were analyzed to screen serum proteomic biomarkers.By bioinformatics analysis,decision classification tree models were to be established and tested.Results A total of 19 effective protein peaks were significantly different between CRF and normal control (P＜0.001) at m/z range of 1 500 to 30 000,among which 18 showed low expression and 1 showed high expression in CRF.CRF and normal control were obviously different in the clustering;By bioinformatics analysis,a CRF-normal controls of the diagnostic decision tree model was developed,which was 87.8% in with prediction accuracy rate of 87.8% sensitivity of 87.1% and a specificity of 89.3%.Condusion Diagnostic decision tree model provides a more accurate prediction and solid experimental evidence for early clinical diagnosis.

Abstract: In this paper, factors contributing to the formation of pulse wave were analyzed based on hemodynamic principles. It is considered that formation of pulse wave was related to its propagation and reflection characteristics. Propagation of the pulse wave was characterized by pulse wave velocity, and reflection of the pulse wave was characterized by reflection coefficient. Pulse wave velocity and reflection coefficient were proposed as the eigenvectors of pulse wave in pulse diagnosis of traditional Chinese medicine, and support vector machine (SVM) was used to recognize slippery pulse, stringy pulse and plain pulse. Pulse wave velocity and reflection coefficient of the slippery, stringy and plain pulses in healthy people were calculated in this study, and SVM with Gaussian radial basis function was used for classifying. Results showed that pulse wave velocity and reflection coefficient with physiological and pathological significance had advantages in distinguishing slippery pulse, stringy pulse and plain pulse, which offered a new idea for recognizing pulse condition.

To develop an inquiry scale for diagnosis of heart system syndromes, and to discuss the provisional standardization of the inquiry method in traditional Chinese medicine (TCM).