Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

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 summarize and analyze relevant literature on image feature extraction,segmentation,and classification of tongue and facial diagnosis,we explore the research hotspots and development trends in this field and provide ideas for future research on image processing of tongue and facial diagnosis.Methods China National Knowledge Infrastructure was used as the data source,and 439 papers were included according to the exclusion criteria,the inclusion criteria,and the search strategy.Finally,Gephi software was applied to visualize and analyze the co-word network of authors,research institutions,and keywords of relevant literature.Results The overall number of articles issued is low as seen in the annual volume,but the overall trend is steadily increasing.The research team is mainly represented by the team of Li Fufeng,Zhang Xinfeng,Xu Jiatuo,Wang Yiqin,and Wang Hongwu.Most of the research institutes are regional medical-industrial crossover collaborations.Conclusion Hot research trends gradually toward deep learning for image processing.Meanwhile,teamwork across regions and institutions needs to be strengthened.It is recommended to further promote the development of multidisciplinary cross-fertilization and intelligent and objective quantification of Traditional Chinese Medicine diagnosis(tongue and face diagnosis).

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

Objective To explore the auricular application pressure added dietary intervention of perimeno-pausal syndrome (PS)the influence of women's sex hormone levels.Methods Research subjects were randomly divided into two groups.The observation group was given auricular application pressure to add dietary intervention, control group was given dietary intervention alone.Before and after six months of follow -up,sex hormone levels in the blood were monitored.Results After the intervention,the estrogen level of the observation group was (272.93 ± 15.71)pmol/L,progesterone was (3.14 ±0.47)nmol/L,which of the control group was (186.32 ±12.80)pmol/L, (2.86 ±0.34)nmol/L;After the intervention,the follicular thorn hormone content of the two groups were decreased, which of the observation group was (12.88 ±1.50)U /L,which of the control group was (21.35 ±4.70)U /L;The perimenopausal symptoms were reduced,Kuppermun score in the observation group were (9.36 ±1.41 )points, (10.43 ±1.63)points,the difference between the two groups were statistically significant (t =40.15,4.52,3.82, 4.65,all P <0.01)for the control group.Conclusion Auricular application press fit dietary intervention for patients with perimenopausal syndrome sex hormone regulation of metabolic disorders has obvious effect,can significantly improve the patients'symptoms of the menopausal transition,it is worthy of further research on intervention measures.

The technical structure of a low-cost thermal imaging system (TIM) lunched on a mobile phone was investigated, which consists of a thermal infrared module and mobile phone and application software. The designing strategies and technical factors toward realizing various TIM array performances are interpreted, including sensor cost and Noise Equivalent Temperature Difference (NETD). In the software algorithm, a mechanism for scene-change detection was implemented to optimize the efficiency of non-uniformity correction (NUC). The performance experiments and analysis indicate that the NETD of the system can be smaller than 150 mK when the integration time is larger than 16 frames. Furthermore, a practical application for human temperature monitoring during physical exercise is proposed and interpreted. The measurement results support the feasibility and facility of the system in the medical application.
Algorithms ; Body Temperature ; Cell Phone ; Humans ; Infrared Rays ; Mobile Applications

Objective To study the effect of modified indwelling catheterization method for the prevention of urethral injury. Methods A total of 136 cases of urethral catheterization were randomly divided into two groups. The observation group had 68 cases using the conventional catheterization method, and the control group had 68 cases using the modified indwelling catheterization method, respectively. The time of inserting catheter, indwelling catheter time, removal time of the catheter, and the incidence of blood urine were compared between two groups. Results The time of inserting catheter, indwelling catheter time, removal time of the catheter, and the incidence of blood urine were significantly of the observation group were significantly lower than those of the control group (χ2 =6. 81,3. 89,8. 38,28. 57, respectively; P<0. 05). The incidence of leakage of urine had no significant difference (P>0. 05). Conclusions The modified indwelling catheterization method can reduce the occurrence of hematuria traumatic urethral and it is worthy of application in clinical environment.

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).