Objective: To compare the changes in the concentration of relevant growth factors released from platelet-rich plasma (PRP) stored at -80℃ by cryopreservation and at 4℃ by refrigerated lyophilization over 2 years, aiming to provide a theoretical basis for prolonging PRP storage duration. Methods: PRP (n=15) was separated using a blood cell separator and stored under -80℃ cryopreservation (F-PRP group) and 4℃ refrigerated freeze-drying conditions (FD-PRP group). The contents of growth factors (PDGF-AA, PDGF-BB, EGF, TGF-β1, and VEGF) in both groups were measured by ELISA at 1, 3, 6, 9, 12 and 24 months. Results: PDGF-AA and VEGF maintained good stability in both groups for up to 24 months. PDGF-BB and TGF-β1 showed high stability in the first 12 months but their stability decreased gradually from 12th to 24th months. EGF demonstrated good stability in the first 6 months, and its stability gradually decreased from the 9th to 24th months. Comparing the F-PRP and FD-PRP groups, the concentrations of the five growth factors in the FD-PRP group were either not statistically different or higher than those in the F-PRP group at all time points. Specifically, the concentrations of EGF were significantly higher in the FD-PRP group at all time points. Conclusion: Both -80℃ freezing and 4℃ freeze-drying enable long-term preservation of PRP. Freeze-drying imposes less stringent storage requirements and facilitates growth factor compared to frozen storage.

AIM:To observe the defocus state and myopia control in myopic children wearing single-vision, defocus, and orthokeratology lenses using multispectral refraction topography(MRT).METHODS: A total of 279 myopic patients aged 8-14 years old, with a spherical equivalent(SE)from -7.00 to -0.50 D, treated at the Chengdu Aier Eye Hospital from June 2022 to December 2023. Patients who volunteered for the study were assigned to three groups. A total of 94 cases were provided with single-vision spectacle lenses(SVL group), 90 cases received individualized ocular refraction customization(IORC group), and 95 cases received orthokeratology lenses(OK group). Simultaneously, the three groups were further categorized into low(-3.00 to -0.50 D), moderate(-6.00 to -3.25 D), and high myopia(-7.00 to -6.25 D)groups according to different SE. MRT was used to measure and compare the defocus changes of the retina in supperior, inferior, nasal, and temporal quadrants(RDV-S, RDV-I, RDV-N, RDV-T), and three angles of field of view, including 0-15°, 15°-30°, and 30°-45°(RDV-15, RDV-30, RDV-45)in the three groups(the data divide for the connected regions is grouped to the latter group). A one-way analysis of variance was used for intergroup comparisons. Univariate and multivariate linear regression analyses were used to analyze the factors related to changes in the axial length(AL)at 1 a after intervention.RESULTS:There were significant differences in 1-year SE and AL growth among patients in the SVL, IORC, and OK groups before and after intervention(P<0.001). The 1-year SE and the difference of AL growth in patients with low myopia was significantly different among SVL, IORC, and OK groups(P<0.001); however, there was no significant difference between the IORC and OK groups(P>0.05); there were significant differences in the SE and AL growth changes between the OK group and the IORC and SVL groups in moderate myopia(P<0.001); and there were significant differences between the OK group and the IORC and SVL groups in SE and AL growth of high myopia group after wearing lenses for 1 a(P<0.001), while there were no significant differences between the IORC and SVL groups(P>0.05). In addition, there were significant differences in the relative peripheral refractive errors(RPRE)of 4 quadrants and 3 eccentric regions among the three groups of patients in different degrees of myopia groups(P<0.001). Pair-wise comparison of the growth difference of eccentric D-RDV-15 in low myopia group after wearing lenses for 1 a showed significant differences between the SVL, IORC, and OK groups(P<0.001), but no significant differences between the IORC and OK groups(P>0.05). The angle of field of view D-RDV-30 in moderate myopia subgroups was statistically different between the SVL group and the IORC and OK groups after wearing lenses for 1 a(P<0.001), while the IORC and OK groups showed no significant differences(P>0.05); the angle of field of view D-RDV-15 in high myopia subgroups was statistically different between the OK group and the IORC and SVL groups after wearing lenses for 1 a(P<0.001), but there was no significant difference between the IORC and SVL groups(P>0.05). Univariate and multivariate linear regression model analysis showed that the changes in D-TRVD, D-RDV-45, D-RDV-N, and D-RDV-I correlated with the increase in the difference in 1 a AL.CONCLUSION: MRT can be used to guide the clinical control of myopia. Myopia development is related to the peripheral retinal defocus state, and the difference of defocus quantity in the inferior nasal side at 30°-45° eccentricity may be a factor regulating the rapid progression of myopia.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

Objective To analyze the trend of global cellulitis disease burden from 1990 to 2019, and to provide a theoretical basis for the prevention and control of cellulitis disease. Methods The Global Burden of Disease 2021 (GBD2021) data were collected, and data on the incidence, mortality, and disability-adjusted life year (DALY) of cellulitis were analyzed for each country worldwide. The estimated annual percentage change (EAPC) and age-standardized rate (ASR) were used to estimate the trend change of cellulitis from 1990 to 2021. Results The global burden of cellulitis increased significantly in 2021, with 55.96 million cases, 28.9 million deaths and 876.1 million DALYs, respectively. Incidence and mortality rates were generally higher in males than in females. The incidence and DALYs were higher in high SDI regions, with the highest burden observed in South Asia. In contrast, East Asia exhibited the lowest burden and demonstrated a declining trend. There were significant differences between countries, with India having the highest prevalence, the United States having the highest incidence, and Bahrain having the fastest growing rate.In 2021, China had the lowest age-standardised incidence of cellulitis in the world and the fastest declining age-standardised incidence and age-standardised DALYs. Conclusion The global disease burden of cellulitis is increasing from 1990-2021, and cellulitis remains an an important global public health problem. Targeted preventive meausres should be taken in areas with different economical levels. Men, middle-aged and elderly people, and newborns are the key groups in need of attention and health education.

Objective To analyze the trend of global cellulitis disease burden from 1990 to 2019, and to provide a theoretical basis for the prevention and control of cellulitis disease. Methods The Global Burden of Disease 2021 (GBD2021) data were collected, and data on the incidence, mortality, and disability-adjusted life year (DALY) of cellulitis were analyzed for each country worldwide. The estimated annual percentage change (EAPC) and age-standardized rate (ASR) were used to estimate the trend change of cellulitis from 1990 to 2021. Results The global burden of cellulitis increased significantly in 2021, with 55.96 million cases, 28.9 million deaths and 876.1 million DALYs, respectively. Incidence and mortality rates were generally higher in males than in females. The incidence and DALYs were higher in high SDI regions, with the highest burden observed in South Asia. In contrast, East Asia exhibited the lowest burden and demonstrated a declining trend. There were significant differences between countries, with India having the highest prevalence, the United States having the highest incidence, and Bahrain having the fastest growing rate.In 2021, China had the lowest age-standardised incidence of cellulitis in the world and the fastest declining age-standardised incidence and age-standardised DALYs. Conclusion The global disease burden of cellulitis is increasing from 1990-2021, and cellulitis remains an an important global public health problem. Targeted preventive meausres should be taken in areas with different economical levels. Men, middle-aged and elderly people, and newborns are the key groups in need of attention and health education.

OBJECTIVE To establish a content determination method for multiple components in Sophora flavescens from different origins and to evaluate its quality by combining with chemometrics. METHODS Thirteen batches （No. K1-K13） of S. flavescens from different origins were selected as test samples. A high-performance liquid chromatography-tandem triple quadrupole mass spectrometry （HPLC-MS/MS） method was established to determine the contents of 12 components， including matrine， oxymatrine， betaine， cytisine， N-methylcytisine， sophoridine， genistein， sophoricoside， sophorone， formononetin， sophorolone Ⅰ and norkurarinone in S. flavescens. Chromatographic separation was performed on a Shim-pack GIST-HP C18 column with a mobile phase consisting of methanol （A） and water containing 0.1% formic acid （B）， using gradient elution at a flow rate of 0.25 mL/min， column temperature of 35 ℃， and an injection volume of 3 μL. Mass spectrometry was conducted using an electrospray ionization source with positive and negative ion scanning. Data were collected in segments using the multiple reaction monitoring mode. Technique for order preference by similarity to ideal solution （TOPSIS） and grey relational analysis （GRA）methods were employed to compare and comprehensively evaluate the 13 batches of S. flavescens from different origins. RESULTS The methodological validation for the content determination met the relevant regulatory requirements. The contents of the 12 components were 490.66-1 231.00， 11 088.10- 18 021.50， 7.91-25.38， 903.97-1 713.64， 336.08-1 485.54，1 065.33-2 075.50， 27.52-71.80， 109.36-517.83， 6 034.55-10 632.73， 21.26-145.35， 814.84-1 911.32， 1 040.87-3 446.37 μg/g）， respectively. TOPSIS results showed that the top 7 samples in Euclidean distance ranking were K6， K12， K11， K3， K5， K10， K13. The GRA results showed that the top 7 samples in the relative correlation ranking were K12， K11， K10， K6， K13， K5， K3. CONCLUSIONS The established HPLC-MS/MS method is rapid， accurate， highly sensitive， stable and reliable. Combined with chemometrics methods， it can be used for the quality control and evaluation of S. flavescens. The comprehensive quality of samples K3， K5， K6（ from Hebei）， K10（ from Sichuan）， K11-K13（ from Shanxi）， etc. is relatively superior.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

Oxidative stress can activate multiple inflammatory pathways， triggering and exacerbating psoriasis lesions. In traditional Chinese medicine （TCM）， blood turbidity refers to a pathological condition in which harmful stimuli or unhealthy lifestyle habits lead to an accumulation of impurities in the blood， resulting in increased viscosity and impaired circulation. Based on the correlation between blood turbidity theory in TCM and the pathological changes of oxidative stress in modern medicine， this paper explored the TCM diagnosis and treatment of psoriasis， proposing that spleen deficiency with latent turbidity is the fundamental cause of the disease. The pathological progression of psoriasis was outlined as follows， spleen deficiency with latent turbidity→phlegm and blood stasis intertwining→internal generation of toxic pathogens. Targeting oxidative stress， the study suggests syndrome differentiation and treatment with angle medicine （角药， means three medicinals combination）. The treatment strategy divided into three stages. For early stage， strengthening the spleen and directing the turbid downward， emphasizing prevention before onset， with angle medicine of Huangqi （Astragali Radix） - Fuling （Poria） - Baizhu （Atractylodis macrocephalae rhizoma） to treat； for middle stage， resolving phlegm and dispersing blood stasis， preventing disease progression， if patient with more phlegm syndrome treated with angle medicine of Banxia （Pinelliae rhizoma） - Chenpi （Citri reticulatae pericarpium） - Zhexie （Alismatis rhizoma）， and if patient with more stasis syndrome treated with Zicao （Arnebiae Radix） - Jixueteng （Spatholobi caulis） - Shouwuteng （Polygonum multiflorum Thunb）； for late stage， resolving toxins and dispelling pathogens， balancing both attack and supplementation， with Quanxie （Scorpio） - Tufuling （Smilacis glabrae rhizoma） - Shudihuang （Rehmanniae radix praeparata） to treat.