ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

By examining the records related to the Fengfu （GV 16） acupoint in BIAN Que Heart Book （《扁鹊心书》） compiled by the Song Dynasty physician DOU Cai， this study analyzed various aspects， including the differentiation of conditions treated with Fengfu （GV 16） acupoint， the theoretical foundation for selection of Fengfu （GV 16） acupoint， the application of needling manipulation， and the sensation of obtaining qi during acupuncture. The findings suggest that DOU Cai's approach to utilizing Fengfu （GV 16） acupoint differs from traditional methods， particularly emphasizing the effectiveness of achieving a sensation of heat and numbness. His unique techniques include transverse insertion at Fengfu （GV 16） acupoint and penetrated insertion to Fengchi （GB 20） and Yifeng （TE 17） acupoints. The records of Fengfu （GV 16） acupoint in BIAN Que Heart Book provide a valuable reference for its modern clinical application and further development.

Endometriosis （EMT） is a common disease with frequent occurrence and difficult to be cured in modern clinical practice of obstetrics and gynaecology. It is characterized by progressively worsening dysmenorrhoea， pelvic mass， and infertility. The incidence of EMT is growing and increasingly younger patients are diagnosed with this disease， which poses a serious threat to the reproductive and psychological health of women of childbearing age and adolescent females. However， the pathogenesis of EMT is still not completely clear， and the disease has a long course. Therefore， developing new therapies is an urgent clinical problem to be solved. Great progress has been achieved in the treatment of EMT with traditional Chinese medicine （TCM）， while the underlying mechanism remains in exploration. Programmed cell death （PCD） is a cell death mode mediated by a variety of bio-molecules with specific signaling cascades. The known PCD processes include apoptosis， pyroptosis， autophagy， ferroptosis， and cuproptosis， which all play a pivotal role in the development of EMT. Researchers have made achievements in the treatment of EMT with TCM， which regulates PCD via multiple pathways， routes， targets， and mechanisms. However， the progress in the regulation of PCD in the treatment of EMT with TCM remains to be reviewed. This paper reviews the research progress in the treatment of EMT with TCM from five PCD processes （apoptosis， pyroptosis， autophagy， ferroptosis， and cuproptosis）， with the aim of providing a theoretical basis for the clinical prevention and treatment of EMT.

ObjectiveMicrotube associated protein-2 （MAP-2）， alpha-tubulin （α-tubulin）， and synaptophysin （SYP） are important proteins in neuronal signal communication. This paper observed the effects of modified Zhigancao Tang on the expression of serum α-Synuclein （α-Syn） and its oligomers， MAP-2， α-tubulin， and SYP of patients with liver and kidney deficiency of Parkinson's disease （PD）， analyzed their correlation， and evaluated the therapeutic effect of modified Zhigancao Tang in patients with liver and kidney deficiency of PD based on α-Syn transmission pathway mediated by neuronal communication in vivo. MethodsA total of 60 patients with PD who met the inclusion criteria were randomly divided into a treatment group （30 cases） and a control group （30 cases）. Both groups were treated on the basis of PD medicine， and the treatment group was treated with modified Zhigancao Tang. Both groups were treated for 12 weeks. The changes in UPDRS score， TCM syndrome score， and expression of serum α-Syn and its oligomers， MAP-2， α-tubulin， and SYP were observed before and after 12 weeks of treatment in each group. The correlation between the above-mentioned serum biological indexes and the levels of serum α-Syn and its oligomers was analyzed. ResultsAfter treatment， the TCM syndrome score， UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ score of the treatment group were significantly decreased （P<0.05， P<0.01）. The UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ scores in the treatment group were significantly decreased compared with those in the control group after treatment （P<0.05）. After treatment， the total effective rate of the control group was 63.3% （19/30）， and that of the treatment group was 86.7% （26/30）. The clinical effect of the observation group was better than the control group （Z=-2.03， P<0.05）. The total effective rate of the observation group was better than that of the control group， and the difference was statistically significant （χ²=5.136， P<0.05）. After treatment， the oligomer level of serum α-Syn and MAP-2 level in the treatment group were significantly decreased （P<0.05， P<0.01）. The levels of serum α-Syn and its oligomers， as well as α-tubulin in the treatment group， were significantly decreased compared with those in the control group after treatment （P<0.05， P<0.01）. Serum α-Syn was correlated with serum MAP-2 and α-Syn oligomer in patients with PD （P<0.05， P<0.01） but not correlated with serum SYP . Serum α-Syn oligomers of patients with PD were correlated with serum MAP-2 and α-tubulin （P<0.05， P<0.01） but not correlated with serum SYP level. Serum SYP of patients with PD was correlated with serum MAP-2 （P<0.05）. ConclusionModified Zhigancao Tang has a therapeutic effect on patients with liver and kidney deficiency of PD by inhibiting the production of α-Syn oligomers and intervening α-Syn microtubule transport pathway in vivo.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

AIM: To analyze the factors affecting non-contact intraocular pressure(IOPNCT)measurements after femtosecond laser-assisted small incision lenticule extraction(SMILE), explore the correlation of IOPNCT with central corneal thickness(CCT)and corneal curvature after SMILE, and construct the corresponding regression model which will provide scientific basis for clinical evaluation of the true IOP of patients after SMILE.METHODS: Data from a retrospective analysis of 107 myopic patients(206 eyes)who underwent SMILE and 107 myopic patients(201 eyes)received femtosecond laser-assisted in situ keratomileusis(FS-LASIK)surgery from June 2023 to May 2024 were examined. IOPNCT, CCT, and corneal curvature before surgery and at 1 and 3 mo were collected. The preoperative and postoperative IOPNCT, CCT and corneal curvature were analyzed by ANOVA and Pearson correlation analysis, and multiple linear regression models were constructed to evaluate the association of postoperative changes of IOPNCT, CCT and corneal curvature.RESULTS: There were significant differences in IOPNCT, CCT, and corneal curvature of both SMILE and FS-LASIK patients(all P<0.001), there was no significant difference between two groups and interaction effects(all P>0.05), and the IOPNCT, CCT and corneal curvature at 1 and 3 mo post-surgery were significantly lower than preoperative(all P<0.05). Pearson correlation analysis showed a positive correlation between IOPNCT and CCT at 1 and 3 mo after SMILE(r=0.261, 0.267, all P<0.001), but no significant correlation with corneal curvature(all P>0.05). Multiple linear regression analysis of IOPNCT with CCT and corneal curvature at 1 mo after SMILE indicated that the regression equation was: Y=3.426+0.019X1-0.058X2(Y represents IOPNCT, X1 represents the CCT, and X2 represents the corneal curvature), with statistical significant difference in the equation(F=7.654, P=0.001); the regression equation for 3 mo after surgery was: Y=2.056+0.020X1-0.038 X2(Y represents IOPNCT, X1 represents the CCT, and X2 represents the corneal curvature), with statistically significance in the equation(F=7.903, P<0.001). The regression equation of postoperative IOPNCT change(△IOPNCT)and intraoperative cutting corneal thickness(△CCT)and corneal curvature at 1 mo was Y=-2.252+0.008X1+0.587X2(Y represents △IOPNCT, X1 stands for the △CCT, X2 represents the corneal curvature change value), with statistical significant difference in the equation(F=17.550, P<0.001); the regression equation for 3 mo after surgery was: Y=-2.168+0.024X1+0.281X2(Y represents △IOPNCT, X1 represents △CCT, X2 indicates the corneal curvature change values), with statistical significant difference in the equation(F=16.030, P<0.001).CONCLUSION: After SMILE and FS-LASIK surgery, the IOPNCT value of patients was mainly affected by CCT compared with preoperative surgery, and the short-term use of hormone eye drops, fluorometholone, did not cause a significant increase in IOP; both the IOP correction formula at 1 and 3 mo postoperatively can be used clinically to evaluate and correct actual IOP in patients after SMILE.

AIM: To analyze the factors affecting non-contact intraocular pressure(IOPNCT)measurements after femtosecond laser-assisted small incision lenticule extraction(SMILE), explore the correlation of IOPNCT with central corneal thickness(CCT)and corneal curvature after SMILE, and construct the corresponding regression model which will provide scientific basis for clinical evaluation of the true IOP of patients after SMILE.METHODS: Data from a retrospective analysis of 107 myopic patients(206 eyes)who underwent SMILE and 107 myopic patients(201 eyes)received femtosecond laser-assisted in situ keratomileusis(FS-LASIK)surgery from June 2023 to May 2024 were examined. IOPNCT, CCT, and corneal curvature before surgery and at 1 and 3 mo were collected. The preoperative and postoperative IOPNCT, CCT and corneal curvature were analyzed by ANOVA and Pearson correlation analysis, and multiple linear regression models were constructed to evaluate the association of postoperative changes of IOPNCT, CCT and corneal curvature.RESULTS: There were significant differences in IOPNCT, CCT, and corneal curvature of both SMILE and FS-LASIK patients(all P<0.001), there was no significant difference between two groups and interaction effects(all P>0.05), and the IOPNCT, CCT and corneal curvature at 1 and 3 mo post-surgery were significantly lower than preoperative(all P<0.05). Pearson correlation analysis showed a positive correlation between IOPNCT and CCT at 1 and 3 mo after SMILE(r=0.261, 0.267, all P<0.001), but no significant correlation with corneal curvature(all P>0.05). Multiple linear regression analysis of IOPNCT with CCT and corneal curvature at 1 mo after SMILE indicated that the regression equation was: Y=3.426+0.019X1-0.058X2(Y represents IOPNCT, X1 represents the CCT, and X2 represents the corneal curvature), with statistical significant difference in the equation(F=7.654, P=0.001); the regression equation for 3 mo after surgery was: Y=2.056+0.020X1-0.038 X2(Y represents IOPNCT, X1 represents the CCT, and X2 represents the corneal curvature), with statistically significance in the equation(F=7.903, P<0.001). The regression equation of postoperative IOPNCT change(△IOPNCT)and intraoperative cutting corneal thickness(△CCT)and corneal curvature at 1 mo was Y=-2.252+0.008X1+0.587X2(Y represents △IOPNCT, X1 stands for the △CCT, X2 represents the corneal curvature change value), with statistical significant difference in the equation(F=17.550, P<0.001); the regression equation for 3 mo after surgery was: Y=-2.168+0.024X1+0.281X2(Y represents △IOPNCT, X1 represents △CCT, X2 indicates the corneal curvature change values), with statistical significant difference in the equation(F=16.030, P<0.001).CONCLUSION: After SMILE and FS-LASIK surgery, the IOPNCT value of patients was mainly affected by CCT compared with preoperative surgery, and the short-term use of hormone eye drops, fluorometholone, did not cause a significant increase in IOP; both the IOP correction formula at 1 and 3 mo postoperatively can be used clinically to evaluate and correct actual IOP in patients after SMILE.

Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.

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.

ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.