ObjectiveTo explore the clinical efficacy of oral administration of modified Tuoli Xiaodusan on postoperative patients with perianal abscess， and its effects on related inflammatory factors and signal transducers and activators of transcription protein 3 （STAT3）/vascular endothelial growth factor （VEGF） signaling pathways. MethodsFrom January 2023 to December 2023 in Inner Mongolia hospital of traditional Chinese medicine， 60 postoperative patients with perianal abscess who met the inclusion criteria were selected. They were divided into a treatment group and a control group using the random number table method， with 30 cases in each group. The control group received conventional treatment， while the treatment group received additional treatment with modified Tuoli Xiaodusan on the basis of the control group. The course of treatment in both groups was three weeks. On the day of operation and on the 7^th， 14^th and 21^st day after operation， enzyme-linked immunosorbent assay （ELISA） was used to measure the expression levels of serum interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α）. Hematoxylin eosin （HE） staining was used to observe the pathological morphology of pathological tissue. Western blot was used to measure the levels of phosphorylated STAT3 （p-STAT3） and vascular endothelial growth factor （VEGF） proteins， and real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to determine the expression level of VEGF mRNA. The clinical efficacy of the two groups was compared according to the wound pain， secretion volume score， and healing rate of patients on the 3^rd， 7^th， 14^th， and 21^st day after operation. ResultsThe total effective rate of the treatment group was higher than that of the control group （P<0.05）. For intra-group comparison， the pain score of the control group decreased at each time period （P<0.05）， and the healing rate increased （P<0.05）. The secretion volume score decreased on the 14^th and 21^st days after operation （P<0.05）. The pain score and secretion volume score of the treatment group decreased at each time period （P<0.05）， and the healing rate increased （P<0.05）. The levels of various inflammatory factors decreased in both groups （P<0.05）. Compared with those on the surgical day， the levels of p-STAT3 and VEGF proteins in the wound tissue of the two groups were different on the 7^th and 21^st days after operation （P<0.05）. There were significant differences in VEGF mRNA levels in wound tissue between the two groups at each time period （P<0.01）. For inter-group comparison， on the 7^th and 14^th days after operation， the pain score in the treatment group was lower than that in the control group. On the 7^th， 14^th and 21^st days after operation， the secretion volume scores and healing rate of the treatment group were better than those of the control group （P<0.05）. The levels of various inflammatory factors in the treatment group were lower than those in the control group （P<0.05）， and the decline rate was faster （P<0.05）. On the 7^th day after operation， the levels of p-STAT3， VEGF protein， and VEGF mRNA in the wound tissue of the treatment group were higher than those in the control group （P<0.05）. HE staining showed that the inflammatory cell infiltration in the treatment group decreased faster. The cell arrangement was more orderly， and new blood vessel lumens were visible. There were no abnormalities in the safety observation indexes of all patients during the study period. ConclusionModified Tuoli Xiaodusan can relieve wound pain after perianal abscess surgery， reduce secretions， and improve wound healing rate. The mechanism may be reducing the levels of serum IL-1β， IL-6， and TNF-α， reducing the inflammatory response of the wound， upregulating the expression of p-STAT3 and VEGF proteins， and stimulating the STAT3/VEGF signaling pathway， thereby accelerating angiogenesis and promoting wound healing.

OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

ObjectiveTo explore the potential mechanism of moxibustion at Guanyuan （CV 4） in delaying skin photoaging. MethodsThirty-two male Wistar rats were randomly divided into four groups， namely blank group， model group， vitamin E group， and moxibustion group， with 8 rats in each group. Except for the blank group， dorsal skin of rats were exposed to ultraviolet （UV） radiation to establish a skin photoaging model. One week after modeling， the moxibustion group received moxibustion at "Guanyuan （CV 4）" once a day， five days per week； the vitamin E group received vitamin E （25 mg/kg·d） once a day by gavage， five days per week； the blank group， model group， and moxibustion group received an equivalent volume of normal saline via gavage； the intervention lasted for 7 weeks. After 7 weeks， dorsal skin tissues were collected to analyze the following indicators， such as skin tissue moisture content， histomorphological changes using hematoxylin-eosin （HE） staining， Collagen Ⅰ and collagen Ⅲ content using ELISA. Malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， superoxide dismutase （SOD）， hydrogen peroxide （H₂O₂）， and catalase （CAT） activity in skin tissue were dectected. Western Blot was used to determin autophagy-related proteins， including microtubule-associated protein 1A/1B-light chain 3 （LC3）， polyubiquitin-binding protein （p62）， and autophagy-specific gene （Beclin-1）； LC3， p62， and Beclin-1 mRNA expression was detected via qRT-PCR， and autophagosome formation was observed using transmission electron microscopy （TEM）. ResultsHE staining showed that the epidermal structure in the blank group was orderly and evenly thick， while the model group exhibited uneven epidermal thickness. In the moxibustion group， the epidermis was well-structured， smooth， and uniform， with densely arranged dermal layers； the epidermis in the vitamin E group was thicker than that in the model group. Compared with the blank group， the model group exhibited decreased skin moisture content and reduced level of Collagen Ⅰ and collagen Ⅲ， reduced SOD， CAT， and GSH-Px activity in skin tissue， increased H₂O₂ and MDA activity， elevated p62 protein and mRNA expression， reduced LC3 and Beclin-1 protein and mRNA expression （P＜0.05 or P＜0.01）. Compared with the model group， the moxibustion group showed significant improvement in all these indicators （P＜0.05 or P＜0.01）； whereas the vitamin E group did not show a statistically significant difference in Collagen Ⅰ and collagen Ⅲ levels （P＞0.05）. TEM results showed that， compared with the blank group， the model group had atrophic skin cells， extensive mitochondrial vacuolization， and degraded cellular structures； the moxibustion group exhibited crescent- or cup-shaped autophagosomes with a significantly increased number of autophagosomes per unit area， whereas the vitamin E group showed less improvement than the moxibustion group. ConclusionMoxibustion at "Guanyuan （CV 4）" may alleviate skin photoaging by regulating oxidative stress imba-lance， modulating cellular autophagy， and promoting collagen synthesis， thereby slowing the aging process of the skin.

ObjectiveTo establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors. MethodsPatients aged ≥18 years，diagnosed with coronary heart disease through coronary angiography from January 2013 to May 2020 in two prominent hospitals in Shanxi Province， were continuously enrolled. Logistic regression，back propagation neural network （BPNN）， and random forest（RF）algorithms were used to construct models for detecting the causative factors of coronary artery stenosis. Sensitivity （TPR）， specificity （TNR）， accuracy （ACC）， positive predictive value （PV+）， negative predictive value （PV-）， area under subject operating characteristic curve （AUC）， and calibration curve were used to compare the discrimination and calibration performance of the models. The best model was then employed to predict the main risk variables associated with coronary stenosis. ResultsThe RF model exhibited superior comprehensive performance compared to logistic regression and BPNN models. The TPR values for logistic regression，BPNN，and RF models were 75.76%， 74.30%， and 93.70%， while ACC values were 74.05%， 72.30%， and 79.49%， respectively. The AUC values were：logistic regression 0.739 9； BPNN 0.723 1； RF 0.752 2. Manifestations such as chest pains，abnormal ST segments on ECG，ventricular premature beats with hypertension， atrial fibrillation， regional wall motion abnormalities（RWMA） by color echocardiography， aortic regurgitation（AR）， pulmonary insufficiency （PI）， family history of cardiovascular diseases，and body mass index（BMI）were identified as top ten important variables affecting coronary stenosis according to the RF model. ConclusionsRandom forest model shows the best comprehensive performance in identification and accurate assessment of coronary artery stenosis. The prediction of risk factors affecting coronary artery stenosis can provide a scientific basis for clinical intervention and help to formulate further diagnosis and treatment strategies so as to delay the disease progression.

The analysis presented here is based on the blood components of Guanxin Qiwei tablets, the key anti-atherosclerosis pathway of Guanxin Qiwei tablets was screened by network pharmacology, and the anti-atherosclerosis mechanism of Guanxin Qiwei tablets was clarified and verified by cell experiments. HPLC-Q-Exactive-MS/MS technique was used to analyze the components of Guanxin Qiwei tablets into blood, to determine the precise mass charge ratio of the compounds, and to conduct a comprehensive analysis of the components by using secondary mass spectrometry fragments and literature comparison. Finally, a total of 42 components of Guanxin Qiwei tablets into blood were identified. To better understand the interactions, we employed the Swiss Target Prediction database to predict the associated targets. Atherosclerosis (AS) disease targets were searched in disease databases Genecard, OMIM and Disgent, and 181 intersection targets of disease targets and component targets were obtained by Venny 2.1.0 software. Protein interactions were analyzed by String database. The 32 core targets were selected by Cytscape software. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed in DAVID database. It was found that the anti-atherosclerosis pathways of Guanxin Qiwei tablets mainly include lipid metabolism and atherosclerosis and AGE-RAGE signaling pathway in diabetic complications and other signal pathways. The core targets and the core compounds were interlinked, and it was found that cryptotanshinone and tanshinone ⅡA in Guanxin Qiwei tablets were well bound to TNF, PPARγ, AKT1, PTG2 and other targets. The lipid metabolism and atherosclerotic pathway was verified using human hl-7702 hepatocytes. This study preliminarily identified the potential pharmacodynamic components of Guanxin Qiwei tablets in the treatment of AS diseases and predicted their pathways of action, and verified the relationship between regulating lipid metabolism and atherosclerosis of Guanxin Qiwei tablets in vitro, providing a reference for the further study of the pharmacodynamic material basis and mechanism of action of this prescription. This experiment was approved by the Medical Ethics Committee of Inner Mongolia Medical University (No. YKD202401262).

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

To investigate the awareness of cognitive impairment disorders among residents of the Xizang Autonomous Region and its influencing factors, thereby providing a basis for targeted prevention and treatment efforts.

Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.