Poloxamer， as a non-ionic surfactant， exhibits a unique triblock [polyethylene oxide-poly （propylene oxide）-polyethylene oxide] structure， which endows it with broad application potential in various fields， including solid dispersion technology， nanotechnology， gel technology， biologics， gene engineering and 3D printing. As a carrier， it enhances the solubility and bioavailability of poorly soluble drugs. In the field of nanotechnology， it serves as a stabilizer etc.， enriching preparation methods. In gel technology， its self-assembly behavior and thermosensitive properties facilitate controlled drug release. In biologics， it improves targeting efficiency and reduces side effects. In gene engineering， it enhances delivery efficiency and expression levels. In 3D printing， it provides novel strategies for precise drug release control and the production of high-quality biological products. As a versatile material， poloxamer holds promising prospects in the pharmaceutical field.

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.

ObjectiveTo identify the active constituents of Kaixuan Jiedu core prescription （KXJD） and investigate its effective components and therapeutic targets in the treatment of common psoriasis. MethodsUltra-performance liquid chromatography-high resolution mass spectrometry （UPLC-Q-TOF MS） was used to identify and analyze the chemical components of KXJD and its blood-entering chemical components. The chemical components of the single decoction were further identified to clarify the source of the chemical components in KXJD. Then， all identified blood-entering compounds were screened for effective active ingredients through the Swiss ADME database. The active ingredient targets of KXJD were searched on the Swiss Target Prediction platform. The targets of common psoriasis were searched in OMIM， GEO， GeneCards， and DISGNET databases to obtain drug-disease intersection targets. The protein-protein interaction network of intersection targets was constructed using STRING， and then the core blood-entering component-intersection target network of KXJD was constructed. The core target proteins in the network were selected for molecular docking with the core components of KXJD. Small molecules and proteins were pretreated， and appropriate docking sites were selected. AutoDock Vina software was used for continuous local search and repeated iterations to find molecular docking conformations. PyMOL software and LigPlot+ software were used for analysis and visualization. Subsequently， the verification was carried out through animal experiments. SPF-grade male C57 mice were randomly divided into a blank group， a model group， a positive drug methotrexate group， and a KXJD group. In the model group， the methotrexate group， and the KXJD group， imiquimod was applied to the backs of the mice for modeling. The blank group and the model group were administered normal saline by gavage， while the methotrexate group and the KXJD group were respectively administered 1 mg·kg^-1 suspension and 30.42 g·kg^-1 decoction of traditional Chinese medicine by gavage. Five days after administration， the mice were sacrificed， and samples were collected. Hematoxylin-eosin （HE） staining was used to observe the skin tissue samples of mice， and the effect of KXJD on the pathological manifestations of psoriasis mice was analyzed. The expression areas of tumor necrosis factor-α （TNF-α）， cyclooxygenase 2 （PTGS2）， interleukin （IL）-1β， and IL-6 in the skin tissue of mice were detected by immunohistochemistry （IHC）. The mRNA expressions of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of mice were detected by real-time fluorescent quantitative polymerase chain reaction （Real-time PCR）. ResultsIn this study， 208 compounds in KXJD were identified by UPLC-Q-TOF MS， and 44 compounds were detected in serum， including 28 prototype components and 16 metabolites. 12 blood-entering active components were screened， and 1 153 active component targets and 1 076 psoriasis-related targets were identified. Eighty-five targets in the intersection set were drug-disease common targets. PPI network analysis showed that TNF-α， IL-1β， IL-6， PTGS2， and ALB were the key target proteins. The results of molecular docking showed that the binding ability of （+）-hexylphenylglycolic acid to key target proteins such as PTGS2 was stable， and PTGS2 showed high stability with a variety of core compounds. Compared with those in the blank group， the stratum corneum and epidermis in the model group mice were significantly thickened， and the pathological Baker score of the mice's skin in the model group was significantly higher than that of the blank group （P<0.01）. The expression areas of PTGS2， TNF-α， IL-1β， and IL-6 proteins in the skin tissue of the model group mice were significantly increased （P<0.01）， and the expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the model group mice were significantly elevated （P<0.01）. Compared with the model group， the pathological Baker scores of the methotrexate group and the KXJD group were both decreased （P<0.01）， and the expression areas in the skin tissue of the methotrexate group and the KXJD group were significantly reduced （P<0.05， P<0.01）. The expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the methotrexate group and the KXJD group were significantly decreased （P<0.01）. ConclusionKXJD can effectively improve the skin lesions of psoriasis model mice and reduce the expression of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of psoriasis model mice. PTGS2 has a stable binding ability with a variety of compounds in the decoction， which may be a key target for the treatment of psoriasis. The compound （+）-hexylphenylglycolic acid may play a key role.

ObjectiveTo identify the active constituents of Kaixuan Jiedu core prescription （KXJD） and investigate its effective components and therapeutic targets in the treatment of common psoriasis. MethodsUltra-performance liquid chromatography-high resolution mass spectrometry （UPLC-Q-TOF MS） was used to identify and analyze the chemical components of KXJD and its blood-entering chemical components. The chemical components of the single decoction were further identified to clarify the source of the chemical components in KXJD. Then， all identified blood-entering compounds were screened for effective active ingredients through the Swiss ADME database. The active ingredient targets of KXJD were searched on the Swiss Target Prediction platform. The targets of common psoriasis were searched in OMIM， GEO， GeneCards， and DISGNET databases to obtain drug-disease intersection targets. The protein-protein interaction network of intersection targets was constructed using STRING， and then the core blood-entering component-intersection target network of KXJD was constructed. The core target proteins in the network were selected for molecular docking with the core components of KXJD. Small molecules and proteins were pretreated， and appropriate docking sites were selected. AutoDock Vina software was used for continuous local search and repeated iterations to find molecular docking conformations. PyMOL software and LigPlot+ software were used for analysis and visualization. Subsequently， the verification was carried out through animal experiments. SPF-grade male C57 mice were randomly divided into a blank group， a model group， a positive drug methotrexate group， and a KXJD group. In the model group， the methotrexate group， and the KXJD group， imiquimod was applied to the backs of the mice for modeling. The blank group and the model group were administered normal saline by gavage， while the methotrexate group and the KXJD group were respectively administered 1 mg·kg^-1 suspension and 30.42 g·kg^-1 decoction of traditional Chinese medicine by gavage. Five days after administration， the mice were sacrificed， and samples were collected. Hematoxylin-eosin （HE） staining was used to observe the skin tissue samples of mice， and the effect of KXJD on the pathological manifestations of psoriasis mice was analyzed. The expression areas of tumor necrosis factor-α （TNF-α）， cyclooxygenase 2 （PTGS2）， interleukin （IL）-1β， and IL-6 in the skin tissue of mice were detected by immunohistochemistry （IHC）. The mRNA expressions of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of mice were detected by real-time fluorescent quantitative polymerase chain reaction （Real-time PCR）. ResultsIn this study， 208 compounds in KXJD were identified by UPLC-Q-TOF MS， and 44 compounds were detected in serum， including 28 prototype components and 16 metabolites. 12 blood-entering active components were screened， and 1 153 active component targets and 1 076 psoriasis-related targets were identified. Eighty-five targets in the intersection set were drug-disease common targets. PPI network analysis showed that TNF-α， IL-1β， IL-6， PTGS2， and ALB were the key target proteins. The results of molecular docking showed that the binding ability of （+）-hexylphenylglycolic acid to key target proteins such as PTGS2 was stable， and PTGS2 showed high stability with a variety of core compounds. Compared with those in the blank group， the stratum corneum and epidermis in the model group mice were significantly thickened， and the pathological Baker score of the mice's skin in the model group was significantly higher than that of the blank group （P<0.01）. The expression areas of PTGS2， TNF-α， IL-1β， and IL-6 proteins in the skin tissue of the model group mice were significantly increased （P<0.01）， and the expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the model group mice were significantly elevated （P<0.01）. Compared with the model group， the pathological Baker scores of the methotrexate group and the KXJD group were both decreased （P<0.01）， and the expression areas in the skin tissue of the methotrexate group and the KXJD group were significantly reduced （P<0.05， P<0.01）. The expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the methotrexate group and the KXJD group were significantly decreased （P<0.01）. ConclusionKXJD can effectively improve the skin lesions of psoriasis model mice and reduce the expression of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of psoriasis model mice. PTGS2 has a stable binding ability with a variety of compounds in the decoction， which may be a key target for the treatment of psoriasis. The compound （+）-hexylphenylglycolic acid may play a key role.

Aim In this study, a mouse model of psoriasis-like lesions induced by 62. 5 mg imiquimod was used to explore the effect and mechanism of Sophorae Flavescentis Radix and Rhizoma Smilacis Glabrae combination for the topical treatment of psoriasis. Methods Firstly, the topical administration of Sophorae Flavescentis Radix and Rhizoma Smilacis Glabrae combination for treating psoriasis in progressive and recurrent stages was evaluated by psoriatic mouse model and HE staining. Secondly, immunohistochemistry was used to study the regulatory effects of Sophorae Flavescentis Radix and Rhizoma Smilacis Glabrae combination on the pivotal pathological mechanism of psoriasis-the positive feedback loop between the abnormal proliferation of keratinocytes and skin immune microenvironment. Finally, metabolomics technology was used to explore whether Sophorae Flavescentis Radix and Rhizoma Smilacis Glabrae combination topically treat psoriasis by regulating inflammation-related metabolism and lipid metabolism pathways. Results The combination of Sophorae Flavescentis Radix and Rhizoma Smilacis Glabrae alleviated psoriasis-like lesions in mice. It effectively relieved the recurrence after the cure of psoriatic lesions in mice, and the efficacy is comparable to that of benweimod. The combination of Sophorae Flavescentis Radix and Rhizoma Smilacis Glabrae inhibited the proliferation of mouse epidermal keratinocytes and reduced the number of T cells in the skin. The potential molecular mechanism was that the combination of Sophorae Flavescentis Radix and Rhizoma Smilacis Glabrae regulated arachidonic acid metabolism, sphin- golipid metabolism, tryptophan metabolism and phenylalanine metabolism. Conclusions The combination of Sophora Flavescens Radix and Rhizoma Smilacis Glabrae can relieve psoriasis-like lesions in mice by inhibiting the proliferation of epidermal keratinocytes and reducing the number of T cells in the skin and regulating metabolism to intervene psoriasis recurrence. This study provides a potential topical drug of psoriasis for relieving psoriasis recurrence.

Human exhaled breath has great application prospects,e.g.,monitoring pharmacokinetics,disease diagnosis,due to its advantages such as non-invasive and high-frequency sampling.Breath samples can be collected from the oral and nasal cavity.However,the oral and nasal environment affect the chemical composition of breath sample.Therefore,the investigation on the chemical composition of mouth-exhaled breath and nose-exhaled breath is crucial for selection of appropriate sampling strategy for individual studies.In this work,secondary electrospray ionization-high resolution mass spectrometry(SESI-HRMS)was applied to analysis of respiratory metabolomics in real time.A quantitative analysis approach was established for 9 kinds of volatile organic compounds(VOCs)e.g.2-butanone,2-pentanone,ethyl acetate,methyl methacrylate,toluene,styrene,mesitylene,isoprene and limonene.The limit of detection was 2.3?240.8 ng/m3.The intra-day(n=6)and inter-day(n=18)relative standard deviations were 0.6%?4.6%and 4.3%?12.2%,respectively.Nine healthy subjects were recruited to investigate the chemical composition of mouth-exhaled and nose-exhaled breath.The results showed the good performance in quantitative analysis of 9 VOCs in breath air.It was found that the number of unique component(m/z)detected in mouth-exhaled breath(167)was 2.2 times greater than that detected in nose-exhaled breath(76),which might result from the complex environment in oral cavity.The signal intensity of commun component(163)was significantly different between mouth-exhaled breath and nose-exhaled breath.Additionally,the elemental composition analysis showed that the proportion of polar compounds detected in nose-exhaled breath was higher than that in mouth-exhaled breath.This study demonstrated that there was significant differences in the chemical composition between mouth-exhaled and nose-exhaled breath,which provided a theoretical basis for selection of exhalation mode.

Objective To observe the clinical efficacy of joint needling method combined with ultrasound in the treatment of qi stagnation and blood stasis type of patellofemoral pain syndrome(PFPS).Methods Eighty-six patients with qi stagnation and blood stasis type of PFPS were randomly divided into observation group and control group,with 43 cases in each group.The control group was given western medicine conventional treatment combined with functional exercise,and the observation group was given joint needling method combined with ultrasound treatment on the basis of the control group.Both groups were treated for 2 consecutive weeks.After 2 weeks of treatment,the clinical efficacy of the two groups was evaluated,and the changes in the Visual Analogue Scale(VAS)scores of knee pain and the Kujala scale scores of the two groups were observed before and after treatment.The changes in active range of motion(AROM)of the affected knee joint were compared before and after treatment between the two groups.Results(1)After treatment,the VAS scores of the two groups of patients were significantly improved(P＜0.05),and the observation group was significantly superior to the control group in improving the level of VAS scores,and the difference was statistically significant(P＜0.05).(2)After treatment,the Kujala scores of patients in the two groups were significantly improved(P＜0.05),and the observation group was significantly superior to the control group in improving the level of Kujala scores,and the difference was statistically significant(P＜0.05).(3)After treatment,the AROM of patients in the two groups were significantly improved(P＜0.05),and the observation group was significantly superior to the control group in improving the level of AROM,and the difference was statistically significant(P＜0.05).(4)The total effective rate was 95.35%(41/43)in the observation group and 81.40%(35/43)in the control group.The efficacy of the observation group was superior to that of the control group,and the difference was statistically significant(P＜0.05).Conclusion The joint needling method combined with ultrasound can significantly relieve the pain symptoms of patients with PFPS and promote the recovery of knee joint function,and the clinical efficacy is remarkable.

Objective Previous studies on the association between lipid profiles and chronic kidney disease(CKD)have yielded inconsistent results and no defined thresholds for blood lipids. Methods A prospective cohort study including 32,351 subjects who completed baseline and follow-up surveys over 5 years was conducted.Restricted cubic splines and Cox models were used to examine the association between the lipid profiles and CKD.A regression discontinuity design was used to determine the cutoff value of lipid profiles that was significantly associated with increased the risk of CKD. Results Over a median follow-up time of 2.2(0.5,4.2)years,648(2.00%)subjects developed CKD.The lipid profiles that were significantly and linearly related to CKD included total cholesterol(TC),triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),TC/HDL-C,and TG/HDL-C,whereas low-density lipoprotein cholesterol(LDL-C)and LDL-C/HDL-C were nonlinearly correlated with CKD.TC,TG,TC/HDL-C,and TG/HDL-C showed an upward jump at the cutoff value,increasing the risk of CKD by 0.90%,1.50%,2.30%,and 1.60%,respectively,whereas HDL-C showed a downward jump at the cutoff value,reducing this risk by 1.0%.Female and participants with dyslipidemia had a higher risk of CKD,while the cutoff values for the different characteristics of the population were different. Conclusion There was a significant association between lipid profiles and CKD in a prospective cohort from Northwest China,while TG,TC/HDL-C,and TG/HDL-C showed a stronger risk association.The specific cutoff values of lipid profiles may provide a clinical reference for screening or diagnosing CKD risk.

Non-neonatal tetanus is an acute, specific, toxic disease in patients over 28 days of age, characterized by continuous rigidity and paroxysmal spasms of the skeletal muscles throughout the body caused by the intrusion of Clostridium tetani through skin or mucosal membrane into the body and reproducing in anaerobic environments to produce exotoxins. The mortality rate of severe patients is close to 100% without medical intervention. Even with aggressive comprehensive treatment, the global mortality rate remains at 30%-50%, making it a potentially fatal disease. In order to standardize the diagnosis, treatment and prevention of non-neonatal tetanus, based on "Regulation for Diagnosis and Treatment of Non-neonatal Tetanus (2019 Edition)", experts have revised this regulation according to clinical practice and recent research progress in this field to guide medical institutions in the prevention and control of non-neonatal tetanus. This article interprets the key points and basis for updating the 2024 edition regulation to guide clinical implementation and application.

Objective:To explore the pathogenesis and potential biomarkers of atrial fibrillation based on bioinformatics.Methods:Differentially expressed genes and module genes related to atrial fibrillation were obtained from GSE41177 and GSE79768 datasets(Chinese-origin tissue samples)through differential expression analysis and weighted gene co-expression network analysis.Candidate hub genes were obtained by taking intersections,and hub genes were obtained after gender stratification.Subsequently,functional enrichment analysis and immune infiltration analysis were performed.Four machine learning models were constructed based on the hub genes,and the optimal model was selected to construct a prediction nomogram.The prediction ability of the nomogram was verified using calibration curves and decision curves.Finally,potential therapeutic drugs for atrial fibrillation were screened from the DGIdb database.Results:A total of 67 differentially expressed genes and 65 module genes related to atrial fibrillation were identified.Functional enrichment analysis indicated that the pathogenesis of atrial fibrillation was closely related to inflammatory response,immune response,and immune and infectious diseases.Four common hub genes(TYROBP,FCER1G,EVI2B and SOD2),and two genes specifically expressed in male(PILRA and SLC35G3)and female(HLA-DRA and GATP)patients with atrial fibrillation were obtained after gender-segregated screening.The extreme gradient boosting model had satisfactory diagnostic efficiency,and the nomogram constructed based on the hub genes,male significant variables(PILRA,SLC35G3 and SOD2),and female significant variables(FCER1G,SOD2 and TYRO BP)had satisfactory predictive ability.Immune infiltration analysis demonstrated a disturbed immune infiltration microenvironment in atrial fibrillation with a higher abundance of plasma cells,neutrophils,and γδT cells,with a higher abundance of neutrophils in males and resting mast cells in females.Two potential drugs for the treatment of atrial fibrillation,valproic acid and methotrexate,were obtained by database and literature screening.Conclusions:The pathogenesis of atrial fibrillation is closely related to inflammation and immune response,and the microenvironment of immune cell infiltration of cardiomyocytes in the atrial tissue of patients with atrial fibrillation is disordered.TYROBP,FCER1G,EVI2B and SOD2 serve as potential diagnostic biomarkers of atrial fibrillation;PILRA and SLC35G3 serve as potential specific diagnostic biomarkers of atrial fibrillation in the male population,which can effectively predict the risk of atrial fibrillation development and are also potential targets for the treatment of atrial fibrillation.