Receptor tyrosine kinases (RTKs) are a class of transmembrane cell surface enzyme-linked receptors that play essential roles in various cellular life processes under normal physiological conditions. Dysregulation of RTKs and their signaling pathways is closely associated with multiple human diseases, including cancer. RON is a member of the RTK family. When RON is abnormally expressed, it can actively drive the proliferation, metastasis, and epithelial-mesenchymal transition of cancer cells through complex downstream signal transduction pathways, thereby contributing to the occurrence and subsequent development process of various types of cancers. Consequently, RON is regarded as a potent target for cancer targeted therapy. In recent years, as RTKs have gradually become popular candidate targets for antibody-drug conjugates (ADCs), a variety of ADCs targeting RON have been successfully developed and studied. To highlight the therapeutic potential of anti-RON ADCs in cancer treatment and to provide a foundation for further development and clinical research of them, this article summarized the selected components and construction strategies of existing anti-RON ADCs, and systematically reviewed their in vitro and in vivo anticancer efficacy, as well as their pharmacological and toxicological characteristics. Anti-RON ADCs demonstrated favorable stability both in vitro and in vivo. In cellular models, anti-RON ADCs carrying different payloads all exhibited potent cytotoxic effects. In animal models, anti-RON ADCs have convincingly demonstrated significant anti-cancer activity, with stable pharmacological properties and manageable toxicity at therapeutic doses. Anti-RON ADCs have a number of distinct therapeutic advantages. Compared with ADCs targeting other RTKs, anti-RON ADCs have unique effects in regulating the immune microenvironment and can potentially provide additional therapeutic options for overcoming drug resistance. Compared with RON antibodies and small molecule inhibitors, anti-RON ADCs do not rely on the RON signaling pathways, thereby significantly enhancing therapeutic efficacy. Moreover, anti-RON ADCs show therapeutic potential for targeting RON variants. In summary, the results of basic researches indicated that anti-RON ADCs have favorable anti-cancer effects and show promising clinical translation prospects. In addition, this article analyzed the current limitations of anti-RON ADCs and emphatically discussed their future development directions. The payloads of the existing anti-RON ADCs are relatively limited, and the drug-to-antibody ratio (DAR) of each ADC is not uniform. There also remains considerable room for improvement in terms of endocytosis efficiency and drug combination strategies. Therefore, the development of the next-generation anti-RON ADCs should focus on the diversification of the payloads, and explore new types of ADCs, dual-load ADCs, etc. Additionally, the structure of antibodies or ADCs could be optimized to enhance the endocytosis efficiency and progressively overcome current limitations. At present, anti-RON ADCs are limited to basic research, and the current research outcomes and observations indicated their potential for clinical application. Therefore, the clinical translation of anti-RON ADCs will be an important objective for future development. To this end, it is necessary to carefully devise a rational clinical translation pathway for anti-RON ADCs, and comprehensively evaluate the potential challenges that may arise during the implementation, so as to accelerate the initiation of clinical trials. Ultimately, clinical application of anti-RON ADCs will be realized, providing more treatment options for cancer patients.

Ovulatory dysfunction (OD) is one of the main causes of infertility in women of childbearing age, which not only affects their reproductive ability, but also physical and mental health. Traditional treatment strategies have limited efficacies, and the emergence of biomedicines provides a promising alternative solution via the strategies of combining engineered design with modern advanced technology. This review explores the pathophysiological characteristics and related induction mechanisms of OD, and evaluates the current cutting-edge advances in its treatments. It emphasizes the potentials of biomedicines strategies such as hydrogels, nanoparticles and extracellular vesicles in improving therapeutic precision and efficacy. By mimicking natural physiological processes, and achieving controlled drug release, these advanced drug carriers are expected to address the challenges in ovarian microenvironment reprogramming, tissue repair, and metabolic and immune regulation. Despite the promising progress, there are still challenges in terms of biomedical complexity, differences between animal models and human physiology, and the demand for intelligent drug carriers in the therapy of OD. Future researches are mainly dedicated to developing precise personalized biomedicines in OD therapy through interdisciplinary collaboration, promoting the development of reproductive regenerative medicine.

Alzheimer's disease (AD) is regarded as a neurodegenerative disease, and it has been proposed that AD may be a systemic disease. Studies have reported associations between non-neurological diseases and AD. The correlations between AD pathology and systemic (non-neurological) pathological changes are intricate, and the mechanisms underlying these correlations and their causality are unclear. In this article, we review the association between AD and disorders of other systems. In addition, we summarize the possible mechanisms associated with AD and disorders of other systems, mainly from the perspective of AD pathology. Regarding the relationship between AD and systemic pathological changes, we aim to provide a new outlook on the early warning signs and treatment of AD, such as establishing a diagnostic and screening system based on more accessible peripheral samples.
Alzheimer Disease/therapy* ; Humans ; Brain/pathology*

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

OBJECTIVE: The analgesic effect of acupuncture has been widely accepted. Nevertheless, the mechanism behind its analgesic effect remains elusive, thus impeding the progress of research geared toward enhancing the analgesic effect of acupuncture. This paper investigated the role of acupuncture needle surface textures on acupuncture's analgesic effect by creating four experimental acupuncture needles with different patterns of surface augmentation. METHODS: Four types of acupuncture needles with different surface textures (the lined needle, circle needle, sandpaper needle, and threaded needle) were designed. Additionally, the force/torque measurement system used a robot arm and mechanical sensor to measure the force on the needle during insertion and manipulation. To perform acupuncture analgesia experiments, four experimental acupuncture needles and a normal needle were inserted into the Zusanli (ST36) acupoint of rats with inflammatory pain. By comparing the force and torque and the analgesic efficacy of the different acupuncture needles, these experiments tested the role of acupuncture needle body texture on acupuncture analgesia. RESULTS: The analgesic effects of different acupuncture needle body textures varied. Specifically, the force required to penetrate the skin with the lined needle was not greater than that for the normal needle; however, the needle with inscribed circles and the sandpaper-roughened needle both required greater force for insertion. Additionally, the torque of the lined needle reached 2 × 10^-4 N·m under twisting manipulation, which was four times greater the torque of a normal needle (5 × 10^-5 N·m). Furthermore, the lined needle improved pain threshold and mast cell degranulation rate compared to the normal needle. CONCLUSION Optimizing the texture of acupuncture needles can enhance acupuncture analgesia. The texture of our experimental acupuncture needles had a significant impact on the force needed to penetrate the skin and the torque needed to manipulate the needle; it was also linked to variable analgesic effects. This study provides a theoretical basis for enhancing the analgesic efficacy of acupuncture through the modification of needles and promoting the development of acupuncture therapy. Please cite this article as: Sun MZ, Wang X, Li YC, Liu YH, Yu Y, Ren LJ, Gu W, Yao W. Effects of acupuncture needle modification on acupuncture analgesia. J Integr Med. 2025; 23(1): 66-78.
Needles ; Acupuncture Analgesia/methods* ; Animals ; Rats ; Male ; Acupuncture Points ; Rats, Sprague-Dawley

ObjectiveTo analyze the trend of lung cancer incidence in Fenghua District, Ningbo City of Zhejiang Province from 2009 to 2023, and to estimate the age-period- cohort effects of incidence rate, so as to provide scientific basis for the formulation of lung cancer prevention and control measures in Fenghua District. MethodsJoinpoint software was utilized to analyze the trends and calculate the average annual percentage change (AAPC) of lung cancer incidence based on the tumor incidence surveillance data from Fenghua District, 2009‒2023. The age-period-cohort (APC) model for lung cancer incidence was analyzed using STATA 17.0 software, and net drift and local drift of lung cancer incidence rates were analyzed using online analytical tools. ResultsThe incidence of lung cancer in Fenghua District showed an overall upward trend from 2009 to 2023, with the standardized incidence rate increasing from 45.05/100 000 in 2009 to 108.20/100 000 in 2023(AAPC=7.05%, P<0.05). The increase in the standardized incidence rate for females (AAPC=12.72%, P<0.05) was higher than that for males (AAPC=2.97%, P<0.05). The overall net drift in lung cancer incidence for residents of Fenghua District was 11.71%, with the net drift for females (16.54%) being higher than that for males (6.64%). The local drift in lung cancer incidence among different age groups ranged from -3.37% to 35.18%. The results of APC model showed that the risk of lung cancer incidence increased and then decreased with age, with the highest age effect coefficient observed in the 65‒69 years age group at 1.08. The period effect showed a gradually increasing trend in lung cancer incidence risk with the progression of time, and the period effect coefficient in 2019‒2023 (0.46) was higher than that in 2009‒2013 (-0.39), increasing by 217.95%. The cohort effect coefficient showed a trend of first decreasing and then increasing with the expansion of the birth cohort, in which the lowest cohort effect coefficient was -1.07 observed in the birth cohort of 1964‒1968 and the highest cohort effect coefficient was 1.77 in the birth cohort of 1924‒1928. ConclusionThe incidence of lung cancer in Fenghua District shows an upward trend from 2009 to 2023, with a higher increase in incidence rates among females than that in males. The risk of lung cancer incidence exists a trend of increasing and then decreasing with age growth. With the progression of time, the risk of lung cancer incidence shows a gradually increasing trend. However, with the expansion the birth cohort, the risk of lung cancer incidence demonstrates a trend of first decreasing and then increasing.

Based on the α7 nicotinic acetylcholine receptor(α7nAChR), this study examined how tetrahydropalmatine(THP) affected BV2 microglia exposed to lipopolysaccharide(LPS), aiming to clarify the possible mechanism underlying the anti-depression effect of THP from the perspectives of preventing inflammation and regulating polarization. First, after molecular docking and determination of the content of Corydalis saxicola Bunting total alkaloids, THP was initially identified as a possible anti-depression component. The BV2 microglia model of inflammation was established with LPS. BV2 microglia were allocated into a normal group, a model group, low-and high-dose(20 and 40 μmol·L~(-1), respectively) THP groups, and a THP(20 μmol·L~(-1))+α7nAChR-specific antagonist MLA(1 μmol·L~(-1)) group. The CCK-8 assay was used to screen the safe concentration of THP. A light microscope was used to examine the morphology of the cells. Western blot and immunofluorescence were used to determine the expression of α7nAChR. qRT-PCR was performed to determine the mRNA levels of inducible nitric oxide synthase(iNOS), cluster of differentiation 86(CD86), suppressor of cytokine signaling 3(SOCS3), arginase-1(Arg-1), cluster of differentiation 206(CD206), tumor necrosis factor(TNF)-α, interleukin(IL)-6, and IL-1β. Enzyme-linked immunosorbent assay(ELISA) was employed to measure the levels of TNF-α, IL-6, and IL-1β in the cell supernatant. The experimental results showed that THP at concentrations of 40 μmol·L~(-1) and below had no effect on BV2 microglia. THP improved the morphology of BV2 microglia, significantly up-regulated the protein level of α7nAChR, significantly down-regulated the mRNA levels of iNOS, CD86, SOCS3, TNF-α, IL-6, and IL-1β, significantly up-regulated the mRNA levels of Arg-1 and CD206, and dramatically lowered the levels of TNF-α, IL-6, and IL-1β in the cell supernatant. However, the antagonist MLA abolished the above-mentioned ameliorative effects of THP on LPS-treated BV2 microglia. As demonstrated by the aforementioned findings, THP protected LPS-treated BV2 microglia by regulating the M1/M2 polarization and preventing inflammation, which might be connected to the regulation of α7nAChR on BV2 microglia.
Berberine Alkaloids/chemistry* ; alpha7 Nicotinic Acetylcholine Receptor/chemistry* ; Microglia/metabolism* ; Mice ; Animals ; Cell Line ; Corydalis/chemistry* ; Humans ; Molecular Docking Simulation ; Inflammation/drug therapy* ; Nitric Oxide Synthase Type II/immunology* ; Tumor Necrosis Factor-alpha/immunology*

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Arson is classified as a violent crime,and often involves accelerants that significantly increase casualties and property damage.These accelerants,typically flammable liquids with low saturated vapor pressure,present volatile characteristic components in fire residues,making evidence preservation critical for accurate forensic analysis.In this study,the preservation performance of AMPAC(American KAPAC polyester sampling bags)and polyethylene(PE)evidence bags were evaluated under simulated field conditions(40 oC)through gas chromatography-mass spectrometry(GC-MS)technique,focusing on background interference,sealing integrity,and cross-contamination.The results demonstrated that AMPAC bags exhibited minimal background interference(C12?C14 alkanes detected after 3?7 days)and effective gasoline sealing,though slight losses of C2?C3 alkylbenzenes and trace cross-contamination were observed.In contrast,PE bags showed significant background hydrocarbons(C15?C19 alkanes)and pronounced gasoline component losses,including C2?C4 alkylbenzenes,naphthalenes,and indenes.Notably,severe cross-contamination of gasoline markers was detected in adjacent blank PE bags,with characteristic components such as C2?C4 alkylbenzenes,naphthalenes,methylnaphthalenes,dimethylnaphthalenes,indenes,indanes,methylindenes,and dimethylindenes identified,indicating substantial cross-contamination issues in PE evidence bags.Microstructural analysis revealed superior sealing in AMPAC bags attributed to their smooth,dense surface morphology compared to PE's rougher,porous structure.This study established a comprehensive evaluation framework for fire residue evidence containers,and found that PE bags were unsuitable for long-term gasoline evidence preservation due to compromised integrity.These findings provided critical references for forensic container selection in fire investigations.

Objective To explore the pathogenesis of Alzheimer's disease by examining the effects of dihydroartemisinin(DHA)on cognitive behavior,hippocampal,cerebral cortex and retinal cell morphology,β-amyloid(Aβ)and autophagy-related proteins in 5×FAD mice.Methods Twenty 5×FAD mice and 5 wild type(WT)mice were selected,all of which were female.The 5×FAD mice were randomly divided into model(M)group,donepezil(D)group,low-dose DHA(DHA-L)group,and high-dose DHA(DHA-H)group.The WT and M groups were not treated,and the D group was given donepezil 0.1 mg/kg per day.DHA-L group and DHA-H group were given 10 mg/kg and 20 mg/kg DHA per day,respectively.Group D,group DHA-L and group DHA-H were given intragastric administration once a day for 3 months.The changes of in cognitive behavior were measured by Morris experiment.HE staining was used to observe the arrangement and morphology of nerve cells in cerebral cortex,hippocampus and retina.The expressions of Aβ protein in cerebral cortex,hippocampus and retina were detected by immunohistochemistry.Western blotting detected the expression of autophagy related proteins(LC3-Ⅰ,LC3-Ⅱ,Beclin-1,P62,β-actin).Results The DHA-H group and the D group exhibited more frequent adoption of both linear and trending exploration routes.Compared to the model group,significant differences in the contents of Aβ in the hippocampal CA1,cerebral cortex S1,and retinal were observed(P＜0.0001)in the other four groups.The analysis also showed significant differences in autophagy-associated proteins between the DHA-L,DHA-H,and model groups(P＜0.01).Conclusion DHA improves cognitive function and increases the number of nerve cells in mice.It also reduces Aβ content in the cerebral cortex,hippocampus,and retina,along with improving autophagy-associated protein deposition in mice.