Aging has emerged as a cutting edge and hotspot in global life science field， with anti-aging and geriatric disease prevention and treatment becoming critical issues urgently demanding solutions in international medical communities. In the face of the challenge of accelerating global population aging， in-depth exploration of aging mechanisms and the development of effective intervention strategies hold significant scientific and clinical value. This study supported by the national key research and development program of China， employed the essence-Qi-spirit theory of Qiluo doctrine as its guiding framework， focusing on the key scientific issue of the core traditional Chinese pathogenesis of aging， namely "depletion of kidney essence， deficiency of primordial Qi， and impairment of body and spirit". The treatment principle of "tonifying the kidney to replenish essence， harmonizing Yin and Yang， warming and invigorating primordial Qi， and nourishing the body and spirit" was established. Centered on holistic aging， systemic aging， and aging-related diseases， the research integrated multidisciplinary research approaches to construct multi-modal aging models and a multi-dimensional evaluation system， and it utilized multi-omics technologies to deeply analyze aging mechanisms. By systematically reviewing historical kidney-tonifying and anti-aging formulas and combining big data with artificial intelligence technologies， an information database of anti-aging traditional Chinese medicine substance was developed to reveal the differences and synergistic effects of various treatment methods and formulas on anti-aging. Based on this treatment method， the research integrated two millennia of kidney-tonifying medicinal experience to develop the innovative anti-aging traditional Chinese medicine， namely Bazhi Bushen capsules. It was validated that this capsule can delay holistic and systemic aging through multiple targets and mechanisms， thereby elucidating the scientific connotation of the essence-Qi-spirit theory of Qiluo doctrine in guiding anti-aging research from multiple dimensions and providing robust support for leveraging the advantages of traditional Chinese medicine to occupy the commanding heights of international anti-aging research.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Objective: To develop and compare multiple machine learning models for identifying high-risk college students exhibiting phubbing behavior and to determine key predictive factors, so as to provide evidence for precise screening and early intervention strategies. Methods: In December 2025, 1 828 undergraduate students, selected from three universities in Wuhan by using convenience sampling method, were surveyed via online qustionnaire for sociodemographic characteristics, phubbing behavior, family cohesion index, mature happiness, fear of negative evaluation, multidimensional state boredom, and psychological vulnerability. Four machine learning algorithms, including multilayer perceptron (MLP), extreme gradient booting (XGBoost), K-nearest neighbors (KNN), and gradient boosting decision tree (GBDT), were applied. The dataset was randomly split into a training set and a test set at a ratio of 7∶3. Model performance was evaluated using accuracy, recall, F1-score, and area under the receiver operating characteristic curve (AUC). The best performing model was further interpreted using shapley additive explanation (SHAP) analysis to assess feature importance. Results: In the training set,955 participants were classified as having low level phubbing behavior, and 325 participants were classified as having high level phubbing behavior. Significant differences were observed in psychological vulnerability, multidimensional state boredom, family cohesion index, and mature happiness between groups ( Z =-10.29, -11.72, -8.17, -7.83, all P <0.05). Significant differences were also found in the detection rate of high level phubbing behavior according to family residence, family status, left behind experience,interpersonal relationships,exercise frequency,physical flexibility,and sleep status ( χ 2=12.22, 38.93, 16.90, 44.64, 58.17, 82.14, 37.89, all P <0.05). Among the four machine learning models (MLP, KNN, GBDT, XGBoost),all showed good discrimination ability, with XGBoost performing best (accuracy 79%, recall 71%, F1-score=0.70, AUC=0.78), while GBDT achieved the highest precision (78%). Feature importance analysis showed that multidimensional state boredom was the most important predictor of phubbing behavior, followed by psychological vulnerability, family cohesion, mature happiness, and fear of negative evaluation. SHAP analysis indicated that multidimensional state boredom, psychological vulnerability, and fear of negative evaluation had positive risk effects, while family cohesion and hedonic well being had protective effects for high risk of phubbing behavior. Conclusions Multidimensional state boredom is the core predictor of phubbing behavior among college students. The XGBoost model demonstrates good predictive performance and can provide a reference for identifying high risk individuals and implementing targeted interventions.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Epilepsy is a chronic neurological disease caused by abnormal synchronous discharge of the brain, which is characterized by recurrent and transient neurological abnormalities, mainly manifested as loss of consciousness and limb convulsions, and can occur in people of all ages. At present, anti-epileptic drugs (AEDs) are still the main means of treatment, but their efficacy is limited by the problem of drug resistance, and long-term use can cause serious side effects, such as cognitive dysfunction and vital organ damage. Although surgical resection of epileptic lesions has achieved certain results in some patients, the high cost and potential risk of neurological damage limit its scope of application. Therefore, the development of safe, accurate and personalized non-invasive treatment strategies has become one of the key directions of epilepsy research. In recent years, photobiomodulation (PBM) has gained significant attention as a promising non-invasive therapeutic approach. PBM uses light of specific wavelengths to penetrate tissues and interact with photosensitive molecules within cells, thereby modulating cellular metabolic processes. Research has shown that PBM can enhance mitochondrial function, promote ATP production, improve meningeal lymphatic drainage, reduce neuroinflammation, and stimulate the growth of neurons and synapses. These biological effects suggest that PBM not only holds the potential to reduce the frequency of seizures but also to improve the metabolic state and network function of neurons, providing a novel therapeutic avenue for epilepsy treatment. Compared to traditional treatment methods, PBM is non-invasive and avoids the risks associated with surgical interventions. Its low risk of significant side effects makes it particularly suitable for patients with drug-resistant epilepsy, offering new therapeutic options for those who have not responded to conventional treatments. Furthermore, PBM’s multi-target mechanism enables it to address a variety of complex etiologies of epilepsy, demonstrating its potential in precision medicine. In contrast to therapies targeting a single pathological mechanism, PBM’s multifaceted approach makes it highly adaptable to different types of epilepsy, positioning it as a promising supplementary or alternative treatment. Although animal studies and preliminary clinical trials have shown positive outcomes with PBM, its clinical application remains in the exploratory phase. Future research should aim to elucidate the precise mechanisms of PBM, optimize light parameters, such as wavelength, dose, and frequency, and investigate potential synergistic effects with other therapeutic modalities. These efforts will be crucial for enhancing the therapeutic efficacy of PBM and ensuring its safety and consistency in clinical settings. This review summarizes the types of epilepsy, diagnostic biomarkers, the advantages of PBM, and its mechanisms and potential applications in epilepsy treatment. The unique value of PBM lies not only in its multi-target therapeutic effects but also in its adaptability to the diverse etiologies of epilepsy. The combination of PBM with traditional treatments, such as pharmacotherapy and neuroregulatory techniques, holds promise for developing a more comprehensive and multidimensional treatment strategy, ultimately alleviating the treatment burden on patients. PBM has also shown beneficial effects on neural network plasticity in various neurodegenerative diseases. The dynamic remodeling of neural networks plays a critical role in the pathogenesis and treatment of epilepsy, and PBM’s multi-target mechanism may promote brain function recovery by facilitating neural network remodeling. In this context, optimizing optical parameters remains a key area of research. By adjusting parameters such as wavelength, dose, and frequency, researchers aim to further enhance the therapeutic effects of PBM while maintaining its safety and stability. Looking forward, interdisciplinary collaboration, particularly in the fields of neuroscience, optical engineering, and clinical medicine, will drive the development of PBM technology and facilitate its transition from laboratory research to clinical application. With the advancement of portable devices, PBM is expected to provide safer and more effective treatments for epilepsy patients and make a significant contribution to personalized medicine, positioning it as a critical component of precision therapeutic strategies.

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.

BACKGROUND:The micro/nanostructured gradient biomimetic surface of implant materials can simulate the structure of the extracellular environment in human bone tissue,thereby achieving perfect bone integration function.However,further research is needed on the mechanisms by which the surface microstructure of bone implant materials regulates cell function and promotes osteogenesis. OBJECTIVE:To analyze the effect of titanium sheet microstructure surface on osteogenic differentiation of MC3T3-E1 osteoblasts. METHODS:(1)At a constant voltage of 5 V or 20 V,nanotube arrays of different diameters were prepared on the surface of titanium sheets by acid etching and anodic oxidation techniques,and were recorded as group R5 and group R20,respectively.The surface morphology,roughness,and hydrophilicity of pure titanium sheet(without acid etching or anodizing treatment)were measured in group R5 and group R20.(2)MC3T3-E1 osteoblasts of logarithmic growth stage were inoculated on the surface of pure titanium sheets,R5 group and R20 group respectively.After 24 hours of osteogenic induction culture,the expression of mechanical sensitive channel protein 1 was analyzed by RT-PCR and immunofluorescence staining.Osteoblast inducible base with or without the mechanosensitive channel protein 1 activator Yada1 was added,and alkaline phosphatase staining was performed after 7 days of culture.Alizarin red staining was performed after 14 days of culture. RESULTS AND CONCLUSION:(1)The surface of pure titanium sheets was smooth under scanning electron microscope.Relatively uniform and orderly nanotube arrays with average diameters of about 30 nm and 100 nm were observed on the surface of titanium sheets of groups R5 and R20,respectively.The results of scanning electron microscope were further verified by atomic force microscopy.The surface roughness of titanium sheet of group R5 was higher than that of pure titanium(P<0.05),and the water contact angle was lower than that of pure titanium(P<0.05).The surface roughness of titanium sheet in group R20 was higher than that in group R5(P<0.05),and the water contact angle was lower than that in group R5(P<0.05).(2)RT-PCR and immunofluorescence staining showed that the expression of mechanosensitive channel protein 1 in group R5 was higher than that in pure titanium group(P<0.05),and the expression of mechanosensitive channel protein 1 in group R20 was higher than that in group R5(P<0.05).Under the osteogenic induction,compared with the condition without Yada1,there were no significant changes in the activity of alkaline phosphatase and the deposition of calcified nodules in pure titanium group after Yada1 addition,while the activity of alkaline phosphatase and the deposition of calcified nodules in groups R5 and R20 after Yada1 addition were significantly increased(P<0.05).With or without Yada1,the alkaline phosphatase activity and calcified nodule deposition in group R5 were higher than those in pure titanium group(P<0.05),and the alkaline phosphatase activity and calcified nodule deposition in group R20 were higher than those in group R5(P<0.05).(3)The results show that the surface microstructure of titanium sheet can promote the osteogenic differentiation of osteoblast MC3T3-E1 by activating mechanosensitive channel protein 1.

This article systematically reviews and verifies the medicinal materials of Dioscoreae Hypoglaucae Rhizoma（DHR）， Dioscoreae Spongiosae Rhizoma（DSR）， Smilacis Chinae Rhizoma（SCR） and Smilacis Glabrae Rhizoma（SGR） from the aspects of name， origin， producing area， quality， harvesting， processing and efficacy by consulting historical literature， in order to provide reference for the development and utilization of famous classical formulas containing the four medicinal materials. DHR， DSR， SCR and SGR have a long history of application as medicinal materials. However， due to their similar growth environment and medicinal properties， as well as their functions of promoting dampness， dispelling wind and removing numbness， there have been instances of homonymous foreign objects and homonymous synonyms throughout history， resulting in confusion of the origin. Therefore， it is necessary to conduct comparative analysis and systematic research for clarifying the historical development and changes of the four， in order to provide a basis for safe and effective medication. According to research， Bixie was first recorded in Shennong Bencaojing and has been historically known as Baizhi， Chijie， Zhumu， and other aliases. From ancient times to the mid-20th century， there has always been a situation where the rhizomes of Dioscorea plants and Smilax plants， and even the rhizomes of Heterosmilax plants， were mixed together to be used as medicinal herbs for Bixie. However， since the Tang dynasty， it has been clearly advocated that the rhizomes of Dioscorea plants have excellent quality and have been the mainstream throughout history. The 2020 edition of Chinese Pharmacopoeia categorized it into two types of medicinal herbs（DHR and DSR）. Among them， the origin of DHR is the dry rhizomes of Dioscorea hypoglauca， and the origins of DSR are the dry rhizomes of D. spongiosa and D. futschauensis. In ancient times， due to different types， the corresponding production areas of DHR and DSR were also different. Nowadays， They are mainly produced in the southern region of the Yangtze River. Since the Tang dynasty， the quality of Bixie has been characterized by its white color and soft nature. In modern times， it has been summarized that those with white color， large and thin pieces， powdery texture， tough and elastic texture， and neat and unbreakable are the best. The harvesting times of DHR and DSR are in spring or autumn， with the best quality harvested in autumn. The mainstream processing methods of them are slicing and then using the raw products or wine-processed products. SCR was first recorded in Mingyi Bielu and has been known as Jinganggen， Tielingjiao， Tieshuazi， and other aliases in history. The mainstream source is the dry rhizomes of Smilax china in the past dynasties， with the best quality being those that are tough and rich in powder. The harvesting time is from the late autumn to the following spring， and the main processing method throughout history has been slicing for raw use. SGR was first recorded under the item of Yuyuliang in Variorum of Shennong's Classic of Materia Medica. It was listed as an independent medicinal material from Bencao Gangmu. In history， there were such aliases as Cao Yuyuliang， Lengfantuan， Xianyiliang， Tubixie， etc. The main source of the past dynasties was dry rhizomes of S. glabra. In history， there have also been instances of multiple plants belonging to the same genus， and even cases of mixing the rhizomes of plants in the genus Heterosmilax. It is mainly produced in Guangdong， Hunan， Hubei， Zhejiang， Sichuan， Anhui and other regions， its quality has been summarized as large in size， powdery in texture， with few veins， and light brown in cross-section since modern times. The harvesting time is in spring or autumn， and the main processing method throughout history has been slicing for raw use. DHR， DSR， SCR and SGR all have the effects of promoting dampness， dispelling wind， relieving rheumatism and detoxifying. However， their detoxification abilities are ranked as follows：SGR>SCR>Bixie（DHR and DSR）. Especially for the treatment of limb spasms， arthralgia and myalgia， scrofula， and scabies caused by syphilis and mercury poisoning， SGR has a unique effect. Based on the research results， DHR is recommended to develop the famous classical formulas containing Bixie as the first choice for medicinal herbs. It should be harvested in autumn， sliced thinly while fresh， and processed according to the requirements of the famous classical formulas， without any requirements for raw use. Selecting the rhizomes of S. china， harvested in late autumn， and thinly sliced while fresh. If there are no special processing requirements in the formulas， use it raw. Selecting the rhizomes of S. glabra， it is harvested in autumn and thinly sliced while fresh. If there are no special processing requirements in the formulas， raw products can be used.