BACKGROUND:During bone remodeling,bone formation and bone resorption are spatially and temporally coordinated,involving intricate interactions between osteoclasts and osteoblasts.Isoginkgetin,a flavonoid found in Ginkgo biloba,has a wide range of anticancer activity and anti-reactive oxygen species activity;however,the effect of isoginkgetin on osteoclast differentiation is unknown.OBJECTIVE:To study the effect and mechanism of action of isoginkgetin on osteoclastogenesis.METHODS:In vitro studies were performed on mouse bone marrow-derived macrophages,and cell counting kit-8 cytotoxicity assay was used to detect the effect of isoginkgetin on cell viability of bone marrow-derived macrophages.Macrophage colony-stimulating factor and receptor activator of nuclear factor kappa-B ligand were used to induce the differentiation of bone marrow-derived macrophages to osteoclasts.Network pharmacology and molecular docking and molecular dynamics simulations were used to predict the processes and targets of the effects of isoginkgetin on the differentiation of osteoclasts.Tartrate-resistant acid phosphatase staining and F-actin staining were used to detect the effects of isoginkgetin on the differentiation and function of osteoclasts.Western blot and RT-PCR were used to detect the effects of isoginkgetin on the expression of genes and proteins related to osteoclast differentiation,reactive oxygen species,and PI3K/AKT pathways.Fluorescent probes were used to detect cellular and mitochondrial reactive oxygen species levels.Flow cytometry technology was used to detect reactive oxygen species levels in cells.RESULTS AND CONCLUSION:(1)Network pharmacology results showed that isoginkgetin affected osteoporosis mainly through the PI3K-AKT pathway and cellular response to drugs and hypoxia,and GSK3β,ESR1,MCL1 and CCNA2 were the key targets.(2)Cell counting kit-8 and tartrate-resistant acid phosphatase staining results showed that isoginkgetin at 8 μmol/L had the most significant inhibitory effect on osteoclastogenesis in vitro,and F-actin results showed that isoginkgetin inhibited osteoclast cytoskeletal actin ring formation in a concentration-dependent manner.(3)Molecular dynamics simulations showed that isoginkgetin bound well to osteoclastogenesis marker proteins(NFATc1,c-Fos,CTSK,and MMP9).Western blot and RT-PCR results indicated that isoginkgetin inhibited the expression of osteoclastogenesis marker proteins and genes(NFATc1,c-Fos,CTSK,and MMP9).(4)Western blot results showed that isoginkgetin inhibited the phosphorylation level of PI3K/AKT/GSK3β and suppressed osteoclastogenesis by activating the PI3K-AKT-GSK3β pathway.(5)The results of reactive oxygen species assay showed that isoginkgetin significantly reduced receptor activator of nuclear factor kappa-B ligand-induced cellular and mitochondrial reactive oxygen species production,and inhibited the differentiation of bone marrow-derived macrophages to osteoclasts.

BACKGROUND:During bone remodeling,bone formation and bone resorption are spatially and temporally coordinated,involving intricate interactions between osteoclasts and osteoblasts.Isoginkgetin,a flavonoid found in Ginkgo biloba,has a wide range of anticancer activity and anti-reactive oxygen species activity;however,the effect of isoginkgetin on osteoclast differentiation is unknown.OBJECTIVE:To study the effect and mechanism of action of isoginkgetin on osteoclastogenesis.METHODS:In vitro studies were performed on mouse bone marrow-derived macrophages,and cell counting kit-8 cytotoxicity assay was used to detect the effect of isoginkgetin on cell viability of bone marrow-derived macrophages.Macrophage colony-stimulating factor and receptor activator of nuclear factor kappa-B ligand were used to induce the differentiation of bone marrow-derived macrophages to osteoclasts.Network pharmacology and molecular docking and molecular dynamics simulations were used to predict the processes and targets of the effects of isoginkgetin on the differentiation of osteoclasts.Tartrate-resistant acid phosphatase staining and F-actin staining were used to detect the effects of isoginkgetin on the differentiation and function of osteoclasts.Western blot and RT-PCR were used to detect the effects of isoginkgetin on the expression of genes and proteins related to osteoclast differentiation,reactive oxygen species,and PI3K/AKT pathways.Fluorescent probes were used to detect cellular and mitochondrial reactive oxygen species levels.Flow cytometry technology was used to detect reactive oxygen species levels in cells.RESULTS AND CONCLUSION:(1)Network pharmacology results showed that isoginkgetin affected osteoporosis mainly through the PI3K-AKT pathway and cellular response to drugs and hypoxia,and GSK3β,ESR1,MCL1 and CCNA2 were the key targets.(2)Cell counting kit-8 and tartrate-resistant acid phosphatase staining results showed that isoginkgetin at 8 μmol/L had the most significant inhibitory effect on osteoclastogenesis in vitro,and F-actin results showed that isoginkgetin inhibited osteoclast cytoskeletal actin ring formation in a concentration-dependent manner.(3)Molecular dynamics simulations showed that isoginkgetin bound well to osteoclastogenesis marker proteins(NFATc1,c-Fos,CTSK,and MMP9).Western blot and RT-PCR results indicated that isoginkgetin inhibited the expression of osteoclastogenesis marker proteins and genes(NFATc1,c-Fos,CTSK,and MMP9).(4)Western blot results showed that isoginkgetin inhibited the phosphorylation level of PI3K/AKT/GSK3β and suppressed osteoclastogenesis by activating the PI3K-AKT-GSK3β pathway.(5)The results of reactive oxygen species assay showed that isoginkgetin significantly reduced receptor activator of nuclear factor kappa-B ligand-induced cellular and mitochondrial reactive oxygen species production,and inhibited the differentiation of bone marrow-derived macrophages to osteoclasts.

By consulting herbal texts， medical records， formula collections， and other relevant literature from various historical periods， as well as modern and contemporary research materials， different aspects of the historical evolution of Zijingpi， including its name， origin， scientific name verification， medicinal part， genuine producing areas， harvesting， processing， and preparation， properties and flavors， and primary indications， were systematically reviewed and verified， providing a basis for the development of famous classical formula preparations containing this medicinal material. According to the textual research， Cercis chinensis was first recorded under the name "Zijingmu" in the Rihuazi Bencao from the Five Dynasties period. From the Song Dynasty to the Qing Dynasty， it was known by various names such as "Zijing"， "Zijingpi"， and "Zijingmupi". In modern and contemporary times， it has been officially named "Zijingpi"， with aliases such as "Mantiaohong"， "Zihuashu"， and "Qingminghua". Historically， the mainstream source of Zijingpi was the dried bark of Cercis chinensis Bunge， a species of the legume family. However， there were also instances of confusion with the Lythraceae plant Lagerstroemia indica L. The producing areas of Zijingpi have no special geographical limitation， and the plant is currently distributed throughout most parts of China. There were no special requirements for harvesting time in ancient times， while modern records indicate harvesting time in spring， summer， and autumn. Ancient processing methods were rarely recorded， with only mentions of stir-frying Zijingpi. Modern practice mostly uses the raw material medicinally. Modern standards prefer it to be "dry， long strips， and thick". The functions of Zijingpi， mainly to promote blood circulation， relieve strangury， and detoxify， have remained consistent from ancient to modern times. Based on the textual research findings， it is recommended that when developing and exploiting the famous classical formulas containing Zijingpi， the bark of C. chinensis should be selected as the source. The processing method should be chosen according to the formula requirements， and if no specific requirements are indicated， it is suggested to use the raw material medicinally.

Objective: To explore the feasibility of constructing a lung cancer early-warning risk model based on facial image features, providing novel insights into the early screening of lung cancer. Methods: This study included patients with pulmonary nodules diagnosed at the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 1, 2019 to December 31, 2024, as well as patients with lung cancer diagnosed in the Oncology Departments of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine and Longhua Hospital during the same period. The facial image information of patients with pulmonary nodules and lung cancer was collected using the TFDA-1 tongue and facial diagnosis instrument, and the facial diagnosis features were extracted from it by deep learning technology. Statistical analysis was conducted on the objective facial diagnosis characteristics of the two groups of participants to explore the differences in their facial image characteristics, and the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables. Based on the screened feature variables, four machine learning methods: random forest, logistic regression, support vector machine (SVM), and gradient boosting decision tree (GBDT) were used to establish lung cancer classification models independently. Meanwhile, the model performance was evaluated by indicators such as sensitivity, specificity, F1 score, precision, accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), and the area under the precision-recall curve (AP). Results: A total of 1 275 patients with pulmonary nodules and 1 623 patients with lung cancer were included in this study. After propensity score matching (PSM) to adjust for gender and age, 535 patients were finally included in the pulmonary nodule group and the lung cancer group, respectively. There were significant differences in multiple color space metrics (such as R, G, B, V, L, a, b, Cr, H, Y, and Cb) and texture metrics [such as gray-levcl co-occurrence matrix (GLCM)-contrast (CON) and GLCM-inverse different moment (IDM)] between the two groups of individuals with pulmonary nodules and lung cancer (P < 0.05). To construct a classification model, LASSO regression was used to select 63 key features from the initial 136 facial features. Based on this feature set, the SVM model demonstrated the best performance after 10-fold stratified cross-validation. The model achieved an average AUC of 0.8729 and average accuracy of 0.799 0 on the internal test set. Further validation on an independent test set confirmed the model’s robust performance (AUC = 0.823 3, accuracy = 0.729 0), indicating its good generalization ability. Feature importance analysis demonstrated that color space indicators and the whole/lip Cr components (including color-B-0, wholecolor-Cr, and lipcolor-Cr) were the core factors in the model’s classification decisions, while texture indicators [GLCM-angular second moment (ASM)_2, GLCM-IDM_1, GLCM-CON_1, GLCM-entropy (ENT)_2] played an important auxiliary role. Conclusion The facial image features of patients with lung cancer and pulmonary nodules show significant differences in color and texture characteristics in multiple areas. The various models constructed based on facial image features all demonstrate good performance, indicating that facial image features can serve as potential biomarkers for lung cancer risk prediction, providing a non-invasive and feasible new approach for early lung cancer screening.

As a common ophthalmic disease, pterygium exhibits a considerably high incidence in global area, particularly in regions with harsh natural environment. While it is unlikely to cause blindness, pterygium frequently disrupts the normal homeostasis of the tear film, leading to discomfort such as dry eyes and foreign body sensation, thereby significantly impairing patients' quality of life. Furthermore, the high surgical intervention rate for pterygium consumes substantial medical resources. Therefore, investigating the underlying mechanisms of pterygium development is essential for its prevention and control. Extensive research has demonstrated the correlation between solar radiation and pterygium occurrence, confirming that ultraviolet rays within solar radiation contribute to the onset and progression of pterygium through multiple pathways, including direct DNA damage to ocular surface cells, oxidative stress-induced injury, involvement in inflammatory regulation, and extracellular matrix remodeling. This paper reviews both domestic and international epidemiological trends of pterygium, as well as the multifaceted mechanisms by which solar radiation influences pterygium development. The aim is to enhance understanding of the relationship between solar exposure and pterygium occurrence, while emphasizing and guiding public awareness of solar radiation protection in clinical practice.

OBJECTIVE: To observe the effects of electroacupuncture at the pterygopalatine region on nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3)-mediated pyroptosis and inflammatory factors in rats with allergic rhinitis (AR). METHODS: Twenty-four SD rats were randomly divided into a blank group, a model group, an acupuncture group and an electroacupuncture group, 6 rats in each group. Except for the blank group, OVA-induced AR model was established in the remaining groups. In the electroacupuncture group, the rats were treated with electroacupuncture at the bilateral pterygopalatine region, with disperse-dense wave, in frequency of 2 Hz/100 Hz and current of 0.5-1 mA, 15 min each time, once every other day, for 3 times. In the acupuncture group, the rats were treated with acupuncture at bilateral pterygopalatine region simply, without electrical stimulation. The rhinitis symptom score was observed, the pathomorphology of the nasal mucosa was observed by HE staining; the serum levels of OVA-specific immunoglobulin E (OVA-sIgE), interleukin (IL)-4, IL-6 and IL-1β were detected by ELISA; the mRNA expression of NLRP3, apoptosis-associated speck-like protein containing CARD (ASC), cysteinyl aspartate specific proteinase-1 (caspase-1) and IL-18 in the nasal mucosa was detected by real-time PCR; the protein expression of NLRP3, ASC, caspase-1 and IL-18 in the nasal mucosa was detected by Western blot. RESULTS: Compared with the blank group, in the model group, the rhinitis symptom score was increased (P<0.01), the serum levels of OVA-sIgE, IL-4, IL-6 and IL-1β were increased (P<0.05), the nasal mucosa showed pathomorphology of inflammatory infiltration; the mRNA and protein expression of NLRP3, ASC, caspase-1 and IL-18 in the nasal mucosa was increased (P<0.05). Compared with the model group, in the electroacupuncture group, the rhinitis symptom score was reduced (P<0.01), the pathology of the nasal mucosa was improved; the serum levels of OVA-sIgE, IL-4, IL-6 and IL-1β were decreased (P<0.05); the mRNA and protein expression of NLRP3, ASC, caspase-1 and IL-18 in the nasal mucosa was decreased (P<0.05). CONCLUSION Electroacupuncture at the pterygopalatine region can exerting the anti-inflammatory effect by inhibiting NLRP3-mediated pyroptosis and inflammatory factor imbalance, thus alleviate rhinitis symptoms in AR rats.
Animals ; Electroacupuncture ; NLR Family, Pyrin Domain-Containing 3 Protein/immunology* ; Rats ; Rats, Sprague-Dawley ; Rhinitis, Allergic/physiopathology* ; Pyroptosis ; Male ; Acupuncture Points ; Humans ; Female ; Interleukin-1beta/genetics* ; Interleukin-18/immunology* ; Interleukin-6/genetics* ; Caspase 1/immunology*

BACKGROUND: Physical activity, sedentary behavior (SB), and sleep duration are associated with brain health. Effects of those on developing Parkinson's disease (PD) are poorly investigated. This study aimed to examine the independent and joint associations of physical activity, SB, sleep with PD risk. METHODS: We analyzed data on 401,697 participants from the UK Biobank cohort, which was enrolled in 2006-2010. Physical activities were measured based on a questionnaire. Sleep and SB time were defined through self-reported total number of hours. Models fitted with restricted cubic spline were conducted to test for linear and non-linear shapes of each association. Cox proportional hazards regression models were used to estimate the association of three modifiable behaviors. RESULTS: Our analytic sample included 401,697 participants with 3030 identified cases of PD (mean age, 63 years; 62.9% male). PD risk was 18% lower in the high total physical activity group (95% CI, 0.75-0.90), 22% lower in the high leisure-time physical activity (LTPA) group (95% CI, 0.71-0.86) compared with the low level and 14% higher in the high sleep duration group (95% CI, 1.05-1.24) compared to moderate group. Total SB time was irrelevant with PD risk, while high TV viewing showed a 12% increase of PD risk compared to the low group (95% CI, 1.02-1.22). Low computer use (0 h/day) was associated with a 14% higher risk compared to 1 h/day use (95% CI, 1.04-1.26). Those associations were independent. A combination of 7 h/day sleep, moderate-to-high computer use, and moderate-to-vigorous intensity of LTPA showed lowest PD risk (HR, 0.70; 95% CI, 0.57-0.85). CONCLUSIONS Physical activity, SB, and sleep were associated with PD risks separately. Our findings emphasize the possibility for changing these three daily activities concurrently to lower the risk of PD. These findings may promote an active lifestyle for PD prevention.
Humans ; Parkinson Disease/physiopathology* ; Male ; Sedentary Behavior ; Female ; Middle Aged ; Exercise/physiology* ; Prospective Studies ; Sleep/physiology* ; Aged ; Surveys and Questionnaires ; Proportional Hazards Models ; Risk Factors

BACKGROUND: Neuroticism has been associated with numerous health outcomes. However, most research has focused on a single specific disorder and has produced controversial results, particularly regarding mortality risk. Here, we aimed to examine the association of neuroticism with morbidity and mortality and to elucidate how neuroticism affects trajectories from a healthy state, to one or more neuroticism-related disorders, and subsequent mortality risk. METHODS: We included 483,916 participants from the UK Biobank at baseline (2006-2010). Neuroticism was measured using the Eysenck Personality Questionnaire. Three clusters were constructed, including worry, depressed affect, and sensitivity to environmental stress and adversity (SESA). Cox proportional hazards regression and multistate models were used. Linear regression was used to examine the association between neuroticism and immune parameters and neuroimaging measures. RESULTS: High neuroticism was associated with 37 non-overlapping diseases, including increased risk of infectious, cardiometabolic, neuropsychiatric, digestive, and respiratory diseases, and decreased risk of cancer. After adjustment for sociodemographic variables, physical measures, healthy behaviors, and baseline diagnoses, moderate-to-high neuroticism was associated with a decreased risk of all-cause mortality. In multistate models, high neuroticism was associated with an increased risk of transitions from a healthy state to a first neuroticism-related disease (hazard ratio [HR] [95% confidence interval (CI)] = 1.09 [1.05-1.13], P  <0.001) and subsequent transitions to multimorbidity (1.08 [1.02-1.14], P  = 0.005), but was associated with a decreased risk of transitions from multimorbidity to death (0.90 [0.84-0.97], P for trend = 0.006). The leading neuroticism cluster showing a detrimental role in the health-illness transition was depressed affect, which correlated with higher amygdala volume and lower insula volume. The protective effect of neuroticism against mortality was mainly contributed by the SESA cluster, which, unlike the other two clusters, did not affect the balance between innate and adaptive immunity. CONCLUSION This study provides new insights into the differential role of neuroticism in health outcomes and into new perspectives for establishing mortality prevention programs for patients with multimorbidity.
Humans ; Neuroticism/physiology* ; Male ; Female ; Middle Aged ; Aged ; Proportional Hazards Models ; Surveys and Questionnaires ; Adult ; Risk Factors

Protein structure determines function, and structural information is critical for predicting protein thermostability. This study proposes a novel method for protein thermostability prediction by integrating graph embedding features and network topological features. By constructing residue interaction networks (RINs) to characterize protein structures, we calculated network topological features and utilize deep neural networks (DNN) to mine inherent characteristics. Using DeepWalk and Node2vec algorithms, we obtained node embeddings and extracted graph embedding features through a TopN strategy combined with bidirectional long short-term memory (BiLSTM) networks. Additionally, we introduced the Doc2vec algorithm to replace the Word2vec module in graph embedding algorithms, generating graph embedding feature vector encodings. By employing an attention mechanism to fuse graph embedding features with network topological features, we constructed a high-precision prediction model, achieving 87.85% prediction accuracy on a bacterial protein dataset. Furthermore, we analyzed the differences in the contributions of network topological features in the model and the differences among various graph embedding methods, and found that the combination of DeepWalk features with Doc2vec and all topological features was crucial for the identification of thermostable proteins. This study provides a practical and effective new method for protein thermostability prediction, and at the same time offers theoretical guidance for exploring protein diversity, discovering new thermostable proteins, and the intelligent modification of mesophilic proteins.
Neural Networks, Computer ; Algorithms ; Protein Stability ; Proteins/chemistry* ; Protein Conformation ; Temperature

ObjectiveTo investigate the change in the expression of magnesium transporter 1 （MagT1） in peripheral blood CD8⁺ T cells in patients with chronic hepatitis B virus （HBV） infection， as well as the correlation of serum Mg²⁺ and MagT1 with HBV DNA load. MethodsA total of 102 patients with HBV infection who were admitted to Tangshan Workers’ Hospital from January 2022 to December 2023 were enrolled， and a case-control study was conducted. According to the stage of disease progression， the subjects were divided into chronic hepatitis B group with 40 patients， compensated liver cirrhosis group with 32 patients， and hepatocellular carcinoma group with 30 patients， and 32 healthy volunteers matched by age and sex were enrolled as normal control group. The serum concentration of Mg²⁺ was measured； RT-qPCR was used to measure the mRNA expression level of MagT1 in CD8⁺ T cells and serum HBV DNA load； flow cytometry was used to measure the expression levels of programmed death-1 （PD-1）， T-cell immunoglobulin and mucin-domain containing-3 （Tim-3）， and natural killer cell group 2D （NKG2D） on the surface of CD8⁺ T cells. A one-way analysis of variance was used for comparison of normally distributed continuous data between multiple groups， and the SNK-q test was used for comparison between two groups； the chi-square test was used for comparison of categorical data between groups； a Pearson linear correlation analysis was used to investigate the correlation between the mRNA expression level of MagT1 and other related indicators. ResultsThere were significant differences in the serum level of Mg²⁺ and the mRNA expression level of MagT1 between the normal control group， the chronic hepatitis B group， the compensated liver cirrhosis group， and the hepatocellular carcinoma group （F=29.014 and 145.578， both P<0.001）. The Pearson correlation analysis showed that the serum level of Mg²⁺ and the mRNA expression level of MagT1 were positively correlated with HBV DNA load （r=0.335 and 0.394， both P<0.05）. The hepatocellular carcinoma group had the highest levels of PD-1 and Tim-3， followed by the compensated liver cirrhosis group， the chronic hepatitis B group， and the normal control group； the normal control group had the highest level of NKG2D， followed by the chronic hepatitis B group， the compensated liver cirrhosis group， and the hepatocellular carcinoma group （all P<0.001）. The Pearson correlation analysis showed that the mRNA expression level of MagT1 was negatively correlated with PD-1 and Tim-3 （r=-0.643 and -0.640， both P<0.05） and was positively correlated with NKG2D （r=0.655， P<0.05）. ConclusionThere is a reduction in the mRNA expression level of MagT1 in peripheral blood CD8⁺ T cells in patients with HBV infection， which is positively correlated with serum HBV DNA load. The reduction in the expression of MagT1 may contribute to CD8⁺ T cell exhaustion by impairing Mg²⁺ influx， manifesting as the upregulation of PD-1 and Tim-3 and the downregulation of NKG2D.