ObjectiveTo investigate the influence of histone deacetylase 3 (HDAC3) on the occurrence, development of psoriasis-like inflammation in mice, and the relative immune mechanisms. MethodsHealthy C57BL/6 mice aged 6-8 weeks were selected and randomly divided into 3 groups: control group (Control), psoriasis model group (IMQ), and HDAC3 inhibitor RGFP966-treated psoriasis model group (IMQ+RGFP966). One day prior to the experiment, the back hair of the mice was shaved. After a one-day stabilization period, the mice in Control group was treated with an equal amount of vaseline, while the mice in IMQ group was treated with imiquimod (62.5 mg/d) applied topically on the back to establish a psoriasis-like inflammation model. The mice in IMQ+RGFP966 group received intervention with a high dose of the HDAC3-selective inhibitor RGFP966 (30 mg/kg) based on the psoriasis-like model. All groups were treated continuously for 5 d, during which psoriasis-like inflammation symptoms (scaling, erythema, skin thickness), body weight, and mental status were observed and recorded, with photographs taken for documentation. After euthanasia, hematoxylin-eosin (HE) staining was used to assess the effect of RGFP966 on the skin tissue structure of the mice, and skin thickness was measured. The mRNA and protein expression levels of HDAC3 in skin tissues were detected using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB), respectively. Flow cytometry was employed to analyze neutrophils in peripheral blood and lymph nodes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes in peripheral blood, and IL-17A secretion by peripheral blood CD4⁺ T lymphocytes. Additionally, spleen CD4⁺ T lymphocyte expression of HDAC3, CCR6, CCR8, and IL-17A secretion levels were analyzed. Immunohistochemistry was used to detect the localization and expression levels of HDAC3, IL-17A, and IL-10 in skin tissues. ResultsCompared with the Control group, the IMQ group exhibited significant psoriasis-like inflammation, characterized by erythema, scaling, and skin wrinkling. Compared with the IMQ group, RGFP966 exacerbated psoriasis-like inflammatory symptoms, leading to increased hyperkeratosis. The psoriasis area and severity index (PASI) skin symptom scores were higher in the IMQ group than those in the Control group, and the scores were further elevated in the IMQ+RGFP966 group compared to the IMQ group. Skin thickness measurements showed a trend of IMQ+RGFP966>IMQ>Control. The numbers of neutrophils in the blood and lymph nodes increased sequentially in the Control, IMQ, and IMQ+RGFP966 groups, with a similar trend observed for CD4⁺ and CD8⁺ T lymphocytes in the blood. In skin tissues, compared with the Control group, the mRNA and protein levels of HDAC3 decreased in the IMQ group, but RGFP966 did not further reduce these expressions. HDAC3 was primarily located in the nucleus. Compared with the Control group, the nuclear HDAC3 content decreased in the skin tissues of the IMQ group, and RGFP966 further reduced nuclear HDAC3. Compared with the Control and IMQ groups, RGFP966 treatment decreased HDAC3 expression in splenic CD4⁺ and CD8⁺ T cells. RGFP966 treatment increased the expression of CCR6 and CCR8 in splenic CD4⁺ T cells and enhanced IL-17A secretion by peripheral blood and splenic CD4⁺ T lymphocytes. Additionally, compared with the IMQ group, RGFP966 reduced IL-10 protein levels and upregulated IL-17A expression in skin tissues. ConclusionRGFP966 exacerbates psoriatic-like inflammatory responses by inhibiting HDAC3, increasing the secretion of the cytokine IL-17A, and upregulating the expression of chemokines CCR8 and CCR6.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Mild cognitive impairment due to Alzheimer′s disease is an inevitable pathological stage in the early development of Alzheimer′s disease, which can be classified as "microlumps in the brain collaterals" in traditional Chinese medicine. Based on the theory of latent toxin blocking collaterals, this article discusses the etiology and pathogenesis, clinical sequelae, and traditional Chinese medicine intervention strategies for mild cognitive impairment due to Alzheimer′s disease. The onset of mild cognitive impairment due to Alzheimer′s disease is very similar to the latent pathogen theory, which states that "the latent pathogen is latent and then develops, the poison is deep and difficult to cure, and the development can be recognized but the latent pathogen cannot be detected." Combining clinical experience, our team believes that the basic nature of the disease is a slight deficiency and a slight excess of symptoms. A slight deficiency of the five zang viscera and six fu viscera as root and a latent toxin colling collaterals of qi, fire, phlegm, and blood stasis as manifestaion. These usually start from the qi depression and develop into phlegm coagulation and blood stasis, then end up in latent toxin and gradually become the healthy qi deficiency. Therefore, the deficiency of vital qi and incubation of evil, latent toxin blocking collaterals the pathogenesis of early intervention of this disease should be carried out, upholding the idea that "the upper workman treats the disease before it is diagnosed." The principle of strengthening vital qi to eliminate pathogenic factors, slowing down and promoting pathogenic factors elimination, establishing the method of supporting correctness and wisdom, simultaneously detoxifying and clearing the blood stasis, pattern differentiation as the main and the disease differentiation as the first, combining the disease and pattern, and adjusting the macroscopic and microscopic, focusing simultaneously on eliminating and replenishing, dispel phlegm and remove blood stasis, achieve a strong vital qi and the elimination of evil, and enhance intelligence, delay or even block the progression of mild cognitive impairment due to Alzheimer′s disease, improve patients′ quality of life, and provide a theoretical basis for the early clinical prevention and treatment of Alzheimer′s disease.

Aim To investigate the mechanism of curcumin inhibition of oxidative stress on osteogenic differentiation and its dose-dependent anti-osteoporosis effect. Methods Cellular oxidative stress models were used, different concentrations of curcumin were added to determinethebone formation markers, and the potential signaling pathways involvedwere detected. Meanwhile, the mouse model of osteoporosis ( ovariecto- mized, 0VX) was used to confirm its effect against osteoporosis. Results In vitro experiments found that low concentrations of curcumin (1-10 μmol · L

The gene GeDRP1E encoding dynamin-related protein 1E in Gastrodia elata was cloned by specific primers which were designed based on the transcriptome data of G. elata. Bioinformatics analysis on GeDRP1E gene was carried out by using ExPASy, ClustalW, MEGA, etc. Positive transgenic Arabidopsis plant and potato minituber were obtained with the genetic transformation system of Arabidopsis and potato. The plant height and seed setting rate of transgenic Arabidopsis, and agronomic characters, such as size, weight and starch content of potato minituber of transgenic potato were tested and analyzed. And GeDRP1E gene function was preliminarily investigated. The results showed that the open reading frame of GeDRP1E gene was 1 899 bp in length and 632 amino acids residues were encoded, with a relative molecular weight of 69.90 kDa and a molecular formula of C₃₀₇₉H₄₉₇₃N₈₈₃O₉₃₃S₁₉. It was predicted that the theoretical isoelectric point was 7.27, the instability coefficient was 43.34, and the average hydrophilicity index was -0.259, which was indicative of an unstable hydrophilic protein. GeDRP1E has no transmembrane structure and signal peptide, and was localized in the cytoplasm. The phylogenetic tree showed that GeDRP1E was highly homologous with DRP1E proteins of other plant species, among which GeDRP1E had the highest homology with DcDRP1E (XP_020689662.1) in Dendrobium candidum, reaching 90.05%. GeDRP1E plant expression vector pCambia1300-35Spro-GeDRP1E was constructed by double digests, and Arabidopsis complementary mutant and potato overexpression strain of GeDRP1E gene were obtained by Agrobacterium-mediated gene transformation. Compared with the Arabidopsis AtDRP1E mutant, the height and seed setting rate of the GeDRP1E complementation mutant were rescued. The minituber of GeDRP1E overexpression potato had larger size, heavier weight and higher starch content, comparing to wild-type potato. It was preliminarily induced that GeDRP1E was involved in mitochondrial morphology regulation, which related to the growth and development of Arabidopsis plants and potato miniature. The research results laid a foundation for further elucidating the molecular mechanisms underlying the growth and development of G. elata tuber development.

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.

Objective To explore the severity of loneliness among the elderly in communities in Shanghai,and to identify factors associated with social and emotional loneliness respectively.Methods A cross-sectional study was conducted in older adults aged 65 years or above in Pudong New Area,Jing'an District and Huangpu District in Shanghai from Mar to Jun 2021.In Pudong New Area,multi-stage stratified random sampling was conducted based on the age and gender distribution of Shanghai,while in Huangpu District and Jing'an District convenience sampling was conducted.A total of 635 samples were included in the study.Loneliness was assessed using the De Jong Gierveld Loneliness Scale with social and emotional loneliness subscales.Logistic regression analyses were conducted to identify factors associated with social and emotional loneliness.Results Among the 635 participants,only 53 older adults(8.4%)were not lonely.Female(OR=0.46,95%CI:0.31-0.70),higher self-efficacy(OR=0.97,95%CI:0.94-1.00),more objective social support(OR=0.96,95%CI:0.93-0.99)were associated with less severe social loneliness.Meanwhile,higher level of education(secondary education,OR=0.56,95%CI:0.34-0.95;college or above,OR=0.30,95%CI:0.11-0.83)and higher self-efficacy(OR=0.96,95%CI:0.93-0.99)were associated with less severe emotional loneliness,while depression(OR=3.41,95%CI:1.76-6.60)and worse social capital(OR=2.02,95%CI:1.29-3.16)were associated with more severe emotional loneliness.Conclusion Up to 91.6%of the elderly in our study sample were moderately lonely or above.The factors associated with social loneliness include self-efficacy,gender and social support.The factors associated with emotional loneliness are self-efficacy,education level,depression,and social capital.

BACKGROUND:Osteonecrosis of the femoral head is one of the refractory diseases in orthopedic diseases.The natural collapse course of osteonecrosis of the femoral head under different stages and types affects the progression and prognosis of the disease. OBJECTIVE:To explore the progression of natural collapse within 5 years in patients under the different classifications of China-Japan Friendship Hospital(CJFH)with stage Ⅱ osteonecrosis of the International Association for Research Circulation Osseous(ARCO),and to analyze the collapse rate and collapse risk of the femoral head under the different classifications of CJFH. METHODS:A retrospective study was performed to select patients diagnosed with ARCO Ⅱ stage osteonecrosis of the femoral head without collapse in the Honghui Hospital Affiliated to Xi'an Jiaotong University from October 2016 to October 2017.According to whether it collapsed,the number of hips was divided into the collapse group(n=82)and the non-collapsed group(n=70).The collapse risk of patients with osteonecrosis of the femoral head under different CJFH classifications,as well as the collapse time,number of collapses,and collapse rate within 5 years were counted,and then the Kaplan-Meier survival curve of the femoral head under different classification of CJFH was plotted. RESULTS AND CONCLUSION:(1)A total of 97 patients with 152 hips were enrolled,and 82 hips collapsed during the follow-up period,with a total collapse rate of 53.9%,of which the collapse rates of M type,C type,L1 type,L2 type,and L3 type were 0.0%,36.7%,51.4%,72.2%,and 77.8%,respectively,and the comparison between the groups was statistically significant(P<0.05).(2)In terms of collapse risk,the collapse risk of L1 type was 1.704 times that of C-type(P>0.05),while the collapse risks of L2 type and L3 type were 3.866 times and 6.423 times that of C type(P<0.05),respectively.(3)In terms of the Kaplan-Meier survival curve,the median survival time of the femoral head of ARCO Ⅱ stage patients was 3 years,with a 95%confidence interval of 2.885-3.471 years,and the survival rates of the femoral head at the first,third and fifth years were 65.1%(99/152),50.7%(77/152),and 46.1%(70/152),respectively.(4)These findings conclude that different CJFH classifications affect the collapse rate of ARCO Ⅱ stage osteonecrosis of the femoral head patients,among which L3 type patients have the highest collapse rate,followed by L2 type and L1 type patients;C type patients have a lower collapse rate,and M type patients do not collapse,which indicates that the preservation of the lateral column of the femoral head is of great significance for the natural collapse course of osteonecrosis of the femoral head.

BACKGROUND:With the innovation of examination technique,the number of patients with spinal metastases in different stages is increasing year by year.Percutaneous vertebroplasty is an important treatment for spinal metastases;however,there is no report on the biomechanical effect in different stages and different activities after operation. OBJECTIVE:To simulate thoracic T10 bone stress and displacement of the different locations of the tumor metastasis based on the three-dimensional finite element model. METHODS:According to thoracic three-dimensional CT images of a 30-year-old healthy male,Mimics software was used to construct a three-dimensional geometric model of thoracic vertebrae(T9-T11),including ribs,ligaments and intervertebral discs.Three-dimensional models of T9-T11 vertebral bodies and different parts of the posterior thoracic vertebrae invaded by thoracic metastatic tumors were simulated,including the control group with intact vertebral structure,unilateral metastasis involving the vertebral body area(experimental group 1),unilateral metastasis involving the vertebral body and pedicle area(experimental group 2),unilateral metastasis involving the vertebral body,pedicle and transverse process area(experimental group 3),and bilateral metastasis involving the vertebral body,pedicle and transverse process area(experimental group 4).Abaqus software was used to create a three-dimensional finite element model.The von Mises stress distribution and the displacement of the model were analyzed under the loading condition,buckling condition,extension condition,and rotation condition. RESULTS AND CONCLUSION:(1)In the study of the maximum total displacement of loading points in different experimental groups under loading,flexion,extension,and rotation conditions,with the increase of metastatic tumor invasion site and invasion surface,the total displacement of loading points increased,and the overall stiffness decreased,especially the total displacement of loading points in experimental group 4 was the largest.(2)Under flexion condition,the maximum Von Mises stress value increased significantly after vertebral body and pedicle destruction,while the maximum Von Mises stress value was almost unchanged when the thoracocostal joint destruction was added.(3)On the basis of finite element analysis and simulation of bone tumor model,the elements in the bone cement region were set as a single set,and the bone cement region was set as the corresponding material properties to simulate bone cement filling.The results showed that the maximum total displacement under loading,flexion,extension,and rotation conditions was less than that of each experimental group.(4)The maximum stress values of the simulated percutaneous vertebroplasty patients in the loading,flexion,extension and rotation conditions were significantly lower than those of the femoral model.(5)It is concluded that the three-dimensional finite element model based on thoracic T9-T11 conducive to the biomechanics characteristics of thoracic vertebrae tumor metastasis,and on the basis of the thoracic vertebrae tumor metastasis model can accurately simulate load point after percutaneous vertebral body under different conditions of total displacement and the maximum Von Mises stress situation.

Objective To observe the alteration of thoracic and lumbar physiological curvature in adolescent idiopathic scoliosis(AIS)and the difference of physiological curvature between different types of scoliosis.Methods A retrospective analysis was conducted on 305 adolescent patients taken full spine X-ray in our hospital from January 2017 to December 2021.The patients were divided into normal group and scoliosis group.The normal group was composed of 179 patients,79 males and 100 females,aged 10 to 18 years old with an average of(12.84±2.10)years old,with cobb agle less than 10 degrees.The scol-iosis group was composed of 126 patients,33 males and 93 females,aged 10 to 18 years old with an average of(13.92±2.20)years old.The gender,age,Risser sign,thoracic kyphosis(TK)and lumbar lordosis(LL)in 2 groups were compared,and the TK and LL were also compared between different genders,different degrees of scoliosis and different segments of scoliosis.Re-sults The female ratio(P=0.001)and age(P＜0.001)in scoliosis group were higher than them in normal group;the ratio of low-grade ossification was higher in normal group than in scoliosis group(P=0.038).TK was significantly smaller in scoliosis group than in normal group(P＜0.001),but there was no significant difference in LL between the 2 groups(P=0.147).There were no significant difference in TK and LL between male and female.The TK was significantly bigger in mild AIS patients than in moderate AIS patients(P＜0.05),but there was no significant difference in LL between mild and moderate patients(P＞0.05).The TK and LL in different segments scoliosis were not found significant difference.Conclusion The physiological curvature of thoracic and lumbar spine is independent of gender.The thoracic physiological curvature becomes smaller in AIS patients,but lumbar curvature remains unchanged.The thoracic physiological curvature in mild AIS patients is greater than that in moderate AIS patients,but the lumbar curvature is almost unchanged between mild and moderate scoliosis and is similar with that in normal adolescent.The alteration of thoracic and lumbar physiological curvature in AIS patients may be related to relative an-terior spinal overgrowth,and the specific detailed mechanism needs to be further studied.