Aim To explore the effect of kaempferol-7- 0-neohesperidoside (K70N) against prostate cancer (PCa) and the underlying mechanism. Methods The effect of K70N on the proliferation of PCa cell lines PC3, DU145, C4-2 and LNCaP was detected using CCK8 assay. The effect of K70N on migration ability of DU145 cells was determined by wound healing assay. The targets of K70N and PCa were screened from SuperPred and other databases. The common targets both related to K70N and PCa were obtained from the Venny online platform, a protein-protein interaction network (PPI) was constructed by the String and Cyto- scape. Meanwhile, the GO and KEGG functional enrichment were analyzed by David database. Then, a "drug-target-disease-pathway" network model was constructed. Cell cycle of PCa cells treated with K70N was analyzed by flow cytometry. The expressions of cycle-associated proteins including Skp2, p27 and p21 protein were detected by Western blot. Molecular docking between Skp2 and K70N was conducted by Sybyl X2. 0. Results K70N significantly inhibited the proliferation and migration of PCa cells. A total number of 34 drug-disease intersection targets were screened. The String results showed that Skp2 and p27, among the common targets, were the key targets of K70N for PCa treatment. Furthermore, GO and KEGG functional en-richment indicated that the mechanism was mainly related to the cell cycle. Flow cytometry showed that K70N treatment induced cell cycle arrest at the S phase. Compared with the control group, the protein expression level of Skp2 was significantly down-regulated, while the protein expression levels of p27 and p21 were up-regulated. The network molecular docking indicated that the ligand K70N had a good binding ability with the receptor Skp2. Conclusions K70N could inhibit the proliferation and migration of PCa cells, block the cell cycle in the S phase, which may be related to the regulation of cell cycle through the Skp2- p27/p21 signaling pathway.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Objective To observe the feasibility of cardiac MR tissue tracking(CMR-TT)technique for quantitatively evaluating myocardial strain of patients with myocardial amyloidosis(CA).Methods Cardiac MRI were collected from 20 patients of immunoglobulin amyloid light-chain CA(AL-CA,group A),20 cases of transthyretin CA(ATTR-CA,group B)and 20 healthy subjects(group C),and myocardial strain parameters were obtained using CMR-TT technique.Left ventricular cardiac function parameters were compared among 3 groups,so were strain parameters of each myocardial segment of left ventricle and global myocardium,including 3D longitudinal strain(LS),3D radial strain(RS)and 3D circumferential strain(CS).Results Compared with those in group C,significant differences of left ventricular cardiac function parameters were found in both group A and B(all P＜0.01),while no statistical difference was found between group A and B(all P＞0.05).Except for apical segment RS(P=0.81),strain parameters in group A and B were both lower than those in group C(all P＜0.01),while no significant difference was detected between group A and B(all P＞0.05).Conclusion CMR-TT technique could be used to quantitatively evaluate left ventricular myocardial strain of CA patients.

Adaptive immunity is a critical component of the human immune system, playing an essential role in identifying antigens and orchestrating a tailored immune response. This review delves into the significant strides made in the development of epitope prediction tools, their integration into vaccine design, and their pivotal role in enhancing immunotherapy strategies. The review emphasizes the transformative potential of these tools in refining our understanding and application of immune responses. Adaptive immunity distinguishes itself from innate immunity by its ability to recognize specific antigens and remember past infections, leading to quicker and more effective responses upon subsequent exposures. This facet of immunity involves complex interactions between various cell types, primarily B cells and T cells, which recognize distinct epitopes presented by antigens. Epitopes are small sequences or configurations on antigens that are recognized by the immune receptors on B cells and T cells, acting as the focal points of immune recognition and response. Epitopes can be broadly classified into two types: linear (or sequential) epitopes and conformational (or discontinuous) epitopes. Linear epitopes consist of a sequence of amino acids in a protein that are recognized by B cells and T cells in their primary structure form. Conformational epitopes, on the other hand, are formed by spatially distinct amino acids that come together in the tertiary structure of the protein, often recognized by the immune system only when the protein folds into its native conformation. The role of epitopes in the immune response is critical as they are the primary triggers for the activation of B cells and T cells. When an epitope is recognized, it can stimulate B cells to produce antibodies, mobilize helper T cells to secrete cytokines, or prompt cytotoxic T cells to kill infected cells. These actions form the basis of the adaptive immune response, tailored to eliminate specific pathogens or infected cells effectively. The prediction of B cell and T cell epitopes has evolved with advances in computational biology, leading to the development of several sophisticated tools that utilize a variety of algorithms to predict the likelihood of epitope regions on antigens. Tools employing machine learning methods, such as support vector machines (SVMs), XGBoost, random forest, analyze large datasets of known epitopes to classify new sequences as potential epitopes based on their similarity to known data. Moreover, deep learning has emerged as a powerful method in epitope prediction, leveraging neural networks capable of learning high-dimensional data from vast amounts of immunological inputs to identify patterns that may not be evident to other predictive models. Deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs) and ESM protein language model have demonstrated superior accuracy in mapping the nonlinear relationships inherent in protein structures and epitope interactions. The application of epitope prediction tools in vaccine design is transformative, enabling the development of epitope-based vaccines that can elicit targeted immune responses against specific parts of the pathogen. These vaccines, by focusing the immune response on highly specific regions of the pathogen, can offer high efficacy and reduced side effects. Similarly, in cancer immunotherapy, epitope prediction tools help identify tumor-specific antigens that can be targeted to develop personalized immunotherapeutic strategies, thereby enhancing the precision of cancer treatments. The future of epitope prediction technology appears promising, with ongoing advancements anticipated to enhance the precision and efficiency of these tools further. The integration of broader immunological data, such as patient-specific immune profiles and pathogen variability, along with advances in AI and machine learning, will likely drive the development of more adaptive, robust, and clinically relevant prediction models. This will not only improve the effectiveness of vaccines and immunotherapies but also contribute to our broader understanding of immune mechanisms, potentially leading to breakthroughs in the treatment and prevention of multiple diseases. In conclusion, the development and refinement of epitope prediction tools stand as a cornerstone in the advancement of immunological research and therapeutic design, highlighting a path toward more precise and personalized medicine. The ongoing integration of computational models with experimental immunology holds the promise of revolutionizing our approach to combating infectious diseases and cancer.

To evaluate the effectiveness and safety of implantable D-shant atrial shunt device in patients with severe pulmonary arterial hypertension(PAH)and right heart failure.A 53-year-old female patient diagnosed with severe idiopathic PAH and right heart failure,her WHO FC grade was Ⅳ.The right heart catheter and implantation of D-shant atrial shunt device were performed under local anesthesia on November 30,2021.A 6 mm×4 cm peripheral artery balloon was selected to dilate the atrial septum and a D-shant atrial shunt device with a fixed 4 mm diameter orifice was implanted into the heart.The clinical symptoms and hemodynamics of the patient was improved after the intervention.Implantation of atrial shunt device as a palliative therapy to established a right to left shunt is another strategy for treating patients with severe PAH in late period,which has good effectiveness and safety.It could be the last replacement therapy to improve symptoms and prolonged lives to drug resistant and severe PAH patients.

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

Objective To explore the effectiveness of different intervention strategies in response to outbreaks of emerging highly pathogenic respiratory infectious diseases(RIDs)in mega-city in China,and provide decision-ma-king basis for effective response to emerging RIDs.Methods A susceptible-exposed-infectious-recovered(SEIR)transmission dynamics model was constructed,referencing to and combining the pathogenicity and infectivity para-meters of previous emerging RIDs.The outbreak of emerging highly pathogenic RIDs with low,moderate,and high infectivity in a mega-city with a population of 10 million in China was simulated,the development of the epidemic within 100 days after implementing different combinations of non-pharmaceutical interventions(NPIs)in response to the outbreak was compared.Results When highly pathogenic RIDs outbreak occurred,and if its infectivity was low(R0 was about 1.5),it was unnecessary to adopt strict NPIs to control epidemic.If its infectivity was moderate(R0 was about 6),different intensities of NPIs were needed based on its existing infection scale.When the initial num-ber of infected cases was 50,moderate-intensity NPIs could keep the infection and death at a low level within 100 days,and the required bed number in hospital for cases could be kept below the national average reserve level.But when the scale of infection exceeded 100 cases,high-intensity NPIs were needed to control the development of the epidemic.In the case of extremely strong infectivity(R0 was about 10),regardless of the scale of infection,only immediate high-intensity NPIs could control the epidemic,infection and death scale.Conclusion In case of out-breaks of highly pathogenic RIDs,adopting appropriate NPIs as early as possible based on their epidemiological characteristics and infection scale is necessary to minimize the harm to the population.

Endodontic diseases are a kind of chronic infectious oral disease.Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha.However,it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy(RCT).Recent research,encompassing bacterial etiology and advanced imaging techniques,contributes to our understanding of the root canal system's anatomy intricacies and the technique sensitivity of RCT.Success in RCT hinges on factors like patients,infection severity,root canal anatomy,and treatment techniques.Therefore,improving disease management is a key issue to combat endodontic diseases and cure periapical lesions.The clinical difficulty assessment system of RCT is established based on patient conditions,tooth conditions,root canal configuration,and root canal needing retreatment,and emphasizes pre-treatment risk assessment for optimal outcomes.The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT.These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment.However,irrigant selection or irrigation procedures are far from clear.The vapor lock effect in the apical region has yet to be solved,impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.Additionally,ambiguous clinical indications for root canal medication and non-standardized dressing protocols must be clarified.Inappropriate intracanal medication may present side effects and jeopardize the therapeutic outcomes.Indeed,clinicians have been aware of these concerns for years.Based on the current evidence of studies,this article reviews the properties of various irrigants and intracanal medicaments and elucidates their effectiveness and interactions.The evolution of different kinetic irrigation methods,their effects,limitations,the paradigm shift,current indications,and effective operational procedures regarding intracanal medication are also discussed.This expert consensus aims to establish the clinical operation guidelines for root canal irrigation and a position statement on intracanal medication,thus facilitating a better understanding of infection control,standardizing clinical practice,and ultimately improving the success of endodontic therapy.

The overall health condition of patients significantly affects the diagnosis,treatment,and prognosis of endodontic diseases.A systemic consideration of the patient's overall health along with oral conditions holds the utmost importance in determining the necessity and feasibility of endodontic therapy,as well as selecting appropriate therapeutic approaches.This expert consensus is a collaborative effort by specialists from endodontics and clinical physicians across the nation based on the current clinical evidence,aiming to provide general guidance on clinical procedures,improve patient safety and enhance clinical outcomes of endodontic therapy in patients with compromised overall health.