In recent years, due to the development of radiotherapy technology and nuclear energy, people have paid more and more attention to the various effects of ionizing radiation on organisms. Ionizing radiation can induce protein, DNA and other biological macromolecules to damage, resulting in apoptosis, senescence, cancer and a series of changes. For a long time, it has been believed that the main target of ionizing radiation damage is DNA in the nucleus. However, it has been reported in recent years that ionizing radiation has both direct and indirect effects, and the theory of ROS damage in the indirect effects believes that ionizing radiation has target uncertainty, so it is not comprehensive enough to evaluate only the DNA damage in the nucleus. It has been reported that ionizing radiation can cause damage to organelles as well as damage to cells. Mitochondria are important damaged organelles because mitochondria occupy as much as 30% of the entire cell volume in the cytoplasm, which contains DNA and related enzymes that are closely related to cellular ATP synthesis, aerobic respiration and other life activities. What is more noteworthy is that mitochondria are the only organelles in which DNA exists in the human body, which makes researchers pay attention to various damage to mitochondrial DNA caused by ionizing radiation (such as double-strand breaks, base mismatching, and fragment loss). Although these damages also occur in the nucleus, mitochondrial DNA is more severely damaged than nuclear DNA due to its lack of histone protection, so mitochondria are important targets of ionizing radiation damage in addition to the nucleus. Mitochondrial DNA is not protected by histones and has little repair ability. When exposed to ionizing radiation, common deletions occur at an increased frequency and are passed on to offspring. For large-scale mitochondrial DNA damage, mitochondria indirectly compensate for the amount of damaged DNA by increasing the number of DNA copies and maintaining the normal function of mitochondrial DNA. Mitochondria are in a state of oxidative stress after exposure to ionizing radiation, and this oxidative stress will promote the change in mitochondrial function. When mitochondria are damaged, the activity of proteins related to aerobic respiration decreases, and oxidative respiration is inhibited to a certain extent. At the same time, a large amount of active superoxide anions are continuously produced to stimulate mitochondrial oxidative stress, and the signal of such damage is transmitted to the surrounding mitochondria, resulting in a cascade of damage reaction, which further activates the signalling pathway between mitochondria and nucleus. The cell nucleus is also in a state of oxidative stress, and finally, the level of free radicals is high, causing secondary damage to the genetic material DNA of mitochondria and nucleus. In this paper, the damage effects of ionizing radiation on mitochondria are reviewed, to provide a new idea for radiation protection.

OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

Objective: To explore the bidirectional associations among body mass index Z scores (BMI Z scores) and weight stigma with depressive symptoms in adolescents, thereby providing evidence for targeted intervention strategies. Methods: A stratified cluster random sampling method was employed to select 18 301 adolescents aged 12-18 years from all 12 prefectures (103 counties) in the Inner Mongolia Autonomous Region, and two waves of longitudinal surveys were conducted in September 2023 (T1) and September 2024 (T2) among the adolescents. Weight stigma was assessed by using a self developed questionnaire, depressive symptom was measured with the Center for Epidemiologic Studies Depression Scale (CES-D), and BMI Z scores were calculated according to the World Health Organization standards. Pearson correlation analysis was used to examine associations among variables, and cross lagged panel models were constructed to investigate the dynamic bidirectional relationships among the three variables. Results: Adolescents BMI Z scores and weight stigma with depressive symptoms all exhibited autoregressive stability across the two time points (autoregressive paths, all P <0.01). Cross lagged model comparisons indicated that the bidirectional path model achieved the best fit ( χ 2=12.65, RMSEA =0.017, CFI =1.000; △ χ 2=193.39, P <0.01), supporting dynamic bidirectional associations among the three variables. After adjusting for gender, age, subjective social status and only child status, T1 BMI Z scores among adolescents positively predicted T2 weight stigma ( β =0.061), and T1 weight stigma positively predicted T2 depressive symptoms ( β =0.608); in the reverse direction, T1 depressive symptoms predicted T2 weight stigma ( β =0.003), and T1 weight stigma predicted T2 BMI Z scores ( β =0.081) (all P <0.01). Conclusions There is a bidirectional cross lagged relationship among adolescents BMI Z scores and weight stigma with depressive symptoms, suggesting that weight stigma may serve as a key psychological variable linking obesity and depressive symptoms. Greater attention should be paid to the potential threat of weight stigma to adolescents mental health, with intervention strategies expanded from a solely physiological focus to encompass psychosocial dimensions.

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.

The outer membrane composed predominantly of lipopolysaccharide (LPS) is an essential biological barrier for most Gram-negative (G^-) bacteria. Lipopolysaccharide transport protein (Lpt) complex LptDE is responsible for the critical final stage of LPS transport and outer membrane assembly. The structure and function of LptDE are highly conserved in most G^- bacteria but absent in mammalian cells, and thus LptDE complex is regarded as an attractive antibacterial target. In recent 10 years, the deciphering of the three-dimensional structure of LptDE protein facilities the drug discovery based on such "non-enzyme" proteins. Murepavadin, a peptidomimetic compound, was reported to be the first compound able to target LptD, enlightening a new class of antibacterial molecules with novel mechanisms of action. This article is devoted to summarize the molecular characteristics, structure-function of LptDE protein complex and review the development of murepavadin and related peptidomimetic compounds, in order to provide references for relevant researches.

Objective To analyze the acupoint selection rules of acupuncture for the treatment of tic disorders in children based on data mining techniques.Methods A computerized search was conducted for the clinical research literature on acupuncture treatment of tic disorders in children included in the CNKI,Wanfang,VIP,SinoMed,and PubMed databases from January 1992 to December 2022.A database was established by Excel 2019 to count the commonly used treatment methods and analyze the high-frequency application methods acupuncture(high-frequency acupoints,channel entry of acupoints,acupoint association rules,and acupoint clustering),auricular point seed-pressing(high-frequency auricular points,and acupoint association rules),and the high frequency division of cluster needling of scalp point.Results A total of 190 valid literature articles were included,involving 270 acupuncture prescriptions;among them,184 acupoints were counted in the acupuncture method,with a total application frequency of 1 906 times,and the high-frequency application of the acupoints in descending order were Baihui(DU20),Taichong(LR3),Fengchi(GB20),Hegu(LI4),Sanyinjiao(SP6),Neiguan(PC6),Shenmen(HT7),Zusanli(ST36),Yintang(EX-HN3),Sishencong(EX-HN1);and the high-frequency meridians were governor vessol,foot taiyang stomach meridian,foot taiyang stomach meridian,foot shaoyang gallbladder meridian,hand taiyang large intestine meridian,foot taiyang bladder meridian,foot jueyin gallbladder meridian;three sets of strong association rules and five clusters of acupoints were analyzed by SPSS modeler 18.0 and IBM SPSS Statistics 26.0 software.There were 29 acupoints of auricular point seed-pressing,application total frequency was 206 times,high-frequency application of auricular points in descending order of Shenmen(HT7),liver,heart,subcortex,kidney;four groups of acupoint strong association rules were obtained through the analysis of SPSS modeler 18.0 software.A total of 14 zones were involved in the application of cephalic acupoint plexus zoning,of which the high-frequency zones were parietal anterior temporal diagonal,parietal parietal 1,and chorea tremor control zone.Conclusion Acupuncture treatment of tic disorders in children,according to its pathogenesis(liver hyperactivity,kidney depletion,spleen deficiency,phlegm disturbance,etc.)and tic site,select acupoints compatibility,and mostly choose yang meridian acupoints,which is related to the nature and treatment characteristics of wind pathogen.Children's tic disorders are closely related to emotional disorders,therefore acupuncture and auricular acupoints all emphasize the method of soothing the liver and clearing the heart,and regulating the emotional state.Cluster needling of scalp point mostly used parietal temporal anterior oblique line,parietal 1 line,and dance tremor control area for the treatment of tic disorders.For children,auricular point seed-pressing and cluster needling of scalp point has the minimun of pain,the effect of treatment is long,and it is not easy to have dangerous situations such as bent needle,broken needle and so on.

Objective: To understand the pubertal development of primary and secondary school students in urban and rural areas of the Inner Mongolia Autonomous Region in 2021, so as to provide clues for further clarification of the health hazards of early pubertal initiation. Methods: From October to November 2021, primary and secondary school students in 12 provinces and cities of Inner Mongolia were selected by stratified cluster random sampling, including 21 662 girls who had reached menarche and 10 600 boys who had their first seminal emission, as well as 46 183 girls who had not reached menarche and 78 995 boys who had not experienced their first seminal emission. The height and weight of the primary and secondary school students were measured, and the time of first seminal emission or menarche was recorded. The study used the Mann-Whitney U test to analyze the differences between urban and rural students, Spearmans rank correlation to analyze the correlation between overweight and obesity and the age of pubertal initiation, and the Logistic regression model to analyze the correlation between pubertal initiation and age of pubertal initiation. Results: The age of menarche for urban girls [(12.31±1.29) years old] was earlier than that of suburban girls [(12.43±1.24) years old], and the age of first spermatozoa for urban boys [(13.85±1.20) years old] was statistically significant compared with that of suburban boys [(13.79±1.36) years old] (t=12.76, 10.58, P<0.05). There was a negative correlation between the age of menarche and overweight/obesity among girls aged 10-14 years (r=-0.169, P<0.05), and there was no statistically significant correlation between the age of spermarche and overweight/obesity in boys aged 5-9, 10-14, and 15-20 years (r=0.122, -0.022, -0.004, P>0.05). The occurrence of menarche in overweight girls was 1.06(95%CI=1.01-1.11) times higher than that in the normal group, and 1.13(95%CI=1.06-1.20) times higher among obese girls than normalweight girls. Compared to urban areas, primary and secondary school students in suburban counties observed the onset of puberty later [OR=0.88(95%CI=0.85-0.91) for menarche, OR=0.94(95%CI=0.89-0.99) for first spermatozoa] (P<0.05). Conclusions Obesity during childhood and adolescence is associated with earlier onset of puberty among female students in Inner Mongolia, and later onset of puberty among primary and secondary school students in suburban counties compared with those in urban areas.

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.

Objective To investigate the effect of BMAL1 on H2O2-induced cardiomyocyte injury through NRF2-regulated ROS/NLRP3 inflammasome pathway.Methods H9c2 cells and H9c2 cells with stable over-expressed BMAL1 were cultured and divided into the control group,the H2O2 group,the BMAL1-OE group,the BMAL1-OE+H2O2 group,the BMAL1-OE+ML385 group and the BMAL1-OE+ML385+H2O2 group.All groups were pre-intervened with corresponding inhibitors,and then treated with 0.2 mmol/L H2O2,except for the control group and the BMAL1-OE group.After the intervention,CCK-8 assay was used to measure cell viability,fluorescent probe DCFH-DA was used to measure ROS generation and Western blot assay was used to detect BMAL1,NRF2 and NLRP3 protein expressions.ELISA was used to determine IL-1β release.Results Compared with the control group,the cell viability was decreased,ROS generation was increased,BMAL1 and NRF2 protein expressions were decreased,NLRP3 expression and IL-1β release were increased in the H2O2 group(P＜0.05).Compared with the H2O2 group,the cell viability was increased,ROS generation was decreased,BMAL1-OE and NRF2 protein expressions were increased,NLRP3 expression and IL-1β release were decreased in the BMAL1-OE+H2O2 group(P＜0.05).Compared with the BMAL1-OE+H2O2 group,the cell viability was decreased,ROS generation was increased,NLRP3 expression and IL-1β release were increased in the BMAL1-OE+ML385+H2O2 group(P＜0.05).Conclusion BMAL1 attenuates H2O2-induced H9c2 cardiomyocyte injury,and its mechanism may be related to the regulation of ROS/NLRP3 inflammasome pathway through NRF2.

Objective To observe the inhibitory effect of Guiqi Yiyuan ointment on tumor growth in mice with Lewis lung cancer,and to explore the molecular mechanism of Guiqi Yiyuan ointment combined with cisplatin through phosphoinositide 3-kinase/protein kinase B/mammalian rapamycin target protein(PI3K/Akt/mTOR)signal pathway.Methods Sixty C57BL/6 mice were randomly divided into 6 groups with 10 mice in each group.Except for the blank group(0.9％NaCl),Lewis lung cancer-bearing mice were randomly divided into model group(0.9％NaCl),control group(0.9％NaCl,cisplatin 5 mg·kg-1)and low,medium,high dose experimental groups(Guiqi Yiyuan ointment 1.6,3.3,6.6 g·kg-1,cisplatin 5 mg·kg-1).Flow cytometry was used to detect bone marrow-derived suppressor cells(MDSCs);the expression of related proteins in tumor tissues was detected by Western blot.Results The tumor inhibition rates in control group and low,medium,high dose experimental groups were(39.87±4.45)％,(45.74±14.97)％,(57.78±4.70)％and(69.82±11.05)％.The proportion of MDSCs in bone marrow of in blank group,model group,control group and low,medium,high dose experimental groups were(36.13±1.08)％,(68.63±2.94)％,(58.93±2.02)％,(58.00±1.50)％,(50.93±5.06)％and(43.07±2.41)％.The protein expressions of p-PI3K/PI3K in model group,control group and low,medium and high experimental groups were 0.97±0.03,0.77±0.02,0.72±0.01,0.68±0.03 and 0.53±0.02;PTEN were 0.21±0.07,0.65±0.07,0.74±0.06,0.99±0.13,1.11±0.13;p-Akt/Akt were 1.01±0.02,0.82±0.02,0.77±0.00,0.72±0.03 and 0.52±0.04;p-mTOR/mTOR were 1.01±0.01,0.76±0.05,0.69±0.07,0.59±0.06 and 0.47±0.06.There were significant differences between low,medium,high experimental groups and control group(all P＜0.05).Conclusion Guiqi Yiyuan ointment combined with cisplatin can significantly improve the quality of life and inhibit tumor growth in mice.The mechanism may be the inhibition of PI3K/Akt/mTOR signal pathway and the enhancement of tumor cell apoptosis and autophagy.