Aromatic Chinese medicinal essential oils are volatile oils extracted from aromatic Chinese herbs， which can prevent and treat respiratory infectious diseases through multiple synergistic mechanisms including pathogen inhibition， immune regulation， and inflammatory response regulation. Essential oils are primarily used externally on the body to prevent infections and alleviate symptoms through methods like inhalation， smearing， topical application， bathing， gargling or as a suppository. They can also be utilized in the environment for disinfection and air purification， through methods like diffusion， vaporization， or spraying. The external application of essential oils extracted from Chinese aromatic herbs has the advantages of convenience， quick absorption， and simultaneous influence on both the body and mind. However， there are still challenges and deficiencies in aspects such as the positioning of functions， indications， safety， and the research on the mechanism of action. It has been proposed to combine the theory of aromatic Chinese medicinals with the characteristics of essential oils， and formulate prescriptions of Chinese medicinal essential oils under the principles of traditional Chinese medicine syndrome differentiation， and prevent and treat respiratory infectious diseases efficiently， accurately， and safely， thereby expanding the clinical application of aromatic Chinese medicinals and the preventive theory of traditional Chinese medicine.

Antibody drug conjugates (ADC) have emerged as a cutting-edge technology in anti-tumor treatment, making significant strides in recent years. ADC couple a highly active small molecule toxin payload to highly specific antibodies through a linker, enabling precise targeting of tumor cells while reducing systemic toxicity, thereby expanding the therapeutic window. However, due to the complexity of ADC molecule design, its efficacy and safety are influenced by various factors. Model-informed drug development (MIDD) is a powerful tool that utilizes various mathematical models for modeling and simulation to conduct quantitative analysis, guiding drug development and decision-making. By integrating multi-faceted data and information using mathematical models, it is possible to gain insights into the complex mechanisms, pharmacokinetics, and pharmacodynamics of ADC, providing unique perspectives for optimizing ADC development processes and clinical translation decisions. This review will introduce the basic concepts of MIDD and ADC and discuss application cases of MIDD in different stages of ADC development, aiming to provide beneficial references for the advancement of ADC.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

Objective: To explore the correlation among picky eating levels in preschool children, parental self-efficacy and parenting stress. Methods: A convenience sampling method was employed to conduct an electronic questionnaire survey among 459 children aged 3-6 years and their parents from five kindergartens in Urumqi in November 2023. The survey included a general information questionnaire, the Children s Eating Behavior Questionnaire (CEBQ), the Parenting Sense of Competence Scale (PSOC), and the Parenting Stress Index-Short Form (PSI-SF). The Mann-Whitney U-test was used for twogroup comparisons, and the Kruskal-Wallis H-test was applied for multi-group comparisons. Spearman correlation analysis was conducted to examine the relationships between children s picky eating levels and parenting selfefficacy as well as parenting stress. Results: The picky eating score of preschool children was 10.00 (4.00), and the parenting self-efficacy score was 58.00 (12.00), both indicating a moderate level. The parenting stress score was 75.00 (16.00), reflecting a moderately low level. Spearman correlation analysis showed that children s picky eating levels were negatively correlated with the total score of parenting self-efficacy ( r =-0.28) and positively correlated with the total score of parenting stress( r =0.25)( P <0.01). Conclusions Picky eating levels of preschool children are closely associated with parenting self-efficacy and parenting stress. Picky eating behaviors in children can be reduced by implementing various effective measures to enhance parenting self-efficacy and alleviate parenting stress.

ObjectiveTo understand the measles, rubella, and mumps antibody seroprevalence among the children aged 18 years and younger in Karamay City, and to evaluate the effectiveness of vaccination. MethodsA stratified whole cluster random sampling method was used to investigate the antibody seroprevalence of measles, rubella, and mumps among the healthy children aged 18 years and younger in Karamay City, and to further analyze the positive antibody rates and the geometric mean concentration (GMC) of antibodies. ResultsA total of 620 people were investigated, and the positive rates of IgG to measles, rubella, and mumps were 72.74%,62.26%, and 86.45%, respectively, with a GMC of308.94 mIU·mL^-1, 21.81 mIU·mL^-1, and 249.10 U·mL^-1. There were statistically significant differences in the positive rates of antibodies to measles, rubella, and mumps among different age groups (χ²_measles=76.707, P<0.001; χ²_rubella=60.804, P<0.001; χ²_mumps=35.407, P<0.001). The differences in positive rates were statistically significant among individuals with different intervals from the time of their last dose vaccination (χ²_measles=60.533, P<0.001; χ²_rubella=46.331, P<0.001; χ²_mumps=22.825, P<0.001). ConclusionThe antibody levels of measles, rubella and mumps among the people aged 18 years and younger in Karamay City are found to be low. Two doses of measles-mumps-rubella (MMR) vaccine should be given to children born before 2020, and if necessary, supplementary immunization with MMR vaccine should be carried out before they are enrolled in nursery and kindergarten. Additionally, regular population-based antibody surveillance should be conducted to promptly identify the people with weak immunity, which is conducive to effectively reducing and controlling the epidemic situation of measles, rubella and mumps in schools.

Objective: To investigate the risk factors affecting the early diagnosis of ABO-hemolytic disease of the fetus and newborn (ABO-HDFN) in neonates with maternal-fetal blood group incompatibility, and to develop a risk prediction model and validate its predictive performance, so as to provide a reference for the early diagnosis of neonates with ABO-HDFN in primary hospitals. Methods: A total of 1 229 neonates with maternal-fetal blood group incompatibility suspected of ABO-HDFN, admitted to our hospital between between June 2021 and September 2024, were enrolled. The sample size was calculated by using the events per variable (EPV) method. The cohort was divided into a modeling group (n=860) and a validation group (n=369), and the results and clinical information of laboratory examination indicators were collected. Univariate and multivariate logistic regression analysis were used to explore the risk factors affecting the early diagnosis of ABO-HDFN in neonates with maternal-fetal blood group incompatibility. The risk prediction model was developed and internally validated by the Bootstrap method. The goodness-of-fit of the model was evaluated by the Hosmer-Lemeshow (H-L) test, and the receiver operating characteristic (ROC) curve was used to analyze the predictive performance of the model. The prediction model was validated by using the validation group data, and the predictive performance of the model was evaluated. Results: Among the 860 neonates with maternal-fetal incompatibility in the modeling group, 346 (346/860, 40.23%) were diagnosed with ABO-HDFN. Univariate and multivariate logistic regression analyses identified the following as significant risk factors for early diagnosis: the number of postnatal days at specimen collection, maternal type O blood group, parity >1, time of onset for pathologic jaundice, maternal-fetal blood group incompatibility due to A antigen, the level of total bilirubin, and the immature reticulocyte fraction (IRF). A risk prediction model was established, and the calibration degree of the model was validated by the Bootstrap internal validation method, Brier=0.143. The results of H-L test showed that χ =3.464, P=0.902. The area under the ROC curve (AUC) was 0.885. The maximum value of the Youden index was 0.611, the sensitivity was 0.832, and the specificity was 0.778. The results of the validation group showed that the area under the ROC curve was 0.863, with a sensitivity of 0.875 and specificity of 0.735. Conclusion: The risk prediction model developed based on these risk factors has good predictive performance for ABO-HDFN, facilitating early diagnosis of suspected ABO-HDFN cases by clinicians in primary hospitals.

Objective: To investigate the risk factors affecting the early diagnosis of ABO-hemolytic disease of the fetus and newborn (ABO-HDFN) in neonates with maternal-fetal blood group incompatibility, and to develop a risk prediction model and validate its predictive performance, so as to provide a reference for the early diagnosis of neonates with ABO-HDFN in primary hospitals. Methods: A total of 1 229 neonates with maternal-fetal blood group incompatibility suspected of ABO-HDFN, admitted to our hospital between between June 2021 and September 2024, were enrolled. The sample size was calculated by using the events per variable (EPV) method. The cohort was divided into a modeling group (n=860) and a validation group (n=369), and the results and clinical information of laboratory examination indicators were collected. Univariate and multivariate logistic regression analysis were used to explore the risk factors affecting the early diagnosis of ABO-HDFN in neonates with maternal-fetal blood group incompatibility. The risk prediction model was developed and internally validated by the Bootstrap method. The goodness-of-fit of the model was evaluated by the Hosmer-Lemeshow (H-L) test, and the receiver operating characteristic (ROC) curve was used to analyze the predictive performance of the model. The prediction model was validated by using the validation group data, and the predictive performance of the model was evaluated. Results: Among the 860 neonates with maternal-fetal incompatibility in the modeling group, 346 (346/860, 40.23%) were diagnosed with ABO-HDFN. Univariate and multivariate logistic regression analyses identified the following as significant risk factors for early diagnosis: the number of postnatal days at specimen collection, maternal type O blood group, parity >1, time of onset for pathologic jaundice, maternal-fetal blood group incompatibility due to A antigen, the level of total bilirubin, and the immature reticulocyte fraction (IRF). A risk prediction model was established, and the calibration degree of the model was validated by the Bootstrap internal validation method, Brier=0.143. The results of H-L test showed that χ =3.464, P=0.902. The area under the ROC curve (AUC) was 0.885. The maximum value of the Youden index was 0.611, the sensitivity was 0.832, and the specificity was 0.778. The results of the validation group showed that the area under the ROC curve was 0.863, with a sensitivity of 0.875 and specificity of 0.735. Conclusion: The risk prediction model developed based on these risk factors has good predictive performance for ABO-HDFN, facilitating early diagnosis of suspected ABO-HDFN cases by clinicians in primary hospitals.

By systematically combing ancient and modern literature， this paper examined Tribuli Fructus and Astragali Complanati Semen（ACS） used in the famous classical formulas from the aspects of name， origin， production area， harvesting and processing， clinical efficacy， so as to provide a basis for the development of famous classical formulas containing such medicinal materials. The results showed that the names of Tribuli Fructus in the past dynasties were mostly derived from its morphology， and there were nicknames such as Baijili， Cijili and Dujili. The name of ACS in the past dynasties were mostly originated from its production areas， and there were nicknames such as Baijili， Shayuan Jili and Tongjili. Because both of them had the name of Baijili， confusion began to appear in the Song dynasty. In ancient and modern times， the main origin of Tribuli Fructus were Tribulus terrestris， and ancient literature recorded the genuine producing areas of Tribuli Fructus was Dali in Shaanxi and Tianshui in Gansu， but today it is mainly cultivated in Anhui and Shandong. The fruit is the medicinal part， harvested in autumn throughout history. There is no description of the quality of Tribuli Fructus in ancient times， and the plump， firm texture， grayish-white color is the best in modern times. Traditional processing methods for Tribuli Fructus included stir-frying and wine processing， while modern commonly used is purified， fried and salt-processed. The ancient records of Tribuli Fructus were spicy， bitter， and warm in nature， with modern research adding that it is slightly toxic. The main effects of ancient and modern times include treating wind disorders， improving vision， promoting muscle growth， and treating vitiligo. The mainstream base of ACS used throughout history is Astragalus complanatus. Ancient texts indicated ACS primarily originated from Shaanxi province. Today， the finest varieties come from Tongguan and Dali in Shaanxi. The medicinal part is the seed， traditionally harvested in autumn. Modern harvesting occurs in late autumn or early winter， followed by sun-drying. Ancient texts valued seeds with a fragrant aroma as superior， while modern standards prioritize plump， uniform and free of impurities. Traditional processing methods for ACS included frying until blackened and wine-frying， while modern practice commonly employs purification methods. In terms of medicinal properties， the ancient and modern records are sweet and warm in nature. Due to originally classified under Tribuli Fructus， its effects were thus regarded as equivalent to those of Tribuli Fructus， serving as the medicine for treating wind disorders， additional functions included tonifying the kidneys and treating vitiligo. The present record of its efficacy is to tonify the kidney and promote Yang， solidify sperm and reduce urine， nourish the liver and brighten the eye， etc. Based on the textual research results， it is suggested that when developing the famous classical formulas of Tribuli Fructus medicinal materials， we should pay attention to the specific reference object of Baijili， T. terrestris and A. complanatus should be identified and selected， and the processing method should be in accordance with the requirements of the formulas.

Objective To investigate the disease characteristics, potential drug interactions, and key points of pharmaceutical care in patients with inflammatory bowel disease and atrial fibrillation, so as to provide a reference for rational clinical medication use. Methods Through involvement in the pharmaceutical care of a patient with inflammatory bowel disease and atrial fibrillation, and by reviewing relevant literature, the clinical pharmacist assessed the rationality of the medication regimen, proposed medication reconciliation recommendations, and assisted the multidisciplinary team in optimizing the treatment plan. Results Following the intervention, the patient's inflammatory bowel disease-related symptoms were improved significantly, atrial fibrillation was effectively controlled, and no significant adverse drug reactions were observed. Conclusion There exists a complex bidirectional interaction between inflammatory bowel disease and atrial fibrillation in terms of pathological mechanisms and pharmacotherapy. Through individualized medication reconciliation and multidisciplinary pharmaceutical care, safe and effective long-term management of those patients can be achieved.

Objective     To evaluate the robustness of cardiovascular meta-analysis with use of fragility index. Methods     By searching PubMed, EMbase, and Web of Science databases from 2018 to 2022, relevant literature on cardiovascular meta-analysis was systematically collected and the fragility indexes were calculated; Spearman correlation analysis was used to explore the relationship between fragility index and sample size, total number of events, effect size and its confidence interval width. Results     A total of 212 meta-analyses from 29 articles were included, with a median fragility index of 11 (5, 25), a median sample size of 10 301 (3 384, 48 330), and a median total number of events of 360 (129, 1 309). Most meta-analyses chose relative risk as the effect measure (179/212), and chose Mantel-Haenszel method (102/212) and random effects model (153/212). The fragility index was positively correlated with the sample size (rs=0.56, P<0.05) and the total number of events (rs=0.61, P<0.05), and negatively correlated with confidence interval width of the effect size (rs=−0.52, P<0.05). No statistically significant results were obtained in the correlation between the fragility index and effect size. Conclusion     The fragility indexes of cardiovascular meta-analyses published in comprehensive journals of high impact factors and professional cardiovascular journals are generally low, and therefore lack robustness. Fragility index is suggested to be reported in medical researches, assisting in explaining the P-value.